Cargando…

Meta-QTL Analysis in Rice and Cross-Genome Talk of the Genomic Regions Controlling Nitrogen Use Efficiency in Cereal Crops Revealing Phylogenetic Relationship

The phenomenal increase in the use of nitrogenous fertilizers coupled with poor nitrogen use efficiency is among the most important threats to the environment, economic, and social health. During the last 2 decades, a number of genomic regions associated with nitrogen use efficiency (NUE) and relate...

Descripción completa

Detalles Bibliográficos
Autores principales: Sandhu, Nitika, Pruthi, Gomsie, Prakash Raigar, Om, Singh, Mohini Prabha, Phagna, Kanika, Kumar, Aman, Sethi, Mehak, Singh, Jasneet, Ade, Pooja Ankush, Saini, Dinesh Kumar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8724540/
https://www.ncbi.nlm.nih.gov/pubmed/34992638
http://dx.doi.org/10.3389/fgene.2021.807210
_version_ 1784625920444727296
author Sandhu, Nitika
Pruthi, Gomsie
Prakash Raigar, Om
Singh, Mohini Prabha
Phagna, Kanika
Kumar, Aman
Sethi, Mehak
Singh, Jasneet
Ade, Pooja Ankush
Saini, Dinesh Kumar
author_facet Sandhu, Nitika
Pruthi, Gomsie
Prakash Raigar, Om
Singh, Mohini Prabha
Phagna, Kanika
Kumar, Aman
Sethi, Mehak
Singh, Jasneet
Ade, Pooja Ankush
Saini, Dinesh Kumar
author_sort Sandhu, Nitika
collection PubMed
description The phenomenal increase in the use of nitrogenous fertilizers coupled with poor nitrogen use efficiency is among the most important threats to the environment, economic, and social health. During the last 2 decades, a number of genomic regions associated with nitrogen use efficiency (NUE) and related traits have been reported by different research groups, but none of the stable and major effect QTL have been utilized in the marker-assisted introgression/pyramiding program. Compiling the data available in the literature could be very useful in identifying stable and major effect genomic regions associated with the root and NUE-related trait improving the rice grain yield. In the present study, we performed meta-QTL analysis on 1,330 QTL from 29 studies published in the past 2 decades. A total of 76 MQTL with a stable effect over different genetic backgrounds and environments were identified. The significant reduction in the confidence interval of the MQTL compared to the initial QTL resulted in the identification of annotated and putative candidate genes related to the traits considered in the present study. A hot spot region associated with correlated traits on chr 1, 4, and 8 and candidate genes associated with nitrate transporters, nitrogen content, and ammonium uptake on chromosomes 2, 4, 6, and 8 have been identified. The identified MQTL, putative candidate genes, and their orthologues were validated on our previous studies conducted on rice and wheat. The research-based interventions such as improving nitrogen use efficiency via identification of major genomic regions and candidate genes can be a plausible, simple, and low-cost solution to address the challenges of the crop improvement program.
format Online
Article
Text
id pubmed-8724540
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-87245402022-01-05 Meta-QTL Analysis in Rice and Cross-Genome Talk of the Genomic Regions Controlling Nitrogen Use Efficiency in Cereal Crops Revealing Phylogenetic Relationship Sandhu, Nitika Pruthi, Gomsie Prakash Raigar, Om Singh, Mohini Prabha Phagna, Kanika Kumar, Aman Sethi, Mehak Singh, Jasneet Ade, Pooja Ankush Saini, Dinesh Kumar Front Genet Genetics The phenomenal increase in the use of nitrogenous fertilizers coupled with poor nitrogen use efficiency is among the most important threats to the environment, economic, and social health. During the last 2 decades, a number of genomic regions associated with nitrogen use efficiency (NUE) and related traits have been reported by different research groups, but none of the stable and major effect QTL have been utilized in the marker-assisted introgression/pyramiding program. Compiling the data available in the literature could be very useful in identifying stable and major effect genomic regions associated with the root and NUE-related trait improving the rice grain yield. In the present study, we performed meta-QTL analysis on 1,330 QTL from 29 studies published in the past 2 decades. A total of 76 MQTL with a stable effect over different genetic backgrounds and environments were identified. The significant reduction in the confidence interval of the MQTL compared to the initial QTL resulted in the identification of annotated and putative candidate genes related to the traits considered in the present study. A hot spot region associated with correlated traits on chr 1, 4, and 8 and candidate genes associated with nitrate transporters, nitrogen content, and ammonium uptake on chromosomes 2, 4, 6, and 8 have been identified. The identified MQTL, putative candidate genes, and their orthologues were validated on our previous studies conducted on rice and wheat. The research-based interventions such as improving nitrogen use efficiency via identification of major genomic regions and candidate genes can be a plausible, simple, and low-cost solution to address the challenges of the crop improvement program. Frontiers Media S.A. 2021-12-21 /pmc/articles/PMC8724540/ /pubmed/34992638 http://dx.doi.org/10.3389/fgene.2021.807210 Text en Copyright © 2021 Sandhu, Pruthi, Prakash Raigar, Singh, Phagna, Kumar, Sethi, Singh, Ade and Saini. 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 Genetics
Sandhu, Nitika
Pruthi, Gomsie
Prakash Raigar, Om
Singh, Mohini Prabha
Phagna, Kanika
Kumar, Aman
Sethi, Mehak
Singh, Jasneet
Ade, Pooja Ankush
Saini, Dinesh Kumar
Meta-QTL Analysis in Rice and Cross-Genome Talk of the Genomic Regions Controlling Nitrogen Use Efficiency in Cereal Crops Revealing Phylogenetic Relationship
title Meta-QTL Analysis in Rice and Cross-Genome Talk of the Genomic Regions Controlling Nitrogen Use Efficiency in Cereal Crops Revealing Phylogenetic Relationship
title_full Meta-QTL Analysis in Rice and Cross-Genome Talk of the Genomic Regions Controlling Nitrogen Use Efficiency in Cereal Crops Revealing Phylogenetic Relationship
title_fullStr Meta-QTL Analysis in Rice and Cross-Genome Talk of the Genomic Regions Controlling Nitrogen Use Efficiency in Cereal Crops Revealing Phylogenetic Relationship
title_full_unstemmed Meta-QTL Analysis in Rice and Cross-Genome Talk of the Genomic Regions Controlling Nitrogen Use Efficiency in Cereal Crops Revealing Phylogenetic Relationship
title_short Meta-QTL Analysis in Rice and Cross-Genome Talk of the Genomic Regions Controlling Nitrogen Use Efficiency in Cereal Crops Revealing Phylogenetic Relationship
title_sort meta-qtl analysis in rice and cross-genome talk of the genomic regions controlling nitrogen use efficiency in cereal crops revealing phylogenetic relationship
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8724540/
https://www.ncbi.nlm.nih.gov/pubmed/34992638
http://dx.doi.org/10.3389/fgene.2021.807210
work_keys_str_mv AT sandhunitika metaqtlanalysisinriceandcrossgenometalkofthegenomicregionscontrollingnitrogenuseefficiencyincerealcropsrevealingphylogeneticrelationship
AT pruthigomsie metaqtlanalysisinriceandcrossgenometalkofthegenomicregionscontrollingnitrogenuseefficiencyincerealcropsrevealingphylogeneticrelationship
AT prakashraigarom metaqtlanalysisinriceandcrossgenometalkofthegenomicregionscontrollingnitrogenuseefficiencyincerealcropsrevealingphylogeneticrelationship
AT singhmohiniprabha metaqtlanalysisinriceandcrossgenometalkofthegenomicregionscontrollingnitrogenuseefficiencyincerealcropsrevealingphylogeneticrelationship
AT phagnakanika metaqtlanalysisinriceandcrossgenometalkofthegenomicregionscontrollingnitrogenuseefficiencyincerealcropsrevealingphylogeneticrelationship
AT kumaraman metaqtlanalysisinriceandcrossgenometalkofthegenomicregionscontrollingnitrogenuseefficiencyincerealcropsrevealingphylogeneticrelationship
AT sethimehak metaqtlanalysisinriceandcrossgenometalkofthegenomicregionscontrollingnitrogenuseefficiencyincerealcropsrevealingphylogeneticrelationship
AT singhjasneet metaqtlanalysisinriceandcrossgenometalkofthegenomicregionscontrollingnitrogenuseefficiencyincerealcropsrevealingphylogeneticrelationship
AT adepoojaankush metaqtlanalysisinriceandcrossgenometalkofthegenomicregionscontrollingnitrogenuseefficiencyincerealcropsrevealingphylogeneticrelationship
AT sainidineshkumar metaqtlanalysisinriceandcrossgenometalkofthegenomicregionscontrollingnitrogenuseefficiencyincerealcropsrevealingphylogeneticrelationship