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普通猪毛菜(Falcaria vulgaris)的遗传多样性及利用逐步回归分析鉴定与性状相关的标记。

Genetic diversity in Sickleweed (Falcaria vulgaris) and using stepwise regression to identify marker associated with traits.

机构信息

Department of Biotechnology, Institute of Science and High Technology and Environmental Sciences, Graduate University of Advanced Technology, Kerman, Iran.

Nuclear Science and Technology Research Institute (NSTRI), Nuclear Agriculture Research School, Karaj, Iran.

出版信息

Sci Rep. 2023 Jul 26;13(1):12142. doi: 10.1038/s41598-023-39419-5.

DOI:10.1038/s41598-023-39419-5
PMID:37495658
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10372081/
Abstract

One of the well-known medicinal plants in the Falcaria genus is Sickleweed. Falcaria species exhibit a high degree of genetic variability, posing challenges in the examination of genetic diversity due to the significant potential for hybridization and introgression among them. Utilizing morphological traits and molecular markers may prove to be a valuable approach in evaluating and harnessing germplasm, considering the current obstacles faced in breeding this medicinal herb. In 2021, fifteen Sickleweed populations were cultivated in pots under field conditions, employing a randomized complete block design with three replications. This aimed to assess genetic diversity and conduct marker-trait association analyses utilizing morpho-physiological characteristics and SSR markers. The Sickleweed populations displayed considerable genetic diversity across all traits. Through cluster analysis of traits and the utilization of the UPGMA method based on the Gower distance matrix, the population was classified into three distinct clusters. Upon examining all genotypes, 52 polymorphic bands were detected, with an average of 8.68 bands per primer. The average expected heterozygosity across all loci was 0.864, while the average PIC was 0.855. Molecular data analysis employing the Jaccard similarity index and UPGMA method revealed the division of Sickleweed populations into two major groups. Furthermore, the results of molecular variance analysis indicated that variation within the population exceeded that between populations. Thirty-two SSR fragments were found to be significantly associated with genomic regions controlling the studied traits, determined through the application of stepwise regression. Selection based on molecular markers offers a rapid method for breeding programs, with the genetic information obtained from these markers playing a crucial role. Therefore, alongside traits, selecting superior genotypes and populations of high value in breeding programs becomes feasible. The findings highlight that certain markers are linked to multiple traits, emphasizing the critical importance of this characteristic in plant breeding for the simultaneous improvement of numerous traits. The study's insights regarding markers hold potential for application in Sickleweed breeding programs.

摘要

镰叶棘豆属是著名的药用植物之一。镰叶棘豆属植物表现出高度的遗传变异性,由于它们之间存在着很大的杂交和渐渗的可能性,因此在检查遗传多样性时会带来挑战。利用形态特征和分子标记可能是评估和利用种质资源的一种有价值的方法,因为在培育这种药用植物时目前面临着许多困难。2021 年,在田间条件下,采用随机完全区组设计,每个区组设 3 个重复,在盆中种植了 15 个镰叶棘豆种群。目的是评估遗传多样性,并利用形态生理特征和 SSR 标记进行标记-性状关联分析。所有性状的镰叶棘豆种群均表现出较高的遗传多样性。通过对性状进行聚类分析,并利用基于 Gower 距离矩阵的 UPGMA 方法,将种群分为 3 个不同的聚类。在检查所有基因型后,共检测到 52 个多态性条带,每个引物平均 8.68 个条带。所有位点的平均期望杂合度为 0.864,平均 PIC 为 0.855。采用 Jaccard 相似指数和 UPGMA 法对分子数据进行分析,结果表明镰叶棘豆种群分为 2 个主要组。此外,分子方差分析的结果表明,群体内的变异大于群体间的变异。通过逐步回归分析,发现 32 个 SSR 片段与控制所研究性状的基因组区域显著相关。基于分子标记的选择为育种计划提供了一种快速的方法,这些标记获得的遗传信息在育种计划中起着至关重要的作用。因此,除了性状之外,在育种计划中选择具有较高价值的优良基因型和群体也成为可能。研究结果表明,某些标记与多个性状相关联,这强调了该特性在植物育种中同时改善多个性状的重要性。该研究的标记见解在镰叶棘豆的育种计划中具有潜在的应用价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b21/10372081/7da50d30377a/41598_2023_39419_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b21/10372081/31bb5e06b66f/41598_2023_39419_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b21/10372081/7da50d30377a/41598_2023_39419_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b21/10372081/31bb5e06b66f/41598_2023_39419_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b21/10372081/7da50d30377a/41598_2023_39419_Fig2_HTML.jpg

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