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Genotyping-by-Sequencing Based Genetic Mapping Identified Major and Consistent Genomic Regions for Productivity and Quality Traits in Peanut

With an objective of identifying the genomic regions for productivity and quality traits in peanut, a recombinant inbred line (RIL) population developed from an elite variety, TMV 2 and its ethyl methane sulfonate (EMS)-derived mutant was phenotyped over six seasons and genotyped with genotyping-by-...

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Autores principales: Jadhav, Mangesh P., Gangurde, Sunil S., Hake, Anil A., Yadawad, Arati, Mahadevaiah, Supriya S., Pattanashetti, Santosh K., Gowda, M. V. Channabyre, Shirasawa, Kenta, Varshney, Rajeev K., Pandey, Manish K., Bhat, Ramesh S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8495222/
https://www.ncbi.nlm.nih.gov/pubmed/34630444
http://dx.doi.org/10.3389/fpls.2021.668020
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author Jadhav, Mangesh P.
Gangurde, Sunil S.
Hake, Anil A.
Yadawad, Arati
Mahadevaiah, Supriya S.
Pattanashetti, Santosh K.
Gowda, M. V. Channabyre
Shirasawa, Kenta
Varshney, Rajeev K.
Pandey, Manish K.
Bhat, Ramesh S.
author_facet Jadhav, Mangesh P.
Gangurde, Sunil S.
Hake, Anil A.
Yadawad, Arati
Mahadevaiah, Supriya S.
Pattanashetti, Santosh K.
Gowda, M. V. Channabyre
Shirasawa, Kenta
Varshney, Rajeev K.
Pandey, Manish K.
Bhat, Ramesh S.
author_sort Jadhav, Mangesh P.
collection PubMed
description With an objective of identifying the genomic regions for productivity and quality traits in peanut, a recombinant inbred line (RIL) population developed from an elite variety, TMV 2 and its ethyl methane sulfonate (EMS)-derived mutant was phenotyped over six seasons and genotyped with genotyping-by-sequencing (GBS), Arachis hypogaea transposable element (AhTE) and simple sequence repeats (SSR) markers. The genetic map with 700 markers spanning 2,438.1 cM was employed for quantitative trait loci (QTL) analysis which identified a total of 47 main-effect QTLs for the productivity and oil quality traits with the phenotypic variance explained (PVE) of 10–52% over the seasons. A common QTL region (46.7–50.1 cM) on Ah02 was identified for the multiple traits, such as a number of pods per plant (NPPP), pod weight per plant (PWPP), shelling percentage (SP), and test weight (TW). Similarly, a QTL (7.1–18.0 cM) on Ah16 was identified for both SP and protein content (PC). Epistatic QTL (epiQTL) analysis revealed intra- and inter-chromosomal interactions for the main-effect QTLs and other genomic regions governing these productivity traits. The markers identified by a single marker analysis (SMA) mapped to the QTL regions for most of the traits. Among the five potential candidate genes identified for PC, SP and oil quality, two genes (Arahy.7A57YA and Arahy.CH9B83) were affected by AhMITE1 transposition, and three genes (Arahy.J5SZ1I, Arahy.MZJT69, and Arahy.X7PJ8H) involved functional single nucleotide polymorphisms (SNPs). With major and consistent effects, the genomic regions, candidate genes, and the associated markers identified in this study would provide an opportunity for gene cloning and genomics-assisted breeding for increasing the productivity and enhancing the quality of peanut.
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spelling pubmed-84952222021-10-08 Genotyping-by-Sequencing Based Genetic Mapping Identified Major and Consistent Genomic Regions for Productivity and Quality Traits in Peanut Jadhav, Mangesh P. Gangurde, Sunil S. Hake, Anil A. Yadawad, Arati Mahadevaiah, Supriya S. Pattanashetti, Santosh K. Gowda, M. V. Channabyre Shirasawa, Kenta Varshney, Rajeev K. Pandey, Manish K. Bhat, Ramesh S. Front Plant Sci Plant Science With an objective of identifying the genomic regions for productivity and quality traits in peanut, a recombinant inbred line (RIL) population developed from an elite variety, TMV 2 and its ethyl methane sulfonate (EMS)-derived mutant was phenotyped over six seasons and genotyped with genotyping-by-sequencing (GBS), Arachis hypogaea transposable element (AhTE) and simple sequence repeats (SSR) markers. The genetic map with 700 markers spanning 2,438.1 cM was employed for quantitative trait loci (QTL) analysis which identified a total of 47 main-effect QTLs for the productivity and oil quality traits with the phenotypic variance explained (PVE) of 10–52% over the seasons. A common QTL region (46.7–50.1 cM) on Ah02 was identified for the multiple traits, such as a number of pods per plant (NPPP), pod weight per plant (PWPP), shelling percentage (SP), and test weight (TW). Similarly, a QTL (7.1–18.0 cM) on Ah16 was identified for both SP and protein content (PC). Epistatic QTL (epiQTL) analysis revealed intra- and inter-chromosomal interactions for the main-effect QTLs and other genomic regions governing these productivity traits. The markers identified by a single marker analysis (SMA) mapped to the QTL regions for most of the traits. Among the five potential candidate genes identified for PC, SP and oil quality, two genes (Arahy.7A57YA and Arahy.CH9B83) were affected by AhMITE1 transposition, and three genes (Arahy.J5SZ1I, Arahy.MZJT69, and Arahy.X7PJ8H) involved functional single nucleotide polymorphisms (SNPs). With major and consistent effects, the genomic regions, candidate genes, and the associated markers identified in this study would provide an opportunity for gene cloning and genomics-assisted breeding for increasing the productivity and enhancing the quality of peanut. Frontiers Media S.A. 2021-09-23 /pmc/articles/PMC8495222/ /pubmed/34630444 http://dx.doi.org/10.3389/fpls.2021.668020 Text en Copyright © 2021 Jadhav, Gangurde, Hake, Yadawad, Mahadevaiah, Pattanashetti, Gowda, Shirasawa, Varshney, Pandey and Bhat. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Jadhav, Mangesh P.
Gangurde, Sunil S.
Hake, Anil A.
Yadawad, Arati
Mahadevaiah, Supriya S.
Pattanashetti, Santosh K.
Gowda, M. V. Channabyre
Shirasawa, Kenta
Varshney, Rajeev K.
Pandey, Manish K.
Bhat, Ramesh S.
Genotyping-by-Sequencing Based Genetic Mapping Identified Major and Consistent Genomic Regions for Productivity and Quality Traits in Peanut
title Genotyping-by-Sequencing Based Genetic Mapping Identified Major and Consistent Genomic Regions for Productivity and Quality Traits in Peanut
title_full Genotyping-by-Sequencing Based Genetic Mapping Identified Major and Consistent Genomic Regions for Productivity and Quality Traits in Peanut
title_fullStr Genotyping-by-Sequencing Based Genetic Mapping Identified Major and Consistent Genomic Regions for Productivity and Quality Traits in Peanut
title_full_unstemmed Genotyping-by-Sequencing Based Genetic Mapping Identified Major and Consistent Genomic Regions for Productivity and Quality Traits in Peanut
title_short Genotyping-by-Sequencing Based Genetic Mapping Identified Major and Consistent Genomic Regions for Productivity and Quality Traits in Peanut
title_sort genotyping-by-sequencing based genetic mapping identified major and consistent genomic regions for productivity and quality traits in peanut
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8495222/
https://www.ncbi.nlm.nih.gov/pubmed/34630444
http://dx.doi.org/10.3389/fpls.2021.668020
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