A systems breeding framework integrating pangenomics multiomics phenomics and precision genome editing for reproductive stage drought resilience in rice

Abstract Rice ( Oryza sativa L.) is highly vulnerable to drought during the reproductive phase, with yield losses exceeding 50% due to spikelet sterility, pollen abortion, and impaired grain filling. Progress through conventional breeding has been constrained by the polygenic nature of drought tolerance and by strong genotype × environment (G × E) interactions. This review proposes a systems breeding strategy integrating five complementary approaches rice pangenomics, genome-wide association studies (GWAS), genomic selection (GS), high-throughput phenomics, and precision genome editing to strengthen drought resilience at the reproductive stage. Structural variants identified through pangenome analyses across diverse Oryza accessions have been implicated in abscisic acid (ABA) signalling, osmolyte biosynthesis, antioxidant defence, and root system architecture pathways central to reproductive-stage drought adaptation. Multi-omics-informed GWAS, combined with co-localisation of eQTLs and protein QTLs in drought-stressed reproductive tissues, highlights high-confidence candidate genes including OsNAC14 , OsbZIP23 , and DRO1 that help explain the physiological basis of water-deficit adaptation. Incorporating envirotyping data into GS models has been shown to improve predictive accuracy across diverse rainfed environments. Alongside marker-assisted selection, base editing and prime editing enable targeted allelic refinement with minimal off-target effects. We present a proposed tiered candidate prioritisation pipeline that advances loci supported by convergent genomic, transcriptomic, proteomic, and field-level evidence toward practical breeding deployment. Translating these discoveries into climate-resilient varieties will require FAIR data sharing, coordinated phenotyping networks, and multi-environment validation platforms linking genomic discovery to scalable breeding pipelines for drought-resistant, high-yielding rice in rainfed systems.

Authors

Institutions

Publication Details

Journal
Discover Plants.
Published
2026-08-24
DOI
https://doi.org/10.1007/s44372-026-00844-1
Primary Topic
Genetic Mapping and Diversity in Plants and Animals
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A systems breeding framework integrating pangenomics multiomics phenomics and precision genome editing for reproductive stage drought resilience in rice

Kumar Ujjwal
Discover Plants.
Genetic Mapping and Diversity in Plants and Animals
article

A systems breeding framework integrating pangenomics multiomics phenomics and precision genome editing for reproductive stage drought resilience in rice

Kumar Ujjwal
article en

Abstract

Abstract Rice ( Oryza sativa L.) is highly vulnerable to drought during the reproductive phase, with yield losses exceeding 50% due to spikelet sterility, pollen abortion, and impaired grain filling. Progress through conventional breeding has been constrained by the polygenic nature of drought tolerance and by strong genotype × environment (G × E) interactions. This review proposes a systems breeding strategy integrating five complementary approaches rice pangenomics, genome-wide association studies (GWAS), genomic selection (GS), high-throughput phenomics, and precision genome editing to strengthen drought resilience at the reproductive stage. Structural variants identified through pangenome analyses across diverse Oryza accessions have been implicated in abscisic acid (ABA) signalling, osmolyte biosynthesis, antioxidant defence, and root system architecture pathways central to reproductive-stage drought adaptation. Multi-omics-informed GWAS, combined with co-localisation of eQTLs and protein QTLs in drought-stressed reproductive tissues, highlights high-confidence candidate genes including OsNAC14 , OsbZIP23 , and DRO1 that help explain the physiological basis of water-deficit adaptation. Incorporating envirotyping data into GS models has been shown to improve predictive accuracy across diverse rainfed environments. Alongside marker-assisted selection, base editing and prime editing enable targeted allelic refinement with minimal off-target effects. We present a proposed tiered candidate prioritisation pipeline that advances loci supported by convergent genomic, transcriptomic, proteomic, and field-level evidence toward practical breeding deployment. Translating these discoveries into climate-resilient varieties will require FAIR data sharing, coordinated phenotyping networks, and multi-environment validation platforms linking genomic discovery to scalable breeding pipelines for drought-resistant, high-yielding rice in rainfed systems.

Discover Plants.Vol. 3(1)
Indira Gandhi Agricultural University (IN)
Climate action
Openalex Percentile: Top 10%
Genetic Mapping and Diversity in Plants and Animals
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.