Association Mapping for Fiber-Related Traits and Digestibility in Alfalfa (Medicago sativa)

Abstract

Association mapping is a powerful approach for exploring the molecular genetic basis of complex quantitative traits. An alfalfa (Medicago sativa) association panel comprised of 336 genotypes from 75 alfalfa accessions represented by four to eight genotypes for each accession. Each genotype was genotyped using 85 simple sequence repeat (SSR) markers and phenotyped for five fiber-related traits in four different environments. A model-based structure analysis was used to group all genotypes into two groups. Most of the genotypes have a low relative kinship (<0.3), suggesting population stratification not be an issue for association analysis. Generally, the Q + K model exhibited the best performance to eliminate the false associated positives. In total, 124 marker-trait associations were predicted (p < 0.005). Among these, eight associations were predicted in two environments repeatedly and 20 markers were predicted to be associated with multiple traits. These trait-associated markers will greatly help marker-assisted breeding programs to improve fiber-related quality traits in alfalfa.

Identification of QTLs for high grain yield and component traits in New Plant Types of rice

“…The value of p is in agreement with previous reports [71,72,79,86]. However, some researchers reported their results at p<0.05-0.01 value, which is much higher compared to our study, where the number of markers is appreciably high [44, 71].…”

“…The 60 genotypes were differentiated into four sub-populations at K=4, i.e., POP1, POP2, POP3, and POP4. Similar sample sizes were used by several researchers in association analysis in rice [69, 70] and alfalfa [71]. The UPGMA cluster analysis grouped 60 genotypes into two major groups at 54 % of genetic similarity.…”

“…GLM model used to have more false positive association as compared to MLM model analysis [20,42,71,78,79]. It does not consider to influence the population structure and kinship [71, 80]. MLM model has higher accuracy and a smaller number of spurious marker-trait association with genotypes as compared to GLM model.…”

“…In association mapping, mixed model (Q+K) showed a significant improvement in goodness of fit and reducing spurious associations. The K and Q matrix corrected the association between eleven phenotypic traits with markers [44, 71] at permutation value is 1000 at p<0.005 for GLM and MLM for the level of significance. In association mapping, p-value plays an essential role because it controls over the level of false-positive association between traits and markers.…”

Harnessing the Potential of Forage Legumes, Alfalfa, Soybean, and Cowpea for Sustainable Agriculture and Global Food Security

“…Therefore, this approach has increasingly been favored in identifying chromosomal loci controlling a particular phenotype expression under certain environmental conditions. In the last few years, several association mapping studies have been conducted using diploid or tetraploid alfalfa breeding populations to identify marker-trait associations for biomass yield and stem composition ( Li et al, 2011 ; Sakiroglu et al, 2012 ), fiber-related traits and digestibility ( Wang et al, 2016a ), and CP concentrations ( Jia et al, 2017 ) ( Table 2 ).…”