Using high-throughput multiple optical phenotyping to decipher the genetic architecture of maize drought tolerance
Abstract Background Drought threatens the food supply of the world population. Dissecting the dynamic responses of plants to drought will be beneficial for breeding drought-tolerant crops, as the genetic controls of these responses remain largely unknown. Results Here we develop a high-throughput mu...
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| Format: | Article |
| Language: | English |
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BMC
2021-06-01
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| Series: | Genome Biology |
| Online Access: | https://doi.org/10.1186/s13059-021-02377-0 |
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doaj-f5985e14b7f14adda4aa409420da0b44 |
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| record_format |
Article |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Xi Wu Hui Feng Di Wu Shijuan Yan Pei Zhang Wenbin Wang Jun Zhang Junli Ye Guoxin Dai Yuan Fan Weikun Li Baoxing Song Zedong Geng Wanli Yang Guoxin Chen Feng Qin William Terzaghi Michelle Stitzer Lin Li Lizhong Xiong Jianbing Yan Edward Buckler Wanneng Yang Mingqiu Dai |
| spellingShingle |
Xi Wu Hui Feng Di Wu Shijuan Yan Pei Zhang Wenbin Wang Jun Zhang Junli Ye Guoxin Dai Yuan Fan Weikun Li Baoxing Song Zedong Geng Wanli Yang Guoxin Chen Feng Qin William Terzaghi Michelle Stitzer Lin Li Lizhong Xiong Jianbing Yan Edward Buckler Wanneng Yang Mingqiu Dai Using high-throughput multiple optical phenotyping to decipher the genetic architecture of maize drought tolerance Genome Biology |
| author_facet |
Xi Wu Hui Feng Di Wu Shijuan Yan Pei Zhang Wenbin Wang Jun Zhang Junli Ye Guoxin Dai Yuan Fan Weikun Li Baoxing Song Zedong Geng Wanli Yang Guoxin Chen Feng Qin William Terzaghi Michelle Stitzer Lin Li Lizhong Xiong Jianbing Yan Edward Buckler Wanneng Yang Mingqiu Dai |
| author_sort |
Xi Wu |
| title |
Using high-throughput multiple optical phenotyping to decipher the genetic architecture of maize drought tolerance |
| title_short |
Using high-throughput multiple optical phenotyping to decipher the genetic architecture of maize drought tolerance |
| title_full |
Using high-throughput multiple optical phenotyping to decipher the genetic architecture of maize drought tolerance |
| title_fullStr |
Using high-throughput multiple optical phenotyping to decipher the genetic architecture of maize drought tolerance |
| title_full_unstemmed |
Using high-throughput multiple optical phenotyping to decipher the genetic architecture of maize drought tolerance |
| title_sort |
using high-throughput multiple optical phenotyping to decipher the genetic architecture of maize drought tolerance |
| publisher |
BMC |
| series |
Genome Biology |
| issn |
1474-760X |
| publishDate |
2021-06-01 |
| description |
Abstract Background Drought threatens the food supply of the world population. Dissecting the dynamic responses of plants to drought will be beneficial for breeding drought-tolerant crops, as the genetic controls of these responses remain largely unknown. Results Here we develop a high-throughput multiple optical phenotyping system to noninvasively phenotype 368 maize genotypes with or without drought stress over a course of 98 days, and collected multiple optical images, including color camera scanning, hyperspectral imaging, and X-ray computed tomography images. We develop high-throughput analysis pipelines to extract image-based traits (i-traits). Of these i-traits, 10,080 were effective and heritable indicators of maize external and internal drought responses. An i-trait-based genome-wide association study reveals 4322 significant locus-trait associations, representing 1529 quantitative trait loci (QTLs) and 2318 candidate genes, many that co-localize with previously reported maize drought responsive QTLs. Expression QTL (eQTL) analysis uncovers many local and distant regulatory variants that control the expression of the candidate genes. We use genetic mutation analysis to validate two new genes, ZmcPGM2 and ZmFAB1A, which regulate i-traits and drought tolerance. Moreover, the value of the candidate genes as drought-tolerant genetic markers is revealed by genome selection analysis, and 15 i-traits are identified as potential markers for maize drought tolerance breeding. Conclusion Our study demonstrates that combining high-throughput multiple optical phenotyping and GWAS is a novel and effective approach to dissect the genetic architecture of complex traits and clone drought-tolerance associated genes. |
| url |
https://doi.org/10.1186/s13059-021-02377-0 |
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doaj-f5985e14b7f14adda4aa409420da0b442021-06-27T11:46:32ZengBMCGenome Biology1474-760X2021-06-0122112610.1186/s13059-021-02377-0Using high-throughput multiple optical phenotyping to decipher the genetic architecture of maize drought toleranceXi Wu0Hui Feng1Di Wu2Shijuan Yan3Pei Zhang4Wenbin Wang5Jun Zhang6Junli Ye7Guoxin Dai8Yuan Fan9Weikun Li10Baoxing Song11Zedong Geng12Wanli Yang13Guoxin Chen14Feng Qin15William Terzaghi16Michelle Stitzer17Lin Li18Lizhong Xiong19Jianbing Yan20Edward Buckler21Wanneng Yang22Mingqiu Dai23National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, and Hubei Key Laboratory of Agricultural Bioinformatics, Huazhong Agricultural UniversityNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, and Hubei Key Laboratory of Agricultural Bioinformatics, Huazhong Agricultural UniversityNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, and Hubei Key Laboratory of Agricultural Bioinformatics, Huazhong Agricultural UniversityGuangdong Academy of Agricultural SciencesNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, and Hubei Key Laboratory of Agricultural Bioinformatics, Huazhong Agricultural UniversityNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, and Hubei Key Laboratory of Agricultural Bioinformatics, Huazhong Agricultural UniversityNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, and Hubei Key Laboratory of Agricultural Bioinformatics, Huazhong Agricultural UniversityNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, and Hubei Key Laboratory of Agricultural Bioinformatics, Huazhong Agricultural UniversityNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, and Hubei Key Laboratory of Agricultural Bioinformatics, Huazhong Agricultural UniversityNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, and Hubei Key Laboratory of Agricultural Bioinformatics, Huazhong Agricultural UniversityNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, and Hubei Key Laboratory of Agricultural Bioinformatics, Huazhong Agricultural UniversitySchool of Integrative Plant Sciences, Section of Plant Breeding and Genetics, Cornell UniversityNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, and Hubei Key Laboratory of Agricultural Bioinformatics, Huazhong Agricultural UniversityNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, and Hubei Key Laboratory of Agricultural Bioinformatics, Huazhong Agricultural UniversityNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, and Hubei Key Laboratory of Agricultural Bioinformatics, Huazhong Agricultural UniversityState Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China Agricultural UniversityDepartment of Biology, Wilkes UniversitySchool of Integrative Plant Sciences, Section of Plant Breeding and Genetics, Cornell UniversityNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, and Hubei Key Laboratory of Agricultural Bioinformatics, Huazhong Agricultural UniversityNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, and Hubei Key Laboratory of Agricultural Bioinformatics, Huazhong Agricultural UniversityNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, and Hubei Key Laboratory of Agricultural Bioinformatics, Huazhong Agricultural UniversitySchool of Integrative Plant Sciences, Section of Plant Breeding and Genetics, Cornell UniversityNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, and Hubei Key Laboratory of Agricultural Bioinformatics, Huazhong Agricultural UniversityNational Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, and Hubei Key Laboratory of Agricultural Bioinformatics, Huazhong Agricultural UniversityAbstract Background Drought threatens the food supply of the world population. Dissecting the dynamic responses of plants to drought will be beneficial for breeding drought-tolerant crops, as the genetic controls of these responses remain largely unknown. Results Here we develop a high-throughput multiple optical phenotyping system to noninvasively phenotype 368 maize genotypes with or without drought stress over a course of 98 days, and collected multiple optical images, including color camera scanning, hyperspectral imaging, and X-ray computed tomography images. We develop high-throughput analysis pipelines to extract image-based traits (i-traits). Of these i-traits, 10,080 were effective and heritable indicators of maize external and internal drought responses. An i-trait-based genome-wide association study reveals 4322 significant locus-trait associations, representing 1529 quantitative trait loci (QTLs) and 2318 candidate genes, many that co-localize with previously reported maize drought responsive QTLs. Expression QTL (eQTL) analysis uncovers many local and distant regulatory variants that control the expression of the candidate genes. We use genetic mutation analysis to validate two new genes, ZmcPGM2 and ZmFAB1A, which regulate i-traits and drought tolerance. Moreover, the value of the candidate genes as drought-tolerant genetic markers is revealed by genome selection analysis, and 15 i-traits are identified as potential markers for maize drought tolerance breeding. Conclusion Our study demonstrates that combining high-throughput multiple optical phenotyping and GWAS is a novel and effective approach to dissect the genetic architecture of complex traits and clone drought-tolerance associated genes.https://doi.org/10.1186/s13059-021-02377-0 |