Single Nucleotide Polymorphism Markers Associated with Seed Quality Characteristics of Cultivated Lentil

Abstract

The dimensions of lentil ( Medik.) seeds are important quality parameters that are major determinants of market preference, cooking time, and post-harvest milling quality. Knowledge of the genetic control of traits related to seed dimensions would be useful for crop improvement. The principal aim of this study was to identify single nucleotide polymorphism (SNP) markers linked to genes that control seed diameter, seed thickness, and seed plumpness. Association mapping analysis with SNP markers was used to study the seed dimensions of 138 diverse cultivated lentil accessions grown at two locations in Saskatchewan, Canada, in 2011 and 2012. Six marker-trait associations were shown to be significant for the studied seed dimension characteristics. Two SNP markers closely associated with seed diameter across locations and years identified in previous work were validated in this study. Three additional marker-seed thickness associations were identified. Using the association mapping strategy, we confirmed the presence of two genomic regions controlling seed diameter and plumpness. This information can be used worldwide as a resource for lentil seed quality improvement programs.

Construction of a high-density interspecific (Lens culinaris x L. odemensis) genetic map based on functional markers for mapping morphological and agronomical traits, and QTLs affecting resistance to Ascochyta in lentil

“…One of the Yc flanking markers was LcC17238p3606 that is located in position 202,217,501 of LcChr1. Using association mapping analysis with SNP makers of 138 cultivated lentil accessions, Khazaei et al [88] validated two SNPs closely associated to the seed diameter trait, located in LcChr7 and LcChr1 which respectively explained 11% and 14% of the observed variation. The location of the SNP in LcChr1 (212,502,660) is relatively close to the Yc linked marker reported by Fedoruk et al [37] and to one of the markers included in the support interval of the QTL detected in LG1 (163,405,141) of the Lc x Lo -map, with 242 genes annotated between them.…”

Genotyping by Sequencing of Cultivated Lentil (Lens culinaris Medik.) Highlights Population Structure in the Mediterranean Gene Pool Associated With Geographic Patterns and Phenotypic Variables

“…Five significant associations were found, and, in addition, the same marker was found to be associated with all the traits related to seed size ( Supplementary Table S6 ), indicating correlation among traits. The upcoming public release of the lentil genome sequence will allow to relate markers with specific genomic regions and verify whether these regions overlap with quantitative trait loci previously characterized for seed size (Fedoruk et al, 2013; Verma et al, 2015; Khazaei et al, 2018).…”

“…Following the advent of next-generation sequencing technologies, single nucleotide polymorphism (SNP) markers have been used in lentil to describe genetic variation of germplasm collections and link-specific markers to phenotypic traits, including seed quality, disease resistance, and micronutrient concentration (Lombardi et al, 2014; Sudheesh et al, 2016; Khazaei et al, 2016; Khazaei et al, 2017; Khazaei et al, 2018). A comprehensive investigation of lentil genetic structure identified three distinct clusters, broadly reflecting three world’s agro-ecological zones: Mediterranean Basin (also including the Nile valley from Egypt to Ethiopia), subtropical Asia, and northern temperate (Khazaei et al, 2016).…”

Identification of anthracnose (Colletotrichum lentis) race 1 resistance loci in lentil by integrating linkage mapping and a genome-wide association study

“…Integration of QTL mapping in biparental populations and GWAS provides the technology to identify trait loci associated with resistance while refining the genomic regions with high resolution (Zhu et al, 2008). Both mapping strategies have been successfully used to identify QTL for multiple traits in lentil (biparental: Fedoruk et al, 2013, Ates et al, 2016; Aldemir et al, 2017; Subedi et al, 2018; Sari et al, 2018; Polanco et al, 2019; and GWAS: Khazaei et al, 2018; Kumar et al, 2018; Kumar et al, 2019).…”