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利用 SSR 标记对印度大豆(Glycine max (L.) Merr.)品种进行分子特征和遗传多样性研究。

Molecular characterization and genetic diversity studies of Indian soybean (Glycine max (L.) Merr.) cultivars using SSR markers.

机构信息

ICAR-Indian Institute of Seed Science, Mau, Kushmaur, Uttar Pradesh, 275103, India.

ICAR-Directorate of Floricultural Research, Pune, Maharashtra, 411 036, India.

出版信息

Mol Biol Rep. 2022 Mar;49(3):2129-2140. doi: 10.1007/s11033-021-07030-4. Epub 2021 Dec 11.

DOI:10.1007/s11033-021-07030-4
PMID:34894334
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8863763/
Abstract

BACKGROUND

The genetic base of soybean cultivars in India has been reported to be extremely narrow, due to repeated use of few selected and elite genotypes as parents in the breeding programmes. This ultimately led to the reduction of genetic variability among existing soybean cultivars and stagnation in crop yield. Thus in order to enhance production and productivity of soybean, broadening of genetic base and exploring untapped valuable genetic diversity has become quite indispensable. This could be successfully accomplished through molecular characterization of soybean genotypes using various DNA based markers. Hence, an attempt was made to study the molecular divergence and relatedness among 29 genotypes of soybean using SSR markers.

METHODS AND RESULTS

A total of 35 SSR primers were deployed to study the genetic divergence among 29 genotypes of soybean. Among them, 14 primer pairs were found to be polymorphic producing a total of 34 polymorphic alleles; and the allele number for each locus ranged from two to four with an average of 2.43 alleles per primer pair. Polymorphic information content (PIC) values of SSRs ranged from 0.064 to 0.689 with an average of 0.331. The dendrogram constructed based on dissimilarity indices clustered the 29 genotypes into two major groups and four sub-groups. Similarly, principal coordinate analysis grouped the genotypes into four major groups that exactly corresponded to the clustering of genotypes among four sub-groups of dendrogram. Besides, the study has reported eight unique and two rare alleles that could be potentially utilized for genetic purity analysis and cultivar identification in soybean.

CONCLUSION

In the present investigation, two major clusters were reported and grouping of large number of genotypes in each cluster indicated high degree of genetic resemblance and narrow genetic base among the genotypes used in the study. With respect to the primers used in the study, the values of PIC and other related parameters revealed that the selected SSR markers are moderately informative and could be potentially utilized for diversity analysis of soybean. The clustering pattern of dendrogram constructed based on SSR loci profile displayed good agreement with the cultivar's pedigree information. High level of genetic similarity observed among the genotypes from the present study necessitates the inclusion of wild relatives, land races and traditional cultivars in future soybean breeding programmes to widen the crop gene pool. Thus, hybridization among diverse gene pool could result in more heterotic combinations ultimately enhancing genetic gain, crop yield and resistance to various stress factors.

摘要

背景

由于在育种计划中反复使用少数精选和精英基因型作为亲本,印度大豆品种的遗传基础已被报道极其狭窄。这最终导致现有大豆品种间遗传变异减少,作物产量停滞不前。因此,为了提高大豆的产量和生产力,拓宽遗传基础和挖掘未开发的有价值的遗传多样性变得非常必要。这可以通过使用各种基于 DNA 的标记对大豆基因型进行分子特征分析来成功实现。因此,尝试使用 SSR 标记研究 29 个大豆基因型之间的分子差异和相关性。

方法和结果

总共使用 35 个 SSR 引物研究 29 个大豆基因型的遗传差异。其中,发现 14 对引物具有多态性,产生了总共 34 个多态等位基因;每个位点的等位基因数量从两个到四个不等,平均每个引物对 2.43 个等位基因。SSR 的多态信息含量 (PIC) 值范围从 0.064 到 0.689,平均值为 0.331。基于不相似性指数构建的聚类树将 29 个基因型分为两个主要组和四个亚组。同样,主坐标分析将基因型分为四个主要组,这与聚类树的四个亚组中基因型的聚类完全对应。此外,该研究报告了八个独特的和两个稀有的等位基因,可用于大豆的遗传纯度分析和品种鉴定。

结论

在本研究中,报告了两个主要聚类,每个聚类中的大量基因型分组表明,在所研究的基因型中存在高度的遗传相似性和狭窄的遗传基础。就研究中使用的引物而言,PIC 值和其他相关参数表明,所选 SSR 标记具有中等信息量,可潜在用于大豆多样性分析。基于 SSR 位点图谱构建的聚类树的聚类模式与品种的系谱信息显示出良好的一致性。本研究中基因型之间观察到的高遗传相似性需要在未来的大豆育种计划中纳入野生近缘种、地方品种和传统品种,以拓宽作物基因库。因此,不同基因库之间的杂交可以产生更多的杂种优势组合,最终提高遗传增益、作物产量和对各种胁迫因素的抗性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e5b/8863763/99303db0cb7e/11033_2021_7030_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e5b/8863763/99800cf7b9f6/11033_2021_7030_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e5b/8863763/0e56f7271671/11033_2021_7030_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e5b/8863763/b462f903100c/11033_2021_7030_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e5b/8863763/99303db0cb7e/11033_2021_7030_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e5b/8863763/99800cf7b9f6/11033_2021_7030_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e5b/8863763/0e56f7271671/11033_2021_7030_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e5b/8863763/b462f903100c/11033_2021_7030_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e5b/8863763/99303db0cb7e/11033_2021_7030_Fig4_HTML.jpg

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