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Kumari A, Sharma D, Sharma P, Wang C, Verma V, Patil A, Imran M, Singh MP, Kumar K, Paritosh K, Caragea D, Kapoor S, Chandel G, Grover A, Jagadish SVK, Katiyar-Agarwal S, Agarwal M. Meta-QTL and haplo-pheno analysis reveal superior haplotype combinations associated with low grain chalkiness under high temperature in rice. Front Plant Sci 2023; 14:1133115. [PMID: 36968399 PMCID: PMC10031497 DOI: 10.3389/fpls.2023.1133115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 02/17/2023] [Indexed: 06/18/2023]
Abstract
Chalk, an undesirable grain quality trait in rice, is primarily formed due to high temperatures during the grain-filling process. Owing to the disordered starch granule structure, air spaces and low amylose content, chalky grains are easily breakable during milling thereby lowering head rice recovery and its market price. Availability of multiple QTLs associated with grain chalkiness and associated attributes, provided us an opportunity to perform a meta-analysis and identify candidate genes and their alleles contributing to enhanced grain quality. From the 403 previously reported QTLs, 64 Meta-QTLs encompassing 5262 non-redundant genes were identified. MQTL analysis reduced the genetic and physical intervals and nearly 73% meta-QTLs were narrower than 5cM and 2Mb, revealing the hotspot genomic regions. By investigating expression profiles of 5262 genes in previously published datasets, 49 candidate genes were shortlisted on the basis of their differential regulation in at least two of the datasets. We identified non-synonymous allelic variations and haplotypes in 39 candidate genes across the 3K rice genome panel. Further, we phenotyped a subset panel of 60 rice accessions by exposing them to high temperature stress under natural field conditions over two Rabi cropping seasons. Haplo-pheno analysis uncovered haplotype combinations of two starch synthesis genes, GBSSI and SSIIa, significantly contributing towards the formation of grain chalk in rice. We, therefore, report not only markers and pre-breeding material, but also propose superior haplotype combinations which can be introduced using either marker-assisted breeding or CRISPR-Cas based prime editing to generate elite rice varieties with low grain chalkiness and high HRY traits.
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Affiliation(s)
- Anita Kumari
- Department of Botany, University of Delhi, Delhi, India
| | - Divya Sharma
- Department of Botany, University of Delhi, Delhi, India
| | - Priya Sharma
- Department of Botany, University of Delhi, Delhi, India
| | - Sahil
- Department of Botany, University of Delhi, Delhi, India
| | - Chaoxin Wang
- Department of Computer Science, Kansas State University, Manhattan, KS, United States
| | - Vibha Verma
- Department of Plant Molecular Biology, University of Delhi, New Delhi, India
| | - Arun Patil
- Department of Plant Molecular Biology and Biotechnology, Indira Gandhi Krishi Vishwavidyalaya, Chattisgarh, India
| | - Md Imran
- Department of Botany, University of Delhi, Delhi, India
| | - Madan Pal Singh
- Division of Plant Physiology, Indian Council of Agricultural Research (ICAR), New Delhi, India
| | - Kuldeep Kumar
- National Institute for Plant Biotechnology, Indian Council of Agricultural Research (ICAR), New Delhi, India
| | - Kumar Paritosh
- Centre for Genetic Manipulation of Crop Plants, New Delhi, India
| | - Doina Caragea
- Department of Computer Science, Kansas State University, Manhattan, KS, United States
| | - Sanjay Kapoor
- Department of Plant Molecular Biology, University of Delhi, New Delhi, India
| | - Girish Chandel
- Department of Plant Molecular Biology and Biotechnology, Indira Gandhi Krishi Vishwavidyalaya, Chattisgarh, India
| | - Anil Grover
- Department of Plant Molecular Biology, University of Delhi, New Delhi, India
| | | | | | - Manu Agarwal
- Department of Botany, University of Delhi, Delhi, India
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Arriagada O, Gadaleta A, Marcotuli I, Maccaferri M, Campana M, Reveco S, Alfaro C, Matus I, Schwember AR. A comprehensive meta-QTL analysis for yield-related traits of durum wheat (Triticum turgidum L. var. durum) grown under different water regimes. Front Plant Sci 2022; 13:984269. [PMID: 36147234 PMCID: PMC9486101 DOI: 10.3389/fpls.2022.984269] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 08/18/2022] [Indexed: 05/13/2023]
Abstract
Abiotic stress strongly affects yield-related traits in durum wheat, in particular drought is one of the main environmental factors that have effect on grain yield and plant architecture. In order to obtain new genotypes well adapted to stress conditions, the highest number of desirable traits needs to be combined in the same genotype. In this context, hundreds of quantitative trait loci (QTL) have been identified for yield-related traits in different genetic backgrounds and environments. Meta-QTL (MQTL) analysis is a useful approach to combine data sets and for creating consensus positions for the QTL detected in independent studies for the reliability of their location and effects. MQTL analysis is a useful method to dissect the genetic architecture of complex traits, which provide an extensive allelic coverage, a higher mapping resolution and allow the identification of putative molecular markers useful for marker-assisted selection (MAS). In the present study, a complete and comprehensive MQTL analysis was carried out to identify genomic regions associated with grain-yield related traits in durum wheat under different water regimes. A total of 724 QTL on all 14 chromosomes (genomes A and B) were collected for the 19 yield-related traits selected, of which 468 were reported under rainfed conditions, and 256 under irrigated conditions. Out of the 590 QTL projected on the consensus map, 421 were grouped into 76 MQTL associated with yield components under both irrigated and rainfed conditions, 12 genomic regions containing stable MQTL on all chromosomes except 1A, 4A, 5A, and 6B. Candidate genes associated to MQTL were identified and an in-silico expression analysis was carried out for 15 genes selected among those that were differentially expressed under drought. These results can be used to increase durum wheat grain yields under different water regimes and to obtain new genotypes adapted to climate change.
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Affiliation(s)
- Osvin Arriagada
- Departamento de Ciencias Vegetales, Facultad de Agronomía e Ingeniería Forestal, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Agata Gadaleta
- Department of Agricultural and Environmental Science, University of Bari Aldo Moro, Bari, Italy
| | - Ilaria Marcotuli
- Department of Agricultural and Environmental Science, University of Bari Aldo Moro, Bari, Italy
| | - Marco Maccaferri
- Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Matteo Campana
- Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy
| | - Samantha Reveco
- Departamento de Ciencias Vegetales, Facultad de Agronomía e Ingeniería Forestal, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Christian Alfaro
- Centro Regional Rayentue, Instituto de Investigaciones Agropecuarias (INIA), Rengo, Chile
| | - Iván Matus
- Centro Regional Quilamapu, Instituto de Investigaciones Agropecuarias (INIA), Chillán, Chile
| | - Andrés R. Schwember
- Departamento de Ciencias Vegetales, Facultad de Agronomía e Ingeniería Forestal, Pontificia Universidad Católica de Chile, Santiago, Chile
- *Correspondence: Andrés R. Schwember,
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