TY - JOUR
T1 - Trends of genetic changes uncovered by Env- and Eigen-GWAS in wheat and barley
AU - Sharma, Rajiv
AU - Cockram, James
AU - Gardner, Keith A.
AU - Russell, Joanne
AU - Ramsay, Luke
AU - Thomas, William T. B.
AU - O'Sullivan, Donal M.
AU - Powell, Wayne
AU - Mackay, Ian J.
N1 - Funding Information:
This project was part funded by projects IMPROMALT BB/K/0070251/1 and WAGTAIL BB/J002542/1, jointly funded by the BBSRC and UK wheat and barley breeders and by direct funding of Rajiv Sharma from SRUC. We thank Mark Looseley and Hazel Bull (JHI), for sharing the genotypic data set of the barley varieties analysed here, as well as Chin Jian Yang, Ian Dawson and David Marshall (SRUC) for helpful discussion throughout the work.
Publisher Copyright:
© 2021, The Author(s).
PY - 2022/2
Y1 - 2022/2
N2 - The process of crop breeding over the last century has delivered new varieties with increased genetic gains, resulting in higher crop performance and yield. However, in many cases, the alleles and genomic regions underpinning this success remain unknown. This is partly due to the difficulty of generating sufficient phenotypic data on large numbers of historical varieties to enable such analyses. Here we demonstrate the ability to circumvent such bottlenecks by identifying genomic regions selected over 100 years of crop breeding using age of a variety as a surrogate for yield. Rather than collecting phenotype data, we deployed ‘environmental genome-wide association scans’ (EnvGWAS) based on variety age in two of the world’s most important crops, wheat and barley, and detected strong signals of selection across both genomes. EnvGWAS identified 16 genomic regions in barley and 10 in wheat with contrasting patterns between spring and winter types of the two crops. To further examine changes in genome structure, we used the genomic relationship matrix of the genotypic data to derive eigenvectors for analysis in EigenGWAS. This detected seven major chromosomal introgressions that contributed to adaptation in wheat. EigenGWAS and EnvGWAS based on variety age avoid costly phenotyping and facilitate the identification of genomic tracts that have been under selection during breeding. Our results demonstrate the potential of using historical cultivar collections coupled with genomic data to identify chromosomal regions under selection and may help guide future plant breeding strategies to maximise the rate of genetic gain and adaptation.
AB - The process of crop breeding over the last century has delivered new varieties with increased genetic gains, resulting in higher crop performance and yield. However, in many cases, the alleles and genomic regions underpinning this success remain unknown. This is partly due to the difficulty of generating sufficient phenotypic data on large numbers of historical varieties to enable such analyses. Here we demonstrate the ability to circumvent such bottlenecks by identifying genomic regions selected over 100 years of crop breeding using age of a variety as a surrogate for yield. Rather than collecting phenotype data, we deployed ‘environmental genome-wide association scans’ (EnvGWAS) based on variety age in two of the world’s most important crops, wheat and barley, and detected strong signals of selection across both genomes. EnvGWAS identified 16 genomic regions in barley and 10 in wheat with contrasting patterns between spring and winter types of the two crops. To further examine changes in genome structure, we used the genomic relationship matrix of the genotypic data to derive eigenvectors for analysis in EigenGWAS. This detected seven major chromosomal introgressions that contributed to adaptation in wheat. EigenGWAS and EnvGWAS based on variety age avoid costly phenotyping and facilitate the identification of genomic tracts that have been under selection during breeding. Our results demonstrate the potential of using historical cultivar collections coupled with genomic data to identify chromosomal regions under selection and may help guide future plant breeding strategies to maximise the rate of genetic gain and adaptation.
UR - http://www.scopus.com/inward/record.url?scp=85119292925&partnerID=8YFLogxK
U2 - 10.1007/s00122-021-03991-z
DO - 10.1007/s00122-021-03991-z
M3 - Article
C2 - 34778903
SN - 0040-5752
VL - 135
SP - 667
EP - 678
JO - Theoretical and Applied Genetics
JF - Theoretical and Applied Genetics
ER -