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Bi Y, Jiang F, Zhang Y, Li Z, Kuang T, Shaw RK, Adnan M, Li K, Fan X. Identification of a novel marker and its associated laccase gene for regulating ear length in tropical and subtropical maize lines. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2024; 137:94. [PMID: 38578443 PMCID: PMC10997716 DOI: 10.1007/s00122-024-04587-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Accepted: 02/20/2024] [Indexed: 04/06/2024]
Abstract
KEY MESSAGE This study revealed the identification of a novel gene, Zm00001d042906, that regulates maize ear length by modulating lignin synthesis and reported a molecular marker for selecting maize lines with elongated ears. Maize ear length has garnered considerable attention due to its high correlation with yield. In this study, six maize inbred lines of significant importance in maize breeding were used as parents. The temperate maize inbred line Ye107, characterized by a short ear, was crossed with five tropical or subtropical inbred lines featuring longer ears, creating a multi-parent population displaying significant variations in ear length. Through genome-wide association studies and mutation analysis, the A/G variation at SNP_183573532 on chromosome 3 was identified as an effective site for discriminating long-ear maize. Furthermore, the associated gene Zm00001d042906 was found to correlate with maize ear length. Zm00001d042906 was functionally annotated as a laccase (Lac4), which showed activity and influenced lignin synthesis in the midsection cells of the cob, thereby regulating maize ear length. This study further reports a novel molecular marker and a new gene that can assist maize breeding programs in selecting varieties with elongated ears.
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Affiliation(s)
- Yaqi Bi
- Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, 650093, China
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming, 650205, China
| | - Fuyan Jiang
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming, 650205, China
| | - Yudong Zhang
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming, 650205, China
| | - Ziwei Li
- Dehong Teachers' College, Luxi, 678400, China
| | - Tianhui Kuang
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming, 650205, China
| | - Ranjan K Shaw
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming, 650205, China
| | - Muhammad Adnan
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming, 650205, China
| | - Kunzhi Li
- Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, 650093, China.
| | - Xingming Fan
- Institute of Food Crops, Yunnan Academy of Agricultural Sciences, Kunming, 650205, China.
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Ruidong S, Shijin H, Yuwei Q, Yimeng L, Xiaohang Z, Ying L, Xihang L, Mingyang D, Xiangling L, Fenghai L. Identification of QTLs and their candidate genes for the number of maize tassel branches in F 2 from two higher generation sister lines using QTL mapping and RNA-seq analysis. FRONTIERS IN PLANT SCIENCE 2023; 14:1202755. [PMID: 37641589 PMCID: PMC10460468 DOI: 10.3389/fpls.2023.1202755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/09/2023] [Accepted: 07/18/2023] [Indexed: 08/31/2023]
Abstract
Tassel branch number is an important agronomic trait that is closely associated with maize kernels and yield. The regulation of genes associated with tassel branch development can provide a theoretical basis for analyzing tassel branch growth and improving maize yield. In this study. we used two high-generation sister maize lines, PCU (unbranched) and PCM (multiple-branched), to construct an F2 population comprising 190 individuals, which were genotyped and mapped using the Maize6H-60K single-nucleotide polymorphism array. Candidate genes associated with tassel development were subsequently identified by analyzing samples collected at three stages of tassel growth via RNA-seq. A total of 13 quantitative trait loci (QTLs) and 22 quantitative trait nucleotides (QTNs) associated with tassel branch number (TBN) were identified, among which, two major QTLs, qTBN6.06-1 and qTBN6.06-2, on chromosome 6 were identified in two progeny populations, accounting for 15.07% to 37.64% of the phenotypic variation. Moreover, we identified 613 genes that were differentially expressed between PCU and PCM, which, according to Kyoto Encyclopedia of Genes and Genomes enrichment analysis, were enriched in amino acid metabolism and plant signal transduction pathways. Additionally, we established that the phytohormone content of Stage I tassels and the levels of indole-3-acetic acid (IAA) and IAA-glucose were higher in PCU than in PCM plants, whereas contrastingly, the levels of 5-deoxymonopolyl alcohol in PCM were higher than those in PCU. On the basis of these findings, we speculate that differences in TBN may be related to hormone content. Collectively, by combining QTL mapping and RNA-seq analysis, we identified five candidate genes associated with TBN. This study provides theoretical insights into the mechanism of tassel branch development in maize.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Lv Xiangling
- Special Corn Institute, Shenyang Agricultural University, Shenyang, China
| | - Li Fenghai
- Special Corn Institute, Shenyang Agricultural University, Shenyang, China
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Dong Z, Wang Y, Bao J, Li Y, Yin Z, Long Y, Wan X. The Genetic Structures and Molecular Mechanisms Underlying Ear Traits in Maize ( Zea mays L.). Cells 2023; 12:1900. [PMID: 37508564 PMCID: PMC10378120 DOI: 10.3390/cells12141900] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 07/12/2023] [Accepted: 07/13/2023] [Indexed: 07/30/2023] Open
Abstract
Maize (Zea mays L.) is one of the world's staple food crops. In order to feed the growing world population, improving maize yield is a top priority for breeding programs. Ear traits are important determinants of maize yield, and are mostly quantitatively inherited. To date, many studies relating to the genetic and molecular dissection of ear traits have been performed; therefore, we explored the genetic loci of the ear traits that were previously discovered in the genome-wide association study (GWAS) and quantitative trait locus (QTL) mapping studies, and refined 153 QTL and 85 quantitative trait nucleotide (QTN) clusters. Next, we shortlisted 19 common intervals (CIs) that can be detected simultaneously by both QTL mapping and GWAS, and 40 CIs that have pleiotropic effects on ear traits. Further, we predicted the best possible candidate genes from 71 QTL and 25 QTN clusters that could be valuable for maize yield improvement.
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Affiliation(s)
- Zhenying Dong
- Research Institute of Biology and Agriculture, Shunde Innovation School, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China; (Z.D.)
- Beijing Engineering Laboratory of Main Crop Bio-Tech Breeding, Beijing International Science and Technology Cooperation Base of Bio-Tech Breeding, Zhongzhi International Institute of Agricultural Biosciences, Beijing 100192, China
| | - Yanbo Wang
- Research Institute of Biology and Agriculture, Shunde Innovation School, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China; (Z.D.)
| | - Jianxi Bao
- Research Institute of Biology and Agriculture, Shunde Innovation School, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China; (Z.D.)
| | - Ya’nan Li
- Research Institute of Biology and Agriculture, Shunde Innovation School, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China; (Z.D.)
| | - Zechao Yin
- Research Institute of Biology and Agriculture, Shunde Innovation School, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China; (Z.D.)
| | - Yan Long
- Research Institute of Biology and Agriculture, Shunde Innovation School, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China; (Z.D.)
- Beijing Engineering Laboratory of Main Crop Bio-Tech Breeding, Beijing International Science and Technology Cooperation Base of Bio-Tech Breeding, Zhongzhi International Institute of Agricultural Biosciences, Beijing 100192, China
| | - Xiangyuan Wan
- Research Institute of Biology and Agriculture, Shunde Innovation School, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China; (Z.D.)
- Beijing Engineering Laboratory of Main Crop Bio-Tech Breeding, Beijing International Science and Technology Cooperation Base of Bio-Tech Breeding, Zhongzhi International Institute of Agricultural Biosciences, Beijing 100192, China
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Shehzad M, Ditta A, Cai X, Ur Rahman S, Xu Y, Wang K, Zhou Z, Fang L. Identification of salt stress-tolerant candidate genes in the BC 2F 2 population at the seedling stages of G. hirsutum and G. darwinii using NGS-based bulked segregant analysis. FRONTIERS IN PLANT SCIENCE 2023; 14:1125805. [PMID: 37465381 PMCID: PMC10350501 DOI: 10.3389/fpls.2023.1125805] [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: 12/16/2022] [Accepted: 05/02/2023] [Indexed: 07/20/2023]
Abstract
Salinity is a major threat to the yield and productivity of cotton seedlings. In the present study, we developed a BC2F2 population of cotton plants from Gossypium darwinii (5-7) and Gossypium hirsutum (CCRI 12-4) salt-susceptible parents to identify salt-resistant candidate genes. The Illumina HiSeq™ strategy was used with bulked segregant analysis. Salt-resistant and salt-susceptible DNA bulks were pooled by using 30 plants from a BC2F2 population. Next-generation sequencing (NGS) technology was used for the sequencing of parents and both bulks. Four significant genomic regions were identified: the first genomic region was located on chromosome 18 (1.86 Mb), the second and third genomic regions were on chromosome 25 (1.06 Mb and 1.94 Mb, respectively), and the fourth was on chromosome 8 (1.41 Mb). The reads of bulk1 and bulk2 were aligned to the G. darwinii and G. hirsutum genomes, respectively, leading to the identification of 20,664,007 single-nucleotide polymorphisms (SNPs) and insertions/deletions (indels). After the screening, 6,573 polymorphic markers were obtained after filtration of the candidate regions. The SNP indices in resistant and susceptible bulks and Δ(SNP-index) values of resistant and susceptible bulks were measured. Based on the higher Δ(SNP-index) value, six effective polymorphic SNPs were selected in a different chromosome. Six effective SNPs were linked to five candidate genes in four genomic regions. Further validation of these five candidate genes was carried out using reverse transcription-quantitative polymerase chain reaction (RT-qPCR), resulting in an expression profile that showed two highly upregulated genes in the salt-tolerant species G. darwinii, i.e., Gohir.D05G367800 and Gohir.D12G239100; however, the opposite was shown in G. hirsutum, for which all genes, except one, showed partial expression. The results indicated that Gohir.D05G367800 and Gohir.D12G239100 may be salt-tolerant genes. We are confident that this study could be helpful for the cloning, transformation, and development of salt-resistant cotton varieties.
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Affiliation(s)
- Muhammad Shehzad
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China
| | - Allah Ditta
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China
- Plant Breeding and Genetics Division, Cotton Group, Nuclear Institute for Agriculture and Biology (NIAB), Faisalabad, Punjab, Pakistan
| | - Xiaoyan Cai
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China
- National Nanfan Research Institute of Chinese Academy of Agriculture Sciences, Sanya, China
| | - Shafeeq Ur Rahman
- MOE Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Yanchao Xu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China
- National Nanfan Research Institute of Chinese Academy of Agriculture Sciences, Sanya, China
| | - Kunbo Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China
| | - Zhongli Zhou
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China
| | - Liu Fang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China
- National Nanfan Research Institute of Chinese Academy of Agriculture Sciences, Sanya, China
- School of Agricultural Sciences, Zhengzhou University, Zhengzhou, Henan, China
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5
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Liu R, Cui Y, Kong L, Zheng F, Zhao W, Meng Q, Yuan J, Zhang M, Chen Y. Evaluating the Genetic Background Effect on Dissecting the Genetic Basis of Kernel Traits in Reciprocal Maize Introgression Lines. Genes (Basel) 2023; 14:genes14051044. [PMID: 37239404 DOI: 10.3390/genes14051044] [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: 04/03/2023] [Revised: 05/03/2023] [Accepted: 05/04/2023] [Indexed: 05/28/2023] Open
Abstract
Maize yield is mostly determined by its grain size. Although numerous quantitative trait loci (QTL) have been identified for kernel-related traits, the application of these QTL in breeding programs has been strongly hindered because the populations used for QTL mapping are often different from breeding populations. However, the effect of genetic background on the efficiency of QTL and the accuracy of trait genomic prediction has not been fully studied. Here, we used a set of reciprocal introgression lines (ILs) derived from 417F × 517F to evaluate how genetic background affects the detection of QTLassociated with kernel shape traits. A total of 51 QTL for kernel size were identified by chromosome segment lines (CSL) and genome-wide association studies (GWAS) methods. These were subsequently clustered into 13 common QTL based on their physical position, including 7 genetic-background-independent and 6 genetic-background-dependent QTL, respectively. Additionally, different digenic epistatic marker pairs were identified in the 417F and 517F ILs. Therefore, our results demonstrated that genetic background strongly affected not only the kernel size QTL mapping via CSL and GWAS but also the genomic prediction accuracy and epistatic detection, thereby enhancing our understanding of how genetic background affects the genetic dissection of grain size-related traits.
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Affiliation(s)
- Ruixiang Liu
- Provincial Key Laboratory of Agrobiology, Institute of Food Crops, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
| | - Yakun Cui
- Provincial Key Laboratory of Agrobiology, Institute of Food Crops, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
| | - Lingjie Kong
- Provincial Key Laboratory of Agrobiology, Institute of Food Crops, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
| | - Fei Zheng
- Provincial Key Laboratory of Agrobiology, Institute of Food Crops, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
| | - Wenming Zhao
- Provincial Key Laboratory of Agrobiology, Institute of Food Crops, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
| | - Qingchang Meng
- Provincial Key Laboratory of Agrobiology, Institute of Food Crops, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
| | - Jianhua Yuan
- Provincial Key Laboratory of Agrobiology, Institute of Food Crops, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
| | - Meijing Zhang
- Provincial Key Laboratory of Agrobiology, Institute of Food Crops, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
| | - Yanping Chen
- Provincial Key Laboratory of Agrobiology, Institute of Food Crops, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
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Jin SK, Xu LN, Yang QQ, Zhang MQ, Wang SL, Wang RA, Tao T, Hong LM, Guo QQ, Jia SW, Song T, Leng YJ, Cai XL, Gao JP. High-resolution quantitative trait locus mapping for rice grain quality traits using genotyping by sequencing. FRONTIERS IN PLANT SCIENCE 2023; 13:1050882. [PMID: 36714703 PMCID: PMC9878556 DOI: 10.3389/fpls.2022.1050882] [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: 09/22/2022] [Accepted: 12/23/2022] [Indexed: 06/18/2023]
Abstract
Rice is a major food crop that sustains approximately half of the world population. Recent worldwide improvements in the standard of living have increased the demand for high-quality rice. Accurate identification of quantitative trait loci (QTLs) for rice grain quality traits will facilitate rice quality breeding and improvement. In the present study, we performed high-resolution QTL mapping for rice grain quality traits using a genotyping-by-sequencing approach. An F2 population derived from a cross between an elite japonica variety, Koshihikari, and an indica variety, Nona Bokra, was used to construct a high-density genetic map. A total of 3,830 single nucleotide polymorphism markers were mapped to 12 linkage groups spanning a total length of 2,456.4 cM, with an average genetic distance of 0.82 cM. Seven grain quality traits-the percentage of whole grain, percentage of head rice, percentage of area of head rice, transparency, percentage of chalky rice, percentage of chalkiness area, and degree of chalkiness-of the F2 population were investigated. In total, 15 QTLs with logarithm of the odds (LOD) scores >4 were identified, which mapped to chromosomes 6, 7, and 9. These loci include four QTLs for transparency, four for percentage of chalky rice, four for percentage of chalkiness area, and three for degree of chalkiness, accounting for 0.01%-61.64% of the total phenotypic variation. Of these QTLs, only one overlapped with previously reported QTLs, and the others were novel. By comparing the major QTL regions in the rice genome, several key candidate genes reported to play crucial roles in grain quality traits were identified. These findings will expedite the fine mapping of these QTLs and QTL pyramiding, which will facilitate the genetic improvement of rice grain quality.
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Affiliation(s)
- Su-Kui Jin
- JiangsuKey Laboratory of Crop Genomics and Molecular Breeding, College of Agriculture, Yangzhou University, Yangzhou, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Key Laboratory of Crop Genetics and Physiology, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, College of Agriculture, Yangzhou University, Yangzhou, China
- National Key Laboratory of Plant Molecular Genetics, Chinese Academy of Sciences (CAS) Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - Li-Na Xu
- National Key Laboratory of Plant Molecular Genetics, Chinese Academy of Sciences (CAS) Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - Qing-Qing Yang
- JiangsuKey Laboratory of Crop Genomics and Molecular Breeding, College of Agriculture, Yangzhou University, Yangzhou, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Key Laboratory of Crop Genetics and Physiology, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, College of Agriculture, Yangzhou University, Yangzhou, China
| | - Ming-Qiu Zhang
- JiangsuKey Laboratory of Crop Genomics and Molecular Breeding, College of Agriculture, Yangzhou University, Yangzhou, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Key Laboratory of Crop Genetics and Physiology, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, College of Agriculture, Yangzhou University, Yangzhou, China
| | - Shui-Lian Wang
- National Key Laboratory of Plant Molecular Genetics, Chinese Academy of Sciences (CAS) Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
- Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Ruo-An Wang
- National Key Laboratory of Plant Molecular Genetics, Chinese Academy of Sciences (CAS) Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - Tao Tao
- JiangsuKey Laboratory of Crop Genomics and Molecular Breeding, College of Agriculture, Yangzhou University, Yangzhou, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Key Laboratory of Crop Genetics and Physiology, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, College of Agriculture, Yangzhou University, Yangzhou, China
| | - Lian-Min Hong
- JiangsuKey Laboratory of Crop Genomics and Molecular Breeding, College of Agriculture, Yangzhou University, Yangzhou, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Key Laboratory of Crop Genetics and Physiology, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, College of Agriculture, Yangzhou University, Yangzhou, China
| | - Qian-Qian Guo
- JiangsuKey Laboratory of Crop Genomics and Molecular Breeding, College of Agriculture, Yangzhou University, Yangzhou, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Key Laboratory of Crop Genetics and Physiology, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, College of Agriculture, Yangzhou University, Yangzhou, China
| | - Shu-Wen Jia
- National Key Laboratory of Plant Molecular Genetics, Chinese Academy of Sciences (CAS) Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - Tao Song
- National Key Laboratory of Plant Molecular Genetics, Chinese Academy of Sciences (CAS) Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
- Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Yu-Jia Leng
- JiangsuKey Laboratory of Crop Genomics and Molecular Breeding, College of Agriculture, Yangzhou University, Yangzhou, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Key Laboratory of Crop Genetics and Physiology, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, College of Agriculture, Yangzhou University, Yangzhou, China
| | - Xiu-Ling Cai
- JiangsuKey Laboratory of Crop Genomics and Molecular Breeding, College of Agriculture, Yangzhou University, Yangzhou, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Key Laboratory of Crop Genetics and Physiology, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, College of Agriculture, Yangzhou University, Yangzhou, China
- National Key Laboratory of Plant Molecular Genetics, Chinese Academy of Sciences (CAS) Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
| | - Ji-Ping Gao
- JiangsuKey Laboratory of Crop Genomics and Molecular Breeding, College of Agriculture, Yangzhou University, Yangzhou, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Key Laboratory of Crop Genetics and Physiology, College of Agriculture, Yangzhou University, Yangzhou, China
- Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, College of Agriculture, Yangzhou University, Yangzhou, China
- National Key Laboratory of Plant Molecular Genetics, Chinese Academy of Sciences (CAS) Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai, China
- Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing, 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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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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9
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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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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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11
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Pan L, Wang M, Yang Y, Chen C, Dai H, Zhang Z, Hua B, Miao M. Whole-genome resequencing identified QTLs, candidate genes and Kompetitive Allele-Specific PCR markers associated with the large fruit of Atlantic Giant ( Cucurbita maxima). FRONTIERS IN PLANT SCIENCE 2022; 13:942004. [PMID: 35937359 PMCID: PMC9354748 DOI: 10.3389/fpls.2022.942004] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 07/01/2022] [Indexed: 06/15/2023]
Abstract
Atlantic Giant (AG) pumpkin (Cucurbita maxima) produces the world's largest fruit. Elucidating the molecular mechanism of AG fruit formation is of scientific and practical importance. In this research, genome-wide resequencing of an F2 population produced by a cross between AG and its small-fruit ancestor Hubbard was used to identify quantitative trait loci (QTLs) and candidate genes. Transgressive segregation of fruit size-related traits was observed in the F2 population, suggesting that fruit size was a quantitative trait controlled by multiple genes. A genetic map with an average physical distance of 154 kb per marker was constructed, and 13 QTLs related to fruit size were identified using bin-map construction. RNA sequencing analysis revealed that pathways associated with assimilate accumulation into the fruit, including carbohydrate metabolism, were significantly enriched in differentially expressed genes. According to the predicted impact of mutation on the biological function of certain proteins, 13 genes were selected as candidate genes associated with fruit size, among which two phytohormone-related genes, CmaCh17G011340 (a flavin-containing monooxygenase) and CmaCh04G029660 (a leucine-rich repeat protein kinase) were chosen for further investigation. Finally, one insertion-deletion (inDel) and three single nucleotide polymorphisms (SNPs) were successfully transformed to Kompetitive Allele-Specific PCR (KASP) markers. The novel QTLs and candidate genes identified provide insights into the genetic mechanism of large fruit formation of AG, and the genetic map and tightly linked KASP markers developed in this study can be employed for marker-assisted breeding to alter fruit size of C. maxima.
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Affiliation(s)
- Liu Pan
- College of Horticulture and Plant Protection, Yangzhou University, Yangzhou, China
| | - Min Wang
- College of Horticulture and Plant Protection, Yangzhou University, Yangzhou, China
| | - Yating Yang
- College of Horticulture and Plant Protection, Yangzhou University, Yangzhou, China
| | - Chen Chen
- College of Horticulture and Plant Protection, Yangzhou University, Yangzhou, China
| | - Haibo Dai
- College of Horticulture and Plant Protection, Yangzhou University, Yangzhou, China
| | - Zhiping Zhang
- College of Horticulture and Plant Protection, Yangzhou University, Yangzhou, China
| | - Bing Hua
- College of Horticulture and Plant Protection, Yangzhou University, Yangzhou, China
| | - Minmin Miao
- College of Horticulture and Plant Protection, Yangzhou University, Yangzhou, China
- Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Yangzhou University, Yangzhou, China
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12
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Qin MF, Li LT, Singh J, Sun MY, Bai B, Li SW, Ni JP, Zhang JY, Zhang X, Wei WL, Zhang MY, Li JM, Qi KJ, Zhang SL, Khan A, Wu J. Construction of a high-density bin-map and identification of fruit quality-related quantitative trait loci and functional genes in pear. HORTICULTURE RESEARCH 2022; 9:uhac141. [PMID: 36072841 PMCID: PMC9437719 DOI: 10.1093/hr/uhac141] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/01/2022] [Accepted: 06/13/2022] [Indexed: 06/01/2023]
Abstract
Pear (Pyrus spp.) is one of the most common fruit crops grown in temperate regions worldwide. Genetic enhancement of fruit quality is a fundamental goal of pear breeding programs. The genetic control of pear fruit quality traits is highly quantitative, and development of high-density genetic maps can facilitate fine-mapping of quantitative trait loci (QTLs) and gene identification. Bin-mapping is a powerful method of constructing high-resolution genetic maps from large-scale genotyping datasets. We performed whole-genome sequencing of pear cultivars 'Niitaka' and 'Hongxiangsu' and their 176 F 1 progeny to identify genome-wide single-nucleotide polymorphism (SNP) markers for constructing a high-density bin-map of pear. This analysis yielded a total of 1.93 million SNPs and a genetic bin-map of 3190 markers spanning 1358.5 cM, with an average adjacent interval of 0.43 cM. This bin-map, along with other high-density genetic maps in pear, improved the reference genome assembly from 75.5 to 83.7% by re-anchoring the scaffolds. A quantitative genetic analysis identified 148 QTLs for 18 fruit-related traits; among them, QTLs for stone cell content, several key monosaccharides, and fruit pulp acids were identified for the first time in pear. A gene expression analysis of six pear cultivars identified 399 candidates in the identified QTL regions, which showed expression specific to fruit developmental stages in pear. Finally, we confirmed the function of PbrtMT1, a tonoplast monosaccharide transporter-related gene responsible for the enhancement of fructose accumulation in pear fruit on linkage group 16, in a transient transformation experiment. This study provides genomic and genetic resources as well as potential candidate genes for fruit quality improvement in pear.
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Affiliation(s)
| | | | - Jugpreet Singh
- Plant Pathology and Plant-Microbe Section, Cornell University, Geneva, NY 14456, USA
| | - Man-Yi Sun
- College of Horticulture, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
| | - Bing Bai
- College of Horticulture, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
| | - Si-Wei Li
- College of Horticulture, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
| | - Jiang-Ping Ni
- College of Horticulture, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
| | - Jia-Ying Zhang
- College of Horticulture, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
| | - Xun Zhang
- College of Horticulture, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
| | - Wei-Lin Wei
- College of Horticulture, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
| | - Ming-Yue Zhang
- College of Horticulture, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
| | - Jia-Ming Li
- College of Horticulture, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
| | - Kai-Jie Qi
- College of Horticulture, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
| | - Shao-Ling Zhang
- College of Horticulture, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
| | | | - Jun Wu
- Corresponding authors. E-mail: ,
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Zheng H, Hou L, Xie J, Cao F, Wei R, Yang M, Qi Z, Zhu R, Zhang Z, Xin D, Li C, Liu C, Jiang H, Chen Q. Construction of Chromosome Segment Substitution Lines and Inheritance of Seed-Pod Characteristics in Wild Soybean. FRONTIERS IN PLANT SCIENCE 2022; 13:869455. [PMID: 35783974 PMCID: PMC9247457 DOI: 10.3389/fpls.2022.869455] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Accepted: 05/27/2022] [Indexed: 06/15/2023]
Abstract
Genetic populations provide the basis for genetic and genomic research, and chromosome segment substitution lines (CSSLs) are a powerful tool for the fine mapping of quantitative traits, new gene mining, and marker-assisted breeding. In this study, 213 CSSLs were obtained by self-crossing, backcrossing, and marker-assisted selection between cultivated soybean (Glycine max [L.] Merr.) variety Suinong14 (SN14) and wild soybean (Glycine soja Sieb. et Zucc.) ZYD00006. The genomes of these 213 CSSLs were resequenced and 580,524 single-nucleotide polymorphism markers were obtained, which were divided into 3,780 bin markers. The seed-pod-related traits were analyzed by quantitative trait locus (QTL) mapping using CSSLs. A total of 170 QTLs were detected, and 32 QTLs were detected stably for more than 2 years. Through epistasis analysis, 955 pairs of epistasis QTLs related to seed-pod traits were obtained. Furthermore, the hundred-seed weight QTL was finely mapped to the region of 64.4 Kb on chromosome 12, and Glyma.12G088900 was identified as a candidate gene. Taken together, a set of wild soybean CSSLs was constructed and upgraded by a resequencing technique. The seed-pod-related traits were studied by bin markers, and a candidate gene for the hundred-seed weight was finely mapped. Our results have revealed the CSSLs can be an effective tool for QTL mapping, epistatic effect analysis, and gene cloning.
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Affiliation(s)
| | - Lilong Hou
- Northeast Agricultural University, Harbin, China
| | - Jianguo Xie
- Jilin Academy of Agricultural Sciences, Soybean Research Institute, Changchun, China
| | - Fubin Cao
- Northeast Agricultural University, Harbin, China
| | - Ruru Wei
- Northeast Agricultural University, Harbin, China
| | | | - Zhaoming Qi
- Northeast Agricultural University, Harbin, China
| | | | | | - Dawei Xin
- Northeast Agricultural University, Harbin, China
| | - Candong Li
- Jiamusi Branch Institute, Heilongjiang Academy of Agricultural Sciences, Jiamusi, China
| | - Chunyan Liu
- Northeast Agricultural University, Harbin, China
| | - Hongwei Jiang
- Jilin Academy of Agricultural Sciences, Soybean Research Institute, Changchun, China
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Wang Y, Bao J, Wei X, Wu S, Fang C, Li Z, Qi Y, Gao Y, Dong Z, Wan X. Genetic Structure and Molecular Mechanisms Underlying the Formation of Tassel, Anther, and Pollen in the Male Inflorescence of Maize (Zea mays L.). Cells 2022; 11:cells11111753. [PMID: 35681448 PMCID: PMC9179574 DOI: 10.3390/cells11111753] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 05/24/2022] [Accepted: 05/24/2022] [Indexed: 02/08/2023] Open
Abstract
Maize tassel is the male reproductive organ which is located at the plant’s apex; both its morphological structure and fertility have a profound impact on maize grain yield. More than 40 functional genes regulating the complex tassel traits have been cloned up to now. However, the detailed molecular mechanisms underlying the whole process, from male inflorescence meristem initiation to tassel morphogenesis, are seldom discussed. Here, we summarize the male inflorescence developmental genes and construct a molecular regulatory network to further reveal the molecular mechanisms underlying tassel-trait formation in maize. Meanwhile, as one of the most frequently studied quantitative traits, hundreds of quantitative trait loci (QTLs) and thousands of quantitative trait nucleotides (QTNs) related to tassel morphology have been identified so far. To reveal the genetic structure of tassel traits, we constructed a consensus physical map for tassel traits by summarizing the genetic studies conducted over the past 20 years, and identified 97 hotspot intervals (HSIs) that can be repeatedly mapped in different labs, which will be helpful for marker-assisted selection (MAS) in improving maize yield as well as for providing theoretical guidance in the subsequent identification of the functional genes modulating tassel morphology. In addition, maize is one of the most successful crops in utilizing heterosis; mining of the genic male sterility (GMS) genes is crucial in developing biotechnology-based male-sterility (BMS) systems for seed production and hybrid breeding. In maize, more than 30 GMS genes have been isolated and characterized, and at least 15 GMS genes have been promptly validated by CRISPR/Cas9 mutagenesis within the past two years. We thus summarize the maize GMS genes and further update the molecular regulatory networks underlying male fertility in maize. Taken together, the identified HSIs, genes and molecular mechanisms underlying tassel morphological structure and male fertility are useful for guiding the subsequent cloning of functional genes and for molecular design breeding in maize. Finally, the strategies concerning efficient and rapid isolation of genes controlling tassel morphological structure and male fertility and their application in maize molecular breeding are also discussed.
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Affiliation(s)
- Yanbo Wang
- Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, Research Center of Biology and Agriculture, University of Science and Technology Beijing, Beijing 100024, China; (Y.W.); (J.B.); (X.W.); (S.W.); (C.F.); (Y.Q.); (Y.G.)
| | - Jianxi Bao
- Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, Research Center of Biology and Agriculture, University of Science and Technology Beijing, Beijing 100024, China; (Y.W.); (J.B.); (X.W.); (S.W.); (C.F.); (Y.Q.); (Y.G.)
| | - Xun Wei
- Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, Research Center of Biology and Agriculture, University of Science and Technology Beijing, Beijing 100024, China; (Y.W.); (J.B.); (X.W.); (S.W.); (C.F.); (Y.Q.); (Y.G.)
- Beijing Engineering Laboratory of Main Crop Bio-Tech Breeding, Beijing International Science and Technology Cooperation Base of Bio-Tech Breeding, Beijing Solidwill Sci-Tech Co., Ltd., Beijing 100192, China;
| | - Suowei Wu
- Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, Research Center of Biology and Agriculture, University of Science and Technology Beijing, Beijing 100024, China; (Y.W.); (J.B.); (X.W.); (S.W.); (C.F.); (Y.Q.); (Y.G.)
- Beijing Engineering Laboratory of Main Crop Bio-Tech Breeding, Beijing International Science and Technology Cooperation Base of Bio-Tech Breeding, Beijing Solidwill Sci-Tech Co., Ltd., Beijing 100192, China;
| | - Chaowei Fang
- Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, Research Center of Biology and Agriculture, University of Science and Technology Beijing, Beijing 100024, China; (Y.W.); (J.B.); (X.W.); (S.W.); (C.F.); (Y.Q.); (Y.G.)
| | - Ziwen Li
- Beijing Engineering Laboratory of Main Crop Bio-Tech Breeding, Beijing International Science and Technology Cooperation Base of Bio-Tech Breeding, Beijing Solidwill Sci-Tech Co., Ltd., Beijing 100192, China;
| | - Yuchen Qi
- Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, Research Center of Biology and Agriculture, University of Science and Technology Beijing, Beijing 100024, China; (Y.W.); (J.B.); (X.W.); (S.W.); (C.F.); (Y.Q.); (Y.G.)
| | - Yuexin Gao
- Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, Research Center of Biology and Agriculture, University of Science and Technology Beijing, Beijing 100024, China; (Y.W.); (J.B.); (X.W.); (S.W.); (C.F.); (Y.Q.); (Y.G.)
| | - Zhenying Dong
- Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, Research Center of Biology and Agriculture, University of Science and Technology Beijing, Beijing 100024, China; (Y.W.); (J.B.); (X.W.); (S.W.); (C.F.); (Y.Q.); (Y.G.)
- Beijing Engineering Laboratory of Main Crop Bio-Tech Breeding, Beijing International Science and Technology Cooperation Base of Bio-Tech Breeding, Beijing Solidwill Sci-Tech Co., Ltd., Beijing 100192, China;
- Correspondence: (Z.D.); (X.W.); Tel.: +86-152-1092-0373 (Z.D.); +86-186-0056-1850 (X.W.)
| | - Xiangyuan Wan
- Zhongzhi International Institute of Agricultural Biosciences, Shunde Graduate School, Research Center of Biology and Agriculture, University of Science and Technology Beijing, Beijing 100024, China; (Y.W.); (J.B.); (X.W.); (S.W.); (C.F.); (Y.Q.); (Y.G.)
- Beijing Engineering Laboratory of Main Crop Bio-Tech Breeding, Beijing International Science and Technology Cooperation Base of Bio-Tech Breeding, Beijing Solidwill Sci-Tech Co., Ltd., Beijing 100192, China;
- Correspondence: (Z.D.); (X.W.); Tel.: +86-152-1092-0373 (Z.D.); +86-186-0056-1850 (X.W.)
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15
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Yepuri V, Jalali S, Mudunuri V, Pothakani S, Kancharla N, Arockiasamy S. Genotyping by sequencing-based linkage map construction and identification of quantitative trait loci for yield-related traits and oil content in Jatropha (Jatropha curcas L.). Mol Biol Rep 2022; 49:4293-4306. [PMID: 35239140 DOI: 10.1007/s11033-022-07264-w] [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: 12/14/2021] [Accepted: 02/14/2022] [Indexed: 10/18/2022]
Abstract
BACKGROUND Jatropha (Jatropha curcas L.) has been considered as a potential bioenergy crop and its genetic improvement is essential for higher seed yield and oil content which has been hampered due to lack of desirable molecular markers. METHODS AND RESULTS An F2 population was created using an intraspecific cross involving a Central American line RJCA9 and an Asiatic species RJCS-9 to develop a dense genetic map and for Quantitative trait loci (QTL) identification. The genotyping-by-sequencing (GBS) approach was used to genotype the mapping population of 136 F2 individuals along with the two parental lines for classification of the genotypes based on single nucleotide polymorphism (SNPs). NextSeq 2500 sequencing technology provided a total of 517.23 million clean reads, with an average of ~ 3.8 million reads per sample. We analysed 411 SNP markers and developed 11 linkage groups. The total length of the genetic map was 4092.3 cM with an average marker interval of 10.04 cM. We have identified a total of 83 QTLs for various yield and oil content governing traits. The percentage of phenotypic variation (PV) was found to be in the range of 8.81 to 65.31%, and a QTL showed the maximum PV of 65.3% for a total seed number on the 6th linkage group (LG). CONCLUSIONS The QTLs detected in this study for various phenotypic traits will lay down the path for marker-assisted breeding in the future and cloning of genes that are responsible for phenotypic variation.
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Affiliation(s)
- Vijay Yepuri
- Agronomy Division, Reliance Technology Group, Reliance Industries Ltd, Ghansoli, Navi Mumbai, 400701, India
| | - Saakshi Jalali
- Agronomy Division, Reliance Technology Group, Reliance Industries Ltd, Ghansoli, Navi Mumbai, 400701, India
| | - Vishwnadharaju Mudunuri
- Jatropha Breeding station, Reliance Industries Ltd, IDA-Peddapuram, ADB Road, Samalkota, Andhra Pradesh, 533440, India
| | - Sai Pothakani
- Jatropha Breeding station, Reliance Industries Ltd, IDA-Peddapuram, ADB Road, Samalkota, Andhra Pradesh, 533440, India
| | - Nagesh Kancharla
- Agronomy Division, Reliance Technology Group, Reliance Industries Ltd, Ghansoli, Navi Mumbai, 400701, India
| | - S Arockiasamy
- Agronomy Division, Reliance Technology Group, Reliance Industries Ltd, Ghansoli, Navi Mumbai, 400701, India.
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16
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Guan H, Chen X, Wang K, Liu X, Zhang D, Li Y, Song Y, Shi Y, Wang T, Li C, Li Y. Genetic Variation in ZmPAT7 Contributes to Tassel Branch Number in Maize. Int J Mol Sci 2022; 23:ijms23052586. [PMID: 35269730 PMCID: PMC8910302 DOI: 10.3390/ijms23052586] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 02/22/2022] [Accepted: 02/24/2022] [Indexed: 02/04/2023] Open
Abstract
Tassel branch number (TBN) is one of the important agronomic traits that contribute to the efficiency of seed production and has been selected strongly during the modern maize breeding process. However, the genetic mechanisms of TBN in maize are not entirely clear. In this study, we used a B73 × CML247 recombination inbred lines (RILs) population to detect quantitative trait loci (QTLs) for TBN. A total of four QTLs (qTBN2a, qTBN2b, qTBN4, and qTBN6) and six candidate genes were identified through expression analysis. Further, one of the candidates (GRMZM2G010011, ZmPAT7) encoding an S-acyltransferase was selected to validate its function by CRISPR-Cas9 technology, and its loss-of-function lines showed a significant increase in TBN. A key SNP(−101) variation in the promoter of ZmPAT7 was significantly associated with TBN. A total of 17 distant eQTLs associated with the expression of ZmPAT7 were identified in expression quantitative trait loci (eQTL) analysis, and ZmNAC3 may be a major factor involved in regulating ZmPAT7. These findings of the present study promote our understanding of the genetic basis of tassel architecture and provide new gene resources for maize breeding improvement.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - Yu Li
- Correspondence: (C.L.); (Y.L.)
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17
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Gong H, Rehman F, Ma Y, A B, Zeng S, Yang T, Huang J, Li Z, Wu D, Wang Y. Germplasm Resources and Strategy for Genetic Breeding of Lycium Species: A Review. FRONTIERS IN PLANT SCIENCE 2022; 13:802936. [PMID: 35222468 PMCID: PMC8874141 DOI: 10.3389/fpls.2022.802936] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 01/07/2022] [Indexed: 06/01/2023]
Abstract
Lycium species (goji), belonging to Solanaceae, are widely spread in the arid to semiarid environments of Eurasia, Africa, North and South America, among which most species have affinal drug and diet functions, resulting in their potential to be a superior healthy food. However, compared with other crop species, scientific research on breeding Lycium species lags behind. This review systematically introduces the present germplasm resources, cytological examination and molecular-assisted breeding progress in Lycium species. Introduction of the distribution of Lycium species around the world could facilitate germplasm collection for breeding. Karyotypes of different species could provide a feasibility analysis of fertility between species. The introduction of mapping technology has discussed strategies for quantitative trait locus (QTL) mapping in Lycium species according to different kinds of traits. Moreover, to extend the number of traits and standardize the protocols of trait detection, we also provide 1,145 potential traits (275 agronomic and 870 metabolic) in different organs based on different reference studies on Lycium, tomato and other Solanaceae species. Finally, perspectives on goji breeding research are discussed and concluded. This review will provide breeders with new insights into breeding Lycium species.
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Affiliation(s)
- Haiguang Gong
- Key Laboratory of South China Agricultural Plant Molecular Analysis and Genetic Improvement, Provincial Key Laboratory of Digital Botanical Garden and Public Science, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
- School of Life Science, University of Chinese Academy of Sciences, Beijing, China
| | - Fazal Rehman
- Key Laboratory of South China Agricultural Plant Molecular Analysis and Genetic Improvement, Provincial Key Laboratory of Digital Botanical Garden and Public Science, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
- School of Life Science, University of Chinese Academy of Sciences, Beijing, China
| | - Yun Ma
- Key Laboratory of South China Agricultural Plant Molecular Analysis and Genetic Improvement, Provincial Key Laboratory of Digital Botanical Garden and Public Science, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
- School of Life Science, University of Chinese Academy of Sciences, Beijing, China
| | - Biao A
- Key Laboratory of South China Agricultural Plant Molecular Analysis and Genetic Improvement, Provincial Key Laboratory of Digital Botanical Garden and Public Science, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
- School of Life Science, University of Chinese Academy of Sciences, Beijing, China
| | - Shaohua Zeng
- Key Laboratory of South China Agricultural Plant Molecular Analysis and Genetic Improvement, Provincial Key Laboratory of Digital Botanical Garden and Public Science, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
- School of Life Science, University of Chinese Academy of Sciences, Beijing, China
| | - Tianshun Yang
- Key Laboratory of South China Agricultural Plant Molecular Analysis and Genetic Improvement, Provincial Key Laboratory of Digital Botanical Garden and Public Science, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
| | - Jianguo Huang
- Key Laboratory of South China Agricultural Plant Molecular Analysis and Genetic Improvement, Provincial Key Laboratory of Digital Botanical Garden and Public Science, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
- School of Life Science, University of Chinese Academy of Sciences, Beijing, China
| | - Zhong Li
- Agricultural Comprehensive Development Center in Ningxia Hui Autonomous Region, Yinchuan, China
| | | | - Ying Wang
- Key Laboratory of South China Agricultural Plant Molecular Analysis and Genetic Improvement, Provincial Key Laboratory of Digital Botanical Garden and Public Science, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
- School of Life Science, Gannan Normal University, Ganzhou, China
- School of Life Science, University of Chinese Academy of Sciences, Beijing, China
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18
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Li Y, Mo T, Ran L, Zeng J, Wang C, Liang A, Dai Y, Wu Y, Zhong Z, Xiao Y. Genome resequencing-based high-density genetic map and QTL detection for yield and fiber quality traits in diploid Asiatic cotton (Gossypium arboreum). Mol Genet Genomics 2022; 297:199-212. [PMID: 35048185 DOI: 10.1007/s00438-021-01848-0] [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: 03/11/2021] [Accepted: 12/14/2021] [Indexed: 10/19/2022]
Abstract
Cotton is the most important fiber crop in the world. Asiatic cotton (Gossypium arboreum, genome A2) is a diploid cotton species producing spinnable fibers and important germplasm for cotton breeding and a significant model for fiber biology. However, the genetic map of Asiatic cotton has been lagging behind tetraploid cottons, as well as other stable crops. This study aimed to construct a high-density SNP genetic map and to map QTLs for important yield and fiber quality traits. Using a recombinant inbred line (RIL) population and genome resequencing technology, we constructed a high-density genetic map that covered 1980.17 cM with an average distance of 0.61 cM between adjacent markers. QTL analysis revealed a total of 297 QTLs for 13 yield and fiber quality traits in three environments, explaining 5.0-37.4% of the phenotypic variance, among which 75 were stably detected in two or three environments. Besides, 47 QTL clusters, comprising 131 QTLs for representative traits, were identified. Our works laid solid foundation for fine mapping and cloning of QTL for yield and fiber quality traits in Asiatic cotton.
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Affiliation(s)
- Yaohua Li
- Biotechnology Research Center, Chongqing Key Laboratory of Application and Safety Control of Genetically Modified Crops, Southwest University, Southwest University Southern Campus, Tiansheng Rd No. 2, Beibei, Chongqing, 400716, China
| | - Tong Mo
- Biotechnology Research Center, Chongqing Key Laboratory of Application and Safety Control of Genetically Modified Crops, Southwest University, Southwest University Southern Campus, Tiansheng Rd No. 2, Beibei, Chongqing, 400716, China
| | - Lingfang Ran
- Biotechnology Research Center, Chongqing Key Laboratory of Application and Safety Control of Genetically Modified Crops, Southwest University, Southwest University Southern Campus, Tiansheng Rd No. 2, Beibei, Chongqing, 400716, China
| | - Jianyan Zeng
- Biotechnology Research Center, Chongqing Key Laboratory of Application and Safety Control of Genetically Modified Crops, Southwest University, Southwest University Southern Campus, Tiansheng Rd No. 2, Beibei, Chongqing, 400716, China
| | - Chuannan Wang
- Biotechnology Research Center, Chongqing Key Laboratory of Application and Safety Control of Genetically Modified Crops, Southwest University, Southwest University Southern Campus, Tiansheng Rd No. 2, Beibei, Chongqing, 400716, China
| | - Aimin Liang
- Biotechnology Research Center, Chongqing Key Laboratory of Application and Safety Control of Genetically Modified Crops, Southwest University, Southwest University Southern Campus, Tiansheng Rd No. 2, Beibei, Chongqing, 400716, China
| | - Yonglu Dai
- Biotechnology Research Center, Chongqing Key Laboratory of Application and Safety Control of Genetically Modified Crops, Southwest University, Southwest University Southern Campus, Tiansheng Rd No. 2, Beibei, Chongqing, 400716, China
| | - Yiping Wu
- Biotechnology Research Center, Chongqing Key Laboratory of Application and Safety Control of Genetically Modified Crops, Southwest University, Southwest University Southern Campus, Tiansheng Rd No. 2, Beibei, Chongqing, 400716, China
| | - Ziman Zhong
- Biotechnology Research Center, Chongqing Key Laboratory of Application and Safety Control of Genetically Modified Crops, Southwest University, Southwest University Southern Campus, Tiansheng Rd No. 2, Beibei, Chongqing, 400716, China
| | - Yuehua Xiao
- Biotechnology Research Center, Chongqing Key Laboratory of Application and Safety Control of Genetically Modified Crops, Southwest University, Southwest University Southern Campus, Tiansheng Rd No. 2, Beibei, Chongqing, 400716, China.
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Xu Z, Wang F, Zhou Z, Meng Q, Chen Y, Han X, Tie S, Liu C, Hao Z, Li M, Zhang D, Han J, Wang Z, Li X, Weng J. Identification and Fine-Mapping of a Novel QTL, qMrdd2, That Confers Resistance to Maize Rough Dwarf Disease. PLANT DISEASE 2022; 106:65-72. [PMID: 34132596 DOI: 10.1094/pdis-03-20-0495-re] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Maize rough dwarf disease (MRDD) is caused by a virus and seriously affects maize quality and yield worldwide. MRDD can be most effectively controlled with disease-resistant hybrids of corn. Here, MRDD-resistant (Qi319) and -susceptible (Ye478) parental inbred maize lines and their 314 recombinant inbred lines (RILs) that were derived from a cross between them were evaluated across three environments. A stable resistance QTL, qMrdd2, was identified and mapped using best linear unbiased prediction (BLUP) values to a 0.55-Mb region between the markers MK807 and MK811 on chromosome 2 (B73 RefGen_v3) and was found to explain 8.6 to 11.0% of the total phenotypic variance in MRDD resistance. We validated the effect of qMrdd2 using a chromosome segment substitution line (CSSL) that was derived from a cross between maize inbred Qi319 as the MRDD resistance donor and Ye478 as the recipient. Disease severity index of the CSSL haplotype II harboring qMrdd2 was significantly lower than that of the susceptible parent Ye478. Subsequently, we fine-mapped qMrdd2 to a 315-kb region flanked by the markers RD81 and RD87, thus testing recombinant-derived progeny using selfed backcrossed families. In this study, we identified a novel QTL for MRDD resistance by combining the RIL and CSSL populations, thus providing important genetic information that can be used for breeding MRDD-resistant varieties of maize.
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Affiliation(s)
- Zhennan Xu
- Institute of Crop Science, Chinese Academy of Agricultural Science, Haidian District, Beijing 100081, China
- Northeast Agricultural University, XiangFang District, Harbin, Heilongjiang 150030, China
| | - Feifei Wang
- Northeast Agricultural University, XiangFang District, Harbin, Heilongjiang 150030, China
| | - Zhiqiang Zhou
- Northeast Agricultural University, XiangFang District, Harbin, Heilongjiang 150030, China
| | - Qingchang Meng
- Institute of Plant Protection, Jiangsu Academy of Agricultural Sciences, Xuanwu District, Nanjing 210014, China
| | - Yanping Chen
- Institute of Plant Protection, Jiangsu Academy of Agricultural Sciences, Xuanwu District, Nanjing 210014, China
| | - Xiaohua Han
- The Cereal Crops Institute, Henan Academy of Agricultural Sciences, Jinshui District, Zhengzhou 450002, China
| | - Shuanggui Tie
- The Cereal Crops Institute, Henan Academy of Agricultural Sciences, Jinshui District, Zhengzhou 450002, China
| | - Changlin Liu
- Northeast Agricultural University, XiangFang District, Harbin, Heilongjiang 150030, China
| | - Zhuanfang Hao
- Northeast Agricultural University, XiangFang District, Harbin, Heilongjiang 150030, China
| | - Mingshun Li
- Northeast Agricultural University, XiangFang District, Harbin, Heilongjiang 150030, China
| | - Degui Zhang
- Northeast Agricultural University, XiangFang District, Harbin, Heilongjiang 150030, China
| | - Jienan Han
- Northeast Agricultural University, XiangFang District, Harbin, Heilongjiang 150030, China
| | - Zhenhua Wang
- Northeast Agricultural University, XiangFang District, Harbin, Heilongjiang 150030, China
| | - Xinhai Li
- Institute of Crop Science, Chinese Academy of Agricultural Science, Haidian District, Beijing 100081, China
| | - Jianfeng Weng
- Institute of Crop Science, Chinese Academy of Agricultural Science, Haidian District, Beijing 100081, China
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20
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Feng L, Ma A, Song B, Yu S, Qi X. Mapping causal genes and genetic interactions for agronomic traits using a large F2 population in rice. G3 (BETHESDA, MD.) 2021; 11:6369515. [PMID: 34515770 PMCID: PMC8527483 DOI: 10.1093/g3journal/jkab318] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Accepted: 08/26/2021] [Indexed: 11/13/2022]
Abstract
Dissecting the genetic mechanisms underlying agronomic traits is of great importance for crop breeding. Agronomic traits are usually controlled by multiple quantitative trait loci (QTLs) and genetic interactions, and mapping the underlying causal genes is still labor-intensive and time-consuming. Here, we present a genetic tool for directly targeting the specific causal genes by using a single-gene resolution linkage map that was constructed from 3756 F2 rice plants via targeted sequencing technology and Tukey-Kramer multiple comparisons test. Three large- and moderate-effect QTLs, qHD6-2, qGL3-1, and qGW5-2, were successfully mapped to their specific causal genes, Hd1, GS3, and GW5, respectively. A complex genetic interaction network containing 30 QTL-QTL interactions was constructed, revealing that the alternative allele of hub QTL, qHD6-2, can hide or release the genetic contributions of the alleles at interacting loci. Moreover, arranging genetic interactions in the models lead to more accurate phenotypic predictions. These results provide a community resource and new feasible strategy for deciphering the genetic mechanisms of complex agronomic traits and accelerating crop breeding.
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Affiliation(s)
- Laibao Feng
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China.,University of Chinese Academy of Sciences, Beijing 100049, China.,Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing 100049, China
| | - Aimin Ma
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China.,Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing 100049, China
| | - Bo Song
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China.,Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing 100049, China
| | - Sibin Yu
- National Key Laboratory of Crop Genetic Improvement, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China
| | - Xiaoquan Qi
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China.,Innovation Academy for Seed Design, Chinese Academy of Sciences, Beijing 100049, China
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21
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Shah A, Mittleman BE, Gilad Y, Li YI. Benchmarking sequencing methods and tools that facilitate the study of alternative polyadenylation. Genome Biol 2021; 22:291. [PMID: 34649612 PMCID: PMC8518154 DOI: 10.1186/s13059-021-02502-z] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Accepted: 09/16/2021] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND Alternative cleavage and polyadenylation (APA), an RNA processing event, occurs in over 70% of human protein-coding genes. APA results in mRNA transcripts with distinct 3' ends. Most APA occurs within 3' UTRs, which harbor regulatory elements that can impact mRNA stability, translation, and localization. RESULTS APA can be profiled using a number of established computational tools that infer polyadenylation sites from standard, short-read RNA-seq datasets. Here, we benchmarked a number of such tools-TAPAS, QAPA, DaPars2, GETUTR, and APATrap- against 3'-Seq, a specialized RNA-seq protocol that enriches for reads at the 3' ends of genes, and Iso-Seq, a Pacific Biosciences (PacBio) single-molecule full-length RNA-seq method in their ability to identify polyadenylation sites and quantify polyadenylation site usage. We demonstrate that 3'-Seq and Iso-Seq are able to identify and quantify the usage of polyadenylation sites more reliably than computational tools that take short-read RNA-seq as input. However, we find that running one such tool, QAPA, with a set of polyadenylation site annotations derived from small quantities of 3'-Seq or Iso-Seq can reliably quantify variation in APA across conditions, such asacross genotypes, as demonstrated by the successful mapping of alternative polyadenylation quantitative trait loci (apaQTL). CONCLUSIONS We envisage that our analyses will shed light on the advantages of studying APA with more specialized sequencing protocols, such as 3'-Seq or Iso-Seq, and the limitations of studying APA with short-read RNA-seq. We provide a computational pipeline to aid in the identification of polyadenylation sites and quantification of polyadenylation site usages using Iso-Seq data as input.
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Affiliation(s)
- Ankeeta Shah
- Genetics, Genomics, and Systems Biology, University of Chicago, Chicago, IL, USA
| | - Briana E Mittleman
- Genetics, Genomics, and Systems Biology, University of Chicago, Chicago, IL, USA
| | - Yoav Gilad
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL, USA
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Yang I Li
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL, USA.
- Department of Human Genetics, University of Chicago, Chicago, IL, USA.
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22
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Mapping of QTL for agronomic traits using high-density SNPs with an RIL population in maize. Genes Genomics 2021; 43:1403-1411. [PMID: 34591233 DOI: 10.1007/s13258-021-01169-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 09/16/2021] [Indexed: 10/20/2022]
Abstract
BACKGROUND Genome wide association studies (GWAS) have been widely used to identify QTLs underlying quantitative traits in humans and animals, and they have also become a popular method of mapping QTLs in many crops, including maize. Advances in high-throughput genotyping technologies enable construction of high-density linkage maps using SNP markers. OBJECTIVES High-density genetic mapping must precede to find molecular markers associated with a particular trait. The objectives of this study were to (1) construct a high-density linkage map using SNP markers and (2) detect the QTLs for grain yield and quality related traits of the Mo17/KW7 RIL population. METHODS In this study, two parental lines, Mo17 (normal maize inbred line) and KW7 (waxy inbred line) and 80 F7:8 lines in the Mo17/KW7 RIL population were genotyped using the MaizeSNP50 BeadChip, an Illumina BeadChip array of 56,110 maize SNPs. Marker integration and detection of QTLs was performed using the inclusive composite interval mapping (ICIM) method within the QTL IciMapping software. RESULTS This study was genotyped using the Illumina MaizeSNP50 BeadChip for maize Mo17/KW7 recombinant inbred line (RIL) population. The 2904 SNP markers were distributed along all 10 maize chromosomes. The total length of the linkage map was 3553.7 cm, with an average interval of 1.22 cm between SNPs. A total of 18 QTLs controlling eight traits were detected in the Mo17/KW7 RIL population. Three QTLs for plant height (PH) were detected on chromosomes 4 and 8 and showed from 16.01% (qPH8) to 19.85% (qPH4a) of phenotypic variance. Five QTLs related to ear height (EH) were identified on chromosomes 3, 4, and 6 and accounted for 3.79% (qEH6) to 27.57% (qEH4b) of phenotypic variance. Five QTLs related to water content (WC) on chromosomes 1, 4, 8, and 9 accounted for 9.55% (qWC8b) to 23.30% (qWC4) of phenotypic variance. One QTL (qAC9) relating to amylose content (AC) on chromosome 9 showed 82.10% of phenotypic variance. CONCLUSIONS The high-density linkage map and putative QTLs of the maize RIL population detected in this study can be effectively utilized in waxy and normal maize breeding programs to facilitate the selection process through marker-assisted selection (MAS) breeding programs.
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23
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Dissecting the Genetic Basis of Flowering Time and Height Related-Traits Using Two Doubled Haploid Populations in Maize. PLANTS 2021; 10:plants10081585. [PMID: 34451629 PMCID: PMC8399143 DOI: 10.3390/plants10081585] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 07/23/2021] [Accepted: 07/27/2021] [Indexed: 11/16/2022]
Abstract
In the field, maize flowering time and height traits are closely linked with yield, planting density, lodging resistance, and grain fill. To explore the genetic basis of flowering time and height traits in maize, we investigated six related traits, namely, days to anthesis (AD), days to silking (SD), the anthesis-silking interval (ASI), plant height (PH), ear height (EH), and the EH/PH ratio (ER) in two locations for two years based on two doubled haploid (DH) populations. Based on the two high-density genetic linkage maps, 12 and 22 quantitative trait loci (QTL) were identified, respectively, for flowering time and height-related traits. Of these, ten QTLs had overlapping confidence intervals between the two populations and were integrated into three consensus QTLs (qFT_YZ1a, qHT_YZ5a, and qHT_YZ7a). Of these, qFT_YZ1a, conferring flowering time, is located at 221.1-277.0 Mb on chromosome 1 and explained 10.0-12.5% of the AD and SD variation, and qHT_YZ5a, conferring height traits, is located at 147.4-217.3 Mb on chromosome 5 and explained 11.6-15.3% of the PH and EH variation. These consensus QTLs, in addition to the other repeatedly detected QTLs, provide useful information for further genetic studies and variety improvements in flowering time and height-related traits.
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24
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Liu N, Du Y, Warburton ML, Xiao Y, Yan J. Phenotypic Plasticity Contributes to Maize Adaptation and Heterosis. Mol Biol Evol 2021; 38:1262-1275. [PMID: 33212480 PMCID: PMC8480182 DOI: 10.1093/molbev/msaa283] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Plant phenotypic plasticity describes altered phenotypic performance of an individual when grown in different environments. Exploring genetic architecture underlying plant plasticity variation may help mitigate the detrimental effects of a rapidly changing climate on agriculture, but little research has been done in this area to date. In the present study, we established a population of 976 maize F1 hybrids by crossing 488 diverse inbred lines with two elite testers. Genome-wide association study identified hundreds of quantitative trait loci associated with phenotypic plasticity variation across diverse F1 hybrids, the majority of which contributed very little variance, in accordance with the polygenic nature of these traits. We identified several quantitative trait locus regions that may have been selected during the tropical-temperate adaptation process. We also observed heterosis in terms of phenotypic plasticity, in addition to the traditional genetic value differences measured between hybrid and inbred lines, and the pattern of which was affected by genetic background. Our results demonstrate a landscape of phenotypic plasticity in maize, which will aid in the understanding of its genetic architecture, its contribution to adaptation and heterosis, and how it may be exploited for future maize breeding in a rapidly changing environment.
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Affiliation(s)
- Nannan Liu
- Horticulture Biology and Metabolomics Center, Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China.,National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Yuanhao Du
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Marilyn L Warburton
- United States Department of Agriculture-Agricultural Research Service: Corn Host Plant Resistance Research Unit, Mississippi State, MS
| | - Yingjie Xiao
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Jianbing Yan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, Hubei, China
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25
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Qin X, Tian S, Zhang W, Dong X, Ma C, Wang Y, Yan J, Yue B. Q Dtbn1 , an F-box gene affecting maize tassel branch number by a dominant model. PLANT BIOTECHNOLOGY JOURNAL 2021; 19:1183-1194. [PMID: 33382512 PMCID: PMC8196637 DOI: 10.1111/pbi.13540] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 12/21/2020] [Accepted: 12/25/2020] [Indexed: 05/26/2023]
Abstract
Tassel branch number (TBN) is one of the important agronomic traits that directly contribute to grain yield in maize (Zea mays L.), and identification of genes precisely regulating TBN in the parental lines is important for maize hybrid breeding. In this study, a quantitative trait nucleotide (QTN), QDtbn1 , related to tassel branch number was identified using a testcrossing association mapping population through association mapping with the Indels/SNPs in the 5'-UTR (untranslated region) of Zm00001d053358, which encodes a Kelch repeat-containing F-box protein. QDtbn1 was further confirmed to be associated with TBN by a dominant model using an F2 population, and over-expressing of the candidate gene resulted in a decreasing of TBN, implying that QDtbn1 was governed by the candidate gene with a negative model. This makes QDtbn1 very useful in maize hybrid breeding. QDtbn1 could interact with a maize Skp1-like protein and a SnRK1 protein, and the SnRK1 could also interact with a SnRK2.8 protein. In addition, quantitative real-time PCR assay showed that five substrates of SnRK2 were down-regulated in the over-expressed plants. These imply that the SCF (Skp1/Cul1/F-box protein/Roc1) complex and ABA signal pathway might be involved in the modulation of TBN in maize.
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Affiliation(s)
- Xiner Qin
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
| | - Shike Tian
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
| | - Wenliang Zhang
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
| | - Xue Dong
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
| | - Chengxin Ma
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
| | - Yi Wang
- Industrial Crops Research InstitutionHeilongjiang Academy of Land Reclamation of SciencesHaerbinChina
| | - Jianbing Yan
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
| | - Bing Yue
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
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26
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Li T, Deng G, Tang Y, Su Y, Wang J, Cheng J, Yang Z, Qiu X, Pu X, Zhang H, Liang J, Yu M, Wei Y, Long H. Identification and Validation of a Novel Locus Controlling Spikelet Number in Bread Wheat ( Triticum aestivum L.). FRONTIERS IN PLANT SCIENCE 2021; 12:611106. [PMID: 33719283 PMCID: PMC7952655 DOI: 10.3389/fpls.2021.611106] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Accepted: 01/29/2021] [Indexed: 05/24/2023]
Abstract
Spikelet number is an important target trait for wheat yield improvement. Thus, the identification and verification of novel quantitative trait locus (QTL)/genes controlling spikelet number are essential for dissecting the underlying molecular mechanisms and hence for improving grain yield. In the present study, we constructed a high-density genetic map for the Kechengmai1/Chuanmai42 doubled haploid (DH) population using 13,068 single-nucleotide polymorphism (SNP) markers from the Wheat 55K SNP array. A comparison between the genetic and physical maps indicated high consistence of the marker orders. Based on this genetic map, a total of 27 QTLs associated with total spikelet number per spike (TSN) and fertile spikelet number per spike (FSN) were detected on chromosomes 1B, 1D, 2B, 2D, 3D, 4A, 4D, 5A, 5B, 5D, 6A, 6B, and 7D in five environments. Among them, five QTLs on chromosome 2D, 3D, 5A, and 7D were detected in multiple environments and combined QTL analysis, explaining the phenotypic variance ranging from 3.64% to 23.28%. Particularly, QTsn/Fsn.cib-3D for TSN and FSN [phenotypic variation explained (PVE) = 5.97-23.28%, limit of detection (LOD) = 3.73-18.51] is probably a novel locus and located in a 4.5-cM interval on chromosome arm 3DL flanking by the markers AX-110914105 and AX-109429351. This QTL was further validated in other two populations with different genetic backgrounds using the closely linked Kompetitive Allele-Specific PCR (KASP) marker KASP_AX-110914105. The results indicated that QTsn/Fsn.cib-3D significantly increased the TSN (5.56-7.96%) and FSN (5.13-9.35%), which were significantly correlated with grain number per spike (GNS). We also preliminary analyzed the candidate genes within this locus by sequence similarity, spatial expression patterns, and collinearity analysis. These results provide solid foundation for future fine mapping and cloning of QTsn/Fsn.cib-3D. The developed and validated KASP markers could be utilized in molecular breeding aiming to increase the grain yield in wheat.
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Affiliation(s)
- Tao Li
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu, China
| | - Guangbing Deng
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Yanyan Tang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Yan Su
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Jinhui Wang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Jie Cheng
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Zhao Yang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Xuebing Qiu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Xi Pu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Haili Zhang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Junjun Liang
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Maoqun Yu
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
| | - Yuming Wei
- Triticeae Research Institute, Sichuan Agricultural University, Chengdu, China
- State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu, China
| | - Hai Long
- Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, China
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Liu C, Chen X, Wang W, Hu X, Han W, He Q, Yang H, Xiang S, Gai J. Identifying Wild Versus Cultivated Gene-Alleles Conferring Seed Coat Color and Days to Flowering in Soybean. Int J Mol Sci 2021; 22:1559. [PMID: 33557103 PMCID: PMC7913812 DOI: 10.3390/ijms22041559] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 01/20/2021] [Accepted: 02/01/2021] [Indexed: 11/22/2022] Open
Abstract
Annual wild soybean (G. soja) is the ancestor of the cultivated soybean (G. max). To reveal the genetic changes from soja to max, an improved wild soybean chromosome segment substitution line (CSSL) population, SojaCSSLP5, composed of 177 CSSLs with 182 SSR markers (SSR-map), was developed based on SojaCSSLP1 generated from NN1138-2(max)×N24852(soja). The SojaCSSLP5 was genotyped further through whole-genome resequencing, resulting in a physical map with 1366 SNPLDBs (SNP linkage-disequilibrium blocks), which are composed of more markers/segments, shorter marker length and more recombination breakpoints than the SSR-map and caused 721 new wild substituted segments. Using the SNPLDB-map, two loci co-segregating with seed-coat color (SCC) and six loci for days to flowering (DTF) with 88.02% phenotypic contribution were identified. Integrated with parental RNA-seq and DNA-resequencing, two SCC and six DTF candidate genes, including three previously cloned (G, E2 and GmPRR3B) and five newly detected ones, were predicted and verified at nucleotide mutant level, and then demonstrated with the consistency between gene-alleles and their phenotypes in SojaCSSLP5. In total, six of the eight genes were identified with the parental allele-pairs coincided to those in 303 germplasm accessions, then were further demonstrated by the consistency between gene-alleles and germplasm phenotypes. Accordingly, the CSSL population integrated with parental DNA and RNA sequencing data was demonstrated to be an efficient platform in identifying candidate wild vs. cultivated gene-alleles.
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Affiliation(s)
| | | | - Wubin Wang
- Soybean Research Institute & MOA National Center for Soybean Improvement & MOA Key Laboratory of Biology and Genetic Improvement of Soybean (General) & State Key Laboratory for Crop Genetics and Germplasm Enhancement & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China; (C.L.); (X.C.); (X.H.); (W.H.); (Q.H.); (H.Y.); (S.X.)
| | | | | | | | | | | | - Junyi Gai
- Soybean Research Institute & MOA National Center for Soybean Improvement & MOA Key Laboratory of Biology and Genetic Improvement of Soybean (General) & State Key Laboratory for Crop Genetics and Germplasm Enhancement & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China; (C.L.); (X.C.); (X.H.); (W.H.); (Q.H.); (H.Y.); (S.X.)
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Liu M, He W, Zhang A, Zhang L, Sun D, Gao Y, Ni P, Ma X, Cui Z, Ruan Y. Genetic analysis of maize shank length by QTL mapping in three recombinant inbred line populations. PLANT SCIENCE : AN INTERNATIONAL JOURNAL OF EXPERIMENTAL PLANT BIOLOGY 2021; 303:110767. [PMID: 33487352 DOI: 10.1016/j.plantsci.2020.110767] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Revised: 11/12/2020] [Accepted: 11/17/2020] [Indexed: 06/12/2023]
Abstract
In maize, the shank is a unique tissue linking the stem to the ear. Shank length (SL) mainly affects the transport of photosynthetic products to the ear and the dehydration of kernels via regulated husk morphology. The limited studies on SL revealed it is a highly heritable quantitative trait controlled by significant additive and additive-dominance effects. However, the genetic basis of SL remains unclear. In this study, we analyzed three maize recombinant inbred line (RIL) populations to elucidate the molecular mechanism underlying the SL. The data indicated the SL varied among the three RIL populations and was highly heritable. Additionally, the SL was positively correlated with the husk length (HL), husk number (HN), ear length (EL), and ear weight (EW) in the BY815/K22 (BYK) and CI7/K22 (CIK) RIL populations, but was negatively correlated with the husk width (HW) in the BYK RIL population. Moreover, 10 quantitative trait loci (QTL) for SL were identified in the three RIL populations, five of which were large-effect QTL. The percentage of the total phenotypic variation explained by the QTL for SL was 13.67 %, 20.45 %, and 30.81 % in the BY815/DE3 (BYD), BYK, and CIK RIL populations, respectively. Further analyses uncovered some genetic overlap between SL and EL, SL and ear row number (ERN), SL and cob weight (CW), and SL and HN. Unlike the large-effect QTL qSL BYK-2-2, which spanned the centromere, the other four large-effect QTL were delimited to a single peak bin via bin map. Furthermore, 2, 5, 6, and 12 genes associated with SL were identified for qSL BYK-2-1, qSL CIK-2-1, qSL CIK-9-1, and qSL CIK-9-2, respectively. Five of the candidate genes for SL may contribute to the hormone metabolism and sphingolipid biosynthesis regulating cell elongation, division, differentiation, and expansion. These results may be relevant for future studies on the genetic basis of SL and for the molecular breeding of maize based on marker-assisted selection to develop new varieties with an ideal SL.
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Affiliation(s)
- Meiling Liu
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China
| | - Wenshu He
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China; Department of Plant Production and Forestry Science, University of Lleida-Agrotecnio Center, Av. Alcalde Rovira Roure, Lleida, 25198, Spain
| | - Ao Zhang
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China
| | - Lijun Zhang
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China
| | - Daqiu Sun
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China
| | - Yuan Gao
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China
| | - Pengzun Ni
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China
| | - Xinglin Ma
- Institute of Crop Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100081, China
| | - Zhenhai Cui
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China.
| | - Yanye Ruan
- College of Biological Science and Technology, Liaoning Province Research Center of Plant Genetic Engineering Technology, Shenyang Key Laboratory of Maize Genomic Selection Breeding, Shenyang Agricultural University, Shenyang, 110866, China.
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Kaur G, Pathak M, Singla D, Chhabra G, Chhuneja P, Kaur Sarao N. Quantitative Trait Loci Mapping for Earliness, Fruit, and Seed Related Traits Using High Density Genotyping-by-Sequencing-Based Genetic Map in Bitter Gourd ( Momordica charantia L.). FRONTIERS IN PLANT SCIENCE 2021; 12:799932. [PMID: 35211132 PMCID: PMC8863046 DOI: 10.3389/fpls.2021.799932] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 12/28/2021] [Indexed: 05/17/2023]
Abstract
Bitter gourd (Momordica charantia L.) is an important vegetable crop having numerous medicinal properties. Earliness and yield related traits are main aims of bitter gourd breeding program. High resolution quantitative trait loci (QTLs) mapping can help in understanding the molecular basis of phenotypic variation of these traits and thus facilitate marker-assisted breeding. The aim of present study was to identify genetic loci controlling earliness, fruit, and seed related traits. To achieve this, genotyping-by-sequencing (GBS) approach was used to genotype 101 individuals of F4 population derived from a cross between an elite cultivar Punjab-14 and PAUBG-6. This population was phenotyped under net-house conditions for three years 2018, 2019, and 2021. The linkage map consisting of 15 linkage groups comprising 3,144 single nucleotide polymorphism (SNP) markers was used to detect the QTLs for nine traits. A total of 50 QTLs for these traits were detected which were distributed on 11 chromosomes. The QTLs explained 5.09-29.82% of the phenotypic variance. The highest logarithm of the odds (LOD) score for a single QTL was 8.68 and the lowest was 2.50. For the earliness related traits, a total of 22 QTLs were detected. For the fruit related traits, a total of 16 QTLs and for seed related traits, a total of 12 QTLs were detected. Out of 50 QTLs, 20 QTLs were considered as frequent QTLs (FQ-QTLs). The information generated in this study is very useful in the future for fine-mapping and marker-assisted selection for these traits in bitter gourd improvement program.
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Affiliation(s)
- Gurpreet Kaur
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana, India
| | - Mamta Pathak
- Department of Vegetable Science, Punjab Agricultural University, Ludhiana, India
| | - Deepak Singla
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana, India
| | - Gautam Chhabra
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana, India
| | - Parveen Chhuneja
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana, India
| | - Navraj Kaur Sarao
- School of Agricultural Biotechnology, Punjab Agricultural University, Ludhiana, India
- *Correspondence: Navraj Kaur Sarao,
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30
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Ren T, Fan T, Chen S, Ou X, Chen Y, Jiang Q, Diao Y, Sun Z, Peng W, Ren Z, Tan F, Li Z. QTL Mapping and Validation for Kernel Area and Circumference in Common Wheat via High-Density SNP-Based Genotyping. FRONTIERS IN PLANT SCIENCE 2021; 12:713890. [PMID: 34484276 PMCID: PMC8415916 DOI: 10.3389/fpls.2021.713890] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 07/20/2021] [Indexed: 05/03/2023]
Abstract
As an important component, 1,000 kernel weight (TKW) plays a significant role in the formation of yield traits of wheat. Kernel size is significantly positively correlated to TKW. Although numerous loci for kernel size in wheat have been reported, our knowledge on loci for kernel area (KA) and kernel circumference (KC) remains limited. In the present study, a recombinant inbred lines (RIL) population containing 371 lines genotyped using the Wheat55K SNP array was used to map quantitative trait loci (QTLs) controlling the KA and KC in multiple environments. A total of 54 and 44 QTLs were mapped by using the biparental population or multienvironment trial module of the inclusive composite interval mapping method, respectively. Twenty-two QTLs were considered major QTLs. BLAST analysis showed that major and stable QTLs QKc.sau-6A.1 (23.12-31.64 cM on 6A) for KC and QKa.sau-6A.2 (66.00-66.57 cM on 6A) for KA were likely novel QTLs, which explained 22.25 and 20.34% of the phenotypic variation on average in the 3 year experiments, respectively. Two Kompetitive allele-specific PCR (KASP) markers, KASP-AX-109894590 and KASP-AX-109380327, were developed and tightly linked to QKc.sau-6A.1 and QKa.sau-6A.2, respectively, and the genetic effects of the different genotypes in the RIL population were successfully confirmed. Furthermore, in the interval where QKa.sau-6A.2 was located on Chinese Spring and T. Turgidum ssp. dicoccoides reference genomes, only 11 genes were found. In addition, digenic epistatic QTLs also showed a significant influence on KC and KA. Altogether, the results revealed the genetic basis of KA and KC and will be useful for the marker-assisted selection of lines with different kernel sizes, laying the foundation for the fine mapping and cloning of the gene(s) underlying the stable QTLs detected in this study.
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Affiliation(s)
- Tianheng Ren
- College of Agronomy, Sichuan Agricultural University, Chengdu, China
- Provincial Key Laboratory for Plant Genetics and Breeding, Chengdu, China
- *Correspondence: Tianheng Ren
| | - Tao Fan
- College of Agronomy, Sichuan Agricultural University, Chengdu, China
- Provincial Key Laboratory for Plant Genetics and Breeding, Chengdu, China
| | - Shulin Chen
- College of Agronomy, Sichuan Agricultural University, Chengdu, China
- Provincial Key Laboratory for Plant Genetics and Breeding, Chengdu, China
| | - Xia Ou
- College of Agronomy, Sichuan Agricultural University, Chengdu, China
- Provincial Key Laboratory for Plant Genetics and Breeding, Chengdu, China
| | - Yongyan Chen
- College of Agronomy, Sichuan Agricultural University, Chengdu, China
- Provincial Key Laboratory for Plant Genetics and Breeding, Chengdu, China
| | - Qing Jiang
- College of Agronomy, Sichuan Agricultural University, Chengdu, China
- Provincial Key Laboratory for Plant Genetics and Breeding, Chengdu, China
| | - Yixin Diao
- College of Agronomy, Sichuan Agricultural University, Chengdu, China
- Provincial Key Laboratory for Plant Genetics and Breeding, Chengdu, China
| | - Zixin Sun
- College of Agronomy, Sichuan Agricultural University, Chengdu, China
- Provincial Key Laboratory for Plant Genetics and Breeding, Chengdu, China
| | - Wanhua Peng
- College of Agronomy, Sichuan Agricultural University, Chengdu, China
- Provincial Key Laboratory for Plant Genetics and Breeding, Chengdu, China
| | - Zhenglong Ren
- College of Agronomy, Sichuan Agricultural University, Chengdu, China
- Provincial Key Laboratory for Plant Genetics and Breeding, Chengdu, China
| | - Feiquan Tan
- College of Agronomy, Sichuan Agricultural University, Chengdu, China
- Provincial Key Laboratory for Plant Genetics and Breeding, Chengdu, China
| | - Zhi Li
- College of Agronomy, Sichuan Agricultural University, Chengdu, China
- Provincial Key Laboratory for Plant Genetics and Breeding, Chengdu, China
- Zhi Li
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Shang Q, Zhang D, Li R, Wang K, Cheng Z, Zhou Z, Hao Z, Pan J, Li X, Shi L. Mapping quantitative trait loci associated with stem-related traits in maize (Zea mays L.). PLANT MOLECULAR BIOLOGY 2020; 104:583-595. [PMID: 32901412 DOI: 10.1007/s11103-020-01062-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Accepted: 08/27/2020] [Indexed: 05/15/2023]
Abstract
Mapping QTL for stem-related traits using RIL population with ultra-high density bin map can better dissect pleiotropic QTL controlling stem architecture that can provide valuable information for maize genetic improvement. The maize stem is one of the most important parts of the plant and is also a component of many agronomic traits in maize. This study aimed to advance our understanding of the genetic mechanisms underlying maize stem traits. A recombinant inbred line (RIL) population derived from a cross between Ye478 and Qi319 was used to identify quantitative trait loci (QTL) controlling stem height (SH), ear height (EH), stem node number (SN), ear node (EN), and stem diameter (SD), and two derived traits (ear height coefficient (EHc) and ear node coefficient (ENc)). Using an available ultra-high density bin map, 46 putative QTL for these traits were detected on chromosomes 1, 3, 4, 5, 6, 7, 8, and 10. Individual QTL explained 3.5-17.7% of the phenotypic variance in different environments. Two QTL for SH, three for EH, two for EHc, one for SN, one for EN, and one for SD were detected in more than one environment. QTL with pleiotropic effects or multiple linked QTL were also identified on chromosomes 1, 3, 4, 6, 8, and 10, which are potential target regions for fine-mapping and marker-assisted selection in maize breeding programs. Further, we discussed segregation of bin markers (mk1630 and mk4452) associated with EHc QTL in the RIL population. We had identified two putative WRKY DNA-binding domain proteins, AC209050.3_FG003 and GRMZM5G851490, and a putative auxin response factor, GRMZM2G437460, which might be involved in regulating plant growth and development, as candidate genes for the control of stem architecture.
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Affiliation(s)
- Qiqi Shang
- College of Plant Science and Technology, Beijing University of Agriculture, 7 Beinong Road, Changping District, Beijing, 102206, China
| | - Degui Zhang
- Institute of Crop Science, The National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Rong Li
- College of Plant Science and Technology, Beijing University of Agriculture, 7 Beinong Road, Changping District, Beijing, 102206, China
| | - Kaixin Wang
- College of Plant Science and Technology, Beijing University of Agriculture, 7 Beinong Road, Changping District, Beijing, 102206, China
| | - Zimeng Cheng
- College of Plant Science and Technology, Beijing University of Agriculture, 7 Beinong Road, Changping District, Beijing, 102206, China
| | - Zhiqiang Zhou
- Institute of Crop Science, The National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Zhuanfang Hao
- Institute of Crop Science, The National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China
| | - Jinbao Pan
- College of Plant Science and Technology, Beijing University of Agriculture, 7 Beinong Road, Changping District, Beijing, 102206, China
| | - Xinhai Li
- Institute of Crop Science, The National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences (CAAS), 12 Zhongguancun South Street, Beijing, 100081, China.
| | - Liyu Shi
- College of Plant Science and Technology, Beijing University of Agriculture, 7 Beinong Road, Changping District, Beijing, 102206, China.
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Sapkota S, Mergoum M, Kumar A, Fiedler JD, Johnson J, Bland D, Lopez B, Sutton S, Ghimire B, Buck J, Chen Z, Harrison S. A novel adult plant leaf rust resistance gene Lr2K38 mapped on wheat chromosome 1AL. THE PLANT GENOME 2020; 13:e20061. [PMID: 33169935 DOI: 10.1002/tpg2.20061] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Accepted: 09/05/2020] [Indexed: 06/11/2023]
Abstract
Soft red winter wheat (SRWW) cultivar AGS 2038 has a high level of seedling and adult plant leaf rust (LR) resistance. To map and characterize LR resistance in AGS 2038, a recombinant inbred line (RIL) population consisting of 225 lines was developed from a cross between AGS 2038 and moderately resistant line UGA 111729. The parents and RIL population were phenotyped for LR response in three field environments at Plains and Griffin, GA, in the 2017-2018 and 2018-2019 growing seasons, one greenhouse environment at the adult-plant stage, and at seedling stage. The RIL population was genotyped with the Illumina iSelect 90K SNP marker array, and a total of 7667 polymorphic markers representing 1513 unique loci were used to construct a linkage map. Quantitative trait loci (QTL) analysis detected six QTL, QLr.ags-1AL, QLr.ags-2AS, QLr.ags-2BS1, QLr.ags-2BS2, QLr.ags-2BS3, and QLr.ags-2DS, for seedling and adult plant LR resistance. Of these, the major adult plant leaf rust resistance QTL, QLr.ags-1AL, was detected on all field and greenhouse adult plant tests and explained up to 34.45% of the phenotypic variation. QLr.ags-1AL, tightly flanked by IWB20487 and IWA4022 markers, was contributed by AGS 2038. Molecular marker analysis using a diagnostic marker linked to Lr59 showed that QLr.ags-1AL was different from Lr59, the only known LR resistance gene on 1AL. Therefore, the QTL was temporarily designated as Lr2K38. Lr2K38-linked marker IWB20487 was highly polymorphic among 30 SRWW lines and should be useful for selecting the Lr2K38 in wheat breeding programs.
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Affiliation(s)
- Suraj Sapkota
- Institute of Plant Breeding, Genetics, and Genomics, University of Georgia, Griffin Campus, Griffin, GA, 30223, USA
| | - Mohamed Mergoum
- Institute of Plant Breeding, Genetics, and Genomics, University of Georgia, Griffin Campus, Griffin, GA, 30223, USA
- Department of Crop and Soil Sciences, University of Georgia, Griffin Campus, Griffin, GA, 30223, USA
| | - Ajay Kumar
- Department of Plant Sciences, North Dakota State University, Fargo, ND, 58102, USA
| | - Jason D Fiedler
- USDA-ARS, Cereal Crops Research Unit, Edward T. Schafer Agricultural Research Center, Fargo, ND, 58102, USA
| | - Jerry Johnson
- Department of Crop and Soil Sciences, University of Georgia, Griffin Campus, Griffin, GA, 30223, USA
| | - Dan Bland
- Department of Crop and Soil Sciences, University of Georgia, Griffin Campus, Griffin, GA, 30223, USA
| | - Benjamin Lopez
- Department of Crop and Soil Sciences, University of Georgia, Griffin Campus, Griffin, GA, 30223, USA
| | - Steve Sutton
- Department of Crop and Soil Sciences, University of Georgia, Griffin Campus, Griffin, GA, 30223, USA
| | - Bikash Ghimire
- Department of Plant Pathology, University of Georgia, Griffin Campus, Griffin, GA, 30223, USA
| | - James Buck
- Department of Plant Pathology, University of Georgia, Griffin Campus, Griffin, GA, 30223, USA
| | - Zhenbang Chen
- Department of Crop and Soil Sciences, University of Georgia, Griffin Campus, Griffin, GA, 30223, USA
| | - Stephen Harrison
- School of Plant, Environmental and Soil Sciences, Louisiana State University, Baton Rouge, LA, 70803, USA
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Yang W, Zheng L, He Y, Zhu L, Chen X, Tao Y. Fine mapping and candidate gene prediction of a major quantitative trait locus for tassel branch number in maize. Gene 2020; 757:144928. [PMID: 32622989 DOI: 10.1016/j.gene.2020.144928] [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: 01/20/2020] [Revised: 05/16/2020] [Accepted: 06/27/2020] [Indexed: 11/16/2022]
Abstract
Tassel branch number (TBN) is the principal component of tassel inflorescence architecture in the maize plant. TBN is believed to be controlled by a set of quantitative trait loci (QTLs). However, it is necessary to identify and genetically evaluate these QTLs before the TBN can be improved upon using a molecular breeding approach. Therefore, in this study, we developed the chromosome segment introgression line (CSIL) TBN1 with the Zong31 (Z31) background and a higher TBN, and then we utilized the CSIL-TBN1-derived populations and identified a major QTL, qTBN6a, by linkage analysis. Fine mapping of the qTBN6a QTL was validated using a set of sub-CSILs and located in a 240-kb genomic region (Bin6.07) in B73RefGen_v4. One allele included in the introgression fragment had a positive effect, noticeably increasing the TBN and demonstrating the potential to improve the TBN of Z31. Afterward, in the qTBN6a interval, gene expression, sequence alignment, functional analysis, and the analysis of motifs in the 5' UTR suggested that candidate genes of qTBN6a are important functional genes at the early stage of immature infected tassel development. Among these candidate genes, a long W22::Mu-insertion/deletion in exon one and an 11-bp insertion/deletion in the promoter region may affect the variation of the qTBN6a QTL observed between Z31 and TBN1. In addition, the candidate genes of qTBN6a were found to encode a pentatricopeptide repeat (PPR)-containing protein and a histone deacetylase (HDA), which are known to be closely associated with RNA editing and stability and chromatin state activity for the transcription of gene expression, respectively. Finally, a model of qTBN6a based on the synergistic regulation of PPR and HDA for the maintenance of inflorescence meristem (IM) identity and its differentiation to the branch meristem (BM) in TBN1 was suggested. Collectively, our results provide an available locus for the molecular improvement of TBN and the isolation of functional genes underlying this QTL.
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Affiliation(s)
- Weifeng Yang
- Hebei Sub-center of Chinese National Maize Improvement Center, North China Key Laboratory for Crop Germplasm Resource of Education Ministry, College of Agronomy, State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding 071000, PR China
| | - Lizhen Zheng
- Hebei Sub-center of Chinese National Maize Improvement Center, North China Key Laboratory for Crop Germplasm Resource of Education Ministry, College of Agronomy, State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding 071000, PR China
| | - Yuan He
- Hebei Sub-center of Chinese National Maize Improvement Center, North China Key Laboratory for Crop Germplasm Resource of Education Ministry, College of Agronomy, State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding 071000, PR China
| | - Liying Zhu
- Hebei Sub-center of Chinese National Maize Improvement Center, North China Key Laboratory for Crop Germplasm Resource of Education Ministry, College of Agronomy, State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding 071000, PR China
| | - Xuqing Chen
- Beijing Agro-Biotechnology Research Center, Beijing Academy of Agricultural and Forestry Science, Beijing 100097, PR China.
| | - Yongsheng Tao
- Hebei Sub-center of Chinese National Maize Improvement Center, North China Key Laboratory for Crop Germplasm Resource of Education Ministry, College of Agronomy, State Key Laboratory of North China Crop Improvement and Regulation, Hebei Agricultural University, Baoding 071000, PR China.
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Lu X, Zhou Z, Yuan Z, Zhang C, Hao Z, Wang Z, Li M, Zhang D, Yong H, Han J, Li X, Weng J. Genetic Dissection of the General Combining Ability of Yield-Related Traits in Maize. FRONTIERS IN PLANT SCIENCE 2020; 11:788. [PMID: 32793248 PMCID: PMC7387702 DOI: 10.3389/fpls.2020.00788] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Accepted: 05/18/2020] [Indexed: 05/27/2023]
Abstract
Maize yield components including row number, kernel number per row, kernel thickness, kernel width, kernel length, 100-kernel weight, and volume weight affect grain yield directly. Previous studies mainly focused on dissecting the genetic basis of per se performances for yield-related traits, but the genetic basis of general combining ability (GCA) for these traits is still unclear. In the present study, 328 RILs were crossed as males to two testers according to the NCII mating design, resulting in a hybrid panel composed of 656 hybrids. Both the hybrids and parental lines were evaluated in four environments in 2015 and 2016. Correlation analysis showed the performances of GCA effects were significantly correlated to the per se performances of RILs for all yield-related traits (0.17 ≤ r ≤ 0.64, P > 0.01). Only 17 of 95 QTL could be detected for both per se performances of RILs and GCA effects for eight yield-related traits. The QTL qKN7-1 and qHKW1-3, which could explain more than 10% of the variation in the GCA effects of KN and HKW, were also detected for per se performances for the traits. The pleiotropic loci qRN3-1 and qRN6, which together explained 14.92% of the observed variation in GCA effects for RN, were associated with the GCA effects of KW and HKW, but not with per se performances for these traits. In contrast, Incw1, which was related to seed weight in maize, was mapped to the region surrounding MK2567 at the qHKW5-2 locus, but no GCA effect was detected. The QTL identified in present study for per se performances and corresponding GCA effects for yield-related traits might be useful for maize hybrid breeding.
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Affiliation(s)
- Xin Lu
- College of Agriculture, Northeast Agricultural University, Harbin, China
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhiqiang Zhou
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhaohui Yuan
- College of Agriculture, Northeast Agricultural University, Harbin, China
| | - Chaoshu Zhang
- College of Agriculture, Northeast Agricultural University, Harbin, China
| | - Zhuanfang Hao
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhenhua Wang
- College of Agriculture, Northeast Agricultural University, Harbin, 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
| | - Xinhai Li
- College of Agriculture, Northeast Agricultural University, Harbin, China
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jianfeng Weng
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
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Lu L, Xu Z, Sun S, Du Q, Zhu Z, Weng J, Duan C. Discovery and Fine Mapping of qSCR6.01, a Novel Major QTL Conferring Southern Rust Resistance in Maize. PLANT DISEASE 2020; 104:1918-1924. [PMID: 32396052 DOI: 10.1094/pdis-01-20-0053-re] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Southern corn rust (SCR), an airborne disease caused by Puccinia polysora, can severely reduce the yield of maize (Zea mays L.). Using recombinant inbred lines (RILs) derived from a cross between susceptible inbred line Ye478 and resistant Qi319 in combination with their high-density genetic map, we located five quantitative trait loci (QTLs) against SCR, designated as qSCR3.04, qSCR5.07, qSCR6.01, qSCR9.03, and qSCR10.01, on chromosomes 3, 5, 6, 9, and 10, respectively. Each QTL could explain 2.84 to 24.15% of the total phenotypic variation. qSCR6.01, detected on chromosome 6, with the highest effect value, accounting for 17.99, 23.47, and 24.15% of total phenotypic variation in two environments and best linear unbiased prediction, was a stably major resistance QTL. The common confidence interval for qSCR6.01 was 2.95 Mb based on the B73 RefGen_v3 sequence. The chromosome segment substitution lines (CSSLs) constructed with Qi319 as the donor parent and Ye478 as the recurrent parent were used to further verify qSCR6.01 resistance to SCR. The line CL183 harboring introgressed qSCR6.01 showed obvious resistance to SCR that was distinctly different from that of Ye478 (P = 0.0038). Further mapping of qSCR6.01 revealed that the resistance QTL was linked to insertion-deletion markers Y6q77 and Y6q79, with physical locations of 77.6 and 79.6 Mb, respectively, on chromosome 6. Different from previous major genes or QTLs against SCR on chromosome 10, qSCR6.01 was a newly identified major QTL resistance to SCR on chromosome 6 for the first time. Using RIL and CSSL populations in combination, the SCR-resistance QTL research can be dissected effectively, which provided important gene resource and genetic information for breeding resistant varieties.
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Affiliation(s)
- Lu Lu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, National Key Facility for Crop Gene Resources and Genetic Improvement, Beijing 100081, China
| | - Zhennan Xu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, National Key Facility for Crop Gene Resources and Genetic Improvement, Beijing 100081, China
| | - Suli Sun
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, National Key Facility for Crop Gene Resources and Genetic Improvement, Beijing 100081, China
| | - Qing Du
- Institute of Maize Research, Guangxi Academy of Agricultural Sciences, Nanning 530007, China
| | - Zhendong Zhu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, National Key Facility for Crop Gene Resources and Genetic Improvement, Beijing 100081, China
| | - Jianfeng Weng
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, National Key Facility for Crop Gene Resources and Genetic Improvement, Beijing 100081, China
| | - Canxing Duan
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, National Key Facility for Crop Gene Resources and Genetic Improvement, Beijing 100081, China
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Jaganathan D, Bohra A, Thudi M, Varshney RK. Fine mapping and gene cloning in the post-NGS era: advances and prospects. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2020; 133:1791-1810. [PMID: 32040676 PMCID: PMC7214393 DOI: 10.1007/s00122-020-03560-w] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Accepted: 01/29/2020] [Indexed: 05/18/2023]
Abstract
Improvement in traits of agronomic importance is the top breeding priority of crop improvement programs. Majority of these agronomic traits show complex quantitative inheritance. Identification of quantitative trait loci (QTLs) followed by fine mapping QTLs and cloning of candidate genes/QTLs is central to trait analysis. Advances in genomic technologies revolutionized our understanding of genetics of complex traits, and genomic regions associated with traits were employed in marker-assisted breeding or cloning of QTLs/genes. Next-generation sequencing (NGS) technologies have enabled genome-wide methodologies for the development of ultra-high-density genetic linkage maps in different crops, thus allowing placement of candidate loci within few kbs in genomes. In this review, we compare the marker systems used for fine mapping and QTL cloning in the pre- and post-NGS era. We then discuss how different NGS platforms in combination with advanced experimental designs have improved trait analysis and fine mapping. We opine that efficient genotyping/sequencing assays may circumvent the need for cumbersome procedures that were earlier used for fine mapping. A deeper understanding of the trait architectures of agricultural significance will be crucial to accelerate crop improvement.
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Affiliation(s)
- Deepa Jaganathan
- Center of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India
- Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University (TNAU), Coimbatore, India
| | - Abhishek Bohra
- Crop Improvement Division, ICAR-Indian Institute of Pulses Research (IIPR), Kanpur, India
| | - Mahendar Thudi
- Center of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India.
| | - Rajeev K Varshney
- Center of Excellence in Genomics and Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, India.
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Jiang S, Yang C, Xu Q, Wang L, Yang X, Song X, Wang J, Zhang X, Li B, Li H, Li Z, Li W. Genetic Dissection of Germinability under Low Temperature by Building a Resequencing Linkage Map in japonica Rice. Int J Mol Sci 2020; 21:ijms21041284. [PMID: 32074988 PMCID: PMC7072905 DOI: 10.3390/ijms21041284] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2020] [Revised: 02/06/2020] [Accepted: 02/13/2020] [Indexed: 12/17/2022] Open
Abstract
Among all cereals, rice is highly sensitive to cold stress, especially at the germination stage, which adversely impacts its germination ability, seed vigor, crop stand establishment, and, ultimately, grain yield. The dissection of novel quantitative trait loci (QTLs) or genes conferring a low-temperature germination (LTG) ability can significantly accelerate cold-tolerant rice breeding to ensure the wide application of rice cultivation through the direct seeding method. In this study, we identified 11 QTLs for LTG using 144 recombinant inbred lines (RILs) derived from a cross between a cold-tolerant variety, Lijiangxintuanheigu (LTH), and a cold-sensitive variety, Shennong265 (SN265). By resequencing two parents and RIL lines, a high-density bin map, including 2,828 bin markers, was constructed using 123,859 single-nucleotide polymorphisms (SNPs) between two parents. The total genetic distance corresponding to all 12 chromosome linkage maps was 2,840.12 cm. Adjacent markers were marked by an average genetic distance of 1.01 cm, corresponding to a 128.80 kb physical distance. Eight and three QTL alleles had positive effects inherited from LTH and SN265, respectively. Moreover, a pleiotropic QTL was identified for a higher number of erected panicles and a higher grain number on Chr-9 near the previously cloned DEP1 gene. Among the LTG QTLs, qLTG3 and qLTG7b were also located at relatively small genetic intervals that define two known LTG genes, qLTG3-1 and OsSAP16. Sequencing comparisons between the two parents demonstrated that LTH possesses qLTG3-1 and OsSAP16 genes, and SN-265 owns the DEP1 gene. These comparison results strengthen the accuracy and mapping resolution power of the bin map and population. Later, fine mapping was done for qLTG6 at 45.80 kb through four key homozygous recombinant lines derived from a population with 1569 segregating plants. Finally, LOC_Os06g01320 was identified as the most possible candidate gene for qLTG6, which contains a missense mutation and a 32-bp deletion/insertion at the promoter between the two parents. LTH was observed to have lower expression levels in comparison with SN265 and was commonly detected at low temperatures. In conclusion, these results strengthen our understanding of the impacts of cold temperature stress on seed vigor and germination abilities and help improve the mechanisms of rice breeding programs to breed cold-tolerant varieties.
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Affiliation(s)
- Shukun Jiang
- Crop Cultivation and Tillage Institute of Heilongjiang Academy of Agricultural Sciences, Heilongjiang Provincial Key Laboratory of Crop Physiology and Ecology in Cold Region, Heilongjiang Provincial Engineering Technology Research Center of Crop Cold Damage, Harbin 150086, China; (L.W.); (X.Y.); (X.Z.); (B.L.)
- Correspondence: (S.J.); (Z.L.); (W.L.)
| | - Chao Yang
- Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China; (C.Y.); (X.S.)
| | - Quan Xu
- Rice Research Institute of Shenyang Agricultural University, Shenyang 110866, China; (Q.X.); (J.W.)
| | - Lizhi Wang
- Crop Cultivation and Tillage Institute of Heilongjiang Academy of Agricultural Sciences, Heilongjiang Provincial Key Laboratory of Crop Physiology and Ecology in Cold Region, Heilongjiang Provincial Engineering Technology Research Center of Crop Cold Damage, Harbin 150086, China; (L.W.); (X.Y.); (X.Z.); (B.L.)
| | - Xianli Yang
- Crop Cultivation and Tillage Institute of Heilongjiang Academy of Agricultural Sciences, Heilongjiang Provincial Key Laboratory of Crop Physiology and Ecology in Cold Region, Heilongjiang Provincial Engineering Technology Research Center of Crop Cold Damage, Harbin 150086, China; (L.W.); (X.Y.); (X.Z.); (B.L.)
| | - Xianwei Song
- Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China; (C.Y.); (X.S.)
| | - Jiayu Wang
- Rice Research Institute of Shenyang Agricultural University, Shenyang 110866, China; (Q.X.); (J.W.)
| | - Xijuan Zhang
- Crop Cultivation and Tillage Institute of Heilongjiang Academy of Agricultural Sciences, Heilongjiang Provincial Key Laboratory of Crop Physiology and Ecology in Cold Region, Heilongjiang Provincial Engineering Technology Research Center of Crop Cold Damage, Harbin 150086, China; (L.W.); (X.Y.); (X.Z.); (B.L.)
| | - Bo Li
- Crop Cultivation and Tillage Institute of Heilongjiang Academy of Agricultural Sciences, Heilongjiang Provincial Key Laboratory of Crop Physiology and Ecology in Cold Region, Heilongjiang Provincial Engineering Technology Research Center of Crop Cold Damage, Harbin 150086, China; (L.W.); (X.Y.); (X.Z.); (B.L.)
| | - Hongyu Li
- College of Agronomy, Heilongjiang Bayi Agricultural University, Daqing 163000, China;
| | - Zhugang Li
- Crop Cultivation and Tillage Institute of Heilongjiang Academy of Agricultural Sciences, Heilongjiang Provincial Key Laboratory of Crop Physiology and Ecology in Cold Region, Heilongjiang Provincial Engineering Technology Research Center of Crop Cold Damage, Harbin 150086, China; (L.W.); (X.Y.); (X.Z.); (B.L.)
- Correspondence: (S.J.); (Z.L.); (W.L.)
| | - Wenhua Li
- Crop Cultivation and Tillage Institute of Heilongjiang Academy of Agricultural Sciences, Heilongjiang Provincial Key Laboratory of Crop Physiology and Ecology in Cold Region, Heilongjiang Provincial Engineering Technology Research Center of Crop Cold Damage, Harbin 150086, China; (L.W.); (X.Y.); (X.Z.); (B.L.)
- Correspondence: (S.J.); (Z.L.); (W.L.)
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Liu Y, Zhou X, Yan M, Wang P, Wang H, Xin Q, Yang L, Hong D, Yang G. Fine mapping and candidate gene analysis of a seed glucosinolate content QTL, qGSL-C2, in rapeseed (Brassica napus L.). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2020; 133:479-490. [PMID: 31832742 DOI: 10.1007/s00122-019-03479-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2019] [Accepted: 11/09/2019] [Indexed: 06/10/2023]
Abstract
QTL mapping and candidate gene analysis indicate that allelic variations in BnaC2.MYB28 resulted from homeologous exchange and determine difference in seed glucosinolate content. A low seed glucosinolate content has long been an important breeding objective in rapeseed improvement. However, the molecular mechanisms underlying seed GSL content variations remain to be elucidated in allotetraploid Brassica napus. Here, we developed a double haploid population from a cross between two B. napus accessions that possess relatively low, but significantly different seed GSL contents and identified a major QTL, qGSL-C2, on chromosome C02 that explains 30.88-72.87% of the phenotypic variation observed in five environments. Using near-isogenic lines, we further delimited qGSL-C2 to a physical region of 49 kb on the B. rapa chromosome A02 which is highly homologous to the target C02 interval. Among five candidate genes, BnaC2.MYB28, a homologue of the Arabidopsis MYB28 encoding a putative R2R3-MYB-type transcription factor functioning in aliphatic methionine-derived GSL synthesis, was most likely to be the target gene underlying the QTL. Sequence analysis revealed multiple insertion/deletion and SNP variations in the genomic region between the alleles of the NILs. Furthermore, the allelic variations in BnaC2.MYB28 in the natural B. napus population were significantly associated with seed GSL content. Remarkably, the phylogenetic analysis and sequence comparison suggested that while the BnaC2.MYB28 allele from the parental line G120 was inherited from B. oleracea BolC2.MYB28, its counterpart from the other parent, 9172, most likely evolved from B. rapa BraA2.MYB28 via possible homeologous exchange. Our study promotes greater understanding of the molecular regulation of seed GSL content and provides useful molecular markers for seed GSL improvement in B. napus.
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Affiliation(s)
- Ying Liu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Xianming Zhou
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Min Yan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Pengfei Wang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Hao Wang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Qiang Xin
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Liyong Yang
- Shanghai Academy of Agricultural Sciences, Shanghai, 201403, China
| | - Dengfeng Hong
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.
| | - Guangsheng Yang
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.
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Zhao S, Zhang C, Mu J, Zhang H, Yao W, Ding X, Ding J, Chang Y. All-in-one sequencing: an improved library preparation method for cost-effective and high-throughput next-generation sequencing. PLANT METHODS 2020; 16:74. [PMID: 32489396 PMCID: PMC7247233 DOI: 10.1186/s13007-020-00615-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Accepted: 05/14/2020] [Indexed: 05/10/2023]
Abstract
BACKGROUND Next generation sequencing (NGS) has been widely used in biological research, due to its rapid decrease in cost and increasing ability to generate data. However, while the sequence generation step has seen many improvements over time, the library preparation step has not, resulting in low-efficiency library preparation methods, especially for the most time-consuming and labor-intensive steps: size-selection and quantification. Consequently, there can be bottlenecks in projects with large sample cohorts. RESULTS We have described the all-in-one sequencing (AIO-seq) method, where instead of performing size-selection and quantification for samples individually, one sample one tube, up to 116 samples are pooled and analyzed in a single tube, 'All-In-One'. The AIO-seq method pools libraries based on the samples' expected data yields and the calculated concentrations of the size selected regions (target region), which can easily be obtained with the Agilent 2100 Bioanalyzer and Qubit Fluorometer. AIO-seq was applied to whole genome sequencing and RNA-seq libraries successfully, and it is envisaged that it could be applied to any type of NGS library, such as chromatin immunoprecipitation coupled with massively parallel sequencing, assays for transposase-accessible chromatin with high-throughput sequencing, and high-throughput chromosome conformation capture. We also demonstrated that for genetic population samples with low coverage sequences, like recombinant inbred lines (RIL), AIO-seq could be further simplified, by mixing the libraries immediately after PCR, without calculating the target region concentrations. CONCLUSIONS The AIO-seq method is thus labor saving and cost effective, and suitable for projects with large sample cohorts, like those used in plant breeding or population genetics research.
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Affiliation(s)
- Sheng Zhao
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120 China
| | - Cuicui Zhang
- College of Life Science and Technology, Guangxi University, Nanning, 530004 China
| | - Jianqiang Mu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120 China
| | - Hui Zhang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120 China
| | - Wen Yao
- National Key Laboratory of Wheat and Maize Crop Science, College of Life Sciences, Henan Agricultural University, Zhengzhou, 450002 China
| | - Xinhua Ding
- State Key Laboratory of Crop Biology, College of Plant Protection, Shandong Agricultural University, Taian, 271018 China
| | - Junqiang Ding
- National Key Laboratory of Wheat and Maize Crop Science, College of Agronomy, Henan Agricultural University, Zhengzhou, 450002 China
| | - Yuxiao Chang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120 China
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A recombination bin-map identified a major QTL for resistance to Tomato Spotted Wilt Virus in peanut (Arachis hypogaea). Sci Rep 2019; 9:18246. [PMID: 31796847 PMCID: PMC6890646 DOI: 10.1038/s41598-019-54747-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Accepted: 10/17/2019] [Indexed: 11/16/2022] Open
Abstract
Tomato spotted wilt virus (TSWV) is a devastating disease to peanut growers in the South-eastern region of the United States. Newly released peanut cultivars in recent years are crucial as they have some levels of resistance to TSWV. One mapping population of recombinant inbred line (RIL) used in this study was derived from peanut lines of SunOleic 97R and NC94022. A whole genome re-sequencing approach was used to sequence these two parents and 140 RILs. A recombination bin-based genetic map was constructed, with 5,816 bins and 20 linkage groups covering a total length of 2004 cM. Using this map, we identified three QTLs which were colocalized on chromosome A01. One QTL had the largest effect of 36.51% to the phenotypic variation and encompassed 89.5 Kb genomic region. This genome region had a cluster of genes, which code for chitinases, strictosidine synthase-like, and NBS-LRR proteins. SNPs linked to this QTL were used to develop Kompetitive allele specific PCR (KASP) markers, and the validated KASP markers showed expected segregation of alleles coming from resistant and susceptible parents within the population. Therefore, this bin-map and QTL associated with TSWV resistance made it possible for functional gene mapping, map-based cloning, and marker-assisted breeding. This study identified the highest number of SNP makers and demonstrated recombination bin-based map for QTL identification in peanut. The chitinase gene clusters and NBS-LRR disease resistance genes in this region suggest the possible involvement in peanut resistance to TSWV.
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Moura EG, Pamplona AKA, Balestre M. Functional models in genome-wide selection. PLoS One 2019; 14:e0222699. [PMID: 31644532 PMCID: PMC6808424 DOI: 10.1371/journal.pone.0222699] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Accepted: 09/05/2019] [Indexed: 11/29/2022] Open
Abstract
The development of sequencing technologies has enabled the discovery of markers that are abundantly distributed over the whole genome. Knowledge about the marker locations in reference genomes provides further insights in the search for causal regions and the prediction of genomic values. The present study proposes a Bayesian functional approach for incorporating the marker locations into genomic analysis using stochastic methods to search causal regions and predict genotypic values. For this, three scenarios were analyzed: F2 population with 300 individuals and three different heritability levels (0.2, 0.5, and 0.8), along with 12,150 SNP markers that were distributed through ten linkage groups; F∞ populations with 320 individuals and three different heritability levels (0.2, 0.5, and 0.8), along with 10,020 SNP markers that were distributed through ten linkage groups; and data related to Eucalyptus spp. to measure the model performance in a real LD setting, with 611 individuals whose phenotypes were simulated from QTLs distributed through a panel of 36,812 SNPs with known positions. The performance of the proposed method was compared with those of other genome selection models, namely, RR-BLUP, Bayes B and Bayesian Lasso. The Bayesian functional model presented higher or similar predictive ability when compared with those classical regressions methods in simulated and real scenarios on different LD structures. In general, the Bayesian functional model also achieved higher computational efficiency, using 12 SNPs per MCMC round. The model was efficient in the identification of causal regions and showed high flexibility of analysis, as it is easily adaptable to any genomic selection model.
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Affiliation(s)
- Ernandes Guedes Moura
- Federal Institute of Maranhão - Campus São João dos Patos, São João dos Patos, Maranhão, Brasil
| | | | - Marcio Balestre
- Department of Statistics - Federal University of Lavras, Lavras, Minas Gerais, Brazil
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Genotyping-by-sequencing based QTL mapping for rice grain yield under reproductive stage drought stress tolerance. Sci Rep 2019; 9:14326. [PMID: 31586108 PMCID: PMC6778106 DOI: 10.1038/s41598-019-50880-z] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Accepted: 09/12/2019] [Indexed: 12/27/2022] Open
Abstract
QTLs for rice grain yield under reproductive stage drought stress (qDTY) identified earlier with low density markers have shown linkage drag and need to be fine mapped before their utilization in breeding programs. In this study, genotyping-by-sequencing (GBS) based high-density linkage map of rice was developed using two BC1F3 mapping populations namely Swarna*2/Dular (3929 SNPs covering 1454.68 cM) and IR11N121*2/Aus196 (1191 SNPs covering 1399.68 cM) with average marker density of 0.37 cM to 1.18 cM respectively. In total, six qDTY QTLs including three consistent effect QTLs were identified in Swarna*2/Dular while eight qDTY QTLs including two consistent effect QTLs were identified in IR11N121*2/Aus 196 mapping population. Comparative analysis revealed four stable and novel QTLs (qDTY2.4, qDTY3.3, qDTY6.3, and qDTY11.2) which explained 8.62 to 14.92% PVE. However, one of the identified stable grain yield QTL qDTY1.1 in both the populations was located nearly at the same physical position of an earlier mapped major qDTY QTL. Further, the effect of the identified qDTY1.1 was validated in a subset of lines derived from five mapping populations confirming robustness of qDTY1.1 across various genetic backgrounds/seasons. The study successfully identified stable grain yield QTLs free from undesirable linkages of tall plant height/early maturity utilizing high density linkage maps.
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Yu K, Liu D, Chen Y, Wang D, Yang W, Yang W, Yin L, Zhang C, Zhao S, Sun J, Liu C, Zhang A. Unraveling the genetic architecture of grain size in einkorn wheat through linkage and homology mapping and transcriptomic profiling. JOURNAL OF EXPERIMENTAL BOTANY 2019; 70:4671-4688. [PMID: 31226200 PMCID: PMC6760303 DOI: 10.1093/jxb/erz247] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2018] [Accepted: 05/15/2019] [Indexed: 05/12/2023]
Abstract
Understanding the genetic architecture of grain size is a prerequisite to manipulating grain development and improving the potential crop yield. In this study, we conducted a whole genome-wide quantitative trait locus (QTL) mapping of grain-size-related traits by constructing a high-density genetic map using 109 recombinant inbred lines of einkorn wheat. We explored the candidate genes underlying QTLs through homologous analysis and RNA sequencing. The high-density genetic map spanned 1873 cM and contained 9937 single nucleotide polymorphism markers assigned to 1551 bins on seven chromosomes. Strong collinearity and high genome coverage of this map were revealed by comparison with physical maps of wheat and barley. Six grain size-related traits were surveyed in five environments. In total, 42 QTLs were identified; these were assigned to 17 genomic regions on six chromosomes and accounted for 52.3-66.7% of the phenotypic variation. Thirty homologous genes involved in grain development were located in 12 regions. RNA sequencing identified 4959 genes differentially expressed between the two parental lines. Twenty differentially expressed genes involved in grain size development and starch biosynthesis were mapped to nine regions that contained 26 QTLs, indicating that the starch biosynthesis pathway plays a vital role in grain development in einkorn wheat. This study provides new insights into the genetic architecture of grain size in einkorn wheat; identification of the underlying genes enables understanding of grain development and wheat genetic improvement. Furthermore, the map facilitates quantitative trait mapping, map-based cloning, genome assembly, and comparative genomics in wheat taxa.
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Affiliation(s)
- Kang Yu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology/Innovation Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, China
- Beijing Genomics Institute-Shenzhen, Shenzhen, China
- State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, China
| | - Dongcheng Liu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology/Innovation Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
| | - Yong Chen
- Science and Technology Department, State Tobacco Monopoly Administration, Beijing, China
| | - Dongzhi Wang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology/Innovation Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Wenlong Yang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology/Innovation Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
| | - Wei Yang
- Beijing Genomics Institute-Shenzhen, Shenzhen, China
| | - Lixin Yin
- Beijing Genomics Institute-Shenzhen, Shenzhen, China
| | - Chi Zhang
- Beijing Genomics Institute-Shenzhen, Shenzhen, China
- State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, China
| | - Shancen Zhao
- Beijing Genomics Institute-Shenzhen, Shenzhen, China
- State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, China
| | - Jiazhu Sun
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology/Innovation Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
| | - Chunming Liu
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, China
- Correspondence: and
| | - Aimin Zhang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology/Innovation Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- Correspondence: and
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Yu K, Liu D, Chen Y, Wang D, Yang W, Yang W, Yin L, Zhang C, Zhao S, Sun J, Liu C, Zhang A. Unraveling the genetic architecture of grain size in einkorn wheat through linkage and homology mapping and transcriptomic profiling. JOURNAL OF EXPERIMENTAL BOTANY 2019. [PMID: 31226200 DOI: 10.1101/377820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Understanding the genetic architecture of grain size is a prerequisite to manipulating grain development and improving the potential crop yield. In this study, we conducted a whole genome-wide quantitative trait locus (QTL) mapping of grain-size-related traits by constructing a high-density genetic map using 109 recombinant inbred lines of einkorn wheat. We explored the candidate genes underlying QTLs through homologous analysis and RNA sequencing. The high-density genetic map spanned 1873 cM and contained 9937 single nucleotide polymorphism markers assigned to 1551 bins on seven chromosomes. Strong collinearity and high genome coverage of this map were revealed by comparison with physical maps of wheat and barley. Six grain size-related traits were surveyed in five environments. In total, 42 QTLs were identified; these were assigned to 17 genomic regions on six chromosomes and accounted for 52.3-66.7% of the phenotypic variation. Thirty homologous genes involved in grain development were located in 12 regions. RNA sequencing identified 4959 genes differentially expressed between the two parental lines. Twenty differentially expressed genes involved in grain size development and starch biosynthesis were mapped to nine regions that contained 26 QTLs, indicating that the starch biosynthesis pathway plays a vital role in grain development in einkorn wheat. This study provides new insights into the genetic architecture of grain size in einkorn wheat; identification of the underlying genes enables understanding of grain development and wheat genetic improvement. Furthermore, the map facilitates quantitative trait mapping, map-based cloning, genome assembly, and comparative genomics in wheat taxa.
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Affiliation(s)
- Kang Yu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology/Innovation Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, China
- Beijing Genomics Institute-Shenzhen, Shenzhen, China
- State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, China
| | - Dongcheng Liu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology/Innovation Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
| | - Yong Chen
- Science and Technology Department, State Tobacco Monopoly Administration, Beijing, China
| | - Dongzhi Wang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology/Innovation Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Wenlong Yang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology/Innovation Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
| | - Wei Yang
- Beijing Genomics Institute-Shenzhen, Shenzhen, China
| | - Lixin Yin
- Beijing Genomics Institute-Shenzhen, Shenzhen, China
| | - Chi Zhang
- Beijing Genomics Institute-Shenzhen, Shenzhen, China
- State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, China
| | - Shancen Zhao
- Beijing Genomics Institute-Shenzhen, Shenzhen, China
- State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, China
| | - Jiazhu Sun
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology/Innovation Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
| | - Chunming Liu
- Key Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, Beijing, China
| | - Aimin Zhang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology/Innovation Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
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Wang Y, Chen J, Guan Z, Zhang X, Zhang Y, Ma L, Yao Y, Peng H, Zhang Q, Zhang B, Liu P, Zou C, Shen Y, Ge F, Pan G. Combination of multi-locus genome-wide association study and QTL mapping reveals genetic basis of tassel architecture in maize. Mol Genet Genomics 2019; 294:1421-1440. [PMID: 31289944 DOI: 10.1007/s00438-019-01586-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2018] [Accepted: 06/10/2019] [Indexed: 11/30/2022]
Abstract
Maize tassel architecture is a complex quantitative trait that is significantly correlated with biomass yield and grain yield. The present study evaluated the major trait of maize tassel architecture, namely, tassel branch number (TBN), in an association population of 359 inbred lines and an IBM Syn 10 population of 273 doubled haploid lines across three environments. Approximately 43,958 high-quality single nucleotide polymorphisms were utilized to detect significant QTNs associated with TBN based on new multi-locus genome-wide association study methods. There were 30, 38, 73, 40, 47, and 53 QTNs associated with tassel architecture that were detected using the FastmrEMMA, FastmrMLM, EM-BLASSO, mrMLM, pkWMEB, and pLARmEB models, respectively. Among these QTNs, 51 were co-identified by at least two of these methods. In addition, 12 QTNs were consistently detected across multiple environments. Furthermore, 19 QTLs distributed on chromosomes 1, 2, 3, 4, 6, and 7 were detected in 3 environments and the BLUP model based on 6618 bin markers, which explained 3.64-10.96% of the observed phenotypic variations in TBN. Of these, three QTLs were co-detected in two environments. One QTN associated with TBN was localized to one QTL. Approximately 55 candidate genes were detected by common QTNs and LD criteria. One candidate gene, Zm00001d016615, was identified as a putative target of the RA1 gene. Meanwhile, RA1 was previously validated to plays an important role in tassel development. In addition, the newly identified candidate genes Zm00001d003939, Zm00001d030212, Zm00001d011189, and Zm00001d042794 have been reported to involve in a spikelet meristem identity module. The findings of the present study improve our understanding of the genetic basis of tassel architecture in maize.
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Affiliation(s)
- Yanli Wang
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Maize Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Jie Chen
- Crop Research Institute, Sichuan Academy of Agricultural Sciences, Chengdu, 610066, China
| | - Zhongrong Guan
- Chongqing Yudongnan Academy of Agricultural Sciences, Chongqing, 408000, China
| | - Xiaoxiang Zhang
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Maize Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Yinchao Zhang
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Maize Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Langlang Ma
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Maize Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Yiming Yao
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Maize Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Huanwei Peng
- Institute of Animal Nutrition, Sichuan Agricultural University, Chengdu, 611130, China
| | - Qian Zhang
- Institute of Agro-products Processing Science and Technology, Sichuan Academy of Agricultural Sciences, Chengdu, 610066, China
| | - Biao Zhang
- Institute of Agro-products Processing Science and Technology, Sichuan Academy of Agricultural Sciences, Chengdu, 610066, China
| | - Peng Liu
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Maize Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Chaoying Zou
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Maize Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Yaou Shen
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Maize Research Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Fei Ge
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Maize Research Institute, Sichuan Agricultural University, Chengdu, 611130, China.
| | - Guangtang Pan
- Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Maize Research Institute, Sichuan Agricultural University, Chengdu, 611130, China.
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Guo W, Lian T, Wang B, Guan J, Yuan D, Wang H, Safiul Azam FM, Wan X, Wang W, Liang Q, Wang H, Tu J, Zhang C, Jiang L. Genetic mapping of folate QTLs using a segregated population in maize. JOURNAL OF INTEGRATIVE PLANT BIOLOGY 2019; 61:675-690. [PMID: 30938052 DOI: 10.1111/jipb.12811] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Accepted: 03/25/2019] [Indexed: 05/06/2023]
Abstract
As essential B vitamin for humans, folates accumulation in edible parts of crops, such as maize kernels, is of great importance for human health. But its breeding is always limited by the prohibitive cost of folate profiling. The molecular breeding is a more executable and efficient way for folate fortification, but is limited by the molecular knowledge of folate regulation. Here we report the genetic mapping of folate quantitative trait loci (QTLs) using a segregated population crossed by two maize lines, one high in folate (GEMS31) and the other low in folate (DAN3130). Two folate QTLs on chromosome 5 were obtained by the combination of F2 whole-exome sequencing and F3 kernel-folate profiling. These two QTLs had been confirmed by bulk segregant analysis using F6 pooled DNA and F7 kernel-folate profiling, and were overlapped with QTLs identified by another segregated population. These two QTLs contributed 41.6% of phenotypic variation of 5-formyltetrahydrofolate, the most abundant storage form among folate derivatives in dry maize grains, in the GEMS31×DAN3130 population. Their fine mapping and functional analysis will reveal details of folate metabolism, and provide a basis for marker-assisted breeding aimed at the enrichment of folates in maize kernels.
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Affiliation(s)
- Wenzhu Guo
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - Tong Lian
- Plant Genetics, Gembloux Agro-Bio Tech, University of Liège, Gembloux, 5030, Belgium
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Baobao Wang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Jiantao Guan
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Dong Yuan
- Department of Chemistry and Chemical Engineering, Qilu Normal University, Jinan, 250200, China
| | - Huan Wang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | | | - Xing Wan
- School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai, 200237, China
| | - Weixuan Wang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Qiuju Liang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Haiyang Wang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Jinxing Tu
- College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China
| | - Chunyi Zhang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Ling Jiang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
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Park M, Lee JH, Han K, Jang S, Han J, Lim JH, Jung JW, Kang BC. A major QTL and candidate genes for capsaicinoid biosynthesis in the pericarp of Capsicum chinense revealed using QTL-seq and RNA-seq. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2019; 132:515-529. [PMID: 30426173 DOI: 10.1007/s00122-018-3238-8] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2018] [Accepted: 11/09/2018] [Indexed: 05/09/2023]
Abstract
A major QTL and candidate genes controlling capsaicinoid content in the pericarp were identified by QTL-seq and RNA-seq in Capsicum chinense. Capsaicinoid biosynthesis was previously thought to be restricted to the placental tissue; however, the recent discovery of their biosynthesis in the pericarp provides new opportunities to increase the capsaicinoid content in pepper fruits. Currently, the genetic mechanisms regulating capsaicinoid biosynthesis in the pericarp remain unknown. Here, we performed quantitative trait loci (QTL) mapping and RNA sequencing (RNA-seq) to reveal the genes controlling capsaicinoid biosynthesis in the pericarp. A whole-genome sequencing-based QTL-seq strategy was employed, identifying a major QTL on chromosome 6. To validate the QTL on chromosome 6, we performed traditional QTL mapping using the same population in QTL-seq with an additional biparental population. A total of 15 QTLs for capsaicinoid content distributed on chromosomes 3, 6, and 11 were newly identified. Among these QTLs, the genetic loci on the lower arm of chromosome 6 were commonly detected in the two mapping populations, corresponding to the location of the major QTL detected using whole-genome sequencing-based QTL-seq. Our RNA-seq analysis identified candidate genes within the common QTL that were differentially expressed in the pungent and non-pungent pericarp tissues. Our results are expected to contribute to the elucidation of the regulation of capsaicinoid biosynthesis. We also demonstrated that a combination of QTL mapping and RNA-seq is helpful for refining the candidate genes of a complicated trait of interest.
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Affiliation(s)
- Minjeong Park
- Department of Plant Science, Plant Genomics and Breeding Institute, and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, 151-921, Republic of Korea
| | - Joung-Ho Lee
- Department of Plant Science, Plant Genomics and Breeding Institute, and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, 151-921, Republic of Korea
| | - Koeun Han
- Department of Plant Science, Plant Genomics and Breeding Institute, and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, 151-921, Republic of Korea
| | - Siyoung Jang
- Department of Plant Science, Plant Genomics and Breeding Institute, and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, 151-921, Republic of Korea
| | - Jiwoong Han
- Department of Plant Science, Plant Genomics and Breeding Institute, and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, 151-921, Republic of Korea
| | - Jung-Hyun Lim
- Research Institute of Biotechnology, CJ CheilJedang Corp., Suwon, 16495, Republic of Korea
| | - Ji-Won Jung
- Research Institute of Biotechnology, CJ CheilJedang Corp., Suwon, 16495, Republic of Korea
| | - Byoung-Cheorl Kang
- Department of Plant Science, Plant Genomics and Breeding Institute, and Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, 151-921, Republic of Korea.
- Crop Biotechnology Institute/GreenBio Science and Technology, Seoul National University, Pyeongchang, 232-916, Republic of Korea.
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Ma JQ, Jin JQ, Yao MZ, Ma CL, Xu YX, Hao WJ, Chen L. Quantitative Trait Loci Mapping for Theobromine and Caffeine Contents in Tea Plant ( Camellia sinensis). JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2018; 66:13321-13327. [PMID: 30486648 DOI: 10.1021/acs.jafc.8b05355] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Understanding the genetic basis of theobromine and caffeine accumulation in the tea plant is important due to their contribution to tea flavor. Quantitative trait loci (QTL) analyses were carried out to identify genetic variants associated with theobromine and caffeine contents and ratio using a pseudo-testcross population derived from an intervarietal cross between two varieties of Camellia sinensis. A total of 10 QTL controlling caffeine content (CAF), theobromine content (TBR), sum of caffeine and theobromine (SCT), and caffeine-to-theobromine ratio (CTR) were identified over four measurement years. The major QTL controlling CAF, qCAF1, was mapped onto LG01 and validated across years, explaining an average of 20.1% of the phenotypic variance. The other QTL were detected in 1 or 2 years, and of them there were four, two, and three for TBR, SCT, and CTR, respectively. The present results provide valuable information for further fine mapping and cloning functional genes and for genetic improvement in tea plant.
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Affiliation(s)
- Jian-Qiang Ma
- Key Laboratory of Tea Plant Biology and Resources Utilization, Ministry of Agriculture , Tea Research Institute of the Chinese Academy of Agricultural Sciences (TRICAAS) , 9 South Meiling Road , Hangzhou 310008 , China
| | - Ji-Qiang Jin
- Key Laboratory of Tea Plant Biology and Resources Utilization, Ministry of Agriculture , Tea Research Institute of the Chinese Academy of Agricultural Sciences (TRICAAS) , 9 South Meiling Road , Hangzhou 310008 , China
| | - Ming-Zhe Yao
- Key Laboratory of Tea Plant Biology and Resources Utilization, Ministry of Agriculture , Tea Research Institute of the Chinese Academy of Agricultural Sciences (TRICAAS) , 9 South Meiling Road , Hangzhou 310008 , China
| | - Chun-Lei Ma
- Key Laboratory of Tea Plant Biology and Resources Utilization, Ministry of Agriculture , Tea Research Institute of the Chinese Academy of Agricultural Sciences (TRICAAS) , 9 South Meiling Road , Hangzhou 310008 , China
| | - Yan-Xia Xu
- Key Laboratory of Tea Plant Biology and Resources Utilization, Ministry of Agriculture , Tea Research Institute of the Chinese Academy of Agricultural Sciences (TRICAAS) , 9 South Meiling Road , Hangzhou 310008 , China
| | - Wan-Jun Hao
- Key Laboratory of Tea Plant Biology and Resources Utilization, Ministry of Agriculture , Tea Research Institute of the Chinese Academy of Agricultural Sciences (TRICAAS) , 9 South Meiling Road , Hangzhou 310008 , China
| | - Liang Chen
- Key Laboratory of Tea Plant Biology and Resources Utilization, Ministry of Agriculture , Tea Research Institute of the Chinese Academy of Agricultural Sciences (TRICAAS) , 9 South Meiling Road , Hangzhou 310008 , China
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Whole Genome Resequencing from Bulked Populations as a Rapid QTL and Gene Identification Method in Rice. Int J Mol Sci 2018; 19:ijms19124000. [PMID: 30545055 PMCID: PMC6321147 DOI: 10.3390/ijms19124000] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Revised: 11/30/2018] [Accepted: 12/02/2018] [Indexed: 11/16/2022] Open
Abstract
Most Quantitative Trait Loci (QTL) and gene isolation approaches, such as positional- or map-based cloning, are time-consuming and low-throughput methods. Understanding and detecting the genetic material that controls a phenotype is a key means to functionally analyzing genes as well as to enhance crop agronomic traits. In this regard, high-throughput technologies have great prospects for changing the paradigms of DNA marker revealing, genotyping, and for discovering crop genetics and genomic study. Bulk segregant analysis, based on whole genome resequencing approaches, permits the rapid isolation of the genes or QTL responsible for the causative mutation of the phenotypes. MutMap, MutMap Gap, MutMap+, modified MutMap, and QTL-seq methods are among those approaches that have been confirmed to be fruitful gene mapping approaches for crop plants, such as rice, irrespective of whether the characters are determined by polygenes. As a result, in the present study we reviewed the progress made by all these methods to identify QTL or genes in rice.
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50
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Yang Q, Yang Z, Tang H, Yu Y, Chen Z, Wei S, Sun Q, Peng Z. High-density genetic map construction and mapping of the homologous transformation sterility gene (hts) in wheat using GBS markers. BMC PLANT BIOLOGY 2018; 18:301. [PMID: 30477426 PMCID: PMC6258151 DOI: 10.1186/s12870-018-1532-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2018] [Accepted: 11/16/2018] [Indexed: 05/07/2023]
Abstract
BACKGROUND Homologous transformation sterility-1 (HTS-1) is a novel wheat mutant that exhibits pistillody, the transformation of stamens into pistils or pistil-like structures. More extreme phenotypes of this mutation can have six pistils or pistil-like structures without any stamens in a floret. Thus, HTS-1 is highly valuable for studies of wheat hybrid breeding and flower development. Previous studies have shown that two major genes (Pis1 and hts) control pistillody in HTS-1. The Pis1 gene controls the three-pistil trait in the three-pistil wheat mutant and has been mapped on chromosome 2D, but the hts gene has not been mapped or identified. To do so, we crossed HTS-1 with CM28TP (three-pistil mutant) and constructed a high-density linkage map with the F2 population (200 individuals). RESULTS The map covered 2779.96 cM, and the genetic distance per chromosome ranged from 37.59 cM to 318.95 cM. The average distance between markers was 1.04 cM. We then mapped hts between GBS-SNP markers 4A_109 and 4A_119, separated by 2.0 cM and 5.2 Mb. To find the candidate genes, the hts region was enlarged to 7.2 Mb, encompassing 752 protein-coding genes. We identified TaWin1 as a possible candidate gene after comparing the 752 genes with 206 common differentially expressed genes between pistillody stamens (PS) versus normal stamens (S) and pistils (P) versus S. Real-time PCR indicated that TaWin1 was highly expressed in HTS-1 during the pistil-and-stamen-differentiating stage, at levels approximately 120 times greater than those in CM28TP. Further analysis indicated that TaWin1 was mainly expressed in HTS-1 PS, supporting its status as a candidate gene of hts. Thus, TaWin1 overexpression probably leads to the transformation of stamens into pistils in wheat. CONCLUSIONS The results of this study provide a foundation for further research on stamen and pistil development, with implications for wheat-hybrid breeding programs.
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Affiliation(s)
- Qian Yang
- Key Laboratory of Southwest China Wildlife Resources Conservation (ministry of education), College of Life Science, China West Normal University, Nanchong, 637009 Sichuan China
| | - Zaijun Yang
- Key Laboratory of Southwest China Wildlife Resources Conservation (ministry of education), College of Life Science, China West Normal University, Nanchong, 637009 Sichuan China
| | - Haifeng Tang
- Key Laboratory of Southwest China Wildlife Resources Conservation (ministry of education), College of Life Science, China West Normal University, Nanchong, 637009 Sichuan China
| | - Yan Yu
- Key Laboratory of Southwest China Wildlife Resources Conservation (ministry of education), College of Life Science, China West Normal University, Nanchong, 637009 Sichuan China
| | - Zhenyong Chen
- Key Laboratory of Southwest China Wildlife Resources Conservation (ministry of education), College of Life Science, China West Normal University, Nanchong, 637009 Sichuan China
| | - Shuhong Wei
- Key Laboratory of Southwest China Wildlife Resources Conservation (ministry of education), College of Life Science, China West Normal University, Nanchong, 637009 Sichuan China
| | - Qinxu Sun
- Key Laboratory of Southwest China Wildlife Resources Conservation (ministry of education), College of Life Science, China West Normal University, Nanchong, 637009 Sichuan China
| | - Zhengsong Peng
- School of Agricultural Science, Xichang University, Xichang, 615000 Sichuan China
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