Focusing the GWASLenson days to flower using latent variable phenotypes derived from global multi-environment trials

Abstract

Adaptation constraints within crop species have resulted in limited genetic diversity in some breeding programs and/or areas where new crops have been introduced, e.g., lentil (Lens culinaris Medik.) in North America. An improved understanding of the underlying genetics involved in phenology-related traits is valuable knowledge to aid breeders in overcoming limitations associated with unadapted germplasm and expanding their genetic diversity by introducing new, exotic material. We used a large, 18 site-year, multi-environment dataset, phenotyped for phenology-related traits across nine locations and over three years, along with accompanying latent variable phenotypes derived from a photothermal model and principal component analysis (PCA) of days from sowing to flower (DTF) data for a lentil diversity panel (324 accessions) which has also been genotyped with an exome capture array. Genome-wide association studies (GWAS) on DTF across multiple environments helped confirm associations with known flowering time genes and identify new quantitative trait loci (QTL), which may contain previously unknown flowering time genes. Additionally, the use of latent variable phenotypes, which can incorporate environmental data such as temperature and photoperiod as both GWAS traits and as covariates, strengthened associations, revealed additional hidden associations, and alluded to potential roles of the associated QTL. Our approach can be replicated with other crop species, and the results from our GWAS serve as a resource for further exploration into the complex nature of phenology-related traits across the major growing environments for cultivated lentil.

Genome-wide association study as a powerful tool for dissecting competitive traits in legumes

“…Abiotic stress tolerance SNP (Zou et al, 2020) Chickpea Agronomic traits SNP (Bajaj et al, 2015a;Bajaj et al, 2016;Kujur et al, 2015a;Upadhyaya et al, 2015;Upadhyaya et al, 2017;Basu et al, 2018;Orsak et al, 2019;Fayaz et al, 2022;Srungarapu et al, 2022) Abiotic stress tolerance SNP (Thudi et al, 2014;Kohli et al, 2020;Ahmed et al, 2021;Kalve et al, 2022) Physiological traits SNP (Basu et al, 2019) Quality traits (Upadhyaya et al, 2016a;Upadhyaya et al, 2016b;Parida et al, 2017;Samineni et al, 2022) Biotic stress resistance (Li et al, 2017;Agarwal et al, 2019;Agarwal et al, 2022;Farahani et al, 2022;Raman et al, 2022) Beans Agronomic traits/ Quality SNP (Warsame et al, 2019;Rasool et al, 2022) Abiotic stress SNP (Ali et al, 2016;Li et al, 2017;Hu et al, 2019b;Breria et al, 2020;Abou-Khater et al, 2022;Maalouf et al, 2022;Sallam et al, 2022) Biotic stress SNP (Faridi et al, 2021) Lentils Agronomic traits SNP, SSR (Kumar et al, 2018a;Kumar et al, 2018b;Singh et al, 2019;Karthika et al, 2021;Neupane et al, 2022) Quality traits, Seed quality SNP (Khazaei et al, 2017;…”