A genome‐wide association study approach to the identification of candidate genes underlying agronomic traits in alfalfa ( Medicago sativa L.)

Zan Wang, Xuemin Wang, Han Zhang, Lin Ma, Haiming Zhao, Chris Stephen Jones, Jin Chen, Guibo Liu
2019 Plant Biotechnology Journal  
Alfalfa (Medicago sativa L.) is one of the most important forage legume crops for hay and silage production worldwide (Li and Brummer, 2012) . Understanding the genetic basis underlying its agronomic performance will provide critical molecular insights in support of alfalfa breeding. Alfalfa is a tetraploid, perennial, open pollinated legume with a high level of heterozygosity, which increases the complexity of the genetics required to support plant breeding. Genotyping-by-sequencing
more » ... genome-wide association studies (GWAS), which utilize genetically diverse accessions, offer an alternative to QTL mapping with biparental mapping populations (Flint-Garcia et al., 2003) and are particularly suitable for orphan crop species, even those without reference genomes. In the present study, we applied the GWAS approach to a collection of 322 alfalfa genotypes of diverse geographic origin to investigate marker-trait associations for nine agronomic traits characterized across three consecutive years. Phenotypic data analysis revealed that all nine traits were significantly influenced by genotype and were of varying degrees of heritability. A total of 115 654 high-quality single nucleotide polymorphisms (SNPs) were identified, and 44 757 SNPs (38.7%) were uniquely and physically mapped onto the M. truncatula reference genome with an average map density of 8.8 kilobases. Population structure on 322 alfalfa genotypes based on these SNPs with a minor allele frequency > 5% in multiple analyses (STRUCTURE, PCoA and phylogenetic trees) showed that the genotypes from China were distinct from those collected from the other regions of the world. The best linear unbiased prediction (BLUP) values of each genotype for nine agronomic traits were used as phenotypic values for GWAS. GWAS were conducted in the mixed linear model using TASSEL 5.0. For the nine agronomic traits, plant height, plant branching, number of stem nodes, first inflorescence position, biomass yield, leaf to stem ratio, plant regrowth, flowering date and plant height in the fall, a total of 42 putative significant marker-trait associations (MTAs) were detected (P < 1/ 44757 % 2.23 9 10 À5 ) with at least one MTA identified for each trait except for biomass yield. To identify the candidate genes associated with the significant loci based on a GWAS, we performed a pairwise alignment using the flanking sequences of the significant SNP loci against the M. truncatula reference genome sequences (Mt4.0 V1) and NCBI nucleotide acid databases.
doi:10.1111/pbi.13251 pmid:31487419 fatcat:h5attqcenja6nehoqssojxothy