Neupane Sandesh, Wright Derek M, Martinez Raul O, Butler Jakob, Weller James L, Bett Kirstin E
Dep. of Plant Sciences, Univ. of Saskatchewan, Saskatoon, SK, S7N 5A8, Canada.
School of Natural Sciences, Univ. of Tasmania, Hobart, TAS, 7001, Australia.
Plant Genome. 2023 Mar;16(1):e20269. doi: 10.1002/tpg2.20269. Epub 2022 Oct 25.
Adaptation constraints within crop species have resulted in limited genetic diversity in some breeding programs and areas where new crops have been introduced, for example, for 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, multienvironment dataset phenotyped for phenology-related traits across nine locations and over 3 yr 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.
作物品种内部的适应性限制导致了一些育种计划以及新作物引入地区的遗传多样性有限，例如在北美的小扁豆（Lens culinaris Medik.）种植中。更好地理解物候相关性状背后的遗传学，对于帮助育种者克服与未适应种质相关的限制，并通过引入新的外来材料扩大其遗传多样性具有重要意义。我们使用了一个大型的、包含18个地点 - 年份的多环境数据集，该数据集对九个地点超过3年的物候相关性状进行了表型分析，同时还有从光热模型和主成分分析（PCA）得出的潜在变量表型，这些分析基于一个小扁豆多样性面板（324份种质）从播种到开花的天数（DTF）数据，该面板也已通过外显子捕获阵列进行了基因分型。对多个环境下的DTF进行全基因组关联研究（GWAS），有助于确认与已知开花时间基因的关联，并鉴定新的数量性状位点（QTL），这些QTL可能包含以前未知的开花时间基因。此外，使用潜在变量表型，既可以将温度和光周期等环境数据纳入GWAS性状，也可以作为协变量，这加强了关联，揭示了额外的隐藏关联，并暗示了相关QTL的潜在作用。我们的方法可以应用于其他作物品种，我们GWAS的结果为进一步探索栽培小扁豆主要生长环境中物候相关性状的复杂本质提供了资源。
