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CUBIC: an atlas of genetic architecture promises directed maize improvement

BACKGROUND: Identifying genotype-phenotype links and causative genes from quantitative trait loci (QTL) is challenging for complex agronomically important traits. To accelerate maize gene discovery and breeding, we present the Complete-diallel design plus Unbalanced Breeding-like Inter-Cross (CUBIC)...

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Autores principales: Liu, Hai-Jun, Wang, Xiaqing, Xiao, Yingjie, Luo, Jingyun, Qiao, Feng, Yang, Wenyu, Zhang, Ruyang, Meng, Yijiang, Sun, Jiamin, Yan, Shijuan, Peng, Yong, Niu, Luyao, Jian, Liumei, Song, Wei, Yan, Jiali, Li, Chunhui, Zhao, Yanxin, Liu, Ya, Warburton, Marilyn L., Zhao, Jiuran, Yan, Jianbing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6979394/
https://www.ncbi.nlm.nih.gov/pubmed/31980033
http://dx.doi.org/10.1186/s13059-020-1930-x
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author Liu, Hai-Jun
Wang, Xiaqing
Xiao, Yingjie
Luo, Jingyun
Qiao, Feng
Yang, Wenyu
Zhang, Ruyang
Meng, Yijiang
Sun, Jiamin
Yan, Shijuan
Peng, Yong
Niu, Luyao
Jian, Liumei
Song, Wei
Yan, Jiali
Li, Chunhui
Zhao, Yanxin
Liu, Ya
Warburton, Marilyn L.
Zhao, Jiuran
Yan, Jianbing
author_facet Liu, Hai-Jun
Wang, Xiaqing
Xiao, Yingjie
Luo, Jingyun
Qiao, Feng
Yang, Wenyu
Zhang, Ruyang
Meng, Yijiang
Sun, Jiamin
Yan, Shijuan
Peng, Yong
Niu, Luyao
Jian, Liumei
Song, Wei
Yan, Jiali
Li, Chunhui
Zhao, Yanxin
Liu, Ya
Warburton, Marilyn L.
Zhao, Jiuran
Yan, Jianbing
author_sort Liu, Hai-Jun
collection PubMed
description BACKGROUND: Identifying genotype-phenotype links and causative genes from quantitative trait loci (QTL) is challenging for complex agronomically important traits. To accelerate maize gene discovery and breeding, we present the Complete-diallel design plus Unbalanced Breeding-like Inter-Cross (CUBIC) population, consisting of 1404 individuals created by extensively inter-crossing 24 widely used Chinese maize founders. RESULTS: Hundreds of QTL for 23 agronomic traits are uncovered with 14 million high-quality SNPs and a high-resolution identity-by-descent map, which account for an average of 75% of the heritability for each trait. We find epistasis contributes to phenotypic variance widely. Integrative cross-population analysis and cross-omics mapping allow effective and rapid discovery of underlying genes, validated here with a case study on leaf width. CONCLUSIONS: Through the integration of experimental genetics and genomics, our study provides useful resources and gene mining strategies to explore complex quantitative traits.
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spelling pubmed-69793942020-01-29 CUBIC: an atlas of genetic architecture promises directed maize improvement Liu, Hai-Jun Wang, Xiaqing Xiao, Yingjie Luo, Jingyun Qiao, Feng Yang, Wenyu Zhang, Ruyang Meng, Yijiang Sun, Jiamin Yan, Shijuan Peng, Yong Niu, Luyao Jian, Liumei Song, Wei Yan, Jiali Li, Chunhui Zhao, Yanxin Liu, Ya Warburton, Marilyn L. Zhao, Jiuran Yan, Jianbing Genome Biol Research BACKGROUND: Identifying genotype-phenotype links and causative genes from quantitative trait loci (QTL) is challenging for complex agronomically important traits. To accelerate maize gene discovery and breeding, we present the Complete-diallel design plus Unbalanced Breeding-like Inter-Cross (CUBIC) population, consisting of 1404 individuals created by extensively inter-crossing 24 widely used Chinese maize founders. RESULTS: Hundreds of QTL for 23 agronomic traits are uncovered with 14 million high-quality SNPs and a high-resolution identity-by-descent map, which account for an average of 75% of the heritability for each trait. We find epistasis contributes to phenotypic variance widely. Integrative cross-population analysis and cross-omics mapping allow effective and rapid discovery of underlying genes, validated here with a case study on leaf width. CONCLUSIONS: Through the integration of experimental genetics and genomics, our study provides useful resources and gene mining strategies to explore complex quantitative traits. BioMed Central 2020-01-24 /pmc/articles/PMC6979394/ /pubmed/31980033 http://dx.doi.org/10.1186/s13059-020-1930-x Text en © The Author(s). 2020 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Liu, Hai-Jun
Wang, Xiaqing
Xiao, Yingjie
Luo, Jingyun
Qiao, Feng
Yang, Wenyu
Zhang, Ruyang
Meng, Yijiang
Sun, Jiamin
Yan, Shijuan
Peng, Yong
Niu, Luyao
Jian, Liumei
Song, Wei
Yan, Jiali
Li, Chunhui
Zhao, Yanxin
Liu, Ya
Warburton, Marilyn L.
Zhao, Jiuran
Yan, Jianbing
CUBIC: an atlas of genetic architecture promises directed maize improvement
title CUBIC: an atlas of genetic architecture promises directed maize improvement
title_full CUBIC: an atlas of genetic architecture promises directed maize improvement
title_fullStr CUBIC: an atlas of genetic architecture promises directed maize improvement
title_full_unstemmed CUBIC: an atlas of genetic architecture promises directed maize improvement
title_short CUBIC: an atlas of genetic architecture promises directed maize improvement
title_sort cubic: an atlas of genetic architecture promises directed maize improvement
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6979394/
https://www.ncbi.nlm.nih.gov/pubmed/31980033
http://dx.doi.org/10.1186/s13059-020-1930-x
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