Evidence map›Paper›PMID 37495658›Full record

ArticleScientific reports2023

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

Mehdi Rahimi, Masoud AhmadiAfzadi, Mojtaba Kordrostami

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Article in Scientific reports, 2023. 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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3citing papers in PubMed
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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Mehdi RahimiDepartment of Biotechnology, Institute of Science and High Technology and Environmental Sciences, Graduate University of Advanced Technology, Kerman, Iran. me.rahimi@kgut.ac.ir.ORCID 0000-0001-5625-3275
Masoud AhmadiAfzadiDepartment of Biotechnology, Institute of Science and High Technology and Environmental Sciences, Graduate University of Advanced Technology, Kerman, Iran.
Mojtaba KordrostamiNuclear Science and Technology Research Institute (NSTRI), Nuclear Agriculture Research School, Karaj, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Genetic VariationMicrosatellite RepeatsGenotypePhenotypePlant Breeding

Identifiers

PMID37495658
PMCPMC10372081

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