Cargando…
QTL Analysis of Five Morpho-Physiological Traits in Bread Wheat Using Two Mapping Populations Derived from Common Parents
Traits such as plant height (PH), juvenile growth habit (GH), heading date (HD), and tiller number are important for both increasing yield potential and improving crop adaptation to climate change. In the present study, these traits were investigated by using the same bi-parental population at early...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8074140/ https://www.ncbi.nlm.nih.gov/pubmed/33923933 http://dx.doi.org/10.3390/genes12040604 |
_version_ | 1783684287882592256 |
---|---|
author | Vitale, Paolo Fania, Fabio Esposito, Salvatore Pecorella, Ivano Pecchioni, Nicola Palombieri, Samuela Sestili, Francesco Lafiandra, Domenico Taranto, Francesca De Vita, Pasquale |
author_facet | Vitale, Paolo Fania, Fabio Esposito, Salvatore Pecorella, Ivano Pecchioni, Nicola Palombieri, Samuela Sestili, Francesco Lafiandra, Domenico Taranto, Francesca De Vita, Pasquale |
author_sort | Vitale, Paolo |
collection | PubMed |
description | Traits such as plant height (PH), juvenile growth habit (GH), heading date (HD), and tiller number are important for both increasing yield potential and improving crop adaptation to climate change. In the present study, these traits were investigated by using the same bi-parental population at early (F(2) and F(2)-derived F(3) families) and late (F(6) and F(7), recombinant inbred lines, RILs) generations to detect quantitative trait loci (QTLs) and search for candidate genes. A total of 176 and 178 lines were genotyped by the wheat Illumina 25K Infinium SNP array. The two genetic maps spanned 2486.97 cM and 3732.84 cM in length, for the F(2) and RILs, respectively. QTLs explaining the highest phenotypic variation were found on chromosomes 2B, 2D, 5A, and 7D for HD and GH, whereas those for PH were found on chromosomes 4B and 4D. Several QTL detected in the early generations (i.e., PH and tiller number) were not detected in the late generations as they were due to dominance effects. Some of the identified QTLs co-mapped to well-known adaptive genes (i.e., Ppd-1, Vrn-1, and Rht-1). Other putative candidate genes were identified for each trait, of which PINE1 and PIF4 may be considered new for GH and TTN in wheat. The use of a large F(2) mapping population combined with NGS-based genotyping techniques could improve map resolution and allow closer QTL tagging. |
format | Online Article Text |
id | pubmed-8074140 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-80741402021-04-27 QTL Analysis of Five Morpho-Physiological Traits in Bread Wheat Using Two Mapping Populations Derived from Common Parents Vitale, Paolo Fania, Fabio Esposito, Salvatore Pecorella, Ivano Pecchioni, Nicola Palombieri, Samuela Sestili, Francesco Lafiandra, Domenico Taranto, Francesca De Vita, Pasquale Genes (Basel) Article Traits such as plant height (PH), juvenile growth habit (GH), heading date (HD), and tiller number are important for both increasing yield potential and improving crop adaptation to climate change. In the present study, these traits were investigated by using the same bi-parental population at early (F(2) and F(2)-derived F(3) families) and late (F(6) and F(7), recombinant inbred lines, RILs) generations to detect quantitative trait loci (QTLs) and search for candidate genes. A total of 176 and 178 lines were genotyped by the wheat Illumina 25K Infinium SNP array. The two genetic maps spanned 2486.97 cM and 3732.84 cM in length, for the F(2) and RILs, respectively. QTLs explaining the highest phenotypic variation were found on chromosomes 2B, 2D, 5A, and 7D for HD and GH, whereas those for PH were found on chromosomes 4B and 4D. Several QTL detected in the early generations (i.e., PH and tiller number) were not detected in the late generations as they were due to dominance effects. Some of the identified QTLs co-mapped to well-known adaptive genes (i.e., Ppd-1, Vrn-1, and Rht-1). Other putative candidate genes were identified for each trait, of which PINE1 and PIF4 may be considered new for GH and TTN in wheat. The use of a large F(2) mapping population combined with NGS-based genotyping techniques could improve map resolution and allow closer QTL tagging. MDPI 2021-04-20 /pmc/articles/PMC8074140/ /pubmed/33923933 http://dx.doi.org/10.3390/genes12040604 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Vitale, Paolo Fania, Fabio Esposito, Salvatore Pecorella, Ivano Pecchioni, Nicola Palombieri, Samuela Sestili, Francesco Lafiandra, Domenico Taranto, Francesca De Vita, Pasquale QTL Analysis of Five Morpho-Physiological Traits in Bread Wheat Using Two Mapping Populations Derived from Common Parents |
title | QTL Analysis of Five Morpho-Physiological Traits in Bread Wheat Using Two Mapping Populations Derived from Common Parents |
title_full | QTL Analysis of Five Morpho-Physiological Traits in Bread Wheat Using Two Mapping Populations Derived from Common Parents |
title_fullStr | QTL Analysis of Five Morpho-Physiological Traits in Bread Wheat Using Two Mapping Populations Derived from Common Parents |
title_full_unstemmed | QTL Analysis of Five Morpho-Physiological Traits in Bread Wheat Using Two Mapping Populations Derived from Common Parents |
title_short | QTL Analysis of Five Morpho-Physiological Traits in Bread Wheat Using Two Mapping Populations Derived from Common Parents |
title_sort | qtl analysis of five morpho-physiological traits in bread wheat using two mapping populations derived from common parents |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8074140/ https://www.ncbi.nlm.nih.gov/pubmed/33923933 http://dx.doi.org/10.3390/genes12040604 |
work_keys_str_mv | AT vitalepaolo qtlanalysisoffivemorphophysiologicaltraitsinbreadwheatusingtwomappingpopulationsderivedfromcommonparents AT faniafabio qtlanalysisoffivemorphophysiologicaltraitsinbreadwheatusingtwomappingpopulationsderivedfromcommonparents AT espositosalvatore qtlanalysisoffivemorphophysiologicaltraitsinbreadwheatusingtwomappingpopulationsderivedfromcommonparents AT pecorellaivano qtlanalysisoffivemorphophysiologicaltraitsinbreadwheatusingtwomappingpopulationsderivedfromcommonparents AT pecchioninicola qtlanalysisoffivemorphophysiologicaltraitsinbreadwheatusingtwomappingpopulationsderivedfromcommonparents AT palombierisamuela qtlanalysisoffivemorphophysiologicaltraitsinbreadwheatusingtwomappingpopulationsderivedfromcommonparents AT sestilifrancesco qtlanalysisoffivemorphophysiologicaltraitsinbreadwheatusingtwomappingpopulationsderivedfromcommonparents AT lafiandradomenico qtlanalysisoffivemorphophysiologicaltraitsinbreadwheatusingtwomappingpopulationsderivedfromcommonparents AT tarantofrancesca qtlanalysisoffivemorphophysiologicaltraitsinbreadwheatusingtwomappingpopulationsderivedfromcommonparents AT devitapasquale qtlanalysisoffivemorphophysiologicaltraitsinbreadwheatusingtwomappingpopulationsderivedfromcommonparents |