Unravelling the genetic framework associated with grain quality and yield-related traits in maize (Zea mays L.)
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 bre...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-08-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2023.1248697/full |
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| author | Mehak Sethi Dinesh Kumar Saini Veena Devi Charanjeet Kaur Mohini Prabha Singh Jasneet Singh Gomsie Pruthi Amanpreet Kaur Alla Singh Dharam Paul Chaudhary |
| author_facet | Mehak Sethi Dinesh Kumar Saini Veena Devi Charanjeet Kaur Mohini Prabha Singh Jasneet Singh Gomsie Pruthi Amanpreet Kaur Alla Singh Dharam Paul Chaudhary |
| author_sort | Mehak Sethi |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-09T00:01:32Z |
| format | Article |
| id | doaj.art-0404eb4f23ca4f4482dda4cbfd6d9cbe |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-03-09T00:01:32Z |
| publishDate | 2023-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-0404eb4f23ca4f4482dda4cbfd6d9cbe2023-12-12T16:03:16ZengFrontiers Media S.A.Frontiers in Genetics1664-80212023-08-011410.3389/fgene.2023.12486971248697Unravelling the genetic framework associated with grain quality and yield-related traits in maize (Zea mays L.)Mehak Sethi0Dinesh Kumar Saini1Veena Devi2Charanjeet Kaur3Mohini Prabha Singh4Jasneet Singh5Gomsie Pruthi6Amanpreet Kaur7Alla Singh8Dharam Paul Chaudhary9Division of Biochemistry, Indian Institute of Maize Research, Ludhiana, Punjab, IndiaDepartment of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, Punjab, IndiaDivision of Biochemistry, Indian Institute of Maize Research, Ludhiana, Punjab, IndiaDepartment of Basic Sciences and Humanities, Punjab Agricultural University, Ludhiana, Punjab, IndiaDepartment of Floriculture and Landscaping, Punjab Agricultural University, Ludhiana, Punjab, IndiaAgricultural and Environmental Sciences, Macdonald Campus, McGill University, Montreal, QC, CanadaDepartment of Biotechnology, Punjab Agricultural University, Ludhiana, Punjab, IndiaDivision of Biochemistry, Indian Institute of Maize Research, Ludhiana, Punjab, IndiaDivision of Biochemistry, Indian Institute of Maize Research, Ludhiana, Punjab, IndiaDivision of Biochemistry, Indian Institute of Maize Research, Ludhiana, Punjab, IndiaMaize 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.https://www.frontiersin.org/articles/10.3389/fgene.2023.1248697/fullmaizeyieldqualitymeta-QTLsbreeder-friendlycandidate genes |
| spellingShingle | Mehak Sethi Dinesh Kumar Saini Veena Devi Charanjeet Kaur Mohini Prabha Singh Jasneet Singh Gomsie Pruthi Amanpreet Kaur Alla Singh Dharam Paul Chaudhary Unravelling the genetic framework associated with grain quality and yield-related traits in maize (Zea mays L.) Frontiers in Genetics maize yield quality meta-QTLs breeder-friendly candidate genes |
| title | Unravelling the genetic framework associated with grain quality and yield-related traits in maize (Zea mays L.) |
| title_full | Unravelling the genetic framework associated with grain quality and yield-related traits in maize (Zea mays L.) |
| title_fullStr | Unravelling the genetic framework associated with grain quality and yield-related traits in maize (Zea mays L.) |
| title_full_unstemmed | Unravelling the genetic framework associated with grain quality and yield-related traits in maize (Zea mays L.) |
| title_short | Unravelling the genetic framework associated with grain quality and yield-related traits in maize (Zea mays L.) |
| title_sort | unravelling the genetic framework associated with grain quality and yield related traits in maize zea mays l |
| topic | maize yield quality meta-QTLs breeder-friendly candidate genes |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2023.1248697/full |
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