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Wei X, Chen M, Zhang Q, Gong J, Liu J, Yong K, Wang Q, Fan J, Chen S, Hua H, Luo Z, Zhao X, Wang X, Li W, Cong J, Yu X, Wang Z, Huang R, Chen J, Zhou X, Qiu J, Xu P, Murray J, Wang H, Xu Y, Xu C, Xu G, Yang J, Han B, Huang X. Genomic investigation of 18,421 lines reveals the genetic architecture of rice. Science 2024; 385:eadm8762. [PMID: 38963845 DOI: 10.1126/science.adm8762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 04/29/2024] [Indexed: 07/06/2024]
Abstract
Understanding how numerous quantitative trait loci (QTL) shape phenotypic variation is an important question in genetics. To address this, we established a permanent population of 18,421 (18K) rice lines with reduced population structure. We generated reference-level genome assemblies of the founders and genotyped all 18K-rice lines through whole-genome sequencing. Through high-resolution mapping, 96 high-quality candidate genes contributing to variation in 16 traits were identified, including OsMADS22 and OsFTL1 verified as causal genes for panicle number and heading date, respectively. We identified epistatic QTL pairs and constructed a genetic interaction network with 19 genes serving as hubs. Overall, 170 masking epistasis pairs were characterized, serving as an important factor contributing to genetic background effects across diverse varieties. The work provides a basis to guide grain yield and quality improvements in rice.
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Affiliation(s)
- Xin Wei
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Mengjiao Chen
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Qi Zhang
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Junyi Gong
- State Key Laboratory of Rice Biology and Breeding, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou 310006, China
| | - Jie Liu
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Kaicheng Yong
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Qin Wang
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Jiongjiong Fan
- State Key Laboratory of Rice Biology and Breeding, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou 310006, China
| | - Suhui Chen
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Hua Hua
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Zhaowei Luo
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Xiaoyan Zhao
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Xuan Wang
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Wei Li
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Jia Cong
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Xiting Yu
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Zhihan Wang
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Ruipeng Huang
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Jiaxin Chen
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Xiaoyi Zhou
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Jie Qiu
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Ping Xu
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
| | - Jeremy Murray
- CAS Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai 200233, China
| | - Hai Wang
- State Key Laboratory of Plant Physiology and Biochemistry, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Yang Xu
- Key Laboratory of Plant Functional Genomics of Ministry of Education, College of Agriculture, Yangzhou University, Yangzhou 225009, China
| | - Chenwu Xu
- Key Laboratory of Plant Functional Genomics of Ministry of Education, College of Agriculture, Yangzhou University, Yangzhou 225009, China
| | - Gen Xu
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68583, USA
| | - Jinliang Yang
- Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68583, USA
| | - Bin Han
- CAS Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai 200233, China
| | - Xuehui Huang
- Shanghai Key Laboratory of Plant Molecular Sciences, Development Center of Plant Germplasm Resources, College of Life Sciences, Shanghai Normal University, Shanghai 200234, China
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Zhang W, Lu Z, Guo T, Yuan C, Liu J. Construction of a high-density genetic map and QTL localization of body weight and wool production related traits in Alpine Merino sheep based on WGR. BMC Genomics 2024; 25:641. [PMID: 38937677 PMCID: PMC11212225 DOI: 10.1186/s12864-024-10535-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 06/17/2024] [Indexed: 06/29/2024] Open
Abstract
BACKGROUND The Alpine Merino is a new breed of fine-wool sheep adapted to the cold and arid climate of the plateau in the world. It has been popularized in Northwest China due to its superior adaptability as well as excellent production performance. Those traits related to body weight, wool yield, and wool fiber characteristics, which are economically essential traits in Alpine Merino sheep, are controlled by QTL (Quantitative Trait Loci). Therefore, the identification of QTL and genetic markers for these key economic traits is a critical step in establishing a MAS (Marker-Assisted Selection) breeding program. RESULTS In this study, we constructed the high-density genetic linkage map of Alpine Merino sheep by sequencing 110 F1 generation individuals using WGR (Whole Genome Resequencing) technology. 14,942 SNPs (Single Nucleotide Polymorphism) were identified and genotyped. The map spanned 2,697.86 cM, with an average genetic marker interval of 1.44 cM. A total of 1,871 high-quality SNP markers were distributed across 27 linkage groups, with an average of 69 markers per LG (Linkage Group). Among them, the smallest genetic distance is 19.62 cM for LG2, while the largest is 237.19 cM for LG19. The average genetic distance between markers in LGs ranged from 0.24 cM (LG2) to 3.57 cM (LG17). The marker density in the LGs ranged from LG14 (39 markers) to LG1 (150 markers). CONCLUSIONS The first genetic map of Alpine Merino sheep we constructed included 14,942 SNPs, while 46 QTLs associated with body weight, wool yield and wool fiber traits were identified, laying the foundation for genetic studies and molecular marker-assisted breeding. Notably, there were QTL intervals for overlapping traits on LG4 and LG8, providing potential opportunities for multi-trait co-breeding and further theoretical support for selection and breeding of ultra-fine and meaty Alpine Merino sheep.
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Affiliation(s)
- Wentao Zhang
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou, 730050, China
- Sheep Breeding Engineering Technology Research Center of Chinese Academy of Agricultural Sciences, Lanzhou, 730050, China
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China
| | - Zengkui Lu
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou, 730050, China
- Sheep Breeding Engineering Technology Research Center of Chinese Academy of Agricultural Sciences, Lanzhou, 730050, China
| | - Tingting Guo
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou, 730050, China
- Sheep Breeding Engineering Technology Research Center of Chinese Academy of Agricultural Sciences, Lanzhou, 730050, China
| | - Chao Yuan
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou, 730050, China.
- Sheep Breeding Engineering Technology Research Center of Chinese Academy of Agricultural Sciences, Lanzhou, 730050, China.
| | - Jianbin Liu
- Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou, 730050, China.
- Sheep Breeding Engineering Technology Research Center of Chinese Academy of Agricultural Sciences, Lanzhou, 730050, China.
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Niu Y, Fan X, Yang Y, Li J, Lian J, Wang L, Zhang Y, Tang Y, Tang Z. Haplotype-resolved assembly of a pig genome using single-sperm sequencing. Commun Biol 2024; 7:738. [PMID: 38890535 PMCID: PMC11189477 DOI: 10.1038/s42003-024-06397-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Accepted: 05/29/2024] [Indexed: 06/20/2024] Open
Abstract
Single gamete cell sequencing together with long-read sequencing can reliably produce chromosome-level phased genomes. In this study, we employed PacBio HiFi and Hi-C sequencing on a male Landrace pig, coupled with single-sperm sequencing of its 102 sperm cells. A haplotype assembly method was developed based on long-read sequencing and sperm-phased markers. The chromosome-level phased assembly showed higher phasing accuracy than methods that rely only on HiFi reads. The use of single-sperm sequencing data enabled the construction of a genetic map, successfully mapping the sperm motility trait to a specific region on chromosome 1 (105.40-110.70 Mb). Furthermore, with the assistance of Y chromosome-bearing sperm data, 26.16 Mb Y chromosome sequences were assembled. We report a reliable approach for assembling chromosome-level phased genomes and reveal the potential of sperm population in basic biology research and sperm phenotype research.
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Affiliation(s)
- Yongchao Niu
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Foshan, China
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agriculture Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Xinhao Fan
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Foshan, China
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agriculture Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- GuangXi Engineering Centre for Resource Development of Bama Xiang Pig, Bama, China
- Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Yalan Yang
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Foshan, China
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agriculture Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Jiang Li
- Biozeron Shenzhen, Inc., Shenzhen, China
| | | | - Liu Wang
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Foshan, China
| | - Yongjin Zhang
- GuangXi Engineering Centre for Resource Development of Bama Xiang Pig, Bama, China
| | - Yijie Tang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agriculture Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Zhonglin Tang
- Kunpeng Institute of Modern Agriculture at Foshan, Agricultural Genomics Institute, Chinese Academy of Agricultural Sciences, Foshan, China.
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Agriculture Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China.
- GuangXi Engineering Centre for Resource Development of Bama Xiang Pig, Bama, China.
- Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China.
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4
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Wang D, Cheng B, Zhang J. High-density genetic map and quantitative trait loci map of skin color in hawthorn ( Crataegus pinnatifida bge. Var. major N.E.Br.). Front Genet 2024; 15:1405604. [PMID: 38873113 PMCID: PMC11169616 DOI: 10.3389/fgene.2024.1405604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2024] [Accepted: 05/09/2024] [Indexed: 06/15/2024] Open
Abstract
Fruit skin color is an important trait of the hawthorn tree, which has an important influence on fruit quality. Crataegus pinnatifida Bge. var. Major N.E.Br. Is one of the most widely cultivated varieties in China and has a long history of medicinal use. In recent years, it has attracted the attention of the world due to its nutritional and medicinal values. Skin color is the focus of breeders and food processors. At present, skin color-related genes have still not been mapped. In this study, "Shandong Da Mianqiu" (♀, red skin color), "Da Huang Mianzha" (♂, yellow skin color) and 131 F1 hybrids were used to construct genetic map of hawthorn by RAD-seq, and QTL mapping was performed by combining these features with the hue angle and the observed color. In this study, 13,260 SNP was assigned to 17 linkage groups, with an integrated map covering 2,297.75 cM was constructed. A total of 5 QTLs related to hawthorn skin color were detected on LG1, LG3 and LG15. Whether hue angle or pericarp color acts as phenotype for QTL mapping, the candidate genes include bHLH086, WD repeat regions and Myb-like. bHLH, WD and Myb play an important role in the color regulation of Hawthorn skin color. These results lay a solid foundation for QTL mapping and molecular marker-assisted breeding of hawthorn.
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Affiliation(s)
- Dongsheng Wang
- Engineering Research Center of Chestnut Industry Technology, Ministry of Education, Hebei Normal University of Science and Technology, Qinhuangdao, China
| | - Beibei Cheng
- College of Horticulture Science and Technology, Hebei Normal University of Science and Technology, Qinhuangdao, China
- Hebei Key Laboratory of Horticultural Germplasm Excavation and Innovative Utilization, Qinhuangdao, China
- Hebei Higher Institute Application Technology Research and Development Center of Horticultural Plant Biological Breeding, Qinhuangdao, China
| | - Jijun Zhang
- College of Horticulture Science and Technology, Hebei Normal University of Science and Technology, Qinhuangdao, China
- Hebei Key Laboratory of Horticultural Germplasm Excavation and Innovative Utilization, Qinhuangdao, China
- Hebei Higher Institute Application Technology Research and Development Center of Horticultural Plant Biological Breeding, Qinhuangdao, China
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Huang J, Zhang Y, Li Y, Xing M, Lei C, Wang S, Nie Y, Wang Y, Zhao M, Han Z, Sun X, Zhou H, Wang Y, Zheng X, Xiao X, Fan W, Liu Z, Guo W, Zhang L, Cheng Y, Qian Q, He H, Yang Q, Qiao W. Haplotype-resolved gapless genome and chromosome segment substitution lines facilitate gene identification in wild rice. Nat Commun 2024; 15:4573. [PMID: 38811581 PMCID: PMC11137157 DOI: 10.1038/s41467-024-48845-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 05/15/2024] [Indexed: 05/31/2024] Open
Abstract
The abundant genetic variation harbored by wild rice (Oryza rufipogon) has provided a reservoir of useful genes for rice breeding. However, the genome of wild rice has not yet been comprehensively assessed. Here, we report the haplotype-resolved gapless genome assembly and annotation of wild rice Y476. In addition, we develop two sets of chromosome segment substitution lines (CSSLs) using Y476 as the donor parent and cultivated rice as the recurrent parents. By analyzing the gapless reference genome and CSSL population, we identify 254 QTLs associated with agronomic traits, biotic and abiotic stresses. We clone a receptor-like kinase gene associated with rice blast resistance and confirm its wild rice allele improves rice blast resistance. Collectively, our study provides a haplotype-resolved gapless reference genome and demonstrates a highly efficient platform for gene identification from wild rice.
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Affiliation(s)
- Jingfen Huang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yilin Zhang
- School of Advanced Agriculture Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking University, Beijing, China
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences at Weifang, Weifang, Shandong, China
| | - Yapeng Li
- National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, Hainan, China
- Hainan Academy of Agricultural Sciences, Haikou, Hainan, China
| | - Meng Xing
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, Hainan, China
| | - Cailin Lei
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, Hainan, China
| | - Shizhuang Wang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, Hainan, China
| | - Yamin Nie
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, Hainan, China
| | - Yanyan Wang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, Hainan, China
| | - Mingchao Zhao
- National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, Hainan, China
- Hainan Academy of Agricultural Sciences, Haikou, Hainan, China
| | - Zhenyun Han
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xianjun Sun
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Han Zhou
- School of Advanced Agriculture Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking University, Beijing, China
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences at Weifang, Weifang, Shandong, China
| | - Yan Wang
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences at Weifang, Weifang, Shandong, China
| | - Xiaoming Zheng
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, Hainan, China
| | - Xiaorong Xiao
- National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, Hainan, China
- Hainan Academy of Agricultural Sciences, Haikou, Hainan, China
| | - Weiya Fan
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Ziran Liu
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Wenlong Guo
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Lifang Zhang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yunlian Cheng
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Qian Qian
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, Hainan, China
| | - Hang He
- School of Advanced Agriculture Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking University, Beijing, China.
- Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences at Weifang, Weifang, Shandong, China.
| | - Qingwen Yang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
- National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, Hainan, China.
| | - Weihua Qiao
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
- National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, Hainan, China.
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Wang C, Qin K, Shang X, Gao Y, Wu J, Ma H, Wei Z, Dai G. Mapping quantitative trait loci associated with self-(in)compatibility in goji berries (Lycium barbarum). BMC PLANT BIOLOGY 2024; 24:441. [PMID: 38778301 PMCID: PMC11112781 DOI: 10.1186/s12870-024-05092-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 05/01/2024] [Indexed: 05/25/2024]
Abstract
BACKGROUND Goji (Lycium barbarum L.) is a perennial deciduous shrub widely distributed in arid and semiarid regions of Northwest China. It is highly valued for its medicinal and functional properties. Most goji varieties are naturally self-incompatible, posing challenges in breeding and cultivation. Self-incompatibility is a complex genetic trait, with ongoing debates regarding the number of self-incompatible loci. To date, no genetic mappings has been conducted for S loci or other loci related to self-incompatibility in goji. RESULTS We used genome resequencing to create a high-resolution map for detecting de novo single-nucleotide polymorphisms (SNP) in goji. We focused on 229 F1 individuals from self-compatible '13-19' and self-incompatible 'new 9' varieties. Subsequently, we conducted a quantitative trait locus (QTL) analysis on traits associated with self-compatibility in goji berries. The genetic map consisted of 249,327 SNPs distributed across 12 linkage groups (LGs), spanning a total distance of 1243.74 cM, with an average interval of 0.002 cM. Phenotypic data related to self-incompatibility, such as average fruit weight, fruit rate, compatibility index, and comparable compatibility index after self-pollination and geitonogamy, were collected for the years 2021-2022, as well as for an extra year representing the mean data from 2021 to 2022 (2021/22). A total of 43 significant QTL, corresponding to multiple traits were identified, accounting for more than 11% of the observed phenotypic variation. Notably, a specific QTL on chromosome 2 consistently appeared across different years, irrespective of the relationship between self-pollination and geitonogamy. Within the localization interval, 1180 genes were annotated, including Lba02g01102 (annotated as an S-RNase gene), which showed pistil-specific expression. Cloning of S-RNase genes revealed that the parents had two different S-RNase alleles, namely S1S11 and S2S8. S-genotype identification of the F1 population indicated segregation of the four S-alleles from the parents in the offspring, with the type of S-RNase gene significantly associated with self-compatibility. CONCLUSIONS In summary, our study provides valuable insights into the genetic mechanism underlying self-compatibility in goji berries. This highlights the importance of further positional cloning investigations and emphasizes the importance of integration of marker-assisted selection in goji breeding programs.
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Affiliation(s)
- Cuiping Wang
- School of Biological Science and Engineering, North Minzu University, Yinchuan, 750021, China.
- State Key Laboratory of Efficient Production of Forest Resources, Yinchuan, 750004, China.
| | - Ken Qin
- National Wolfberry Engineering Research Center, Ningxia Academy of Agriculture and Forestry Sciences, Yinchuan, 750002, China
| | - Xiaohui Shang
- School of Biological Science and Engineering, North Minzu University, Yinchuan, 750021, China
| | - Yan Gao
- National Wolfberry Engineering Research Center, Ningxia Academy of Agriculture and Forestry Sciences, Yinchuan, 750002, China
| | - Jiali Wu
- School of Biological Science and Engineering, North Minzu University, Yinchuan, 750021, China
| | - Haijun Ma
- School of Biological Science and Engineering, North Minzu University, Yinchuan, 750021, China
- Ningxia Grape and Wine Technology Center, North Minzu University, Yinchuan, 750021, China
| | - Zhaojun Wei
- School of Biological Science and Engineering, North Minzu University, Yinchuan, 750021, China
| | - Guoli Dai
- National Wolfberry Engineering Research Center, Ningxia Academy of Agriculture and Forestry Sciences, Yinchuan, 750002, China.
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Jiang W, Liu Y, Zhang C, Pan L, Wang W, Zhao C, Zhao T, Li Y. Identification of major QTLs for drought tolerance in soybean, together with a novel candidate gene, GmUAA6. JOURNAL OF EXPERIMENTAL BOTANY 2024; 75:1852-1871. [PMID: 38226463 DOI: 10.1093/jxb/erad483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 01/12/2024] [Indexed: 01/17/2024]
Abstract
Drought tolerance is a complex trait in soybean that is controlled by polygenetic quantitative trait loci (QTLs). In this study, wilting score, days-to-wilting, leaf relative water content, and leaf relative conductivity were used to identify QTLs associated with drought tolerance in recombinant inbred lines derived from a cross between a drought-sensitive variety, Lin, and a drought-tolerant variety, Meng. A total of 33 drought-tolerance QTLs were detected. Of these 17 were major QTLs. In addition, 15 were novel drought-tolerance QTLs. The most predominant QTL was on chromosome 11. This was detected in at least three environments. The overlapped mapping interval of the four measured traits was 0.2 cM in genetic distance (about 220 kb in physical length). Glyma.11g143500 (designated as GmUAA6), which encodes a UDP-N-acetylglucosamine transporter, was identified as the most likely candidate gene. The allele of GmUAA6 from Lin (GmUAA6Lin) was associated with improved soybean drought tolerance. Overexpression of GmUAA6Lin in Arabidopsis and soybean hairy roots enhanced drought tolerance. Furthermore, a 3-bp insertion/deletion (InDel) in the coding sequence of GmUAA6 explained up to 49.9% of the phenotypic variation in drought tolerance-related traits, suggesting that this InDel might be used in future marker-assisted selection of drought-tolerant lines in soybean breeding programs.
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Affiliation(s)
- Wei Jiang
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, National Center for Soybean Improvement, Key Laboratory for Biology and Genetic Improvement of Soybeans (General, Ministry of Agriculture), Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
- Zhongshan Biological Breeding Laboratory, Nanjing, Jiangsu 210014, China
| | - Yandang Liu
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, National Center for Soybean Improvement, Key Laboratory for Biology and Genetic Improvement of Soybeans (General, Ministry of Agriculture), Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
- Zhongshan Biological Breeding Laboratory, Nanjing, Jiangsu 210014, China
| | - Chi Zhang
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, National Center for Soybean Improvement, Key Laboratory for Biology and Genetic Improvement of Soybeans (General, Ministry of Agriculture), Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Lang Pan
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, National Center for Soybean Improvement, Key Laboratory for Biology and Genetic Improvement of Soybeans (General, Ministry of Agriculture), Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Wei Wang
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, National Center for Soybean Improvement, Key Laboratory for Biology and Genetic Improvement of Soybeans (General, Ministry of Agriculture), Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
| | - Chunzhao Zhao
- Shanghai Center for Plant Stress Biology and Center of Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai 200032, China
| | - Tuanjie Zhao
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, National Center for Soybean Improvement, Key Laboratory for Biology and Genetic Improvement of Soybeans (General, Ministry of Agriculture), Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
- Zhongshan Biological Breeding Laboratory, Nanjing, Jiangsu 210014, China
| | - Yan Li
- State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization, National Center for Soybean Improvement, Key Laboratory for Biology and Genetic Improvement of Soybeans (General, Ministry of Agriculture), Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
- Zhongshan Biological Breeding Laboratory, Nanjing, Jiangsu 210014, China
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Meng QL, Qiang CG, Li JL, Geng MF, Ren NN, Cai Z, Wang MX, Jiao ZH, Zhang FM, Song XJ, Ge S. Genetic architecture of ecological divergence between Oryza rufipogon and Oryza nivara. Mol Ecol 2024; 33:e17268. [PMID: 38230514 DOI: 10.1111/mec.17268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 01/04/2024] [Accepted: 01/08/2024] [Indexed: 01/18/2024]
Abstract
Ecological divergence due to habitat difference plays a prominent role in the formation of new species, but the genetic architecture during ecological speciation and the mechanism underlying phenotypic divergence remain less understood. Two wild ancestors of rice (Oryza rufipogon and Oryza nivara) are a progenitor-derivative species pair with ecological divergence and provide a unique system for studying ecological adaptation/speciation. Here, we constructed a high-resolution linkage map and conducted a quantitative trait locus (QTL) analysis of 19 phenotypic traits using an F2 population generated from a cross between the two Oryza species. We identified 113 QTLs associated with interspecific divergence of 16 quantitative traits, with effect sizes ranging from 1.61% to 34.1% in terms of the percentage of variation explained (PVE). The distribution of effect sizes of QTLs followed a negative exponential, suggesting that a few genes of large effect and many genes of small effect were responsible for the phenotypic divergence. We observed 18 clusters of QTLs (QTL hotspots) on 11 chromosomes, significantly more than that expected by chance, demonstrating the importance of coinheritance of loci/genes in ecological adaptation/speciation. Analysis of effect direction and v-test statistics revealed that interspecific differentiation of most traits was driven by divergent natural selection, supporting the argument that ecological adaptation/speciation would proceed rapidly under coordinated selection on multiple traits. Our findings provide new insights into the understanding of genetic architecture of ecological adaptation and speciation in plants and help effective manipulation of specific genes or gene cluster in rice breeding.
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Affiliation(s)
- Qing-Lin Meng
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Cheng-Gen Qiang
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Ji-Long Li
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Mu-Fan Geng
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Ning-Ning Ren
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China
| | - Zhe Cai
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China
| | - Mei-Xia Wang
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Zi-Hui Jiao
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Fu-Min Zhang
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xian-Jun Song
- Key Laboratory of Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, China
| | - Song Ge
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
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9
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Gong D, Li J, Wang S, Sha A, Wang L. Mapping and Detection of Genes Related to Trichome Development in Black Gram ( Vigna mungo (L.) Hepper). Genes (Basel) 2024; 15:308. [PMID: 38540367 PMCID: PMC10970695 DOI: 10.3390/genes15030308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 02/20/2024] [Accepted: 02/24/2024] [Indexed: 06/14/2024] Open
Abstract
Black gram (Vigna mungo (L.) Hepper) is a pulses crop with good digestible protein and a high carbohydrate content, so it is widely consumed as human food and animal feed. Trichomes are large, specialized epidermal cells that confer advantages on plants under biotic and abiotic stresses. Genes regulating the development of trichomes are well characterized in Arabidopsis and tomato. However, little is known about trichome development in black gram. In this study, a high-density map with 5734 bin markers using an F2 population derived from a trichome-bearing and a glabrous cultivar of black gram was constructed, and a major quantitative trait locus (QTL) related to trichomes was identified. Six candidate genes were located in the mapped interval region. Fourteen single-nucleotide polymorphisms (SNPs) or insertion/deletions (indels) were associated with those genes. One indel was located in the coding region of the gene designated as Scaffold_9372_HRSCAF_11447.164. Real-time quantitative PCR (qPCR) analysis demonstrated that only one candidate gene, Scaffold_9372_HRSCAF_11447.166, was differentially expressed in the stem between the two parental lines. These two candidate genes encoded the RNA polymerase-associated protein Rtf1 and Bromodomain adjacent to zinc finger domain protein 1A (BAZ1A). These results provide insights into the regulation of trichome development in black gram. The candidate genes may be useful for creating transgenic plants with improved stress resistance and for developing molecular markers for trichome selection in black gram breeding programs.
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Affiliation(s)
- Dan Gong
- Key Laboratory Grain Crop Genetic Resources Evaluation and Utilization, Ministry of Agriculture and Rural Affairs, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing 100081, China
- College of Agriculture, Yangtze University, Jingzhou 434025, China
| | - Jianling Li
- Key Laboratory Grain Crop Genetic Resources Evaluation and Utilization, Ministry of Agriculture and Rural Affairs, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing 100081, China
| | - Suhua Wang
- Key Laboratory Grain Crop Genetic Resources Evaluation and Utilization, Ministry of Agriculture and Rural Affairs, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing 100081, China
| | - Aihua Sha
- College of Agriculture, Yangtze University, Jingzhou 434025, China
| | - Lixia Wang
- Key Laboratory Grain Crop Genetic Resources Evaluation and Utilization, Ministry of Agriculture and Rural Affairs, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (ICS-CAAS), Beijing 100081, China
- College of Agriculture, Yangtze University, Jingzhou 434025, China
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10
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Wang Z, Zhang Y, Huai D, Chen Y, Wang X, Kang Y, Yan L, Jiang H, Liu K, Lei Y, Liao B. Detection of two homologous major QTLs and development of diagnostic molecular markers for sucrose content in peanut. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2024; 137:61. [PMID: 38411751 DOI: 10.1007/s00122-024-04549-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 01/10/2024] [Indexed: 02/28/2024]
Abstract
KEY MESSAGE We identified two stable and homologous major QTLs for sucrose content in peanut, and developed breeder-friendly molecular markers for marker-assisted selection breeding. Sucrose content is a crucial quality trait for edible peanuts, and increasing sucrose content is a key breeding objective. However, the genetic basis of sucrose content in peanut remains unclear, and major quantitative trait loci (QTLs) for sucrose content have yet to be identified. In this study, a high-density genetic map was constructed based on whole-genome re-sequencing data from a peanut RIL population. This map consisted of 2,042 bins and 24,142 SNP markers, making it one of the most comprehensive maps to date in terms of marker density. Two major QTLs (qSCA06.2 and qSCB06.2) were identified, explaining 31.41% and 24.13% of the phenotypic variance, respectively. Notably, these two QTLs were located in homologous genomic regions between the A and B subgenomes. The elite allele of qSCA06.2 was exclusive to Valencia-type, while the elite allele of qSCB06.2 existed in other peanut types. Importantly, the distribution of alleles from two homologous QTLs in the RIL population and diverse germplasm accessions consistently demonstrated that only the combination of elite allelic genotypes from both QTLs/genes resulted in a significantly dominant phenotype, accompanied by a substantial increase in sucrose content. The newly developed diagnostic markers for these QTLs were confirmed to be reliable and could facilitate future breeding efforts to enhance sucrose content using marker-assisted selection techniques. Overall, this study highlights the co-regulation of sucrose content by two major homologous QTLs/genes and provides valuable insights into the genetic basis of sucrose in peanuts.
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Affiliation(s)
- Zhihui Wang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences (CAAS), Wuhan, 430062, China
- National Key Laboratory of Crop Genetic Improvement, National Center of Crop Molecular Breeding Technology, National Center of Oil Crop Improvement (Wuhan), Huazhong Agricultural University, Wuhan, 430070, China
| | - Yue Zhang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences (CAAS), Wuhan, 430062, China
| | - Dongxin Huai
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences (CAAS), Wuhan, 430062, China
| | - Yuning Chen
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences (CAAS), Wuhan, 430062, China
| | - Xin Wang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences (CAAS), Wuhan, 430062, China
| | - Yanping Kang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences (CAAS), Wuhan, 430062, China
| | - Liying Yan
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences (CAAS), Wuhan, 430062, China
| | - Huifang Jiang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences (CAAS), Wuhan, 430062, China
| | - Kede Liu
- National Key Laboratory of Crop Genetic Improvement, National Center of Crop Molecular Breeding Technology, National Center of Oil Crop Improvement (Wuhan), Huazhong Agricultural University, Wuhan, 430070, China.
| | - Yong Lei
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences (CAAS), Wuhan, 430062, China.
| | - Boshou Liao
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences (CAAS), Wuhan, 430062, China.
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Yun P, Zhang C, Ma T, Xia J, Zhou K, Wang Y, Li Z. Identification of qGL4.1 and qGL4.2, two closely linked QTL controlling grain length in rice. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2024; 44:11. [PMID: 38304382 PMCID: PMC10828150 DOI: 10.1007/s11032-024-01447-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 01/03/2024] [Indexed: 02/03/2024]
Abstract
Grain size is an important appearance quality trait in rice, which also affects grain yield. In this study, a recombinant inbred line (RIL) population derived from a cross between indica variety 9311 and japonica variety Cypress was constructed. And 181 out of 600 RILs were sequenced, and a high-density genetic map containing 2842 bin markers was constructed, with a total map length of 1500.6 cM. A total of 10 quantitative trait loci (QTL) related to grain length (GL), grain width (GW), grain length-to-width ratio (LWR), and 1000-grain weight (TGW) were detected under two environments. The genetic effect of qGL4, a minor QTL for GL and TGW, was validated using three heterogeneous inbred family (HIF) segregation populations. It was further dissected into two closed linked QTL, qGL4.1 and qGL4.2. By progeny testing, qGL4.1 and qGL4.2 were successfully delimited to intervals of 1304-kb and 423-kb, respectively. Our results lay the foundation for the map-based cloning of qGL4.1 and qGL4.2 and provide new gene resources for the improvement of grain yield and quality in rice. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-024-01447-y.
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Affiliation(s)
- Peng Yun
- Rice Research Institute/Key Laboratory of Rice Genetics and Breeding of Anhui Province, Anhui Academy of Agricultural Sciences, Hefei, 230031 China
| | - Caijuan Zhang
- Rice Research Institute/Key Laboratory of Rice Genetics and Breeding of Anhui Province, Anhui Academy of Agricultural Sciences, Hefei, 230031 China
| | - Tingchen Ma
- Rice Research Institute/Key Laboratory of Rice Genetics and Breeding of Anhui Province, Anhui Academy of Agricultural Sciences, Hefei, 230031 China
| | - Jiafa Xia
- Rice Research Institute/Key Laboratory of Rice Genetics and Breeding of Anhui Province, Anhui Academy of Agricultural Sciences, Hefei, 230031 China
| | - Kunneng Zhou
- Rice Research Institute/Key Laboratory of Rice Genetics and Breeding of Anhui Province, Anhui Academy of Agricultural Sciences, Hefei, 230031 China
| | - Yuanlei Wang
- Rice Research Institute/Key Laboratory of Rice Genetics and Breeding of Anhui Province, Anhui Academy of Agricultural Sciences, Hefei, 230031 China
| | - Zefu Li
- Rice Research Institute/Key Laboratory of Rice Genetics and Breeding of Anhui Province, Anhui Academy of Agricultural Sciences, Hefei, 230031 China
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12
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Zhao X, Xu Z, Chen Y, Du Y, Li M, Huang B, Ge Y, Gu M, Tang S, Liu Q, Zhang H. Development of introgression lines and mapping of qGW2, a novel QTL that confers grain width, in rice ( Oryza sativa L.). MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2024; 44:10. [PMID: 38298743 PMCID: PMC10825081 DOI: 10.1007/s11032-024-01453-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 01/19/2024] [Indexed: 02/02/2024]
Abstract
Rice grain size is a key determinant of both grain yield and quality. Identification of favorable alleles for use in rice breeding may help to meet the demand for increased yield. In this study, we developed a set of 210 introgression lines (ILs) by using indica variety Huanghuazhan as the donor parent and erect-panicle japonica rice variety Wuyujing3R as the recurrent parent. A total of 133 ILs were selected for high-throughput sequencing. Using specific-locus amplified fragment (SLAF) sequencing technology, 10,103 high-quality SLAF labels evenly distributed on 12 chromosomes were obtained and selected for subsequent analysis. Using a high-density map, quantitative trait locus (QTL) mapping of grain size-related traits was performed, and a total of 38 QTLs were obtained in two environments. Furthermore, qGW2, a novel QTL that controls grain width on chromosome 2, was validated and delimited to a region of 309 kb via substitution mapping. These findings provide new genetic material and a basis for future fine mapping and cloning of favorable QTLs. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-024-01453-0.
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Affiliation(s)
- Xiangqiang Zhao
- School of Life Sciences, Nantong University, Nantong, 226019 Jiangsu China
| | - Zuopeng Xu
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Zhongshan Biological Breeding Laboratory/Key Laboratory of Plant Functional Genomics of the Ministry of Education, Agricultural College of Yangzhou University, Yangzhou, 225009 China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops/Jiangsu Key Laboratory of Crop Genetics and Physiology, Yangzhou University, Yangzhou, 225009 China
| | - YiBo Chen
- Guangdong Academy of Agricultural Sciences, Rice Research Institute, Guangzhou, 510640 Guangdong China
| | - Yuanyue Du
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Zhongshan Biological Breeding Laboratory/Key Laboratory of Plant Functional Genomics of the Ministry of Education, Agricultural College of Yangzhou University, Yangzhou, 225009 China
| | - Meng Li
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Zhongshan Biological Breeding Laboratory/Key Laboratory of Plant Functional Genomics of the Ministry of Education, Agricultural College of Yangzhou University, Yangzhou, 225009 China
| | - Benxi Huang
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Zhongshan Biological Breeding Laboratory/Key Laboratory of Plant Functional Genomics of the Ministry of Education, Agricultural College of Yangzhou University, Yangzhou, 225009 China
| | - Yongshen Ge
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Zhongshan Biological Breeding Laboratory/Key Laboratory of Plant Functional Genomics of the Ministry of Education, Agricultural College of Yangzhou University, Yangzhou, 225009 China
| | - Minghong Gu
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Zhongshan Biological Breeding Laboratory/Key Laboratory of Plant Functional Genomics of the Ministry of Education, Agricultural College of Yangzhou University, Yangzhou, 225009 China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops/Jiangsu Key Laboratory of Crop Genetics and Physiology, Yangzhou University, Yangzhou, 225009 China
| | - Shuzhu Tang
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Zhongshan Biological Breeding Laboratory/Key Laboratory of Plant Functional Genomics of the Ministry of Education, Agricultural College of Yangzhou University, Yangzhou, 225009 China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops/Jiangsu Key Laboratory of Crop Genetics and Physiology, Yangzhou University, Yangzhou, 225009 China
| | - Qiaoquan Liu
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Zhongshan Biological Breeding Laboratory/Key Laboratory of Plant Functional Genomics of the Ministry of Education, Agricultural College of Yangzhou University, Yangzhou, 225009 China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops/Jiangsu Key Laboratory of Crop Genetics and Physiology, Yangzhou University, Yangzhou, 225009 China
| | - Honggen Zhang
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Zhongshan Biological Breeding Laboratory/Key Laboratory of Plant Functional Genomics of the Ministry of Education, Agricultural College of Yangzhou University, Yangzhou, 225009 China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops/Jiangsu Key Laboratory of Crop Genetics and Physiology, Yangzhou University, Yangzhou, 225009 China
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13
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Lamb HJ, Nguyen LT, Copley JP, Engle BN, Hayes BJ, Ross EM. Imputation strategies for genomic prediction using nanopore sequencing. BMC Biol 2023; 21:286. [PMID: 38066581 PMCID: PMC10709982 DOI: 10.1186/s12915-023-01782-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 11/27/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND Genomic prediction describes the use of SNP genotypes to predict complex traits and has been widely applied in humans and agricultural species. Genotyping-by-sequencing, a method which uses low-coverage sequence data paired with genotype imputation, is becoming an increasingly popular SNP genotyping method for genomic prediction. The development of Oxford Nanopore Technologies' (ONT) MinION sequencer has now made genotyping-by-sequencing portable and rapid. Here we evaluate the speed and accuracy of genomic predictions using low-coverage ONT sequence data in a population of cattle using four imputation approaches. We also investigate the effect of SNP reference panel size on imputation performance. RESULTS SNP array genotypes and ONT sequence data for 62 beef heifers were used to calculate genomic estimated breeding values (GEBVs) from 641 k SNP for four traits. GEBV accuracy was much higher when genome-wide flanking SNP from sequence data were used to help impute the 641 k panel used for genomic predictions. Using the imputation package QUILT, correlations between ONT and low-density SNP array genomic breeding values were greater than 0.91 and up to 0.97 for sequencing coverages as low as 0.1 × using a reference panel of 48 million SNP. Imputation time was significantly reduced by decreasing the number of flanking sequence SNP used in imputation for all methods. When compared to high-density SNP arrays, genotyping accuracy and genomic breeding value correlations at 0.5 × coverage were also found to be higher than those imputed from low-density arrays. CONCLUSIONS Here we demonstrated accurate genomic prediction is possible with ONT sequence data from sequencing coverages as low as 0.1 × , and imputation time can be as short as 10 min per sample. We also demonstrate that in this population, genotyping-by-sequencing at 0.1 × coverage can be more accurate than imputation from low-density SNP arrays.
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Affiliation(s)
- H J Lamb
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St. Lucia, QLD, 4067, Australia.
| | - L T Nguyen
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St. Lucia, QLD, 4067, Australia
| | - J P Copley
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St. Lucia, QLD, 4067, Australia
| | - B N Engle
- USDA, ARS, U.S. Meat Animal Research Centre, Clay Centre, NE, 68933, USA
| | - B J Hayes
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St. Lucia, QLD, 4067, Australia
| | - E M Ross
- Centre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St. Lucia, QLD, 4067, Australia
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14
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Luo H, Zhang Y, Liu F, Zhao Y, Peng J, Xu Y, Chen X, Huang Y, Ji C, Liu Q, He P, Feng P, Yang C, Wei P, Ma Z, Qin J, Zhou S, Dai S, Zhang Y, Zhao Z, Liu H, Zheng H, Zhang J, Lin Y, Chen X. The male and female genomes of golden pompano (Trachinotus ovatus) provide insights into the sex chromosome evolution and rapid growth. J Adv Res 2023:S2090-1232(23)00369-7. [PMID: 38043610 DOI: 10.1016/j.jare.2023.11.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Revised: 11/19/2023] [Accepted: 11/24/2023] [Indexed: 12/05/2023] Open
Abstract
INTRODUCTION Golden pompano (Trachinotus ovatus) is economically significant important for offshore cage aquaculture in China and Southeast Asian countries. Lack of high-quality genomic data and accurate gene annotations greatly restricts its genetic breeding progress. OBJECTIVES To decode the mechanisms of sex determination and rapid growth in golden pompano and facilitate the sex- and growth-aimed genetic breeding. METHODS Genome assemblies of male and female golden pompano were generated using Illumina, PacBio, BioNano, genetic maps and Hi-C sequencing data. Genomic comparisons, whole genome re-sequencing of 202 F1 individuals, QTL mapping and gonadal transcriptomes were used to analyze the sex determining region, sex chromosome evolution, SNP loci, and growth candidate genes. Zebrafish model was used to investigate the functions of growth candidate gene. RESULTS Female (644.45 Mb) and male (652.12 Mb) genomes of golden pompano were assembled and annotated at the chromosome level. Both genomes are highly conserved and no new or highly differentiated sex chromosomes occur. A 3.5 Mb sex determining region on LG15 was identified, where Hsd17b1, Micall2 and Lmx1a were putative candidates for sex determination. Three SNP loci significantly linked to growth were pinpointed, and a growth-linked gene gpsstr1 was identified by locus BSNP1369 (G→C, 17489695, Chr23). Loss of sstr1a (homologue of gpsstr1) in zebrafish caused growth retardation. CONCLUSION This study provides insights into sex chromosome evolution, sex determination and rapid growth of golden pompano.
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Affiliation(s)
- Honglin Luo
- Guangxi Key Laboratory for Aquatic Genetic Breeding and Healthy Aquaculture, Guangxi Academy of Fishery Sciences, Nanning, 530021, China; Institute of Oncology, Guangxi Academy of Medical Sciences, Nanning, Guangxi, 530021, China
| | - Yongde Zhang
- Guangxi Key Laboratory for Aquatic Genetic Breeding and Healthy Aquaculture, Guangxi Academy of Fishery Sciences, Nanning, 530021, China
| | - Fuyan Liu
- Biomarker Technologies, Beijing, 101300, China; BGI-Beijing, Beijing, 102601, China
| | - Yongzhen Zhao
- Guangxi Key Laboratory for Aquatic Genetic Breeding and Healthy Aquaculture, Guangxi Academy of Fishery Sciences, Nanning, 530021, China
| | - Jinxia Peng
- Guangxi Key Laboratory for Aquatic Genetic Breeding and Healthy Aquaculture, Guangxi Academy of Fishery Sciences, Nanning, 530021, China
| | - Yuhui Xu
- Biomarker Technologies, Beijing, 101300, China
| | - Xiuli Chen
- Guangxi Key Laboratory for Aquatic Genetic Breeding and Healthy Aquaculture, Guangxi Academy of Fishery Sciences, Nanning, 530021, China
| | - Yin Huang
- Guangxi Key Laboratory for Aquatic Genetic Breeding and Healthy Aquaculture, Guangxi Academy of Fishery Sciences, Nanning, 530021, China
| | | | - Qingyun Liu
- Guangxi Key Laboratory for Aquatic Genetic Breeding and Healthy Aquaculture, Guangxi Academy of Fishery Sciences, Nanning, 530021, China
| | - Pingping He
- Guangxi Key Laboratory for Aquatic Genetic Breeding and Healthy Aquaculture, Guangxi Academy of Fishery Sciences, Nanning, 530021, China
| | - Pengfei Feng
- Guangxi Key Laboratory for Aquatic Genetic Breeding and Healthy Aquaculture, Guangxi Academy of Fishery Sciences, Nanning, 530021, China
| | - Chunling Yang
- Guangxi Key Laboratory for Aquatic Genetic Breeding and Healthy Aquaculture, Guangxi Academy of Fishery Sciences, Nanning, 530021, China
| | - Pinyuan Wei
- Guangxi Key Laboratory for Aquatic Genetic Breeding and Healthy Aquaculture, Guangxi Academy of Fishery Sciences, Nanning, 530021, China
| | - Zhenhua Ma
- South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, 510300, China
| | - Jianguang Qin
- College of Science and Engineering, Flinders University, GPO Box 2100, Adelaide, South Australia 5001, Australia
| | - Shengjie Zhou
- Sanya Tropical Fisheries Research Institute, Sanya, 572018, China
| | - Shiming Dai
- Sanya Tropical Fisheries Research Institute, Sanya, 572018, China
| | - Yaoyao Zhang
- The Pirbright Institute, Ash Road, Pirbright, Woking, Surrey, GU24 0NF, UK
| | - Zhongquan Zhao
- College of Animal Science and Technology, Southwest University, Beibei, Chongqing, 400715, China
| | | | - Hongkun Zheng
- Biomarker Technologies, Beijing, 101300, China; Institute of Oncology, Guangxi Academy of Medical Sciences, Nanning, Guangxi, 530021, China.
| | - Jisen Zhang
- Center for Genomics and Biotechnology, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, China; State Key Lab for Conservation and Utilization of Subtropical Agro-Biological Resources & Guangxi Key Lab for Sugarcane Biology, Guangxi University, Nanning, China.
| | - Yong Lin
- Guangxi Key Laboratory for Aquatic Genetic Breeding and Healthy Aquaculture, Guangxi Academy of Fishery Sciences, Nanning, 530021, China.
| | - Xiaohan Chen
- Guangxi Key Laboratory for Aquatic Genetic Breeding and Healthy Aquaculture, Guangxi Academy of Fishery Sciences, Nanning, 530021, China.
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15
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Ma X, Feng L, Tao A, Zenda T, He Y, Zhang D, Duan H, Tao Y. Identification and validation of seed dormancy loci and candidate genes and construction of regulatory networks by WGCNA in maize introgression lines. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:259. [PMID: 38038768 DOI: 10.1007/s00122-023-04495-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 10/26/2023] [Indexed: 12/02/2023]
Abstract
KEY MESSAGE Seventeen PHS-QTLs and candidate genes were obtained, including eleven major loci, three under multiple environments and two with co-localization by the other mapping methods; The functions of three candidate genes were validated using mutants; nine target proteins and five networks were filtered by joint analysis of GWAS and WGCNA. Seed dormancy (SD) and pre-harvest sprouting (PHS) affect yield, as well as grain and hybrid quality in seed production. Therefore, identification of genetic and regulatory pathways underlying PHS and SD is key to gene function analysis, allelic variation mining and genetic improvement. In this study, 78,360 SNPs by SLAF-seq of 230 maize chromosome segment introgression lines (ILs), PHS under five environments were used to conduct GWAS (genome wide association study) (a threshold of 1/n), and seventeen unreported PHS QTLs were obtained, including eleven QTLs with PVE > 10% and three QTLs under multiple environments. Two QTL loci were co-located between the other two genetic mapping methods. Using differential gene expression analyses at two stages of grain development, gene functional analysis of Arabidopsis mutants, and gene functional analysis in the QTL region, seventeen PHS QTL-linked candidate genes were identified, and their five molecular regulatory networks constructed. Based on the Arabidopsis T-DNA mutations, three candidate genes were shown to regulate for SD and PHS. Meanwhile, using RNA-seq of grain development, the weighted correlation network analysis (WGCNA) was performed, deducing five regulatory pathways and target genes that regulate PHS and SD. Based on the conjoint analysis of GWAS and WGCNA, four pathways, nine target proteins and target genes were revealed, most of which regulate cell wall metabolism, cell proliferation and seed dehydration tolerance. This has important theoretical and practical significance for elucidating the genetic basis of maize PHS and SD, as well as mining of genetic resources and genetic improvement of traits.
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Affiliation(s)
- Xiaolin Ma
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of the Education Ministry, College of Agronomy, Hebei Agricultural University, Baoding, 071001, China
| | - Liqing Feng
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of the Education Ministry, College of Agronomy, Hebei Agricultural University, Baoding, 071001, China
| | - Anyan Tao
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of the Education Ministry, College of Agronomy, Hebei Agricultural University, Baoding, 071001, China
| | - Tinashe Zenda
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of the Education Ministry, College of Agronomy, Hebei Agricultural University, Baoding, 071001, China
| | - Yuan He
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of the Education Ministry, College of Agronomy, Hebei Agricultural University, Baoding, 071001, China
| | - Daxiao Zhang
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of the Education Ministry, College of Agronomy, Hebei Agricultural University, Baoding, 071001, China
| | - Huijun Duan
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of the Education Ministry, College of Agronomy, Hebei Agricultural University, Baoding, 071001, China.
| | - Yongsheng Tao
- State Key Laboratory of North China Crop Improvement and Regulation, North China Key Laboratory for Crop Germplasm Resources of the Education Ministry, College of Agronomy, Hebei Agricultural University, Baoding, 071001, China.
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16
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Zhu Y, Ma T, Lin Y, Peng Y, Huang Y, Jiang J. SSR molecular marker developments and genetic diversity analysis of Zanthoxylum nitidum (Roxb.) DC. Sci Rep 2023; 13:20767. [PMID: 38008750 PMCID: PMC10679188 DOI: 10.1038/s41598-023-48022-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 11/21/2023] [Indexed: 11/28/2023] Open
Abstract
Zanthoxylum nitidum (Roxb.) is a commonly used traditional Chinese medicine. However, the collection and protection of wild germplasm resources of Z. nitidum are still insufficient, and there is limited research on its genetic diversity and fingerprint. In the present study, 15 simple sequence repeat (SSR) markers were developed by genotyping based on multiplexed shotgun sequencing. The genetic diversity of 51 populations (142 individuals) of Z. nitidum was evaluated using these 15 SSRs. A total of 245 alleles (Na) were detected, with an average value of 16.333, and the average polymorphism information content was 0.756. The genetic distance among 51 populations was 0.164~1.000, with an average of 0.659. Analysis of molecular variance showed low genetic differentiation (40%) and high genetic differentiation (60%) between populations and individuals, respectively. The genetic differentiation coefficient (Fst) of the population was 0.338, indicating that 66.2% of the genetic variation occurred within the population, and the gene flow (Nm) was 0.636, demonstrating that the gene exchange between populations was low. Clustering analysis revealed that the genetic similarity coefficient was 0.30, dividing the 51 populations into 4 groups of 2, 17, 3, and 29 populations. There was no specific relationship between geographical location differences and genetic distance. The genetic diversity level of Z. nitidum is relatively high, and our results provide a theoretical basis for the rapid identification of Z. nitidum germplasm resources and variety selection.
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Affiliation(s)
- Yanxia Zhu
- National Center for Traditional Chinese Medicine Inheritance and Innovation, Guangxi Botanical Garden of Medicinal Plants, Nanning, 530023, China
| | - Tao Ma
- College of Agriculture and Engineering, Guangxi Vocational University of Agriculture, Nanning, 530009, China
| | - Yang Lin
- National Center for Traditional Chinese Medicine Inheritance and Innovation, Guangxi Botanical Garden of Medicinal Plants, Nanning, 530023, China
| | - Yude Peng
- National Center for Traditional Chinese Medicine Inheritance and Innovation, Guangxi Botanical Garden of Medicinal Plants, Nanning, 530023, China
| | - Yuan Huang
- National Center for Traditional Chinese Medicine Inheritance and Innovation, Guangxi Botanical Garden of Medicinal Plants, Nanning, 530023, China
| | - Jianping Jiang
- National Center for Traditional Chinese Medicine Inheritance and Innovation, Guangxi Botanical Garden of Medicinal Plants, Nanning, 530023, China.
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17
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Guo N, Han S, Zong M, Wang G, Duan M, Liu F. Construction and Application of an F1-Derived Doubled-Haploid Population and High-Density Genetic Map for Ornamental Kale Breeding. Genes (Basel) 2023; 14:2104. [PMID: 38003047 PMCID: PMC10670981 DOI: 10.3390/genes14112104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Revised: 11/14/2023] [Accepted: 11/17/2023] [Indexed: 11/26/2023] Open
Abstract
Ornamental kale (Brassica oleracea var. acephala) is an attractive ornamental plant with a range of leaf colors and shapes. Breeding new varieties of ornamental kale has proven challenging due to its lengthy breeding cycle and the limited availability of genetic markers. In this study, a F1DH ornamental kale population comprising 300 DH lines was constructed using microspore culture. A high-density genetic map was developed by conducting whole-genome sequencing on 150 individuals from the F1DH population. The genetic map contained 1696 bin markers with 982,642 single-nucleotide polymorphisms (SNPs) spanning a total distance of 775.81 cM on all nine chromosomes with an average distance between markers of 0.46 cM. The ornamental kale genetic map contained substantially more SNP markers compared with published genetic maps for other B. oleracea crops. Furthermore, utilizing this high-density genetic map, we identified seven quantitative trait loci (QTLs) that significantly influence the leaf shape of ornamental kale. These findings are valuable for understanding the genetic basis of key agronomic traits in ornamental kale. The F1DH progenies provide an excellent resource for germplasm innovation and breeding new varieties of ornamental kale. Additionally, the high-density genetic map provides crucial insights for gene mapping and unraveling the molecular mechanisms behind important agronomic traits in ornamental kale.
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Affiliation(s)
| | | | | | | | | | - Fan Liu
- State Key Laboratory of Vegetable Biobreeding, National Engineering Research Center for Vegetables, Beijing Key Laboratory of Vegetable Germplasms Improvement, Key Laboratory of Biology and Genetics Improvement of Horticultural Crops (North China), Beijing Vegetable Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China; (N.G.); (S.H.); (M.Z.); (G.W.); (M.D.)
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18
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Arifuzzaman M, Mamidi S, Sanz-Saez A, Zakeri H, Scaboo A, Fritschi FB. Identification of loci associated with water use efficiency and symbiotic nitrogen fixation in soybean. FRONTIERS IN PLANT SCIENCE 2023; 14:1271849. [PMID: 38034552 PMCID: PMC10687445 DOI: 10.3389/fpls.2023.1271849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 10/20/2023] [Indexed: 12/02/2023]
Abstract
Soybean (Glycine max) production is greatly affected by persistent and/or intermittent droughts in rainfed soybean-growing regions worldwide. Symbiotic N2 fixation (SNF) in soybean can also be significantly hampered even under moderate drought stress. The objective of this study was to identify genomic regions associated with shoot carbon isotope ratio (δ13C) as a surrogate measure for water use efficiency (WUE), nitrogen isotope ratio (δ15N) to assess relative SNF, N concentration ([N]), and carbon/nitrogen ratio (C/N). Genome-wide association mapping was performed with 105 genotypes and approximately 4 million single-nucleotide polymorphism markers derived from whole-genome resequencing information. A total of 11, 21, 22, and 22 genomic loci associated with δ13C, δ15N, [N], and C/N, respectively, were identified in two environments. Nine of these 76 loci were stable across environments, as they were detected in both environments. In addition to the 62 novel loci identified, 14 loci aligned with previously reported quantitative trait loci for different C and N traits related to drought, WUE, and N2 fixation in soybean. A total of 58 Glyma gene models encoding for different genes related to the four traits were identified in the vicinity of the genomic loci.
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Affiliation(s)
- Muhammad Arifuzzaman
- Division of Plant Science and Technology, University of Missouri, Columbia, MO, United States
| | - Sujan Mamidi
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, United States
| | - Alvaro Sanz-Saez
- Department of Crop, Soil and Environmental Sciences, Auburn University, Auburn, AL, United States
| | - Hossein Zakeri
- College of Agriculture, California State University-Chico, Chico, CA, United States
| | - Andrew Scaboo
- Division of Plant Science and Technology, University of Missouri, Columbia, MO, United States
| | - Felix B. Fritschi
- Division of Plant Science and Technology, University of Missouri, Columbia, MO, United States
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19
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Zhang Y, Li J, Chu P, Shang R, Yin S, Wang T. Construction of a high-density genetic linkage map and QTL mapping of growth and cold tolerance traits in Takifugu fasciatus. BMC Genomics 2023; 24:645. [PMID: 37891474 PMCID: PMC10604518 DOI: 10.1186/s12864-023-09740-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2023] [Accepted: 10/13/2023] [Indexed: 10/29/2023] Open
Abstract
Takifugu fasciatus is an aquaculture species with high economic value. In recent years, problems such as environmental pollution and inbreeding have caused a serious decline in T. fasciatus germplasm resources. In this study, a high-density genetic linkage map was constructed by whole-genome resequencing. The map consists of 4891 bin markers distributed across 22 linkage groups (LGs), with a total genetic coverage of 2381.353 cM and a mean density of 0.535 cM. Quantitative trait locus (QTL) localization analysis showed that a total of 19 QTLs associated with growth traits of T. fasciatus in the genome-wide significance threshold range, distributed on 11 LGs. In addition, 11 QTLs associated with cold tolerance traits were identified, each scattered on a different LG. Furthermore, we used QTL localization analysis to screen out three candidate genes (IGF1, IGF2, ADGRB) related to growth in T. fasciatus. Meanwhile, we screened three candidate genes (HSP90, HSP70, and HMGB1) related to T. fasciatus cold tolerance. Our study can provide a theoretical basis for the selection and breeding of cold-tolerant or fast-growing T. fasciatus.
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Affiliation(s)
- Ying Zhang
- College of Marine Science and Engineering, Nanjing Normal University, Nanjing, 210023, Jiangsu, China
| | - Jie Li
- College of Marine Science and Engineering, Nanjing Normal University, Nanjing, 210023, Jiangsu, China
| | - Peng Chu
- College of Marine Science and Engineering, Nanjing Normal University, Nanjing, 210023, Jiangsu, China
| | - Ruhua Shang
- College of Marine Science and Engineering, Nanjing Normal University, Nanjing, 210023, Jiangsu, China
| | - Shaowu Yin
- College of Marine Science and Engineering, Nanjing Normal University, Nanjing, 210023, Jiangsu, China
| | - Tao Wang
- College of Marine Science and Engineering, Nanjing Normal University, Nanjing, 210023, Jiangsu, China.
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20
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Della Coletta R, Fernandes SB, Monnahan PJ, Mikel MA, Bohn MO, Lipka AE, Hirsch CN. Importance of genetic architecture in marker selection decisions for genomic prediction. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:220. [PMID: 37819415 DOI: 10.1007/s00122-023-04469-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 09/25/2023] [Indexed: 10/13/2023]
Abstract
KEY MESSAGE We demonstrate potential for improved multi-environment genomic prediction accuracy using structural variant markers. However, the degree of observed improvement is highly dependent on the genetic architecture of the trait. Breeders commonly use genetic markers to predict the performance of untested individuals as a way to improve the efficiency of breeding programs. These genomic prediction models have almost exclusively used single nucleotide polymorphisms (SNPs) as their source of genetic information, even though other types of markers exist, such as structural variants (SVs). Given that SVs are associated with environmental adaptation and not all of them are in linkage disequilibrium to SNPs, SVs have the potential to bring additional information to multi-environment prediction models that are not captured by SNPs alone. Here, we evaluated different marker types (SNPs and/or SVs) on prediction accuracy across a range of genetic architectures for simulated traits across multiple environments. Our results show that SVs can improve prediction accuracy, but it is highly dependent on the genetic architecture of the trait and the relative gain in accuracy is minimal. When SVs are the only causative variant type, 70% of the time SV predictors outperform SNP predictors. However, the improvement in accuracy in these instances is only 1.5% on average. Further simulations with predictors in varying degrees of LD with causative variants of different types (e.g., SNPs, SVs, SNPs and SVs) showed that prediction accuracy increased as linkage disequilibrium between causative variants and predictors increased regardless of the marker type. This study demonstrates that knowing the genetic architecture of a trait in deciding what markers to use in large-scale genomic prediction modeling in a breeding program is more important than what types of markers to use.
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Affiliation(s)
- Rafael Della Coletta
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108, USA
| | - Samuel B Fernandes
- Department of Crop, Soil and Environmental Sciences at University of Arkansas, Fayetteville, AR, 72701, USA
| | - Patrick J Monnahan
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108, USA
| | - Mark A Mikel
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
- Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Martin O Bohn
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Alexander E Lipka
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA
| | - Candice N Hirsch
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108, USA.
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21
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Gu Z, Gong J, Zhu Z, Li Z, Feng Q, Wang C, Zhao Y, Zhan Q, Zhou C, Wang A, Huang T, Zhang L, Tian Q, Fan D, Lu Y, Zhao Q, Huang X, Yang S, Han B. Structure and function of rice hybrid genomes reveal genetic basis and optimal performance of heterosis. Nat Genet 2023; 55:1745-1756. [PMID: 37679493 PMCID: PMC10562254 DOI: 10.1038/s41588-023-01495-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 08/02/2023] [Indexed: 09/09/2023]
Abstract
Exploitation of crop heterosis is crucial for increasing global agriculture production. However, the quantitative genomic analysis of heterosis was lacking, and there is currently no effective prediction tool to optimize cross-combinations. Here 2,839 rice hybrid cultivars and 9,839 segregation individuals were resequenced and phenotyped. Our findings demonstrated that indica-indica hybrid-improving breeding was a process that broadened genetic resources, pyramided breeding-favorable alleles through combinatorial selection and collaboratively improved both parents by eliminating the inferior alleles at negative dominant loci. Furthermore, we revealed that widespread genetic complementarity contributed to indica-japonica intersubspecific heterosis in yield traits, with dominance effect loci making a greater contribution to phenotypic variance than overdominance effect loci. On the basis of the comprehensive dataset, a genomic model applicable to diverse rice varieties was developed and optimized to predict the performance of hybrid combinations. Our data offer a valuable resource for advancing the understanding and facilitating the utilization of heterosis in rice.
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Affiliation(s)
- Zhoulin Gu
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - Junyi Gong
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, China
| | - Zhou Zhu
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Zhen Li
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
- College of Life Sciences, Anhui Normal University, Wuhu, China
| | - Qi Feng
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - Changsheng Wang
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - Yan Zhao
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - Qilin Zhan
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - Congcong Zhou
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - Ahong Wang
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - Tao Huang
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - Lei Zhang
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - Qilin Tian
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - Danlin Fan
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - Yiqi Lu
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - Qiang Zhao
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - Xuehui Huang
- College of Life Sciences, Shanghai Normal University, Shanghai, China
| | - Shihua Yang
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, China.
| | - Bin Han
- National Center for Gene Research, State Key Laboratory of Plant Molecular Genetics, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China.
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22
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Song J, Liu K, Yang X, Chen Y, Xiong Y, Yang Q, Wang J, Zhang Z, Wu C, Wang J, Qiu L. QTL Mapping of Soybean ( Glycine max) Vine Growth Habit Trait. Int J Mol Sci 2023; 24:14770. [PMID: 37834218 PMCID: PMC10572949 DOI: 10.3390/ijms241914770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 09/15/2023] [Accepted: 09/28/2023] [Indexed: 10/15/2023] Open
Abstract
The vine growth habit (VGH) is a notable property of wild soybean plants that also holds a high degree of importance in domestication as it can preclude using these wild cultivars for breeding and improving domesticated soybeans. Here, a bulked segregant analysis (BSA) approach was employed to study the genetic etiology of the VGH in soybean plants by integrating linkage mapping and population sequencing approaches. To develop a recombinant inbred line (RIL) population, the cultivated Zhongdou41 (ZD41) soybean cultivar was bred with ZYD02787, a wild soybean accession. The VGH status of each line in the resultant population was assessed, ultimately leading to the identification of six and nine QTLs from the BSA sequencing of the F4 population and F6-F8 population sequence mapping, respectively. One QTL shared across these analyzed generations was detected on chromosome 19. Three other QTLs detected by BSA-seq were validated and localized to the 90.93 kb, 2.9 Mb, and 602.08 kb regions of chromosomes 6 and 13, harboring 14, 53, and 4 genes, respectively. Three consistent VGH-related QTLs located on chromosomes 2 and 19 were detected in a minimum of three environments, while an additional six loci on chromosomes 2, 10, 13, and 18 were detected in at least two environments via ICIM mapping. Of all the detected loci, five had been reported previously whereas seven represent novel QTLs. Together, these data offer new insights into the genetic basis of the VGH in soybean plants, providing a rational basis to inform the use of wild accessions in future breeding efforts.
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Affiliation(s)
- Jian Song
- College of Life Science, Yangtze University, Jingzhou 434025, China; (J.S.); (C.W.)
| | - Kanglin Liu
- College of Agriculture, Yangtze University, Jingzhou 434025, China; (K.L.); (X.Y.); (Y.C.); (Y.X.); (Q.Y.); (J.W.)
| | - Xuezhen Yang
- College of Agriculture, Yangtze University, Jingzhou 434025, China; (K.L.); (X.Y.); (Y.C.); (Y.X.); (Q.Y.); (J.W.)
| | - Yijie Chen
- College of Agriculture, Yangtze University, Jingzhou 434025, China; (K.L.); (X.Y.); (Y.C.); (Y.X.); (Q.Y.); (J.W.)
| | - Yajun Xiong
- College of Agriculture, Yangtze University, Jingzhou 434025, China; (K.L.); (X.Y.); (Y.C.); (Y.X.); (Q.Y.); (J.W.)
| | - Qichao Yang
- College of Agriculture, Yangtze University, Jingzhou 434025, China; (K.L.); (X.Y.); (Y.C.); (Y.X.); (Q.Y.); (J.W.)
| | - Jing Wang
- College of Agriculture, Yangtze University, Jingzhou 434025, China; (K.L.); (X.Y.); (Y.C.); (Y.X.); (Q.Y.); (J.W.)
| | - Zhihao Zhang
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China;
| | - Caiyu Wu
- College of Life Science, Yangtze University, Jingzhou 434025, China; (J.S.); (C.W.)
| | - Jun Wang
- College of Agriculture, Yangtze University, Jingzhou 434025, China; (K.L.); (X.Y.); (Y.C.); (Y.X.); (Q.Y.); (J.W.)
| | - Lijuan Qiu
- National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China;
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Xu F, Valappil AK, Mathiyalagan R, Tran TNA, Ramadhania ZM, Awais M, Yang DC. In Vitro Cultivation and Ginsenosides Accumulation in Panax ginseng: A Review. PLANTS (BASEL, SWITZERLAND) 2023; 12:3165. [PMID: 37687411 PMCID: PMC10489967 DOI: 10.3390/plants12173165] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 08/03/2023] [Accepted: 08/10/2023] [Indexed: 09/10/2023]
Abstract
The use of in vitro tissue culture for herbal medicines has been recognized as a valuable source of botanical secondary metabolites. The tissue culture of ginseng species is used in the production of bioactive compounds such as phenolics, polysaccharides, and especially ginsenosides, which are utilized in the food, cosmetics, and pharmaceutical industries. This review paper focuses on the in vitro culture of Panax ginseng and accumulation of ginsenosides. In vitro culture has been applied to study organogenesis and biomass culture, and is involved in direct organogenesis for rooting and shooting from explants and in indirect morphogenesis for somatic embryogenesis via the callus, which is a mass of disorganized cells. Biomass production was conducted with different types of tissue cultures, such as adventitious roots, cell suspension, and hairy roots, and subsequently on a large scale in a bioreactor. This review provides the cumulative knowledge of biotechnological methods to increase the ginsenoside resources of P. ginseng. In addition, ginsenosides are summarized at enhanced levels of activity and content with elicitor treatment, together with perspectives of new breeding tools which can be developed in P. ginseng in the future.
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Affiliation(s)
- Fengjiao Xu
- Graduate School of Biotechnology, College of Life Sciences, Kyung Hee University, Yongin-si 17104, Gyeonggi-do, Republic of Korea; (F.X.); (T.N.A.T.); (Z.M.R.); (M.A.)
| | - Anjali Kariyarath Valappil
- Department of Biopharmaceutical Biotechnology, College of Life Science, Kyung Hee University, Yongin-si 17104, Gyeonggi-do, Republic of Korea; (A.K.V.); (R.M.)
| | - Ramya Mathiyalagan
- Department of Biopharmaceutical Biotechnology, College of Life Science, Kyung Hee University, Yongin-si 17104, Gyeonggi-do, Republic of Korea; (A.K.V.); (R.M.)
| | - Thi Ngoc Anh Tran
- Graduate School of Biotechnology, College of Life Sciences, Kyung Hee University, Yongin-si 17104, Gyeonggi-do, Republic of Korea; (F.X.); (T.N.A.T.); (Z.M.R.); (M.A.)
| | - Zelika Mega Ramadhania
- Graduate School of Biotechnology, College of Life Sciences, Kyung Hee University, Yongin-si 17104, Gyeonggi-do, Republic of Korea; (F.X.); (T.N.A.T.); (Z.M.R.); (M.A.)
| | - Muhammad Awais
- Graduate School of Biotechnology, College of Life Sciences, Kyung Hee University, Yongin-si 17104, Gyeonggi-do, Republic of Korea; (F.X.); (T.N.A.T.); (Z.M.R.); (M.A.)
| | - Deok Chun Yang
- Graduate School of Biotechnology, College of Life Sciences, Kyung Hee University, Yongin-si 17104, Gyeonggi-do, Republic of Korea; (F.X.); (T.N.A.T.); (Z.M.R.); (M.A.)
- Department of Biopharmaceutical Biotechnology, College of Life Science, Kyung Hee University, Yongin-si 17104, Gyeonggi-do, Republic of Korea; (A.K.V.); (R.M.)
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Yan H, Wang K, Wang M, Feng L, Zhang H, Wei X. QTL Mapping and Genome-Wide Association Study Reveal Genetic Loci and Candidate Genes Related to Soluble Solids Content in Melon. Curr Issues Mol Biol 2023; 45:7110-7129. [PMID: 37754234 PMCID: PMC10530127 DOI: 10.3390/cimb45090450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 08/21/2023] [Accepted: 08/25/2023] [Indexed: 09/28/2023] Open
Abstract
Melon (Cucumis melo L.) is an economically important Cucurbitaceae crop grown around the globe. The sweetness of melon is a significant factor in fruit quality and consumer appeal, and the soluble solids content (SSC) is a key index of melon sweetness. In this study, 146 recombinant inbred lines (RILs) derived from two oriental melon materials with different levels of sweetness containing 1427 bin markers, and 213 melon accessions containing 1,681,775 single nucleotide polymorphism (SNP) markers were used to identify genomic regions influencing SSC. Linkage mapping detected 10 quantitative trait loci (QTLs) distributed on six chromosomes, seven of which were overlapped with the reported QTLs. A total of 211 significant SNPs were identified by genome-wide association study (GWAS), 138 of which overlapped with the reported QTLs. Two new stable, co-localized regions on chromosome 3 were identified by QTL mapping and GWAS across multiple environments, which explained large phenotypic variance. Five candidate genes related to SSC were identified by QTL mapping, GWAS, and qRT-PCR, two of which were involved in hydrolysis of raffinose and sucrose located in the new stable loci. The other three candidate genes were involved in raffinose synthesis, sugar transport, and production of substrate for sugar synthesis. The genomic regions and candidate genes will be helpful for molecular breeding programs and elucidating the mechanisms of sugar accumulation.
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Saripalli G, Adhikari L, Amos C, Kibriya A, Ahmed HI, Heuberger M, Raupp J, Athiyannan N, Wicker T, Abrouk M, Wallace S, Hosseinirad S, Chhuneja P, Livesay J, Rawat N, Krattinger SG, Poland J, Tiwari V. Integration of genetic and genomics resources in einkorn wheat enables precision mapping of important traits. Commun Biol 2023; 6:835. [PMID: 37573415 PMCID: PMC10423216 DOI: 10.1038/s42003-023-05189-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 07/26/2023] [Indexed: 08/14/2023] Open
Abstract
Einkorn wheat (Triticum monococcum) is an ancient grain crop and a close relative of the diploid progenitor (T. urartu) of polyploid wheat. It is the only diploid wheat species having both domesticated and wild forms and therefore provides an excellent system to identify domestication genes and genes for traits of interest to utilize in wheat improvement. Here, we leverage genomic advancements for einkorn wheat using an einkorn reference genome assembly combined with skim-sequencing of a large genetic population of 812 recombinant inbred lines (RILs) developed from a cross between a wild and a domesticated T. monococcum accession. We identify 15,919 crossover breakpoints delimited to a median and average interval of 114 Kbp and 219 Kbp, respectively. This high-resolution mapping resource enables us to perform fine-scale mapping of one qualitative (red coleoptile) and one quantitative (spikelet number per spike) trait, resulting in the identification of small physical intervals (400 Kb to 700 Kb) with a limited number of candidate genes. Furthermore, an important domestication locus for brittle rachis is also identified on chromosome 7A. This resource presents an exciting route to perform trait discovery in diploid wheat for agronomically important traits and their further deployment in einkorn as well as tetraploid pasta wheat and hexaploid bread wheat cultivars.
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Affiliation(s)
- Gautam Saripalli
- Department of Plant Science and Landscape Architecture, University of Maryland, College Park, MD, 20783, USA
| | - Laxman Adhikari
- Plant Science Program, Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia
- Center for Desert Agriculture, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Cameron Amos
- Department of Plant Pathology, Kansas State University, Manhattan, KS, 66506, USA
| | - Ashraf Kibriya
- Plant Science Program, Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia
| | - Hanin Ibrahim Ahmed
- Plant Science Program, Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia
- Center for Desert Agriculture, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Matthias Heuberger
- Department of Plant and Microbial Biology, University of Zurich, Zurich, Switzerland
| | - John Raupp
- Wheat Genetics Resource Center and Department of Plant Pathology, Kansas State University, Manhattan, KS, 66506, USA
| | - Naveenkumar Athiyannan
- Plant Science Program, Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia
- Center for Desert Agriculture, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Thomas Wicker
- Department of Plant and Microbial Biology, University of Zurich, Zurich, Switzerland
| | - Michael Abrouk
- Plant Science Program, Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia
- Center for Desert Agriculture, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Sydney Wallace
- Department of Plant Science and Landscape Architecture, University of Maryland, College Park, MD, 20783, USA
| | - Seyedali Hosseinirad
- Department of Plant Science and Landscape Architecture, University of Maryland, College Park, MD, 20783, USA
| | - Parveen Chhuneja
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana, 141004, Punjab, India
| | - Janelle Livesay
- Department of Plant Science and Landscape Architecture, University of Maryland, College Park, MD, 20783, USA
| | - Nidhi Rawat
- Department of Plant Science and Landscape Architecture, University of Maryland, College Park, MD, 20783, USA
| | - Simon G Krattinger
- Plant Science Program, Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia
- Center for Desert Agriculture, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Jesse Poland
- Plant Science Program, Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Saudi Arabia.
- Center for Desert Agriculture, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.
| | - Vijay Tiwari
- Department of Plant Science and Landscape Architecture, University of Maryland, College Park, MD, 20783, USA.
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26
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Wei M, Luo T, Huang D, Ma Z, Liu C, Qin Y, Wu Z, Zhou X, Lu Y, Yan L, Qin G, Zhang Y. Construction of High-Density Genetic Map and QTL Mapping for Grain Shape in the Rice RIL Population. PLANTS (BASEL, SWITZERLAND) 2023; 12:2911. [PMID: 37631123 PMCID: PMC10458266 DOI: 10.3390/plants12162911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 08/07/2023] [Accepted: 08/07/2023] [Indexed: 08/27/2023]
Abstract
Grain shape is an important agronomic trait directly associated with yield in rice. In order to explore new genes related to rice grain shape, a high-density genetic map containing 2193 Bin markers (526957 SNP) was constructed by whole-genome resequencing of 208 recombinant inbred (RILs) derived from a cross between ZP37 and R8605, with a total genetic distance of 1542.27 cM. The average genetic distance between markers was 0.76 cM, and the physical distance was 201.29 kb. Quantitative trait locus (QTL) mapping was performed for six agronomic traits related to rice grain length, grain width, length-to-width ratio, thousand-grain weight, grain cross-sectional area, and grain perimeter under three different environments. A total of 39 QTLs were identified, with mapping intervals ranging from 8.1 kb to 1781.6 kb and an average physical distance of 517.5 kb. Among them, 15 QTLs were repeatedly detected in multiple environments. Analysis of the genetic effects of the identified QTLs revealed 14 stable genetic loci, including three loci that overlapped with previously reported gene positions, and the remaining 11 loci were newly identified loci associated with two or more environments or traits. Locus 1, Locus 3, Locus 10, and Locus 14 were novel loci exhibiting pleiotropic effects on at least three traits and were detected in multiple environments. Locus 14, with a contribution rate greater than 10%, influenced grain width, length-to-width ratio, and grain cross-sectional area. Furthermore, pyramiding effects analysis of three stable genetic loci showed that increasing the number of QTL could effectively improve the phenotypic value of grain shape. Collectively, our findings provided a theoretical basis and genetic resources for the cloning, functional analysis, and molecular breeding of genes related to rice grain shape.
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Affiliation(s)
- Minyi Wei
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning 530007, China; (M.W.); (T.L.); (D.H.); (Z.M.); (C.L.); (Z.W.); (X.Z.); (L.Y.)
| | - Tongping Luo
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning 530007, China; (M.W.); (T.L.); (D.H.); (Z.M.); (C.L.); (Z.W.); (X.Z.); (L.Y.)
| | - Dahui Huang
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning 530007, China; (M.W.); (T.L.); (D.H.); (Z.M.); (C.L.); (Z.W.); (X.Z.); (L.Y.)
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Nanning 530004, China
| | - Zengfeng Ma
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning 530007, China; (M.W.); (T.L.); (D.H.); (Z.M.); (C.L.); (Z.W.); (X.Z.); (L.Y.)
| | - Chi Liu
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning 530007, China; (M.W.); (T.L.); (D.H.); (Z.M.); (C.L.); (Z.W.); (X.Z.); (L.Y.)
| | - Yuanyuan Qin
- Agricultural Science and Technology Information Research Institute, Guangxi Academy of Agricultural Sciences, Nanning 530007, China;
| | - Zishuai Wu
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning 530007, China; (M.W.); (T.L.); (D.H.); (Z.M.); (C.L.); (Z.W.); (X.Z.); (L.Y.)
| | - Xiaolong Zhou
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning 530007, China; (M.W.); (T.L.); (D.H.); (Z.M.); (C.L.); (Z.W.); (X.Z.); (L.Y.)
| | - Yingping Lu
- Liuzhou Branch, Guangxi Academy of Agricultural Sciences, Liuzhou Research Center of Agricultural Sciences, Liuzhou 545000, China;
| | - Liuhui Yan
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning 530007, China; (M.W.); (T.L.); (D.H.); (Z.M.); (C.L.); (Z.W.); (X.Z.); (L.Y.)
- Liuzhou Branch, Guangxi Academy of Agricultural Sciences, Liuzhou Research Center of Agricultural Sciences, Liuzhou 545000, China;
| | - Gang Qin
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning 530007, China; (M.W.); (T.L.); (D.H.); (Z.M.); (C.L.); (Z.W.); (X.Z.); (L.Y.)
| | - Yuexiong Zhang
- Guangxi Key Laboratory of Rice Genetics and Breeding, Rice Research Institute, Guangxi Academy of Agricultural Sciences, Nanning 530007, China; (M.W.); (T.L.); (D.H.); (Z.M.); (C.L.); (Z.W.); (X.Z.); (L.Y.)
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Nanning 530004, China
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Della Coletta R, Liese SE, Fernandes SB, Mikel MA, Bohn MO, Lipka AE, Hirsch CN. Linking genetic and environmental factors through marker effect networks to understand trait plasticity. Genetics 2023; 224:iyad103. [PMID: 37246567 DOI: 10.1093/genetics/iyad103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 05/19/2023] [Accepted: 05/24/2023] [Indexed: 05/30/2023] Open
Abstract
Understanding how plants adapt to specific environmental changes and identifying genetic markers associated with phenotypic plasticity can help breeders develop plant varieties adapted to a rapidly changing climate. Here, we propose the use of marker effect networks as a novel method to identify markers associated with environmental adaptability. These marker effect networks are built by adapting commonly used software for building gene coexpression networks with marker effects across growth environments as the input data into the networks. To demonstrate the utility of these networks, we built networks from the marker effects of ∼2,000 nonredundant markers from 400 maize hybrids across 9 environments. We demonstrate that networks can be generated using this approach, and that the markers that are covarying are rarely in linkage disequilibrium, thus representing higher biological relevance. Multiple covarying marker modules associated with different weather factors throughout the growing season were identified within the marker effect networks. Finally, a factorial test of analysis parameters demonstrated that marker effect networks are relatively robust to these options, with high overlap in modules associated with the same weather factors across analysis parameters. This novel application of network analysis provides unique insights into phenotypic plasticity and specific environmental factors that modulate the genome.
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Affiliation(s)
- Rafael Della Coletta
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
| | - Sharon E Liese
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Samuel B Fernandes
- Department of Crop, Soil, and Environmental Sciences, University of Arkansas, Fayetteville, AR 72701, USA
| | - Mark A Mikel
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Martin O Bohn
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Alexander E Lipka
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Candice N Hirsch
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
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28
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Feng F, Ma X, Yan M, Zhang H, Mei D, Fan P, Xu X, Wei C, Lou Q, Li T, Liu H, Luo L, Mei H. Identification of Genetic Loci for Rice Seedling Mesocotyl Elongation in Both Natural and Artificial Segregating Populations. PLANTS (BASEL, SWITZERLAND) 2023; 12:2743. [PMID: 37514357 PMCID: PMC10385686 DOI: 10.3390/plants12142743] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Revised: 07/06/2023] [Accepted: 07/07/2023] [Indexed: 07/30/2023]
Abstract
Mesocotyl elongation of rice seedlings is a key trait for deep sowing tolerance and well seedling establishment in dry direct sowing rice (DDSR) production. Subsets of the Rice Diversity Panel 1 (RDP1, 294 accessions) and Hanyou 73 (HY73) recombinant inbred line (RIL) population (312 lines) were screened for mesocotyl length (ML) via dark germination. Six RDP1 accessions (Phudugey, Kasalath, CA902B21, Surjamkuhi, Djimoron, and Goria) had an ML longer than 10 cm, with the other 19 accessions being over 4 cm. A GWAS in RDP1 detected 118 associated SNPs on all 12 chromosomes using a threshold of FDR-adjusted p < 0.05, including 11 SNPs on chromosomes 1, 4, 5, 7, 10, and 12 declared by -log10(P) > 5.868 as the Bonferroni-corrected threshold. Using phenotypic data of three successive trials and a high-density bin map from resequencing genotypic data, four to six QTLs were detected on chromosomes 1, 2, 5, 6, and 10, including three loci repeatedly mapped for ML from two or three replicated trials. Candidate genes were predicted from the chromosomal regions covered by the associated LD blocks and the confidence intervals (CIs) of QTLs and partially validated by the dynamic RNA-seq data in the mesocotyl along different periods of light exposure. Potential strategies of donor parent selection for seedling establishment in DDSR breeding were discussed.
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Affiliation(s)
- Fangjun Feng
- Shanghai Agrobiological Gene Center, Shanghai 201106, China
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization, Ministry of Agriculture and Rural Affairs, Shanghai 201106, China
| | - Xiaosong Ma
- Shanghai Agrobiological Gene Center, Shanghai 201106, China
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization, Ministry of Agriculture and Rural Affairs, Shanghai 201106, China
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Ming Yan
- Shanghai Agrobiological Gene Center, Shanghai 201106, China
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization, Ministry of Agriculture and Rural Affairs, Shanghai 201106, China
| | - Hong Zhang
- Anji Administrative Station of Water and Soil Conservation, Huzhou 313300, China
| | - Daoliang Mei
- Anji Administrative Station of Water and Soil Conservation, Huzhou 313300, China
| | - Peiqing Fan
- Shanghai Agrobiological Gene Center, Shanghai 201106, China
| | - Xiaoyan Xu
- Shanghai Agrobiological Gene Center, Shanghai 201106, China
| | - Chunlong Wei
- Shanghai Agrobiological Gene Center, Shanghai 201106, China
| | - Qiaojun Lou
- Shanghai Agrobiological Gene Center, Shanghai 201106, China
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization, Ministry of Agriculture and Rural Affairs, Shanghai 201106, China
| | - Tianfei Li
- Shanghai Agrobiological Gene Center, Shanghai 201106, China
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization, Ministry of Agriculture and Rural Affairs, Shanghai 201106, China
| | - Hongyan Liu
- Shanghai Agrobiological Gene Center, Shanghai 201106, China
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization, Ministry of Agriculture and Rural Affairs, Shanghai 201106, China
| | - Lijun Luo
- Shanghai Agrobiological Gene Center, Shanghai 201106, China
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization, Ministry of Agriculture and Rural Affairs, Shanghai 201106, China
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Hanwei Mei
- Shanghai Agrobiological Gene Center, Shanghai 201106, China
- Key Laboratory of Grain Crop Genetic Resources Evaluation and Utilization, Ministry of Agriculture and Rural Affairs, Shanghai 201106, China
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29
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Lu L, Choi SR, Lim YP, Kang SY, Yi SY. A GBS-based genetic linkage map and quantitative trait loci (QTL) associated with resistance to Xanthomonas campestris pv. campestris race 1 identified in Brassica oleracea. FRONTIERS IN PLANT SCIENCE 2023; 14:1205681. [PMID: 37384357 PMCID: PMC10293835 DOI: 10.3389/fpls.2023.1205681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 05/24/2023] [Indexed: 06/30/2023]
Abstract
The production of Brassica oleracea, an important vegetable crop, is severely affected by black rot disease caused by the bacterial pathogen Xanthomonas campestris pv. campestris. Resistance to race 1, the most virulent and widespread race in B. oleracea, is under quantitative control; therefore, identifying the genes and genetic markers associated with resistance is crucial for developing resistant cultivars. Quantitative trait locus (QTL) analysis of resistance in the F2 population developed by crossing the resistant parent BR155 with the susceptible parent SC31 was performed. Sequence GBS approach was used to develop a genetic linkage map. The map contained 7,940 single nucleotide polymorphism markers consisting of nine linkage groups spanning 675.64 cM with an average marker distance of 0.66 cM. The F2:3 population (N = 126) was evaluated for resistance to black rot disease in summer (2020), fall (2020), and spring (2021). QTL analysis, using a genetic map and phenotyping data, identified seven QTLs with LOD values between 2.10 and 4.27. The major QTL, qCaBR1, was an area of overlap between the two QTLs identified in the 2nd and 3rd trials located at C06. Among the genes located in the major QTL interval, 96 genes had annotation results, and eight were found to respond to biotic stimuli. We compared the expression patterns of eight candidate genes in susceptible (SC31) and resistant (BR155) lines using qRT-PCR and observed their early and transient increases or suppression in response to Xanthomonas campestris pv. campestris inoculation. These results support the involvement of the eight candidate genes in black rot resistance. The findings of this study will contribute towards marker-assisted selection, additionally the functional analysis of candidate genes may elucidate the molecular mechanisms underlying black rot resistance in B. oleracea.
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Affiliation(s)
- Lu Lu
- Institute of Agricultural Science, Chungnam National University, Daejeon, Republic of Korea
| | - Su Ryun Choi
- Institute of Agricultural Science, Chungnam National University, Daejeon, Republic of Korea
| | - Yong Pyo Lim
- Molecular Genetics and Genomics Laboratory, Department of Horticulture, Chungnam National University, Daejeon, Republic of Korea
| | - Si-Yong Kang
- Department of Horticulture, College of Industrial Sciences, Kongju National University, Yesan, Republic of Korea
- Research Center of Crop Breeding for Omics and Artificial Intelligence, Kongju National University, Yesan, Republic of Korea
| | - So Young Yi
- Institute of Agricultural Science, Chungnam National University, Daejeon, Republic of Korea
- Research Center of Crop Breeding for Omics and Artificial Intelligence, Kongju National University, Yesan, Republic of Korea
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30
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Campos-Martin R, Schmickler S, Goel M, Schneeberger K, Tresch A. Reliable genotyping of recombinant genomes using a robust hidden Markov model. PLANT PHYSIOLOGY 2023; 192:821-836. [PMID: 36946207 PMCID: PMC10231367 DOI: 10.1093/plphys/kiad191] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 01/20/2023] [Accepted: 01/27/2023] [Indexed: 06/01/2023]
Abstract
Meiotic recombination is an essential mechanism during sexual reproduction and includes the exchange of chromosome segments between homologous chromosomes. New allelic combinations are transmitted to the new generation, introducing novel genetic variation in the offspring genomes. With the improvement of high-throughput whole-genome sequencing technologies, large numbers of recombinant individuals can now be sequenced with low sequencing depth at low costs, necessitating computational methods for reconstructing their haplotypes. The main challenge is the uncertainty in haplotype calling that arises from the low information content of a single genomic position. Straightforward sliding window-based approaches are difficult to tune and fail to place recombination breakpoints precisely. Hidden Markov model (HMM)-based approaches, on the other hand, tend to over-segment the genome. Here, we present RTIGER, an HMM-based model that exploits in a mathematically precise way the fact that true chromosome segments typically have a certain minimum length. We further separate the task of identifying the correct haplotype sequence from the accurate placement of haplotype borders, thereby maximizing the accuracy of border positions. By comparing segmentations based on simulated data with known underlying haplotypes, we highlight the reasons for RTIGER outperforming traditional segmentation approaches. We then analyze the meiotic recombination pattern of segregants of 2 Arabidopsis (Arabidopsis thaliana) accessions and a previously described hyper-recombining mutant. RTIGER is available as an R package with an efficient Julia implementation of the core algorithm.
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Affiliation(s)
- Rafael Campos-Martin
- Faculty of Medicine, University Hospital Cologne, Cologne 50937, Germany
- Department of Chromosome Biology, Max Planck Institute for Plant Breeding Research, Cologne 50829, Germany
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, University of Cologne, Medical Faculty, Cologne 50937, Germany
| | - Sophia Schmickler
- Faculty of Medicine, University Hospital Cologne, Cologne 50937, Germany
| | - Manish Goel
- Department of Chromosome Biology, Max Planck Institute for Plant Breeding Research, Cologne 50829, Germany
- Faculty for Biology, LMU Munich, Planegg-Martinsried 82152, Germany
| | - Korbinian Schneeberger
- Department of Chromosome Biology, Max Planck Institute for Plant Breeding Research, Cologne 50829, Germany
- Faculty for Biology, LMU Munich, Planegg-Martinsried 82152, Germany
- Cluster of Excellence on Plant Sciences, Heinrich-Heine University, Düsseldorf 40225, Germany
| | - Achim Tresch
- Faculty of Medicine, University Hospital Cologne, Cologne 50937, Germany
- CECAD, University of Cologne, Cologne 50931, Germany
- Center for Data and Simulation Science, University of Cologne, Cologne 50931, Germany
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31
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George L, Alex R, Sukhija N, Jaglan K, Vohra V, Kumar R, Verma A. Genetic improvement of economic traits in Murrah buffalo using significant SNPs from genome-wide association study. Trop Anim Health Prod 2023; 55:199. [PMID: 37184817 DOI: 10.1007/s11250-023-03606-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 04/27/2023] [Indexed: 05/16/2023]
Abstract
GWAS helps to identify QTL and candidate genes of specific traits. Buffalo breeding has primarily focused on milk production, but its negative correlation with reproduction traits resulted in unfavorable decline of reproductive performance among buffaloes. A genome wide scan was performed on a total of 120 Murrah buffaloes genotyped by ddRAD sequencing for 13 traits related to female fertility, production, and growth. The identified 25 significant single nucleotide polymorphisms (SNPs) (P <1×106) are associated with age at first calving (AFC), age at first service (AFS), period from calving to 1st Artifical Insemination (AI), service period (SP) and 6 month body weight (6M). Fifteen genetic variants overlapped with different QTL regions of reported studies. Among the associated loci, outstanding candidate genes for fertility, including AQP1, TRNAE-CUC, NRIP1, CPNE4, and VOPP1, have effect in different fertility traits. AQP1 gene is expressed in ovulatory phase and various stages of pregnancy. TRNAE-CUC gene is associated with AFC and number . of calvings after 4 years of age. Glycogen content-associated gene CPNE4 regulates muscle glycogen and is upregulated during early pregnancy. NRIP1 generegulates ovulation, corpus luteum at pregnancy, and mammary gland development. The objective is to identify potential genomic regions and genetic variants associated with economic traits and to select the most significant SNP which have positive effect on all the traits.
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Affiliation(s)
- Linda George
- Division of Animal Genetics and Breeding, ICAR- National Dairy Research Institute, Karnal, Haryana, 132001, India.
| | - Rani Alex
- Division of Animal Genetics and Breeding, ICAR- National Dairy Research Institute, Karnal, Haryana, 132001, India
| | - Nidhi Sukhija
- Division of Animal Genetics and Breeding, ICAR- National Dairy Research Institute, Karnal, Haryana, 132001, India
| | - Komal Jaglan
- Division of Animal Genetics and Breeding, ICAR- National Dairy Research Institute, Karnal, Haryana, 132001, India
| | - Vikas Vohra
- Division of Animal Genetics and Breeding, ICAR- National Dairy Research Institute, Karnal, Haryana, 132001, India
| | - Ravi Kumar
- Division of Animal Genetics and Breeding, ICAR- National Dairy Research Institute, Karnal, Haryana, 132001, India
| | - Archana Verma
- Division of Animal Genetics and Breeding, ICAR- National Dairy Research Institute, Karnal, Haryana, 132001, India
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The study of selection signature and its applications on identification of candidate genes using whole genome sequencing data in chicken - a review. Poult Sci 2023; 102:102657. [PMID: 37054499 PMCID: PMC10123265 DOI: 10.1016/j.psj.2023.102657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Revised: 03/09/2023] [Accepted: 03/10/2023] [Indexed: 03/17/2023] Open
Abstract
Chicken is a major source of protein for the increasing human population and is useful for research purposes. There are almost 1,600 distinct regional breeds of chicken across the globe, among which a large body of genetic and phenotypic variations has been accumulated due to extensive natural and artificial selection. Moreover, natural selection is a crucial force for animal domestication. Several approaches have been adopted to detect selection signatures in different breeds of chicken using whole genome sequencing (WGS) data including integrated haplotype score (iHS), cross-populated extend haplotype homozygosity test (XP-EHH), fixation index (FST), cross-population composite likelihood ratio (XP-CLR), nucleotide diversity (Pi), and others. In addition, gene enrichment analyses are utilized to determine KEGG pathways and gene ontology (GO) terms related to traits of interest in chicken. Herein, we review different studies that have adopted diverse approaches to detect selection signatures in different breeds of chicken. This review systematically summarizes different findings on selection signatures and related candidate genes in chickens. Future studies could combine different selection signatures approaches to strengthen the quality of the results thereby providing more affirmative inference. This would further aid in deciphering the importance of selection in chicken conservation for the increasing human population.
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Dissecting the Meiotic Recombination Patterns in a Brassica napus Double Haploid Population Using 60K SNP Array. Int J Mol Sci 2023; 24:ijms24054469. [PMID: 36901901 PMCID: PMC10003086 DOI: 10.3390/ijms24054469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 02/14/2023] [Accepted: 02/22/2023] [Indexed: 02/26/2023] Open
Abstract
Meiotic recombination not only maintains the stability of the chromosome structure but also creates genetic variations for adapting to changeable environments. A better understanding of the mechanism of crossover (CO) patterns at the population level is useful for crop improvement. However, there are limited cost-effective and universal methods to detect the recombination frequency at the population level in Brassica napus. Here, the Brassica 60K Illumina Infinium SNP array (Brassica 60K array) was used to systematically study the recombination landscape in a double haploid (DH) population of B. napus. It was found that COs were unevenly distributed across the whole genome, and a higher frequency of COs existed at the distal ends of each chromosome. A considerable number of genes (more than 30%) in the CO hot regions were associated with plant defense and regulation. In most tissues, the average gene expression level in the hot regions (CO frequency of greater than 2 cM/Mb) was significantly higher than that in the regions with a CO frequency of less than 1 cM/Mb. In addition, a bin map was constructed with 1995 recombination bins. For seed oil content, Bin 1131 to 1134, Bin 1308 to 1311, Bin 1864 to 1869, and Bin 2184 to 2230 were identified on chromosomes A08, A09, C03, and C06, respectively, which could explain 8.5%, 17.3%, 8.6%, and 3.9% of the phenotypic variation. These results could not only deepen our understanding of meiotic recombination in B. napus at the population level, and provide useful information for rapeseed breeding in the future, but also provided a reference for studying CO frequency in other species.
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Zhu Y, Song B, Guo Y, Wang B, Xu C, Zhu H, E L, Lai J, Song W, Zhao H. QTL Analysis Reveals Conserved and Differential Genetic Regulation of Maize Lateral Angles above the Ear. PLANTS (BASEL, SWITZERLAND) 2023; 12:680. [PMID: 36771763 PMCID: PMC9920044 DOI: 10.3390/plants12030680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Revised: 01/30/2023] [Accepted: 01/31/2023] [Indexed: 06/18/2023]
Abstract
Improving the density tolerance and planting density has great importance for increasing maize production. The key to promoting high density planting is breeding maize with a compact canopy architecture, which is mainly influenced by the angles of the leaves and tassel branches above the ear. It is still unclear whether the leaf angles of different stem nodes and tassel branches are controlled by similar genetic regulatory mechanisms, which limits the ability to breed for density-tolerant maize. Here, we developed a population with 571 double haploid lines derived from inbred lines, PHBA6 and Chang7-2, showing significant differences in canopy architecture. Phenotypic and QTL analyses revealed that the genetic regulation mechanism was largely similar for closely adjacent leaves above the ears. In contrast, the regulation mechanisms specifying the angles of distant leaves and the angles of leaves vs. tassel branches are largely different. The liguless1 gene was identified as a candidate gene for QTLs co-regulating the angles of different leaves and the tassel branch, consistent with its known roles in regulating plant architecture. Our findings can be used to develop strategies for the improvement of leaf and tassel architecture through the introduction of trait-specific or pleiotropic genes, thus benefiting the breeding of maize with increased density tolerance in the future.
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Affiliation(s)
- Yanbin Zhu
- State Key Laboratory of Plant Physiology and Biochemistry, National Maize Improvement Center, Department of Plant Genetics and Breeding, China Agricultural University, Beijing 100193, China
- National Key Laboratory of Maize Biological Breeding, Key Laboratory of Genetics and Breeding of Main Crops in Northeast Region, Ministry of Agriculture and Rural Affairs, Liaoning Dongya Seed Industry Co., Ltd., Shenyang 110164, China
- Sanya Institute of Henan University, Sanya 572025, China
| | - Bo Song
- State Key Laboratory of Plant Physiology and Biochemistry, National Maize Improvement Center, Department of Plant Genetics and Breeding, China Agricultural University, Beijing 100193, China
- National Key Laboratory of Maize Biological Breeding, Key Laboratory of Genetics and Breeding of Main Crops in Northeast Region, Ministry of Agriculture and Rural Affairs, Liaoning Dongya Seed Industry Co., Ltd., Shenyang 110164, China
| | - Yanling Guo
- State Key Laboratory of Plant Physiology and Biochemistry, National Maize Improvement Center, Department of Plant Genetics and Breeding, China Agricultural University, Beijing 100193, China
- National Key Laboratory of Maize Biological Breeding, Key Laboratory of Genetics and Breeding of Main Crops in Northeast Region, Ministry of Agriculture and Rural Affairs, Liaoning Dongya Seed Industry Co., Ltd., Shenyang 110164, China
| | - Baobao Wang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Changcheng Xu
- National Key Laboratory of Maize Biological Breeding, Key Laboratory of Genetics and Breeding of Main Crops in Northeast Region, Ministry of Agriculture and Rural Affairs, Liaoning Dongya Seed Industry Co., Ltd., Shenyang 110164, China
| | - Hongyu Zhu
- National Key Laboratory of Maize Biological Breeding, Key Laboratory of Genetics and Breeding of Main Crops in Northeast Region, Ministry of Agriculture and Rural Affairs, Liaoning Dongya Seed Industry Co., Ltd., Shenyang 110164, China
| | - Lizhu E
- State Key Laboratory of Plant Physiology and Biochemistry, National Maize Improvement Center, Department of Plant Genetics and Breeding, China Agricultural University, Beijing 100193, China
| | - Jinsheng Lai
- State Key Laboratory of Plant Physiology and Biochemistry, National Maize Improvement Center, Department of Plant Genetics and Breeding, China Agricultural University, Beijing 100193, China
| | - Weibin Song
- State Key Laboratory of Plant Physiology and Biochemistry, National Maize Improvement Center, Department of Plant Genetics and Breeding, China Agricultural University, Beijing 100193, China
| | - Haiming Zhao
- State Key Laboratory of Plant Physiology and Biochemistry, National Maize Improvement Center, Department of Plant Genetics and Breeding, China Agricultural University, Beijing 100193, China
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Wu M, Zhang Q, Dong Y, Wang Z, Zhan W, Ke Z, Li S, He L, Ruf S, Bock R, Zhang J. Transplastomic tomatoes expressing double-stranded RNA against a conserved gene are efficiently protected from multiple spider mites. THE NEW PHYTOLOGIST 2023; 237:1363-1373. [PMID: 36328788 DOI: 10.1111/nph.18595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 11/02/2022] [Indexed: 06/16/2023]
Abstract
Spider mites are serious pests and have evolved significant resistance to many chemical pesticides, thus making their control challenging. Several insect pests can be combated by plastid-mediated RNA interference (PM-RNAi), but whether PM-RNAi can be utilized to control noninsect pests is unknown. Here, we show that three species of spider mites (Tetranychus evansi, Tetranychus truncatus, and Tetranychus cinnabarinus) take up plastid RNA upon feeding. We generated transplastomic tomato plants expressing double-stranded RNA (dsRNA) targeted against a conserved region of the spider mite β-Actin mRNA. Transplastomic plants exhibited high levels of resistance to all three spider mite species, as evidenced by increased mortality and suppression of target gene expression. Notably, transplastomic plants induced a more robust RNAi response, caused higher mortality, and were overall better protected from spider mites than dsRNA-expressing nuclear transgenic plants. Our data demonstrate the potential of PM-RNAi as an efficient pest control measure for spider mites and extend the application range of the technology to noninsect pests.
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Affiliation(s)
- Mengting Wu
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Hubei Hongshan Laboratory, School of Life Sciences, Hubei University, Wuhan, 430062, China
- Max-Planck-Institut für Molekulare Pflanzenphysiologie, Am Mühlenberg 1, D-14476, Potsdam-Golm, Germany
| | - Qi Zhang
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Hubei Hongshan Laboratory, School of Life Sciences, Hubei University, Wuhan, 430062, China
| | - Yi Dong
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Hubei Hongshan Laboratory, School of Life Sciences, Hubei University, Wuhan, 430062, China
| | - Zican Wang
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Hubei Hongshan Laboratory, School of Life Sciences, Hubei University, Wuhan, 430062, China
| | - Wenqin Zhan
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Hubei Hongshan Laboratory, School of Life Sciences, Hubei University, Wuhan, 430062, China
| | - Zebin Ke
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Hubei Hongshan Laboratory, School of Life Sciences, Hubei University, Wuhan, 430062, China
| | - Shengchun Li
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Hubei Hongshan Laboratory, School of Life Sciences, Hubei University, Wuhan, 430062, China
| | - Lin He
- Key Laboratory of Entomology and Pest Control Engineering, College of Plant Protection, Southwest University, Chongqing, 400715, China
| | - Stephanie Ruf
- Max-Planck-Institut für Molekulare Pflanzenphysiologie, Am Mühlenberg 1, D-14476, Potsdam-Golm, Germany
| | - Ralph Bock
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Hubei Hongshan Laboratory, School of Life Sciences, Hubei University, Wuhan, 430062, China
- Max-Planck-Institut für Molekulare Pflanzenphysiologie, Am Mühlenberg 1, D-14476, Potsdam-Golm, Germany
| | - Jiang Zhang
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Hubei Hongshan Laboratory, School of Life Sciences, Hubei University, Wuhan, 430062, China
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Geng L, Zhang W, Zou T, Du Q, Ma X, Cui D, Han B, Zhang Q, Han L. Integrating linkage mapping and comparative transcriptome analysis for discovering candidate genes associated with salt tolerance in rice. FRONTIERS IN PLANT SCIENCE 2023; 14:1065334. [PMID: 36760644 PMCID: PMC9904508 DOI: 10.3389/fpls.2023.1065334] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Accepted: 01/04/2023] [Indexed: 06/18/2023]
Abstract
Salinity is one of the most widespread abiotic stresses affecting rice productivity worldwide. Understanding the genetic basis of salt tolerance is key for breeding salt-tolerant rice varieties. Numerous QTLs have been identified to help dissect rice salt-tolerance genetic mechanisms, yet only rare genes located in significant QTLs have been thoroughly studied or fine-mapped. Here, a combination of linkage mapping and transcriptome profiling analysis was used to identify salt tolerance-related functional candidate genes underlying stable QTLs. A recombinant inbred line (RIL) population derived from a cross between Jileng 1 (salt-sensitive) and Milyang 23 (salt-tolerant) was constructed. Subsequently, a high-density genetic map was constructed by using 2921 recombination bin markers developed from whole genome resequencing. A total of twelve QTLs controlling the standard evaluation score under salt stress were identified by linkage analysis and distributed on chromosomes 2, 3, 4, 6, 8 and 11. Notably, five QTL intervals were detected as environmentally stable QTLs in this study, and their functions were verified by comparative transcriptome analysis. By comparing the transcriptome profiles of the two parents and two bulks, we found 551 salt stress-specific differentially expressed genes. Among them, fifteen DEGs located in stable QTL intervals were considered promising candidate genes for salt tolerance. According to gene annotations, the gene OsRCI2-8(Os06g0184800) was the most promising, as it is known to be associated with salt stress, and its differential expression between the tolerant and sensitive RIL bulks highlights its important role in salt stress response pathways. Our findings provide five stable salt tolerance-related QTLs and one promising candidate gene, which will facilitate breeding for improved salt tolerance in rice varieties and promote the exploration of salt stress tolerance mechanisms in rice.
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Affiliation(s)
- Leiyue Geng
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- Institute of Coastal Agriculture, Hebei Academy of Agriculture and Forestry Sciences, Tangshan, China
- Tangshan Key Laboratory of Rice Breeding, Tangshan, China
| | - Wei Zhang
- Institute of Coastal Agriculture, Hebei Academy of Agriculture and Forestry Sciences, Tangshan, China
- Tangshan Key Laboratory of Rice Breeding, Tangshan, China
| | - Tuo Zou
- Institute of Coastal Agriculture, Hebei Academy of Agriculture and Forestry Sciences, Tangshan, China
- Tangshan Key Laboratory of Rice Breeding, Tangshan, China
| | - Qi Du
- Institute of Coastal Agriculture, Hebei Academy of Agriculture and Forestry Sciences, Tangshan, China
- Tangshan Key Laboratory of Rice Breeding, Tangshan, China
| | - Xiaoding Ma
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Di Cui
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Bing Han
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Qixing Zhang
- Institute of Coastal Agriculture, Hebei Academy of Agriculture and Forestry Sciences, Tangshan, China
- Tangshan Key Laboratory of Rice Breeding, Tangshan, China
| | - Longzhi Han
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
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Xu M, Kong K, Miao L, He J, Liu T, Zhang K, Yue X, Jin T, Gai J, Li Y. Identification of major quantitative trait loci and candidate genes for seed weight in soybean. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:22. [PMID: 36688967 PMCID: PMC9870841 DOI: 10.1007/s00122-023-04299-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 01/09/2023] [Indexed: 06/17/2023]
Abstract
Four major quantitative trait loci for 100-seed weight were identified in a soybean RIL population under five environments, and the most likely candidate genes underlying these loci were identified. Seed weight is an important target of soybean breeding. However, the genes underlying the major quantitative trait loci (QTL) controlling seed weight remain largely unknown. In this study, a soybean population of 300 recombinant inbred lines (RILs) derived from a cross between PI595843 (PI) and WH was used to map the QTL and identify candidate genes for seed weight. The RIL population was genotyped through whole genome resequencing, and phenotyped for 100-seed weight under five environments. A total of 38 QTL were detected, and four major QTL, each explained at least 10% of the variation in 100-seed weight, were identified. Six candidate genes within these four major QTL regions were identified by analyses of their tissue expression patterns, gene annotations, and differential gene expression levels in soybean seeds during four developmental stages between two parental lines. Further sequence variation analyses revealed a C to T substitution in the first exon of the Glyma.19G143300, resulting in an amino acid change between PI and WH, and thus leading to a different predicted kinase domain, which might affect its protein function. Glyma.19G143300 is highly expressed in soybean seeds and encodes a leucine-rich repeat receptor-like protein kinase (LRR-RLK). Its predicted protein has typical domains of LRR-RLK family, and phylogenetic analyses reveled its similarity with the known LRR-RLK protein XIAO (LOC_Os04g48760), which is involved in controlling seed size. The major QTL and candidate genes identified in this study provide useful information for molecular breeding of new soybean cultivars with desirable seed weight.
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Affiliation(s)
- Mengge Xu
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Key Laboratory for Biology and Genetic Improvement of Soybean (General, Ministry of Agriculture), Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
| | - Keke Kong
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Key Laboratory for Biology and Genetic Improvement of Soybean (General, Ministry of Agriculture), Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
| | - Long Miao
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Key Laboratory for Biology and Genetic Improvement of Soybean (General, Ministry of Agriculture), Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
| | - Jianbo He
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Key Laboratory for Biology and Genetic Improvement of Soybean (General, Ministry of Agriculture), Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
| | - Tengfei Liu
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Key Laboratory for Biology and Genetic Improvement of Soybean (General, Ministry of Agriculture), Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
| | - Kai Zhang
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Key Laboratory for Biology and Genetic Improvement of Soybean (General, Ministry of Agriculture), Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
| | - Xiuli Yue
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Key Laboratory for Biology and Genetic Improvement of Soybean (General, Ministry of Agriculture), Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
| | - Ting Jin
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Key Laboratory for Biology and Genetic Improvement of Soybean (General, Ministry of Agriculture), Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
| | - Junyi Gai
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Key Laboratory for Biology and Genetic Improvement of Soybean (General, Ministry of Agriculture), Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China
| | - Yan Li
- National Key Laboratory of Crop Genetics and Germplasm Enhancement, National Center for Soybean Improvement, Key Laboratory for Biology and Genetic Improvement of Soybean (General, Ministry of Agriculture), Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, China.
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Liang W, Du H, Pang B, Cheng J, He B, Hu F, Lv Y, Zhang Y. High-density genetic mapping identified QTLs for anaerobic germination tolerance in rice. FRONTIERS IN PLANT SCIENCE 2022; 13:1076600. [PMID: 36618635 PMCID: PMC9822775 DOI: 10.3389/fpls.2022.1076600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 12/05/2022] [Indexed: 06/17/2023]
Abstract
The tolerance of rice anaerobic germination (AG) is the main limiting factor for direct seeding application, yet the genetics mechanism is still in its infancy. In the study, recombinant inbred lines population of TD70 Japonica cultivar and Kasalath Indica cultivar, was employed to construct a high-density genetic map by whole genome re-sequencing. As a result, a genetic map containing 12,328 bin-markers was constructed and a total of 50 QTLs were then detected for CL(coleoptile length), CD (coleoptile diameter), CSA (coleoptile surface area) and CV (coleoptile volume) related traits in the two stages of anaerobic treatment using complete interval mapping method (inclusive composite interval mapping, ICIM). Among the four traits associated with coleoptile, coleoptile volume had the largest number of QTLs (17), followed by coleoptile diameter (16), and coleoptile length had 5 QTLs. These QTLs could explain phenotypic contribution rates ranging from 0.34% to 11.17% and LOD values ranging from 2.52 to 11.57. Combined with transcriptome analysis, 31 candidate genes were identified. Furthermore, 12 stable QTLs were used to detect the aggregation effect analysis. Besides, It was found that individuals with more aggregation synergistic alleles had higher phenotypic values in different environments. Totally, high-density genetic map, QTL mapping and aggregation effect analysis of different loci related to the anaerobic germination of rice seeds were conducted to lay a foundation for the fine mapping of related genes in subsequent assisted breeding.
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Affiliation(s)
- Wenhua Liang
- Institute of Food Crops, Jiangsu Academy of Agricultural Sciences, Nanjing, China
| | - Hongyang Du
- Excellence and Innovation Center, Jiangsu Academy of Agricultural, Sciences, Nanjing, China
- Key Laboratory of Rice Genetic Breeding of Anhui Province, Rice Research Institute, Anhui Academy of Agricultural Science, Hefei, China
| | - Bingwen Pang
- Excellence and Innovation Center, Jiangsu Academy of Agricultural, Sciences, Nanjing, China
| | - Junjie Cheng
- Excellence and Innovation Center, Jiangsu Academy of Agricultural, Sciences, Nanjing, China
| | - Bing He
- Excellence and Innovation Center, Jiangsu Academy of Agricultural, Sciences, Nanjing, China
| | - Fengqin Hu
- Excellence and Innovation Center, Jiangsu Academy of Agricultural, Sciences, Nanjing, China
| | - Yuanda Lv
- Excellence and Innovation Center, Jiangsu Academy of Agricultural, Sciences, Nanjing, China
| | - Yadong Zhang
- Institute of Food Crops, Jiangsu Academy of Agricultural Sciences, Nanjing, China
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Lu X, Zhou Z, Wang Y, Wang R, Hao Z, Li M, Zhang D, Yong H, Han J, Wang Z, Weng J, Zhou Y, Li X. Genetic basis of maize kernel protein content revealed by high-density bin mapping using recombinant inbred lines. FRONTIERS IN PLANT SCIENCE 2022; 13:1045854. [PMID: 36589123 PMCID: PMC9798238 DOI: 10.3389/fpls.2022.1045854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 11/29/2022] [Indexed: 06/17/2023]
Abstract
Maize with a high kernel protein content (PC) is desirable for human food and livestock fodder. However, improvements in its PC have been hampered by a lack of desirable molecular markers. To identify quantitative trait loci (QTL) and candidate genes for kernel PC, we employed a genotyping-by-sequencing strategy to construct a high-resolution linkage map with 6,433 bin markers for 275 recombinant inbred lines (RILs) derived from a high-PC female Ji846 and low-PC male Ye3189. The total genetic distance covered by the linkage map was 2180.93 cM, and the average distance between adjacent markers was 0.32 cM, with a physical distance of approximately 0.37 Mb. Using this linkage map, 11 QTLs affecting kernel PC were identified, including qPC7 and qPC2-2, which were identified in at least two environments. For the qPC2-2 locus, a marker named IndelPC2-2 was developed with closely linked polymorphisms in both parents, and when tested in 30 high and 30 low PC inbred lines, it showed significant differences (P = 1.9E-03). To identify the candidate genes for this locus, transcriptome sequencing data and PC best linear unbiased estimates (BLUE) for 348 inbred lines were combined, and the expression levels of the four genes were correlated with PC. Among the four genes, Zm00001d002625, which encodes an S-adenosyl-L-methionine-dependent methyltransferase superfamily protein, showed significantly different expression levels between two RIL parents in the endosperm and is speculated to be a potential candidate gene for qPC2-2. This study will contribute to further research on the mechanisms underlying the regulation of maize PC, while also providing a genetic basis for marker-assisted selection in the future.
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Affiliation(s)
- Xin Lu
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhiqiang Zhou
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yunhe Wang
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
- College of Agriculture, Northeast Agricultural University, Harbin, Heilongjiang, China
| | - Ruiqi Wang
- College of Agriculture, Northeast Agricultural University, Harbin, Heilongjiang, China
| | - Zhuanfang Hao
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Mingshun Li
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Degui Zhang
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Hongjun Yong
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jienan Han
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhenhua Wang
- College of Agriculture, Northeast Agricultural University, Harbin, Heilongjiang, China
| | - Jianfeng Weng
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yu Zhou
- College of Agriculture, Northeast Agricultural University, Harbin, Heilongjiang, China
| | - Xinhai Li
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
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Genetic Dissection of Phosphorus Use Efficiency and Genotype-by-Environment Interaction in Maize. Int J Mol Sci 2022; 23:ijms232213943. [PMID: 36430424 PMCID: PMC9697416 DOI: 10.3390/ijms232213943] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 11/07/2022] [Accepted: 11/08/2022] [Indexed: 11/16/2022] Open
Abstract
Genotype-by-environment interaction (G-by-E) is a common but potentially problematic phenomenon in plant breeding. In this study, we investigated the genotypic performance and two measures of plasticity on a phenotypic and genetic level by assessing 234 maize doubled haploid lines from six populations for 15 traits in seven macro-environments with a focus on varying soil phosphorus levels. It was found intergenic regions contributed the most to the variation of phenotypic linear plasticity. For 15 traits, 124 and 31 quantitative trait loci (QTL) were identified for genotypic performance and phenotypic plasticity, respectively. Further, some genes associated with phosphorus use efficiency, such as Zm00001eb117170, Zm00001eb258520, and Zm00001eb265410, encode small ubiquitin-like modifier E3 ligase were identified. By significantly testing the main effect and G-by-E effect, 38 main QTL and 17 interaction QTL were identified, respectively, in which MQTL38 contained the gene Zm00001eb374120, and its effect was related to phosphorus concentration in the soil, the lower the concentration, the greater the effect. Differences in the size and sign of the QTL effect in multiple environments could account for G-by-E. At last, the superiority of G-by-E in genomic selection was observed. In summary, our findings will provide theoretical guidance for breeding P-efficient and broadly adaptable varieties.
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Wu L, Zheng Y, Jiao F, Wang M, Zhang J, Zhang Z, Huang Y, Jia X, Zhu L, Zhao Y, Guo J, Chen J. Identification of quantitative trait loci for related traits of stalk lodging resistance using genome-wide association studies in maize (Zea mays L.). BMC Genom Data 2022; 23:76. [PMID: 36319954 PMCID: PMC9623923 DOI: 10.1186/s12863-022-01091-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2021] [Accepted: 10/10/2022] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND Stalk lodging is one of the main factors affecting maize (Zea mays L.) yield and limiting mechanized harvesting. Developing maize varieties with high stalk lodging resistance requires exploring the genetic basis of lodging resistance-associated agronomic traits. Stalk strength is an important indicator to evaluate maize lodging and can be evaluated by measuring stalk rind penetrometer resistance (RPR) and stalk buckling strength (SBS). Along with morphological traits of the stalk for the third internodes length (TIL), fourth internode length (FIL), third internode diameter (TID), and the fourth internode diameter (FID) traits are associated with stalk lodging resistance. RESULTS In this study, a natural population containing 248 diverse maize inbred lines genotyped with 83,057 single nucleotide polymorphism (SNP) markers was used for genome-wide association study (GWAS) for six stalk lodging resistance-related traits. The heritability of all traits ranged from 0.59 to 0.72 in the association mapping panel. A total of 85 significant SNPs were identified for the association mapping panel using best linear unbiased prediction (BLUP) values of all traits. Additionally, five candidate genes were associated with stalk strength traits, which were either directly or indirectly associated with cell wall components. CONCLUSIONS These findings contribute to our understanding of the genetic basis of maize stalk lodging and provide valuable theoretical guidance for lodging resistance in maize breeding in the future.
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Affiliation(s)
- Lifen Wu
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Sub-Center for National Maize Improvement Center, College of Agronomy, Hebei Agricultural University, Hebei, Baoding 071001 China
| | - Yunxiao Zheng
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Sub-Center for National Maize Improvement Center, College of Agronomy, Hebei Agricultural University, Hebei, Baoding 071001 China
| | - Fuchao Jiao
- grid.412608.90000 0000 9526 6338College of Agronomy, Qingdao Agricultural University, Shandong, Qingdao 266109 China
| | - Ming Wang
- grid.412608.90000 0000 9526 6338College of Agronomy, Qingdao Agricultural University, Shandong, Qingdao 266109 China
| | - Jing Zhang
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Sub-Center for National Maize Improvement Center, College of Agronomy, Hebei Agricultural University, Hebei, Baoding 071001 China
| | - Zhongqin Zhang
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Sub-Center for National Maize Improvement Center, College of Agronomy, Hebei Agricultural University, Hebei, Baoding 071001 China
| | - Yaqun Huang
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Sub-Center for National Maize Improvement Center, College of Agronomy, Hebei Agricultural University, Hebei, Baoding 071001 China
| | - Xiaoyan Jia
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Sub-Center for National Maize Improvement Center, College of Agronomy, Hebei Agricultural University, Hebei, Baoding 071001 China
| | - Liying Zhu
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Sub-Center for National Maize Improvement Center, College of Agronomy, Hebei Agricultural University, Hebei, Baoding 071001 China
| | - Yongfeng Zhao
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Sub-Center for National Maize Improvement Center, College of Agronomy, Hebei Agricultural University, Hebei, Baoding 071001 China
| | - Jinjie Guo
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Sub-Center for National Maize Improvement Center, College of Agronomy, Hebei Agricultural University, Hebei, Baoding 071001 China
| | - Jingtang Chen
- State Key Laboratory of North China Crop Improvement and Regulation, Hebei Sub-Center for National Maize Improvement Center, College of Agronomy, Hebei Agricultural University, Hebei, Baoding 071001 China ,grid.412608.90000 0000 9526 6338College of Agronomy, Qingdao Agricultural University, Shandong, Qingdao 266109 China
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Yi S, Lee DG, Back S, Hong JP, Jang S, Han K, Kang BC. Genetic mapping revealed that the Pun2 gene in Capsicum chacoense encodes a putative aminotransferase. FRONTIERS IN PLANT SCIENCE 2022; 13:1039393. [PMID: 36388488 PMCID: PMC9664168 DOI: 10.3389/fpls.2022.1039393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Accepted: 10/05/2022] [Indexed: 06/16/2023]
Abstract
Several genes regulating capsaicinoid biosynthesis including Pun1 (also known as CS), Pun3, pAMT, and CaKR1 have been studied. However, the gene encoded by Pun2 in the non-pungent Capsicum chacoense is unknown. This study aimed to identify the Pun2 gene by genetic mapping using interspecific (C. chacoense × Capsicum annuum) and intraspecific (C. chacoense × C. chacoense) populations. QTL mapping using the interspecific F2 population revealed two major QTLs on chromosomes 3 and 9. Two bin markers within the QTL regions on two chromosomes were highly correlated with the capsaicinoid content in the interspecific population. The major QTL, Pun2_PJ_Gibbs_3.11 on chromosome 3, contained the pAMT gene, indicating that the non-pungency of C. chacoense may be attributed to a mutation in the pAMT gene. Sequence analysis revealed a 7 bp nucleotide insertion in the 8th exon of pAMT of the non-pungent C. chacoense. This mutation resulted in the generation of an early stop codon, resulting in a truncated mutant lacking the PLP binding site, which is critical for pAMT enzymatic activity. This insertion co-segregated with the pungency phenotype in the intraspecific F2 population. We named this novel pAMT allele pamt11 . Taken together, these data indicate that the non-pungency of C. chacoense is due to the non-functional pAMT allele, and Pun2 encodes the pAMT gene.
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Liu K, Chen E, Gu Z, Dai B, Wang A, Zhu Z, Feng Q, Zhou C, Zhu J, Shangguan Y, Wang Y, Li Z, Hou Q, Lv D, Wang C, Huang T, Wang Z, Huang X, Han B. A retrotransposon insertion in MUTL-HOMOLOG 1 affects wild rice seed set and cultivated rice crossover rate. PLANT PHYSIOLOGY 2022; 190:1747-1762. [PMID: 35976143 PMCID: PMC9614510 DOI: 10.1093/plphys/kiac378] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 07/12/2022] [Indexed: 06/06/2023]
Abstract
Wild rice (Oryza rufipogon) has a lower panicle seed setting rate (PSSR) and gamete fertility than domesticated rice (Oryza sativa), but the genetic mechanisms of this phenomenon remain unknown. Here, we cloned a null allele of OsMLH1, an ortholog of MutL-homolog 1 to yeast and mammals, from wild rice O. rufipogon W1943 and revealed a 5.4-kb retrotransposon insertion in OsMLH1 is responsible for the low PSSR in wild rice. In contrast to the wild-type, a near isogenic line NIL-mlh1 exhibits defective crossover (CO) formation during meiosis, resulting in reduced pollen viability, partial embryo lethality, and low PSSR. Except for the mutant of mismatch repair gene postmeiotic segregation 1 (Ospms1), all other MutL mutants from O. sativa indica subspecies displayed male and female semi-sterility similar to NIL-mlh1, but less severe than those from O. sativa japonica subspecies. MLH1 and MLH3 did not contribute in an additive fashion to fertility. Two types of MutL heterodimers, MLH1-PMS1 and MLH1-MLH3, were identified in rice, but only the latter functions in promoting meiotic CO formation. Compared to japonica varieties, indica cultivars had greater numbers of CO events per meiosis. Our results suggest that low fertility in wild rice may be caused by different gene defects, and indica and japonica subspecies have substantially different CO rates responsible for the discrepancy between the fertility of mlh1 and mlh3 mutants.
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Affiliation(s)
- Kun Liu
- College of Life Sciences, Anhui Normal University, Wuhu, 241000, China
- National Center for Gene Research, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200233, China
| | - Erwang Chen
- National Center for Gene Research, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200233, China
| | - Zhoulin Gu
- National Center for Gene Research, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200233, China
| | - Bingxin Dai
- National Center for Gene Research, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200233, China
- School of Life Science and Technology, Shanghai Tech University, Shanghai, 201210, China
| | - Ahong Wang
- National Center for Gene Research, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200233, China
| | - Zhou Zhu
- National Center for Gene Research, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200233, China
| | - Qi Feng
- National Center for Gene Research, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200233, China
| | - Congcong Zhou
- National Center for Gene Research, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200233, China
| | - Jingjie Zhu
- National Center for Gene Research, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200233, China
| | - Yingying Shangguan
- National Center for Gene Research, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200233, China
| | - Yongchun Wang
- National Center for Gene Research, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200233, China
| | - Zhen Li
- College of Life Sciences, Anhui Normal University, Wuhu, 241000, China
- National Center for Gene Research, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200233, China
| | - Qingqing Hou
- National Center for Gene Research, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200233, China
| | - Danfeng Lv
- National Center for Gene Research, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200233, China
| | - Changsheng Wang
- National Center for Gene Research, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200233, China
| | - Tao Huang
- National Center for Gene Research, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200233, China
| | - Zixuan Wang
- National Center for Gene Research, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200233, China
| | - Xuehui Huang
- College of Life Sciences, Shanghai Normal University, Shanghai, 200234, China
| | - Bin Han
- National Center for Gene Research, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, 200233, China
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Yang J, Wei J, Xu J, Xiong Y, Deng G, Liu J, Fahad S, Wang H. Mapping QTLs for anaerobic tolerance at germination and bud stages using new high density genetic map of rice. FRONTIERS IN PLANT SCIENCE 2022; 13:985080. [PMID: 36325568 PMCID: PMC9618957 DOI: 10.3389/fpls.2022.985080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Accepted: 09/26/2022] [Indexed: 06/16/2023]
Abstract
Due to its low cost and convenience, direct seeding is an efficient technique for the production of rice in different rice growing areas. However, anaerobic conditions are a major obstacle to the direct seeding of rice and result in poor seedling establishment, which leads to yield losses. We constructed a collection of recombinant inbred lines (RIL) comprising 275 lines derived from the H335 and CHA-1 cross by the method of single seed descent. Via a genotyping-by-sequencing (GBS) strategy, a high-density genetic map containing 2498 recombination bin markers was constructed, the average physical distance between the markers was only 149.38 Kb. After anaerobic treatment, 12 phenotypes related to both the coleoptile at germination and seedling quality at budding were evaluated. There were no significant correlations between seedling and bud traits. Genetic mapping of quantitative traits was performed for these traits across two cropping seasons. A total of 20 loci were detected, named locus 1~20. Three of them were repeatedly detected across both seasons. Six loci overlapped with those in previous reports, and nine loci were associated with multiple traits at both stages. Notably, locus 3, which is located on chromosome 2 (26,713,837 to 27,333,897 bp), was detected for both the germination and bud traits. By focusing on the locus 3 interval and by combining gene annotation and expression analyses, we identified a promising candidate gene, trehalose-6-phosphate phosphatase (OsTPP1, LOC_Os02g44230). Furthermore, RILs (G289, G379, G403, G430 and G454) that have superior phenotypes and that pyramid elite alleles were recognized. The findings of present study provide new genetic resources for direct-seeding rice (DSR) varieties for molecular breeding strategies and expand our knowledge of genetic regulation of seedling establishment under anaerobic conditions.
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Affiliation(s)
- Jing Yang
- Yunnan Key Laboratory of Potato Biology, Yunnan Normal University, Kunming, China
| | - Ji Wei
- Yunnan Key Laboratory of Potato Biology, Yunnan Normal University, Kunming, China
| | - Jifen Xu
- Yunnan Key Laboratory of Potato Biology, Yunnan Normal University, Kunming, China
| | - Yumeng Xiong
- Yunnan Key Laboratory of Potato Biology, Yunnan Normal University, Kunming, China
| | - Gang Deng
- School of Agriculture, Yunnan University, Kunming, China
| | - Jing Liu
- Yunnan Key Laboratory of Potato Biology, Yunnan Normal University, Kunming, China
| | - Shah Fahad
- Department of Agriculture, Abdul Wali Khan University Mardan, Khyber Pakhtunkhwa, Pakistan
- Department of Agronomy, The University of Haripur, Haripur, Pakistan
| | - Hongyang Wang
- Yunnan Key Laboratory of Potato Biology, Yunnan Normal University, Kunming, China
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45
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Chen L, Lei W, He W, Wang Y, Tian J, Gong J, Hao B, Cheng X, Shu Y, Fan Z. Mapping of Two Major QTLs Controlling Flowering Time in Brassica napus Using a High-Density Genetic Map. PLANTS (BASEL, SWITZERLAND) 2022; 11:plants11192635. [PMID: 36235500 PMCID: PMC9571212 DOI: 10.3390/plants11192635] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 10/01/2022] [Accepted: 10/05/2022] [Indexed: 05/31/2023]
Abstract
Research on the flowering habit of rapeseed is important for the selection of varieties adapted to specific ecological environments. Here, quantitative trait loci (QTL) for the days-to-flowering trait were identified using a doubled haploid population of 178 lines derived from a cross between the winter type SGDH284 and the semi-winter type 158A. A linkage map encompassing 3268.01 cM was constructed using 2777 bin markers obtained from next-generation sequencing. The preliminary mapping results revealed 56 QTLs for the days to flowering in the six replicates in the three environments. Twelve consensus QTLs were identified by a QTL meta-analysis, two of which (cqDTF-C02 and cqDTF-C06) were designated as major QTLs. Based on the micro-collinearity of the target regions between B. napus and Arabidopsis, four genes possibly related to flowering time were identified in the cqDTF-C02 interval, and only one gene possibly related to flowering time was identified in the cqDTF-C06 interval. A tightly linked insertion-deletion marker for the cqFT-C02 locus was developed. These findings will aid the breeding of early maturing B. napus varieties.
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Affiliation(s)
- Lei Chen
- College of Agriculture, Anhui Science and Technology University, Fengyang 233100, China
| | - Weixia Lei
- Crop Institute, Anhui Academy of Agricultural Sciences, Hefei 230031, China
| | - Wangfei He
- College of Agriculture, Anhui Science and Technology University, Fengyang 233100, China
| | - Yifan Wang
- College of Agriculture, Anhui Science and Technology University, Fengyang 233100, China
| | - Jie Tian
- College of Agriculture, Anhui Science and Technology University, Fengyang 233100, China
| | - Jihui Gong
- College of Agriculture, Anhui Science and Technology University, Fengyang 233100, China
| | - Bing Hao
- Bengbu Ludu Crop Residue Biotechnology Co., Ltd., Bengbu 233000, China
| | - Xinxin Cheng
- College of Agriculture, Anhui Science and Technology University, Fengyang 233100, China
| | - Yingjie Shu
- College of Agriculture, Anhui Science and Technology University, Fengyang 233100, China
| | - Zhixiong Fan
- Crop Institute, Anhui Academy of Agricultural Sciences, Hefei 230031, China
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Ma J, Jiang Y, Pei W, Wu M, Ma Q, Liu J, Song J, Jia B, Liu S, Wu J, Zhang J, Yu J. Expressed genes and their new alleles identification during fibre elongation reveal the genetic factors underlying improvements of fibre length in cotton. PLANT BIOTECHNOLOGY JOURNAL 2022; 20:1940-1955. [PMID: 35718938 PMCID: PMC9491459 DOI: 10.1111/pbi.13874] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Revised: 05/29/2022] [Accepted: 06/11/2022] [Indexed: 05/27/2023]
Abstract
Interspecific breeding in cotton takes advantage of genetic recombination among desirable genes from different parental lines. However, the expression new alleles (ENAs) from crossovers within genic regions and their significance in fibre length (FL) improvement are currently not understood. Here, we generated resequencing genomes of 191 interspecific backcross inbred lines derived from CRI36 (Gossypium hirsutum) × Hai7124 (Gossypium barbadense) and 277 dynamic fibre transcriptomes to identify the ENAs and extremely expressed genes (eGenes) potentially influencing FL, and uncovered the dynamic regulatory network of fibre elongation. Of 35 420 eGenes in developing fibres, 10 366 ENAs were identified and preferentially distributed in chromosomes subtelomeric regions. In total, 1056-1255 ENAs showed transgressive expression in fibres at 5-15 dpa (days post-anthesis) of some BILs, 520 of which were located in FL-quantitative trait locus (QTLs) and GhFLA9 (recombination allele) was identified with a larger effect for FL than GhFLA9 of CRI36 allele. Using ENAs as a type of markers, we identified three novel FL-QTLs. Additionally, 456 extremely eGenes were identified that were preferentially distributed in recombination hotspots. Importantly, 34 of them were significantly associated with FL. Gene expression quantitative trait locus analysis identified 1286, 1089 and 1059 eGenes that were colocalized with the FL trait at 5, 10 and 15 dpa, respectively. Finally, we verified the Ghir_D10G011050 gene linked to fibre elongation by the CRISPR-cas9 system. This study provides the first glimpse into the occurrence, distribution and expression of the developing fibres genes (especially ENAs) in an introgression population, and their possible biological significance in FL.
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Affiliation(s)
- Jianjiang Ma
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
- Zhengzhou Research Base, State Key Laboratory of Cotton BiologyZhengzhou UniversityZhengzhouChina
| | - Yafei Jiang
- Novogene Bioinformatics InstituteBeijingChina
| | - Wenfeng Pei
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
| | - Man Wu
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
| | - Qifeng Ma
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
| | - Ji Liu
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
| | - Jikun Song
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
| | - Bing Jia
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
| | - Shang Liu
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
| | - Jianyong Wu
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
- Zhengzhou Research Base, State Key Laboratory of Cotton BiologyZhengzhou UniversityZhengzhouChina
| | - Jinfa Zhang
- Department of Plant and Environmental SciencesNew Mexico State UniversityLas CrucesNew MexicoUSA
| | - Jiwen Yu
- State Key Laboratory of Cotton BiologyInstitute of Cotton Research of Chinese Academy of Agricultural SciencesKey Laboratory of Cotton Genetic ImprovementMinistry of AgricultureAnyangChina
- Zhengzhou Research Base, State Key Laboratory of Cotton BiologyZhengzhou UniversityZhengzhouChina
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Wang Q, Liao Z, Zhu C, Gou X, Liu Y, Xie W, Wu F, Feng X, Xu J, Li J, Lu Y. Teosinte confers specific alleles and yield potential to maize improvement. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:3545-3562. [PMID: 36121453 DOI: 10.1007/s00122-022-04199-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Accepted: 08/10/2022] [Indexed: 06/15/2023]
Abstract
Teosinte improves maize grain yield and broadens the maize germplasm. Seventy-one quantitative trait loci associated with 24 differential traits between maize and teosinte were identified. Maize is a major cereal crop with a narrow germplasm that has limited its production and breeding progress. Teosinte, an ancestor of maize, provides valuable genetic resources for maize breeding. To identify the favorable alien alleles in teosinte and its yield potential for maize breeding, 4 backcrossed maize-teosinte recombinant inbred line (RIL) populations were cultivated under five conditions. A North Carolina mating design II experiment was conducted on inbred lines with B73 and Mo17 pedigree backgrounds to analyze their combining ability. Abundant phenotypic variation on 26 traits of four RIL populations were found, of which barren tip length, kernel height, and test weight showed positive genetic improvement potential. The hybrid FM132 (BD138/MP116) showed a superior grain yield to that of the check, with an average yield gain of 4.86%. Moreover, inbred lines BD138 and MP048 showed a higher general grain yield combining ability than those of their corresponding checks. We screened 4,964,439 high-quality single-nucleotide polymorphisms in the BD (B73/Zea diploperennis) RIL population for bin construction and used 2322 bin markers for genetic map construction and quantitative trait loci (QTL) mapping. Via inclusive composite interval mapping, 71 QTL associated with 24 differential traits were identified. Gene annotation and transcriptional expression suggested that Zm00001eb352570 and Zm00001eb352580, both annotated as ethylene-responsive transcription factors, were key candidate genes that regulate ear height and the ratio of ear to plant height. Our results indicate that teosinte could broaden the narrow maize germplasm, improve yield potential, and provide desirable alleles for maize breeding.
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Affiliation(s)
- Qingjun Wang
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Wenjiang District, China
- Maize Research Institute, Sichuan Agricultural University, Wenjiang District, China
| | - Zhengqiao Liao
- Maize Research Institute, Sichuan Agricultural University, Wenjiang District, China
- College of Life Science and Technology, Mianyang Teachers' College, Mianyang, China
| | - Chuntao Zhu
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Wenjiang District, China
- Maize Research Institute, Sichuan Agricultural University, Wenjiang District, China
| | - Xiangjian Gou
- Maize Research Institute, Sichuan Agricultural University, Wenjiang District, China
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Yaxi Liu
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Wenjiang District, China
- Triticeae Research Institute, Sichuan Agricultural University, Wenjiang District, China
| | - Wubing Xie
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Wenjiang District, China
- Maize Research Institute, Sichuan Agricultural University, Wenjiang District, China
| | - Fengkai Wu
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Wenjiang District, China
- Maize Research Institute, Sichuan Agricultural University, Wenjiang District, China
| | - Xuanjun Feng
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Wenjiang District, China
- Maize Research Institute, Sichuan Agricultural University, Wenjiang District, China
| | - Jie Xu
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Wenjiang District, China
- Maize Research Institute, Sichuan Agricultural University, Wenjiang District, China
| | - Jingwei Li
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Wenjiang District, China
- Maize Research Institute, Sichuan Agricultural University, Wenjiang District, China
| | - Yanli Lu
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Sichuan Agricultural University, Wenjiang District, China.
- Maize Research Institute, Sichuan Agricultural University, Wenjiang District, China.
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48
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González-Castro M, Cardoso YP, Hughes LC, Ortí G. Hybridization is strongly constrained by salinity during secondary contact between silverside fishes (Odontesthes, Atheriniformes). Heredity (Edinb) 2022; 129:233-243. [PMID: 35821279 PMCID: PMC9519950 DOI: 10.1038/s41437-022-00555-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 06/28/2022] [Accepted: 06/28/2022] [Indexed: 11/08/2022] Open
Abstract
This study investigates a contact zone between two silverside fish species (marine Odontesthes argentinensis and freshwater O. bonariensis) in the estuarine Mar Chiquita lagoon along the Atlantic coast in Argentina (MChL), in which intermediate morphs had been reported. It has been suggested that admixture and introgression occur in MChL between these two species, but direct genetic evidence is lacking. Leveraging samples collected over several years (n = 676), we document the spatial distribution of both species and intermediate morphs within this habitat and collect landmark-based morphometric and multilocus genetic data (9876 loci for n = 110 individuals) to test the hypothesis of hybridization. Our analysis unambiguously characterizes intermediate morphs as F1 or F2 hybrids. We show that the low frequency of hybrid individuals in MChL may be explained by uneven abundance of parental species, which in turn are strongly affected by water salinity, limiting the size of the contact zone. Although hybrids seem to be fertile, their fitness may be reduced by external and intrinsic factors that may limit their success and suggest that this is an unstable hybrid zone. Genetic distinctiveness of both parental species is strongly supported by genome-wide data, explaining a known pattern of mitonuclear discordance as a consequence of hybridization followed by mitochondrial introgression. A clear signature of population genetic structure was detected in O. argentinensis, distinguishing MChL residents from marine populations of this species, that also was supported by distinctive morphometric features among these groups. Previous hypotheses of speciation in these fishes are discussed in the light of the new findings.
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Affiliation(s)
- Mariano González-Castro
- Grupo de Biotaxonomía Morfológica y molecular de peces, IIMyC-CONICET, Universidad Nacional de Mar del Plata, Mar del Plata, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
| | - Yamila P Cardoso
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina.
- Laboratorio de Sistemática y Biología Evolutiva, Facultad de Ciencias Naturales y Museo, Universidad Nacional de La Plata, La Plata, Argentina.
- Department of Biological Sciences, George Washington University, Washington, DC, USA.
| | - Lily C Hughes
- Department of Biological Sciences, George Washington University, Washington, DC, USA
- Department of Vertebrate Zoology, National Museum of Natural History, Smithsonian Institution, Washington, DC, USA
| | - Guillermo Ortí
- Department of Biological Sciences, George Washington University, Washington, DC, USA
- Department of Vertebrate Zoology, National Museum of Natural History, Smithsonian Institution, Washington, DC, USA
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Ouyang W, Chen L, Ma J, Liu X, Chen H, Yang H, Guo W, Shan Z, Yang Z, Chen S, Zhan Y, Zhang H, Cao D, Zhou X. Identification of Quantitative Trait Locus and Candidate Genes for Drought Tolerance in a Soybean Recombinant Inbred Line Population. Int J Mol Sci 2022; 23:ijms231810828. [PMID: 36142739 PMCID: PMC9504156 DOI: 10.3390/ijms231810828] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 09/09/2022] [Accepted: 09/10/2022] [Indexed: 12/18/2022] Open
Abstract
With global warming and regional decreases in precipitation, drought has become a problem worldwide. As the number of arid regions in the world is increasing, drought has become a major factor leading to significant crop yield reductions and food crises. Soybean is a crop that is relatively sensitive to drought. It is also a crop that requires more water during growth and development. The aim of this study was to identify the quantitative trait locus (QTL) that affects drought tolerance in soybean by using a recombinant inbred line (RIL) population from a cross between the drought-tolerant cultivar ‘Jindou21’ and the drought-sensitive cultivar ‘Zhongdou33’. Nine agronomic and physiological traits were identified under drought and well-watered conditions. Genetic maps were constructed with 923,420 polymorphic single nucleotide polymorphism (SNP) markers distributed on 20 chromosomes at an average genetic distance of 0.57 centimorgan (cM) between markers. A total of five QTLs with a logarithm of odds (LOD) value of 4.035–8.681 were identified on five chromosomes. Under well-watered conditions and drought-stress conditions, one QTL related to the main stem node number was located on chromosome 16, accounting for 17.177% of the phenotypic variation. Nine candidate genes for drought resistance were screened from this QTL, namely Glyma.16G036700, Glyma.16G036400, Glyma.16G036600, Glyma.16G036800, Glyma.13G312700, Glyma.13G312800, Glyma.16G042900, Glyma.16G043200, and Glyma.15G100700. These genes were annotated as NAC transport factor, GATA transport factor, and BTB/POZ-MATH proteins. This result can be used for molecular marker-assisted selection and provide a reference for breeding for drought tolerance in soybean.
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Affiliation(s)
- Wenqi Ouyang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Limiao Chen
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Junkui Ma
- The Industrial Crop Institute, Shanxi Academy of Agricultural Sciences, Taiyuan 030006, China
| | - Xiaorong Liu
- The Industrial Crop Institute, Shanxi Academy of Agricultural Sciences, Taiyuan 030006, China
| | - Haifeng Chen
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Hongli Yang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Wei Guo
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Zhihui Shan
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Zhonglu Yang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Shuilian Chen
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China
| | - Yong Zhan
- Crop Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Key Laboratory of Cereal Quality Research and Genetic Improvement, Xinjiang Production and Construction Crops, Shihezi 832000, China
| | - Hengbin Zhang
- Crop Research Institute, Xinjiang Academy of Agricultural and Reclamation Science, Key Laboratory of Cereal Quality Research and Genetic Improvement, Xinjiang Production and Construction Crops, Shihezi 832000, China
| | - Dong Cao
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China
- Correspondence: (D.C.); (X.Z.)
| | - Xinan Zhou
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, Wuhan 430062, China
- Correspondence: (D.C.); (X.Z.)
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50
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Chen Y, Li R, Sun J, Li C, Xiao H, Chen S. Genome-Wide Population Structure and Selection Signatures of Yunling Goat Based on RAD-seq. Animals (Basel) 2022; 12:ani12182401. [PMID: 36139261 PMCID: PMC9495202 DOI: 10.3390/ani12182401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 09/07/2022] [Accepted: 09/10/2022] [Indexed: 12/04/2022] Open
Abstract
Simple Summary Goats are important domestic animals that provide meat, milk, fur, and other products for humans. The demand for these products has increased in recent years. Disease resistance among goat breeds is different, but the genetic basis of the differences in resistance to diseases is still unclear and needs to be further studied. In this study, many genes and pathways related to immunity and diseases were identified to be under positive selection between Yunling and Nubian goats using RAD-seq technology. This study on the selection signatures of Yunling goats provides the scientific basis and technical support for the breeding of domestic goats for disease resistance, which has important social and economic significance. Abstract Animal diseases impose a huge burden on the countries where diseases are endemic. Conventional control strategies of vaccines and veterinary drugs are to control diseases from a pharmaceutical perspective. Another alternative approach is using pre-existing genetic disease resistance or tolerance. We know that the Yunling goat is an excellent local breed from Yunnan, southwestern China, which has characteristics of strong disease resistance and remarkable adaptability. However, genetic information about the selection signatures of Yunling goats is limited. We reasoned that the genes underlying the observed difference in disease resistance might be identified by investigating selection signatures between two different goat breeds. Herein, we selected the Nubian goat as the reference group to perform the population structure and selection signature analysis by using RAD-seq technology. The results showed that two goat breeds were divided into two clusters, but there also existed gene flow. We used Fst (F-statistics) and π (pi/θπ) methods to carry out selection signature analysis. Eight selected regions and 91 candidate genes were identified, in which some genes such as DOK2, TIMM17A, MAVS, and DOCK8 related to disease and immunity and some genes such as SPEFI, CDC25B, and MIR103 were associated with reproduction. Four GO (Gene Ontology) terms (GO:0010591, GO:001601, GO:0038023, and GO:0017166) were associated with cell migration, signal transduction, and immune responses. The KEGG (Kyoto Encyclopedia of Genes and Genomes) signaling pathways were mainly associated with immune responses, inflammatory responses, and stress reactions. This study preliminarily revealed the genetic basis of strong disease resistance and adaptability of Yunling goats. It provides a theoretical basis for the subsequent genetic breeding of disease resistance of goats.
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Affiliation(s)
- Yuming Chen
- School of Ecology and Environmental Science, Yunnan University, Kunming 650500, China; (Y.C.); (R.L.); (C.L.); (H.X.)
- School of Life Sciences, Yunnan University, Kunming 650500, China;
| | - Rong Li
- School of Ecology and Environmental Science, Yunnan University, Kunming 650500, China; (Y.C.); (R.L.); (C.L.); (H.X.)
- College of Life Science, Yunnan Normal University, Kunming 650500, China
| | - Jianshu Sun
- School of Life Sciences, Yunnan University, Kunming 650500, China;
| | - Chunqing Li
- School of Ecology and Environmental Science, Yunnan University, Kunming 650500, China; (Y.C.); (R.L.); (C.L.); (H.X.)
| | - Heng Xiao
- School of Ecology and Environmental Science, Yunnan University, Kunming 650500, China; (Y.C.); (R.L.); (C.L.); (H.X.)
| | - Shanyuan Chen
- School of Ecology and Environmental Science, Yunnan University, Kunming 650500, China; (Y.C.); (R.L.); (C.L.); (H.X.)
- Correspondence: ; Tel.: +86-18687122260
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