ArticleBiomolecules2022
Combined Analysis of BSA-Seq Based Mapping, RNA-Seq, and Metabolomic Unraveled Candidate Genes Associated with Panicle Grain Number in Rice (
Article in Biomolecules, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 13 citations in OpenAlex.
- Multi-Omics Integration Unravels the Genetic and Hormonal Regulatory Mechanisms Underlying Increased Main Stem Node Number in Soybean.Plants (Basel, Switzerland) · 2026Article
- Identifying Candidate Genes for Cotton Fruit Branch Length Using BSA-Seq and RNA-Seq.Plants (Basel, Switzerland) · 2026Article
- Article
- Light-Regulated Gene Expression Patterns During Conidial Formation inCurrent issues in molecular biology · 2025Article
- Article
- Conjunctive Analysis of BSA-Seq and SSR Markers Unveil the Candidate Genes for Resistance to Rice False Smut.Biomolecules · 2024Article
- Combined BSA-Seq and RNA-Seq Reveal Genes Associated with the Visual Stay-Green of Maize (International journal of molecular sciences · 2023Article
- New Genes Identified as Modulating Salt Tolerance in Maize Seedlings Using the Combination of Transcriptome Analysis and BSA.Plants (Basel, Switzerland) · 2023Article
- Detection of QTLs Regulating Six Agronomic Traits of Rice Based on Chromosome Segment Substitution Lines of Common Wild Rice (Biomolecules · 2022Article
- Molecular-Genetic Basis of Plant Breeding.Biomolecules · 2022Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Rice grain yield is a complex and highly variable quantitative trait consisting of several key components, including the grain weight, the effective panicles per unit area, and the grain number per panicle (GNPP). The GNPP is a significant contributor to grain yield controlled by multiple genes (QTL) and is crucial for improvement. Attempts have been made to find genes for this trait, which has always been a challenging and arduous task through conventional methods. We combined a BSA analysis, RNA profiling, and a metabolome analysis in the present study to identify new candidate genes involved in the GNPP. The F
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Registered trials
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