Association analysis for seed yield, forage yield and traits related to drought tolerance in orchardgrass (Dactylis glomerata)

Abstract

Polycross designs bridge the two usual mapping approaches (bi-parental mapping and association analysis) and increase mapping power by incorporating greater genetic diversity. In this study, we used diverse genotypes selected from polycrossed progenies to identify marker loci associated with a set of seed- and forage-related traits as well as drought tolerance in orchardgrass (Dactylis glomerata L.). Associations were estimated between phenotypic traits and 923 DNA markers (including 446 inter-simple sequence repeats and 477 sequence-related amplified polymorphism markers). Positive relationship was found between forage yield and seed yield under normal and water-stress conditions, indicating that simultaneous improvement of seed and forage yield could be achieved in orchardgrass. The results of population structure analysis identified five main subpopulations possessing significant genetic differences. Under normal and water-stress conditions, respectively, 341 and 359 markers were significantly associated with the studied traits. Most of these markers were associated with more than one trait. Water-environment specificity of trait-associated markers indicates that genotype × environment interactions influence association analysis. However, 75 stable associations were identified across two moisture conditions for traits such as seed and forage yield. Marker–trait association revealed that markers M1/E1-5, M2/E6-5, M3/E4-6, P14-7 and P845-7 were consistently linked with drought-tolerance index. The identified marker alleles associated with multiple traits across environments may be considered for further analysis for their chromosome locations, the corresponding sequences and their potential functions.

Marker-trait association analysis for drought tolerance in smooth bromegrass

“…Based on the results of GLM and MLM models, some markers had simultaneously signi cant associations with more than one trait. These markers may be effectively used for the improvement of several traits, concurrently [33,34]. Multi-association among different traits could be attributed to the coexpression mediated by expression of quantitative trait loci or e-QTLs [48].…”

Marker-trait association analysis for drought tolerance in smooth bromegrass

“…Based on the results of GLM and MLM models, some markers had simultaneously significant associations with more than one trait. These markers may be effectively used for the improvement of several traits, concurrently [33,34]. Multi-association among different traits could be ascribed to coexpression mediated by expression of quantitative trait loci or e-QTLs [49].…”

Genome-wide association study revealed loci linked to post-drought recovery and traits related to persistence of smooth bromegrass (Bromus inermis)

“…Based on the results, some markers had simultaneously significant associations with more than one trait and may be effectively used for the improvement of several traits, concurrently (Sun et al ., 2015; Abtahi et al ., 2018b). Association between multiple traits could be attributed to the co-expression mediated by expression of quantitative trait loci or e-QTLs (House et al ., 2014).…”

“…In recent years, association analysis in forage grasses is applied extensively for dissecting the genetic bases of different quantitative traits in several species such as perennial ryegrass ( Lolium perenne ) (Auzanneau et al ., 2011; Yu et al ., 2011; Tang et al ., 2013; Yu et al ., 2013), tall fescue ( Festuca arundinacea ) (Lou et al ., 2015; Sun et al ., 2015), and orchardgrass ( Dactylis glomerata L.) (Yan et al ., 2016; Zhao et al ., 2017; Abtahi et al ., 2018b). These studies have demonstrated that GWAS is an efficient technique for identifying genomic regions linked to the quantitative traits.…”