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Liang Q, Pan H, He X, Wang S, Hou Y, Xiao H, Xu G, Yi R, Lin D, Yang Z. Population structure and genetic diversity of mango ( Mangifera indica L.) germplasm resources as revealed by single-nucleotide polymorphism markers. FRONTIERS IN PLANT SCIENCE 2024; 15:1328126. [PMID: 39022611 PMCID: PMC11251951 DOI: 10.3389/fpls.2024.1328126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 06/10/2024] [Indexed: 07/20/2024]
Abstract
Introduction Mango is a vital horticultural fruit crop, and breeding is an essential strategy to enhance ongoing sustainability. Knowledge regarding population structure and genetic diversity in mango germplasm is essential for crop improvement. Methods A set of 284 mango accessions from different regions of the world were subjected to high-throughput sequencing and specific-locus amplified fragment (SLAF) library construction to generate genomic single-nucleotide polymorphism (SNP). Results After filtering, raw data containing 539.61 M reads were obtained. A total of 505,300 SLAFs were detected, of which, 205,299 were polymorphic. Finally, 29,136 SNPs were employed to dissect the population structure, genetic relationships, and genetic diversity. The 284 mango accessions were divided into two major groups: one group consisted mainly of mango accessions from Australia, the United States, Cuba, India, Caribbean, Israel, Pakistan, Guinea, Burma, China, and Sri Lanka, which belonged to the Indian type (P1); the other group contained mango accessions from the Philippines, Thailand, Indonesia, Vietnam, Cambodia, Malaysia, and Singapore, which belonged to Southeast Asian type (P2). Genetic diversity, principal component analysis (PCA), and population structure analyses revealed distinct accession clusters. Current results indicated that the proposed hybridization occurred widely between P1 and P2. Discussion Most of the accessions (80.99%) were of mixed ancestry, perhaps including multiple hybridization events and regional selection, which merits further investigation.
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Affiliation(s)
- Qingzhi Liang
- College of Coastal Agricultural Sciences, Guangdong Ocean University, Zhanjiang, China
- South Subtropical Crops Research Institute, Chinese Academy of Tropical Agricultural Sciences, Zhanjiang, China
| | - Hongbing Pan
- Fruits Research Institute, Panzhihua Academy of Agricultural and Forestry Sciences, Panzhihua, China
| | - Xiaolong He
- South Subtropical Crops Research Institute, Chinese Academy of Tropical Agricultural Sciences, Zhanjiang, China
| | - Songbiao Wang
- South Subtropical Crops Research Institute, Chinese Academy of Tropical Agricultural Sciences, Zhanjiang, China
| | - Yuanhua Hou
- College of Coastal Agricultural Sciences, Guangdong Ocean University, Zhanjiang, China
- College of Tropical Crops, Yunnan Agricultural University, Puer, China
| | - Hua Xiao
- College of Electronic and Information Engineering, Guangdong Ocean University, Zhanjiang, China
| | - Guangzhao Xu
- College of Coastal Agricultural Sciences, Guangdong Ocean University, Zhanjiang, China
| | - Runhua Yi
- College of Coastal Agricultural Sciences, Guangdong Ocean University, Zhanjiang, China
| | - Dongbo Lin
- College of Coastal Agricultural Sciences, Guangdong Ocean University, Zhanjiang, China
| | - Zhuanying Yang
- College of Coastal Agricultural Sciences, Guangdong Ocean University, Zhanjiang, China
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2
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Li Z, Li C, Zhang R, Duan M, Tian H, Yi H, Xu L, Wang F, Shi Z, Wang X, Wang J, Su A, Wang S, Sun X, Zhao Y, Wang S, Zhang Y, Wang Y, Song W, Zhao J. Genomic analysis of a new heterotic maize group reveals key loci for pedigree breeding. FRONTIERS IN PLANT SCIENCE 2023; 14:1213675. [PMID: 37636101 PMCID: PMC10451083 DOI: 10.3389/fpls.2023.1213675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 07/21/2023] [Indexed: 08/29/2023]
Abstract
Genome-wide analyses of maize populations have clarified the genetic basis of crop domestication and improvement. However, limited information is available on how breeding improvement reshaped the genome in the process of the formation of heterotic groups. In this study, we identified a new heterotic group (X group) based on an examination of 512 Chinese maize inbred lines. The X group was clearly distinct from the other non-H&L groups, implying that X × HIL is a new heterotic pattern. We selected the core inbred lines for an analysis of yield-related traits. Almost all yield-related traits were better in the X lines than those in the parental lines, indicating that the primary genetic improvement in the X group during breeding was yield-related traits. We generated whole-genome sequences of these lines with an average coverage of 17.35× to explore genome changes further. We analyzed the identity-by-descent (IBD) segments transferred from the two parents to the X lines and identified 29 and 28 IBD conserved regions (ICRs) from the parents PH4CV and PH6WC, respectively, accounting for 28.8% and 12.8% of the genome. We also identified 103, 89, and 131 selective sweeps (SSWs) using methods that involved the π, Tajima's D, and CLR values, respectively. Notably, 96.13% of the ICRs co-localized with SSWs, indicating that SSW signals concentrated in ICRs. We identified 171 annotated genes associated with yield-related traits in maize both in ICRs and SSWs. To identify the genetic factors associated with yield improvement, we conducted QTL mapping for 240 lines from a DH population (PH4CV × PH6WC, which are the parents of X1132X) for ten key yield-related traits and identified a total of 55 QTLs. Furthermore, we detected three QTL clusters both in ICRs and SSWs. Based on the genetic evidence, we finally identified three key genes contributing to yield improvement in breeding the X group. These findings reveal key loci and genes targeted during pedigree breeding and provide new insights for future genomic breeding.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Yuandong Wang
- Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Maize Research Institute, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Wei Song
- Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Maize Research Institute, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Jiuran Zhao
- Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Maize Research Institute, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
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3
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Wang B, Hou M, Shi J, Ku L, Song W, Li C, Ning Q, Li X, Li C, Zhao B, Zhang R, Xu H, Bai Z, Xia Z, Wang H, Kong D, Wei H, Jing Y, Dai Z, Wang HH, Zhu X, Li C, Sun X, Wang S, Yao W, Hou G, Qi Z, Dai H, Li X, Zheng H, Zhang Z, Li Y, Wang T, Jiang T, Wan Z, Chen Y, Zhao J, Lai J, Wang H. De novo genome assembly and analyses of 12 founder inbred lines provide insights into maize heterosis. Nat Genet 2023; 55:312-323. [PMID: 36646891 DOI: 10.1038/s41588-022-01283-w] [Citation(s) in RCA: 30] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 12/09/2022] [Indexed: 01/18/2023]
Abstract
Hybrid maize displays superior heterosis and contributes over 30% of total worldwide cereal production. However, the molecular mechanisms of heterosis remain obscure. Here we show that structural variants (SVs) between the parental lines have a predominant role underpinning maize heterosis. De novo assembly and analyses of 12 maize founder inbred lines (FILs) reveal abundant genetic variations among these FILs and, through expression quantitative trait loci and association analyses, we identify several SVs contributing to genomic and phenotypic differentiations of various heterotic groups. Using a set of 91 diallel-cross F1 hybrids, we found strong positive correlations between better-parent heterosis of the F1 hybrids and the numbers of SVs between the parental lines, providing concrete genomic support for a prevalent role of genetic complementation underlying heterosis. Further, we document evidence that SVs in both ZAR1 and ZmACO2 contribute to yield heterosis in an overdominance fashion. Our results should promote genomics-based breeding of hybrid maize.
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Affiliation(s)
- Baobao Wang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Mei Hou
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China.,Key Laboratory of Herbage and Endemic Crop Biology, Ministry of Education, Inner Mongolia University, Hohhot, China
| | - Junpeng Shi
- State Key Laboratory of Plant Physiology and Biochemistry & National Maize Improvement Center, Department of Plant Genetics and Breeding, China Agricultural University, Beijing, China
| | - Lixia Ku
- College of Agronomy and National Key Laboratory of Wheat and Maize Crop Science, Henan Agricultural University, Zhengzhou, China
| | - Wei Song
- Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences, Beijing, China
| | - Chunhui Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Qiang Ning
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
| | - Xin Li
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Changyu Li
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Binbin Zhao
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Ruyang Zhang
- Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences, Beijing, China
| | - Hua Xu
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhijing Bai
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhanchao Xia
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Hai Wang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Dexin Kong
- Guangdong Laboratory for Lingnan Modern Agriculture, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, China
| | - Hongbin Wei
- Guangdong Laboratory for Lingnan Modern Agriculture, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, China
| | - Yifeng Jing
- Guangdong Laboratory for Lingnan Modern Agriculture, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, China
| | - Zhouyan Dai
- Guangdong Laboratory for Lingnan Modern Agriculture, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, China
| | - Hu Hailing Wang
- Guangdong Laboratory for Lingnan Modern Agriculture, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, China
| | - Xinyu Zhu
- Guangdong Laboratory for Lingnan Modern Agriculture, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, China
| | - Chunhui Li
- Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences, Beijing, China
| | - Xuan Sun
- Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences, Beijing, China
| | - Shuaishuai Wang
- Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences, Beijing, China
| | - Wen Yao
- College of Agronomy and National Key Laboratory of Wheat and Maize Crop Science, Henan Agricultural University, Zhengzhou, China
| | - Gege Hou
- College of Agronomy and National Key Laboratory of Wheat and Maize Crop Science, Henan Agricultural University, Zhengzhou, China
| | - Zhi Qi
- Key Laboratory of Herbage and Endemic Crop Biology, Ministry of Education, Inner Mongolia University, Hohhot, China
| | - He Dai
- Biomarker Technologies Corporation, Beijing, China
| | - Xuming Li
- Biomarker Technologies Corporation, Beijing, China
| | | | - Zuxin Zhang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan, China
| | - Yu Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Tianyu Wang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Taijiao Jiang
- Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou, China.,Guangzhou Laboratory, Guangzhou, China
| | - Zhaoman Wan
- Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou, China
| | - Yanhui Chen
- College of Agronomy and National Key Laboratory of Wheat and Maize Crop Science, Henan Agricultural University, Zhengzhou, China.
| | - Jiuran Zhao
- Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences, Beijing, China.
| | - Jinsheng Lai
- State Key Laboratory of Plant Physiology and Biochemistry & National Maize Improvement Center, Department of Plant Genetics and Breeding, China Agricultural University, Beijing, China.
| | - Haiyang Wang
- Guangdong Laboratory for Lingnan Modern Agriculture, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, China.
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4
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Safiul Azam FM, Lian T, Liang Q, Wang W, Zhang C, Jiang L. Variation of vitamin B contents in maize inbred lines: Potential genetic resources for biofortification. Front Nutr 2022; 9:1029119. [PMID: 36337650 PMCID: PMC9634661 DOI: 10.3389/fnut.2022.1029119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 10/06/2022] [Indexed: 11/17/2022] Open
Abstract
Vitamin B and its derivatives possess diverse physiological functions and are essential micronutrients for humans. Their variation in crops is important for the identification of genetic resources used to develop new varieties with enhanced vitamin B. In this research, remarkable variations were observed in kernels of 156 maize inbred lines, ranging from 107.61 to 2654.54 μg per 100 g for vitamin B1, 1.19-37.37 μg per 100 g for B2, 19.60-213.75 μg per 100 g for B3, 43.47-590.86 μg per 100 g for B5, and 138.59-1065.11 μg per 100 g for B6. Growing inbreeds in Hainan and Hebei provinces of China revealed environmental and genotype interactions among these vitamins and the correlations between them in maize grain. Several inbred lines were identified as good sources of vitamin B and promising germplasms for maize breeding, namely By855 and Si273 are overall rich in all the studied vitamins, and GY386B and CML118 are specially enriched with derivatives of vitamin B6. The present study can assist maize breeders with germplasm resources of vitamin B for biofortification to offer people nutritious foods.
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Affiliation(s)
| | - Tong Lian
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
- Sanya Institute, Hainan Academy of Agricultural Sciences, Sanya, China
| | - Qiuju Liang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Weixuan Wang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Chunyi Zhang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
- Sanya Institute, Hainan Academy of Agricultural Sciences, Sanya, China
| | - Ling Jiang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
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5
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Li C, Guan H, Jing X, Li Y, Wang B, Li Y, Liu X, Zhang D, Liu C, Xie X, Zhao H, Wang Y, Liu J, Zhang P, Hu G, Li G, Li S, Sun D, Wang X, Shi Y, Song Y, Jiao C, Ross-Ibarra J, Li Y, Wang T, Wang H. Genomic insights into historical improvement of heterotic groups during modern hybrid maize breeding. NATURE PLANTS 2022; 8:750-763. [PMID: 35851624 DOI: 10.1038/s41477-022-01190-2] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2022] [Accepted: 06/07/2022] [Indexed: 06/15/2023]
Abstract
Single-cross maize hybrids display superior heterosis and are produced from crossing two parental inbred lines belonging to genetically different heterotic groups. Here we assembled 1,604 historically utilized maize inbred lines belonging to various female heterotic groups (FHGs) and male heterotic groups (MHGs), and conducted phenotyping and genomic sequencing analyses. We found that the FHGs and MHGs have undergone both convergent and divergent changes for different sets of agronomic traits. Using genome-wide selection scans and association analyses, we identified a large number of candidate genes that contributed to the improvement of agronomic traits of the FHGs and MHGs. Moreover, we observed increased genetic differentiation between the FHGs and MHGs across the breeding eras, and we found a positive correlation between increasing heterozygosity levels in the differentiated genes and heterosis in hybrids. Furthermore, we validated the function of two selected genes and a differentiated gene. This study provides insights into the genomic basis of modern hybrid maize breeding.
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Affiliation(s)
- Chunhui Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Honghui Guan
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xin Jing
- Novogene Bioinformatics Institute, Beijing, China
| | - Yaoyao Li
- Guangdong Laboratory for Lingnan Modern Agriculture, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, China
| | - Baobao Wang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yongxiang Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xuyang Liu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Dengfeng Zhang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Cheng Liu
- Institute of Food Crops, Xinjiang Academy of Agricultural Sciences, Urumqi, China
| | - Xiaoqing Xie
- Institute of Food Crops, Xinjiang Academy of Agricultural Sciences, Urumqi, China
| | - Haiyan Zhao
- Institute of Maize Research, Liaoning Academy of Agricultural Sciences, Shenyang, China
| | - Yanbo Wang
- Institute of Maize Research, Liaoning Academy of Agricultural Sciences, Shenyang, China
| | - Jingbao Liu
- Institute of Cereal Crops, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Panpan Zhang
- Institute of Cereal Crops, Henan Academy of Agricultural Sciences, Zhengzhou, China
| | - Guanghui Hu
- Institute of Maize Research, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Guoliang Li
- Institute of Maize Research, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Suiyan Li
- Institute of Forage and Grassland Sciences, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Dequan Sun
- Institute of Forage and Grassland Sciences, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Xiaoming Wang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yunsu Shi
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yanchun Song
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | | | - Jeffrey Ross-Ibarra
- Department of Evolution and Ecology, University of California, Davis, CA, USA.
- Center for Population Biology and Genome Center, University of California, Davis, CA, USA.
| | - Yu Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
| | - Tianyu Wang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
| | - Haiyang Wang
- Guangdong Laboratory for Lingnan Modern Agriculture, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, China.
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6
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Yang Z, Wang Z, Wang W, Xie X, Chai L, Wang X, Feng X, Li J, Peng H, Su Z, You M, Yao Y, Xin M, Hu Z, Liu J, Liang R, Ni Z, Sun Q, Guo W. ggComp enables dissection of germplasm resources and construction of a multiscale germplasm network in wheat. PLANT PHYSIOLOGY 2022; 188:1950-1965. [PMID: 35088857 PMCID: PMC8968352 DOI: 10.1093/plphys/kiac029] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 12/10/2021] [Indexed: 05/31/2023]
Abstract
Accurate germplasm characterization is a vital step for accelerating crop genetic improvement, which remains largely infeasible for crops such as bread wheat (Triticum aestivum L.), which has a complex genome that undergoes frequent introgression and contains many structural variations. Here, we propose a genomic strategy called ggComp, which integrates resequencing data with copy number variations and stratified single-nucleotide polymorphism densities to enable unsupervised identification of pairwise germplasm resource-based Identity-By-Descent (gIBD) blocks. The reliability of ggComp was verified in wheat cultivar Nongda5181 by dissecting parental-descent patterns represented by inherited genomic blocks. With gIBD blocks identified among 212 wheat accessions, we constructed a multi-scale genomic-based germplasm network. At the whole-genome level, the network helps to clarify pedigree relationship, demonstrate genetic flow, and identify key founder lines. At the chromosome level, we were able to trace the utilization of 1RS introgression in modern wheat breeding by hitchhiked segments. At the single block scale, the dissected germplasm-based haplotypes nicely matched with previously identified alleles of "Green Revolution" genes and can guide allele mining and dissect the trajectory of beneficial alleles in wheat breeding. Our work presents a model-based framework for precisely evaluating germplasm resources with genomic data. A database, WheatCompDB (http://wheat.cau.edu.cn/WheatCompDB/), is available for researchers to exploit the identified gIBDs with a multi-scale network.
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Affiliation(s)
| | | | | | - Xiaoming Xie
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Lingling Chai
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Xiaobo Wang
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Xibo Feng
- Tibet Key Experiments of Crop Cultivation and Farming/College of Plant Science, Tibet Agriculture and Animal Husbandry University, Linzhi 860000, China
| | - Jinghui Li
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
- Wheat Center, Henan Institute of Science and Technology/Henan Provincial Key Laboratory of Hybrid Wheat, Xinxiang 453003, China
| | - Huiru Peng
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Zhenqi Su
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Mingshan You
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Yingyin Yao
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Mingming Xin
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Zhaorong Hu
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Jie Liu
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Rongqi Liang
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Zhongfu Ni
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
| | - Qixin Sun
- State Key Laboratory for Agrobiotechnology/Key Laboratory of Crop Heterosis and Utilization, Ministry of Education/Beijing Key Laboratory of Crop Genetic Improvement/College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China
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7
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Wu J, Sun D, Zhao Q, Yong H, Zhang D, Hao Z, Zhou Z, Han J, Zhang X, Xu Z, Li X, Li M, Weng J. Transcriptome Reveals Allele Contribution to Heterosis in Maize. FRONTIERS IN PLANT SCIENCE 2021; 12:739072. [PMID: 34630491 PMCID: PMC8494984 DOI: 10.3389/fpls.2021.739072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Accepted: 09/06/2021] [Indexed: 06/13/2023]
Abstract
Heterosis, which has greatly increased maize yields, is associated with gene expression patterns during key developmental stages that enhance hybrid phenotypes relative to parental phenotypes. Before heterosis can be more effectively used for crop improvement, hybrid maize developmental gene expression patterns must be better understood. Here, six maize hybrids, including the popular hybrid Zhengdan958 (ZC) from China, were studied. Maize hybrids created in-house were generated using an incomplete diallel cross (NCII)-based strategy from four elite inbred parental lines. Differential gene expression (DEG) profiles corresponding to three developmental stages revealed that hybrid partial expression patterns exhibited complementarity of expression of certain parental genes, with parental allelic expression patterns varying both qualitatively and quantitatively in hybrids. Single-parent expression (SPE) and parent-specific expression (PSE) types of qualitative variation were most prevalent, 43.73 and 41.07% of variation, respectively. Meanwhile, negative super-dominance (NSD) and positive super-dominance (PSD) types of quantitative variation were most prevalent, 31.06 and 24.30% of variation, respectively. During the early reproductive growth stage, the gene expression pattern differed markedly from other developmental stage patterns, with allelic expression patterns during seed development skewed toward low-value parental alleles in hybrid seeds exhibiting significant quantitative variation-associated superiority. Comparisons of qualitative gene expression variation rates between ZC and other hybrids revealed proportions of SPE-DEGs (41.36%) in ZC seed DEGs that significantly exceeded the average proportion of SPE-DEGs found in seeds of other hybrids (28.36%). Importantly, quantitative gene expression variation rate comparisons between ZC and hybrids, except for transgressive expression, revealed that the ZC rate exceeded the average rate for other hybrids, highlighting the importance of partial gene expression in heterosis. Moreover, enriched ZC DEGs exhibiting distinct tissue-specific expression patterns belonged to four biological pathways, including photosynthesis, plant hormone signal transduction, biology metabolism and biosynthesis. These results provide valuable technical insights for creating hybrids exhibiting strong heterosis.
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Affiliation(s)
- Jianzhong Wu
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
- Institute of Forage and Grassland Sciences, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Dequan Sun
- Institute of Forage and Grassland Sciences, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Qian Zhao
- Institute of Crop Cultivation and Tillage, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Hongjun Yong
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Degui Zhang
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhuanfang Hao
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhiqiang Zhou
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jienan Han
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xiaocong Zhang
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhennan Xu
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xinhai Li
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Mingshun Li
- 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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Genome-wide selection and genetic improvement during modern maize breeding. Nat Genet 2020; 52:565-571. [DOI: 10.1038/s41588-020-0616-3] [Citation(s) in RCA: 65] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2019] [Accepted: 03/23/2020] [Indexed: 11/08/2022]
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Li C, Song W, Luo Y, Gao S, Zhang R, Shi Z, Wang X, Wang R, Wang F, Wang J, Zhao Y, Su A, Wang S, Li X, Luo M, Wang S, Zhang Y, Ge J, Tan X, Yuan Y, Bi X, He H, Yan J, Wang Y, Hu S, Zhao J. The HuangZaoSi Maize Genome Provides Insights into Genomic Variation and Improvement History of Maize. MOLECULAR PLANT 2019; 12:402-409. [PMID: 30807824 DOI: 10.1016/j.molp.2019.02.009] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 01/31/2019] [Accepted: 02/17/2019] [Indexed: 06/09/2023]
Abstract
Maize is a globally important crop that was a classic model plant for genetic studies. Here, we report a 2.2 Gb draft genome sequence of an elite maize line, HuangZaoSi (HZS). Hybrids bred from HZS-improved lines (HILs) are planted in more than 60% of maize fields in China. Proteome clustering of six completed sequenced maize genomes show that 638 proteins fall into 264 HZS-specific gene families with the majority of contributions from tandem duplication events. Resequencing and comparative analysis of 40 HZS-related lines reveals the breeding history of HILs. More than 60% of identified selective sweeps were clustered in identity-by-descent conserved regions, and yield-related genes/QTLs were enriched in HZS characteristic selected regions. Furthermore, we demonstrated that HZS-specific family genes were not uniformly distributed in the genome but enriched in improvement/function-related genomic regions. This study provides an important and novel resource for maize genome research and expands our knowledge on the breadth of genomic variation and improvement history of maize.
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Affiliation(s)
- Chunhui Li
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China
| | - Wei Song
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China
| | - Yingfeng Luo
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Shenghan Gao
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Ruyang Zhang
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China
| | - Zi Shi
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China
| | - Xiaqing Wang
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China
| | - Ronghuan Wang
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China
| | - Fengge Wang
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China
| | - Jidong Wang
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China
| | - Yanxin Zhao
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China
| | - Aiguo Su
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China
| | - Shuai Wang
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China
| | - Xin Li
- School of Advanced Agriculture Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking University, Beijing 100871, China
| | - Meijie Luo
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China
| | - Shuaishuai Wang
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China
| | - Yunxia Zhang
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China
| | - Jianrong Ge
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China
| | - Xinyu Tan
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Ye Yuan
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Xiaochun Bi
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Hang He
- School of Advanced Agriculture Sciences and School of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Peking University, Beijing 100871, China
| | - Jianbing Yan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan 430070, China
| | - Yuandong Wang
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China.
| | - Songnian Hu
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China.
| | - Jiuran Zhao
- Maize Research Center, Beijing Academy of Agriculture & Forestry Sciences (BAAFS), Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Shuguang Garden Middle Road No. 9, Beijing 100097, China.
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Li T, Qu J, Wang Y, Chang L, He K, Guo D, Zhang X, Xu S, Xue J. Genetic characterization of inbred lines from Shaan A and B groups for identifying loci associated with maize grain yield. BMC Genet 2018; 19:63. [PMID: 30139352 PMCID: PMC6108135 DOI: 10.1186/s12863-018-0669-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2018] [Accepted: 08/14/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Increasing grain yield is a primary objective of maize breeding. Dissecting the genetic architecture of grain yield furthers genetic improvements to increase yield. Presented here is an association panel composed of 126 maize inbreds (AM126), which were genotyped by the genotyping-by-sequencing (tGBS) method. We performed genetic characterization and association analysis related to grain yield in the association panel. RESULTS In total, 46,046 SNPs with a minor allele frequency (MAF) ≥0.01 were used to assess genetic diversity and kinship in AM126. The results showed that the average MAF and polymorphism information content (PIC) were 0.164 and 0.198, respectively. The Shaan B group, with 11,284 unique SNPs, exhibited greater genetic diversity than did the Shaan A group, with 2644 SNPs. The 61.82% kinship coefficient in AM126 was equal to 0, and only 0.15% of that percentage was greater than 0.7. A total of 31,983 SNPs with MAF ≥0.05 were used to characterize population structure, LD decay and association mapping. Population structure analysis suggested that AM126 can be divided into 6 subgroups, which is consistent with breeding experience and pedigree information. The LD decay distance in AM126 was 150 kb. A total of 51 significant SNPs associated with grain yield were identified at P < 1 × 10- 3 across two environments (Yangling and Yulin). Among those SNPs, two loci displayed overlapping regions in the two environments. Finally, 30 candidate genes were found to be associated with grain yield. CONCLUSIONS These results contribute to the genetic characterization of this breeding population, which serves as a reference for hybrid breeding and population improvement, and demonstrate the genetic architecture of maize grain yield, potentially facilitating genetic improvement.
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Affiliation(s)
- Ting Li
- Key Laboratory of Biology and Genetic Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre of Shaanxi Province, Yangling, China
| | - Jianzhou Qu
- Key Laboratory of Biology and Genetic Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre of Shaanxi Province, Yangling, China
| | - Yahui Wang
- Key Laboratory of Biology and Genetic Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre of Shaanxi Province, Yangling, China
| | - Liguo Chang
- Key Laboratory of Biology and Genetic Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre of Shaanxi Province, Yangling, China
| | - Kunhui He
- Key Laboratory of Biology and Genetic Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre of Shaanxi Province, Yangling, China
| | - Dongwei Guo
- Key Laboratory of Biology and Genetic Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre of Shaanxi Province, Yangling, China
| | - Xinghua Zhang
- Key Laboratory of Biology and Genetic Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre of Shaanxi Province, Yangling, China
| | - Shutu Xu
- Key Laboratory of Biology and Genetic Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre of Shaanxi Province, Yangling, China
| | - Jiquan Xue
- Key Laboratory of Biology and Genetic Improvement of Maize in Arid Area of Northwest Region, Ministry of Agriculture, College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China
- Maize Engineering Technology Research Centre of Shaanxi Province, Yangling, China
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