ArticlePloS one2025
Genome-wide association study uncovers key genomic regions governing agro-morphological and quality traits in Indian mustard [Brassica juncea (L.) Czern. and Coss.].
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Article
- Genome-wide association studies and candidate gene identification under salinity stress in bread wheat (Frontiers in plant science · 2026Article
- Genetic analysis of silique and seed traits in Brassica juncea (L.) Czern. under differential doses of nitrogen application.Scientific reports · 2025Article
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12 authors.
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Abstract
In Indian mustard, improving agro-morphological and quality traits through conventional methods are both cumbersome and resource-intensive. Marker-aided breeding presents a promising solution to these challenges. Hence, the present research aimed to identify genomic regions governing agro-morphological and quality traits using genome-wide association studies (GWAS). The GWAS panel comprised 142 diverse genotypes of Indian mustard were evaluated for 20 different agro-morphological and quality traits, revealing significant difference among genotypes. Subsequently, the GWAS panel genotyped using the Brassica 90K SNP array (Illumina). Structure and diversity analysis grouped the GWAS panel into 3 sub-populations or groups, and LD decay of 1.05 Mb was confirmed through genotypic analysis. GWAS using the BLINK model revealed a total of 49 marker-trait associations (MTAs), in which 28 and 21 MTAs were observed during rabi 2020-21 and rabi 2021-22 for various agro-morphological and quality traits, respectively. Amongst them, twelve MTAs demonstrated stable associations with the studied traits, including days to 50% flowering (DF), days to 100% flower termination (DFT), days to maturity (DM), plant height (PH), main shoot length (MSL), siliqua length (SL), seeds per siliqua (SPS), oil content (OC), and glucosinolates content (Glu) in both years. Moreover, in silico analysis of nearby regions of these stable SNPs revealed their association with 31 candidate genes known to be involved in various molecular, physiological, and biochemical pathways relevant to the studied traits. These genes can be further characterized and deciphered for more precise utilization in breeding programs in the future.
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