AUTHOR=Bhinder Gurleen , Sharma Sanjula , Kaur Harjeevan , Akhatar Javed , Mittal Meenakshi , Sandhu Surinder 

TITLE=Genomic Regions Associated With Seed Meal Quality Traits in Brassica napus Germplasm

JOURNAL=Frontiers in Plant Science

VOLUME=13

YEAR=2022

URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2022.882766

DOI=10.3389/fpls.2022.882766

ISSN=1664-462X

ABSTRACT=<p>The defatted <italic>Brassica napus</italic> (rapeseed) meal can be high-protein feed for livestock as the protein value of rapeseed meal is higher than that of the majority of other vegetable proteins. Extensive work has already been carried out on developing canola rapeseed where the focus was on reducing erucic acid and glucosinolate content, with less consideration to other antinutritional factors such as tannin, phytate, sinapine, crude fiber, etc. The presence of these antinutrients limits the use and marketing of rapeseed meals and a significant amount of it goes unused and ends up as waste. We investigated the genetic architecture of crude protein, methionine, tryptophan, total phenols, β-carotene, glucosinolates (GLSs), phytate, tannins, sinapine, and crude fiber content of defatted seed meal samples by conducting a genome-wide association study (GWAS), using a diversity panel comprising 96 <italic>B. napus</italic> genotypes. Genotyping by sequencing was used to identify 77,889 SNPs, spread over 19 chromosomes. Genetic diversity and phenotypic variations were generally high for the studied traits. A total of eleven genotypes were identified which showed high-quality protein, high antioxidants, and lower amount of antinutrients. A significant negative correlation between protein and limiting amino acids and a significant positive correlation between GLS and phytic acid were observed. General and mixed linear models were used to estimate the association between the SNP markers and the seed quality traits and quantile-quantile (QQ) plots were generated to allow the best-fit algorithm. Annotation of genomic regions around associated SNPs helped to predict various trait-related candidates such as <italic>ASP2</italic> and <italic>EMB1027</italic> (amino acid biosynthesis); <italic>HEMA2, GLU1</italic>, and <italic>PGM</italic> (tryptophan biosynthesis); <italic>MS3, CYSD1</italic>, and <italic>MTO1</italic> (methionine biosynthesis); <italic>LYC</italic> (β-carotene biosynthesis); <italic>HDR</italic> and <italic>ISPF</italic> (MEP pathway); <italic>COS1</italic> (riboflavin synthesis); <italic>UGT</italic> (phenolics biosynthesis); <italic>NAC073</italic> (cellulose and hemicellulose biosynthesis); <italic>CYT1</italic> (cellulose biosynthesis); <italic>BGLU45</italic> and <italic>BGLU46</italic> (lignin biosynthesis); <italic>SOT12</italic> and <italic>UGT88A1</italic> (flavonoid pathway); and <italic>CYP79A2, DIN2</italic>, and <italic>GSTT2</italic> (GLS metabolism), etc. The functional validation of these candidate genes could confirm key seed meal quality genes for germplasm enhancement programs directed at improving protein quality and reducing the antinutritional components in <italic>B. napus</italic>.</p>