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Comparative analysis of genetic architectures for nine developmental traits of rye
Genetic architectures of plant height, stem thickness, spike length, awn length, heading date, thousand-kernel weight, kernel length, leaf area and chlorophyll content were aligned on the DArT-based high-density map of the 541 × Ot1–3 RILs population of rye using the genes interaction assorting by d...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5509807/ https://www.ncbi.nlm.nih.gov/pubmed/28488059 http://dx.doi.org/10.1007/s13353-017-0396-3 |
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author | Masojć, Piotr Milczarski, P. Kruszona, P. |
author_facet | Masojć, Piotr Milczarski, P. Kruszona, P. |
author_sort | Masojć, Piotr |
collection | PubMed |
description | Genetic architectures of plant height, stem thickness, spike length, awn length, heading date, thousand-kernel weight, kernel length, leaf area and chlorophyll content were aligned on the DArT-based high-density map of the 541 × Ot1–3 RILs population of rye using the genes interaction assorting by divergent selection (GIABDS) method. Complex sets of QTL for particular traits contained 1–5 loci of the epistatic D class and 10–28 loci of the hypostatic, mostly R and E classes controlling traits variation through D–E or D–R types of two-loci interactions. QTL were distributed on each of the seven rye chromosomes in unique positions or as a coinciding loci for 2–8 traits. Detection of considerable numbers of the reversed (D′, E′ and R′) classes of QTL might be attributed to the transgression effects observed for most of the studied traits. First examples of E* and F QTL classes, defined in the model, are reported for awn length, leaf area, thousand-kernel weight and kernel length. The results of this study extend experimental data to 11 quantitative traits (together with pre-harvest sprouting and alpha-amylase activity) for which genetic architectures fit the model of mechanism underlying alleles distribution within tails of bi-parental populations. They are also a valuable starting point for map-based search of genes underlying detected QTL and for planning advanced marker-assisted multi-trait breeding strategies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s13353-017-0396-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5509807 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-55098072017-07-28 Comparative analysis of genetic architectures for nine developmental traits of rye Masojć, Piotr Milczarski, P. Kruszona, P. J Appl Genet Plant Genetics • Original Paper Genetic architectures of plant height, stem thickness, spike length, awn length, heading date, thousand-kernel weight, kernel length, leaf area and chlorophyll content were aligned on the DArT-based high-density map of the 541 × Ot1–3 RILs population of rye using the genes interaction assorting by divergent selection (GIABDS) method. Complex sets of QTL for particular traits contained 1–5 loci of the epistatic D class and 10–28 loci of the hypostatic, mostly R and E classes controlling traits variation through D–E or D–R types of two-loci interactions. QTL were distributed on each of the seven rye chromosomes in unique positions or as a coinciding loci for 2–8 traits. Detection of considerable numbers of the reversed (D′, E′ and R′) classes of QTL might be attributed to the transgression effects observed for most of the studied traits. First examples of E* and F QTL classes, defined in the model, are reported for awn length, leaf area, thousand-kernel weight and kernel length. The results of this study extend experimental data to 11 quantitative traits (together with pre-harvest sprouting and alpha-amylase activity) for which genetic architectures fit the model of mechanism underlying alleles distribution within tails of bi-parental populations. They are also a valuable starting point for map-based search of genes underlying detected QTL and for planning advanced marker-assisted multi-trait breeding strategies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s13353-017-0396-3) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2017-05-09 2017 /pmc/articles/PMC5509807/ /pubmed/28488059 http://dx.doi.org/10.1007/s13353-017-0396-3 Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Plant Genetics • Original Paper Masojć, Piotr Milczarski, P. Kruszona, P. Comparative analysis of genetic architectures for nine developmental traits of rye |
title | Comparative analysis of genetic architectures for nine developmental traits of rye |
title_full | Comparative analysis of genetic architectures for nine developmental traits of rye |
title_fullStr | Comparative analysis of genetic architectures for nine developmental traits of rye |
title_full_unstemmed | Comparative analysis of genetic architectures for nine developmental traits of rye |
title_short | Comparative analysis of genetic architectures for nine developmental traits of rye |
title_sort | comparative analysis of genetic architectures for nine developmental traits of rye |
topic | Plant Genetics • Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5509807/ https://www.ncbi.nlm.nih.gov/pubmed/28488059 http://dx.doi.org/10.1007/s13353-017-0396-3 |
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