Genome-Wide Analysis for Yield-Related Agronomic and Biochemical Traits of Chinese and Bangladeshi Grass Pea Genotypes Using SSR Markers

文献类型： 外文期刊

第一作者： Rahman, Md. Mosiur

作者： Rahman, Md. Mosiur;Liu, Rong;Li, Mengwei;Yan, Xin;Li, Guan;Ji, Yishan;Wang, Chenyu;Yang, Tao;Zong, Xuxiao;Rahman, Md. Mosiur;Hossain, Muhammad Malek;Quddus, Md. Ruhul;Xu, Quanle;Sarker, Ashutosh;Hossain, Md. Monoar;Alfarraj, Saleh;Ansari, Mohammad Javed;Maitra, Sagar;Hossain, Akbar

作者机构：

关键词： Grass pea; dryland agriculture; genome-wide association; yield contributing traits; SSR markers

期刊名称：PHYTON-INTERNATIONAL JOURNAL OF EXPERIMENTAL BOTANY （ 影响因子：1.3； 五年影响因子：1.2 ）

ISSN： 0031-9457

年卷期： 2024 年

页码：

收录情况： SCI

摘要： Grass pea ( Lathyrus sativus L.) is an imperative food crop cultured in dryland agricultural ecology. It is a vital source of dietary protein to millions of populaces living in low-income countries in South-East Asia and Africa. This study highlights the improvement of genomic properties and their application in marker-trait relationships for 17 yield-related characters in 400 grass pea genotypes from China and Bangladesh. These characters were assessed via 56 polymorphic markers using general linear model (GLM) (P+G+Q) and mixed linear model (MLM) (P+G+Q+K) in the tassel software based on the linkage disequilibrium and population structure analysis. Population structure analysis showed two major groups and one admixed group in the populace. Statistically signi fi cant loci pairs of linkage disequilibrium (LD) mean value (D ' ) was 0.479. A total of 99 and 61 marker-trait associations in GLM and MLM models allied to the 17 traits were accepted at a 5% level of signi fi cance. Among these markers, 21 markers were associated with more than one trait; 12 marker-trait associations passed the Bonferroni correction threshold. Both models found six markers C41936, C39067, C34100, C47146, C47638, and C43047 signi fi cantly associated with days to maturity, fl ower color, plant height, and seed per pod were detected in the Hebei and Liaoyang location ( p <= 0.01), and the interpretation rate (R 2 value) 11.2% to 43.6%. Conferring to the consequences, the association analysis methodology may operative system for quantitative, qualitative, and biochemical traits related to gene position mapping and support breeders in improving novel approaches for advancing the grass pea quality.

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