Identification of SNP loci and candidate genes related to four important fatty acid composition in Brassica napus using genome wide association study

Abstract

Rapeseed oil (canola, Brassica napus L.) is an important healthy vegetable oil throughout the world, the nutritional and economical value of which largely depends on its seed fatty acid composition. In this study, based on 201,187 SNP markers developed from the SLAF-seq (specific locus amplified fragment sequencing), a genome wide association study of four important fatty acid content traits (erucic acid, oleic acid, linoleic acid and linolenic acid) in a panel of 300 inbred lines of rapeseed in two environments (JXAU and JXRIS) was carried out. A total of 148 SNP loci significantly associated with these traits were detected by MLM model analysis respectively, and 30 SNP loci on A08 and C03 chromosomes were detected in three traits of erucic acid, oleic acid and linoleic acid contents simultaneously. Furthermore, 108 highly favorable alleles for increasing oleic acid and linoleic acid content, also for decreasing erucic acid content simultaneously were observed. By a basic local alignment search tool (BLAST) search with in a distance of 100 Kb around these significantly SNP-trait associations, we identified 20 orthologs of the functional candidate genes related to fatty acid biosynthesis, including the known vital fatty acid biosynthesis genes of BnaA . FAE1 and BnaC . FAE1 on the A08 and C03 chromosomes, and other potential candidate genes involving in the fatty acid biosynthesis pathway, such as the orthologs genes of FAD2 , LACS09 , KCS17 , CER4 , TT16 and ACBP5 . This study lays a basis for uncovering the genetic variations and the improvement of fatty acid composition in B . napus .

Genetic Characterization of Russian Rapeseed Collection and Association Mapping of Novel Loci Affecting Glucosinolate Content

“…To find new candidate genes that potentially contribute to the control of glucosinolate content, we studied the annotation of genes located 100 kb upstream and downstream of the significant SNPs. Such threshold was selected since, first, it was previously used in the similar studies in rapeseed [ 7 , 52 , 53 ]. Second, more than 30% of SNP pairs located within the 100 kb frame demonstrated the r 2 value of more than 0.25 ( Figure 2 B).…”

“…Rapeseed genome is sequenced and annotated [3,4], which makes it a perfect model organism to study genetic diversity and to reveal the genetic bases of complex phenotype traits on a genome-wide scale with high resolution. Thus, a number of studies have been performed in order to find genetic associations for the agronomically important traits related to oil quality, plant productivity and architecture, and resistance to unfavorable environmental conditions by means of the modern genotyping approaches in rapeseed [5][6][7]. In addition, several studies were focused on the description of genetic diversity, evolution, domestication footprints, and population structure of the rapeseed [8][9][10][11][12].…”

Innovative Strategies to Develop Abiotic and Biotic Stress Tolerance in Mustard (Brassicaceae)

“…In various crops, QTLs were recognized for a several beneficial agronomic traits, such as enhancing abiotic and biotic stress tolerance, yield and yield contributing factors of the crop, flowering time, root development and uptake of nutrients and nitrogen fixation. Molecular markers linked with various agronomic traits derived from association mapping are reported in crops including soybean [35] and brassica [36,37]. Lu et al reported that resequencing of 588 Brassica napus accessions from 21 countries has generated 5,294,158 (single nucleotide polymorphisms) SNPsand 1,307,151 indels.…”

Breeding and biotechnological interventions for trait improvement: status and prospects

“…For genotyping, restriction-site associated sequencing (RAD-Seq), genotyping-by-sequencing (GBS), skim-sequencing, and whole-genome resequencing approach are being exploited for mid to high-density trait mapping through QTL-based analysis (Roorkiwal et al 2020 ). Molecular markers linked with various agronomic traits derived from association mapping are reported in crops including soybean (Hu et al 2014 ), brassica (Qu et al 2017 ; Zhu et al 2019 ), rice (Feng et al 2016 ; Rao et al 2018 ), chickpea (Bajaj et al 2016 ; Li et al 2018 ), foxtail millet (Jaiswal et al 2019a , b ) and various others plants (reviewed by Muthamilarasan et al 2019 ). In plants, QTLs were mostly identified for a variety of agronomic traits, including abiotic and biotic stress tolerance, yield and yield contributing factors, flowering time, root architecture and nutrient uptake, and nitrogen fixation (in case of soybean).…”