KRISHI
ICAR RESEARCH DATA REPOSITORY FOR KNOWLEDGE MANAGEMENT
(An Institutional Publication and Data Inventory Repository)
"Not Available": Please do not remove the default option "Not Available" for the fields where metadata information is not available
"1001-01-01": Date not available or not applicable for filling metadata infromation
"1001-01-01": Date not available or not applicable for filling metadata infromation
Please use this identifier to cite or link to this item:
http://krishi.icar.gov.in/jspui/handle/123456789/81701
Title: | Unraveling the genetic framework associated with grain quality and yield-related traits in maize (Zea mays L.) |
Other Titles: | Not Available |
Authors: | Mehak Sethi, Dinesh Kumar Saini, Veena Devi, Charanjeet Kaur, Mohini Prabha Singh, Jasneet Singh, Gomsie Pruthi, Amanpreet Kaur, Alla Singh & Dharam Paul Chaudhary |
ICAR Data Use Licennce: | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf |
Author's Affiliated institute: | NIL |
Published/ Complete Date: | 2023-08-07 |
Project Code: | Not Available |
Keywords: | maize, yield, quality, meta-QTLs, breeder-friendly, candidate genes |
Publisher: | Frontiers in Genetics |
Citation: | Sethi M, Saini DK, Devi V, Kaur C, Singh MP, Singh J, Pruthi G, Kaur A, Singh A and Chaudhary DP (2023), Unravelling the genetic framework associated with grain quality and yield related traits in maize (Zea mays L.). Front. Genet. 14:1248697. doi: 10.3389/fgene.2023.1248697 |
Series/Report no.: | Not Available; |
Abstract/Description: | Maize serves as a crucial nutrient reservoir for a significant portion of the global population. However, to effectively address the growing world population’s hidden hunger, it is essential to focus on two key aspects: biofortification of maize and improving its yield potential through advanced breeding techniques. Moreover, the coordination of multiple targets within a single breeding program poses a complex challenge. This study compiled mapping studies conducted over the past decade, identifying quantitative trait loci associated with grain quality and yield related traits in maize. Meta-QTL analysis of 2,974 QTLs for 169 component traits (associated with quality and yield related traits) revealed 68 MQTLs across different genetic backgrounds and environments. Most of these MQTLs were further validated using the data from genome-wide association studies (GWAS). Further, ten MQTLs, referred to as breeding-friendly MQTLs (BF-MQTLs), with a significant phenotypic variation explained over 10% and confidence interval less than 2 Mb, were shortlisted. BF-MQTLs were further used to identify potential candidate genes, including 59 genes encoding important proteins/products involved in essential metabolic pathways. Five BF-MQTLs associated with both quality and yield traits were also recommended to be utilized in future breeding programs. Synteny analysis with wheat and rice genomes revealed conserved regions across the genomes, indicating these hotspot regions as validated targets for developing biofortified, high-yielding maize varieties in future breeding programs. After validation, the identified candidate genes can also be utilized to effectively model the plant architecture and enhance desirable quality traits through various approaches such as marker-assisted breeding, genetic engineering, and genome editing. |
Description: | Not Available |
ISSN: | Not Available |
Type(s) of content: | Research Paper |
Sponsors: | Not Available |
Language: | English |
Name of Journal: | Frontiers in Genetics |
Journal Type: | Included NAAS Journal |
NAAS Rating: | 9.70 |
Impact Factor: | 3.70 |
Volume No.: | Not Available |
Page Number: | 15 |
Name of the Division/Regional Station: | Not Available |
Source, DOI or any other URL: | DOI 10.3389/fgene.2023.1248697 |
URI: | http://krishi.icar.gov.in/jspui/handle/123456789/81701 |
Appears in Collections: | CS-IIMR-Publication |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Unraveling_Front_Genet_Mehak.pdf | 2.92 MB | Adobe PDF | View/Open |
Items in KRISHI are protected by copyright, with all rights reserved, unless otherwise indicated.