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      Population structure and genetic diversity of a germplasm for hybrid breeding in rye ( Secale cereale L.) using high-density DArTseq-based silicoDArT and SNP markers

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          Abstract

          Investigating genetic structure and diversity is crucial for the rye hybrid breeding strategy, leading to improved plant productivity and adaptation. The present study elucidated the population structure and genetic diversity of 188 rye accessions, comprising 94 pollen fertility restoration lines (RF) and 94 cytoplasmic male-sterile (CMS) lines with Pampa sterilizing cytoplasm using SNP and silicoDArT markers from the diversity array technology (DArT)-based sequencing platform (DArTseq). Expected heterozygosity ( H e ) and Shanon’s diversity ( I) indexes varied slightly between marker systems and groups of germplasms ( H e  = 0.34, I = 0.51 for RF and CMS lines genotyped using SNPs; H e  = 0.31, I = 0.48, and H e  = 0.35, I = 0.53 for RF and CMS using silicoDArTs, respectively). ANOVA indicated moderate variation (7%) between RF and CMS breeding materials. The same parameter varied when chromosome-assigned markers were used and ranged from 5.8% for 5R to 7.4% for 4R. However, when silicoDArT markers were applied, the respective values varied from 6.4% (1R) to 8.2% (3R and 4R). The model-based (Bayesian) population structure analysis based on the total marker pool identified two major subpopulations for the studied rye germplasm. The first one (P1) encompasses 93 RF accessions, and the second one (P2) encompasses 94 CMS and one RF accession. However, a similar analysis related to markers assigned to selected chromosomes failed to put plant materials into any of the populations in the same way as the total marker pool. Furthermore, the differences in grouping depended on marker types used for analysis.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s13353-022-00740-w.

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          Detecting the number of clusters of individuals using the software structure: a simulation study

          The identification of genetically homogeneous groups of individuals is a long standing issue in population genetics. A recent Bayesian algorithm implemented in the software STRUCTURE allows the identification of such groups. However, the ability of this algorithm to detect the true number of clusters (K) in a sample of individuals when patterns of dispersal among populations are not homogeneous has not been tested. The goal of this study is to carry out such tests, using various dispersal scenarios from data generated with an individual-based model. We found that in most cases the estimated 'log probability of data' does not provide a correct estimation of the number of clusters, K. However, using an ad hoc statistic DeltaK based on the rate of change in the log probability of data between successive K values, we found that STRUCTURE accurately detects the uppermost hierarchical level of structure for the scenarios we tested. As might be expected, the results are sensitive to the type of genetic marker used (AFLP vs. microsatellite), the number of loci scored, the number of populations sampled, and the number of individuals typed in each sample.
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            STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method

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              GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research—an update

              Summary: GenAlEx: Genetic Analysis in Excel is a cross-platform package for population genetic analyses that runs within Microsoft Excel. GenAlEx offers analysis of diploid codominant, haploid and binary genetic loci and DNA sequences. Both frequency-based (F-statistics, heterozygosity, HWE, population assignment, relatedness) and distance-based (AMOVA, PCoA, Mantel tests, multivariate spatial autocorrelation) analyses are provided. New features include calculation of new estimators of population structure: G′ST, G′′ST, Jost’s D est and F′ST through AMOVA, Shannon Information analysis, linkage disequilibrium analysis for biallelic data and novel heterogeneity tests for spatial autocorrelation analysis. Export to more than 30 other data formats is provided. Teaching tutorials and expanded step-by-step output options are included. The comprehensive guide has been fully revised. Availability and implementation: GenAlEx is written in VBA and provided as a Microsoft Excel Add-in (compatible with Excel 2003, 2007, 2010 on PC; Excel 2004, 2011 on Macintosh). GenAlEx, and supporting documentation and tutorials are freely available at: http://biology.anu.edu.au/GenAlEx. Contact: rod.peakall@anu.edu.au
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                Author and article information

                Contributors
                p.bednarek@ihar.edu.pl
                Journal
                J Appl Genet
                J Appl Genet
                Journal of Applied Genetics
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                1234-1983
                2190-3883
                3 January 2023
                3 January 2023
                2023
                : 64
                : 2
                : 217-229
                Affiliations
                GRID grid.425508.e, ISNI 0000 0001 2323 609X, Plant Breeding and Acclimatization Institute - National Research Institute, ; 05-870 Błonie, Radzików, Poland
                Author notes

                Communicated by Izabela Pawłowicz

                Author information
                http://orcid.org/0000-0002-1553-8378
                Article
                740
                10.1007/s13353-022-00740-w
                10076414
                36595165
                20b47d9e-1c6d-4fb9-be96-468fc9ed7e48
                © The Author(s) 2023

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 23 September 2022
                : 25 November 2022
                : 2 December 2022
                Categories
                Plant Genetics • Original Paper
                Custom metadata
                © The Author(s), under exclusive licence to Institute of Plant Genetics Polish Academy of Sciences 2023

                Genetics
                rye,genetic diversity,cms pampa,hybrid breeding
                Genetics
                rye, genetic diversity, cms pampa, hybrid breeding

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