Integrating Multi-omics Data and Genomic Selection in Rice

A special issue of Plants (ISSN 2223-7747). This special issue belongs to the section "Plant Genetics, Genomics and Biotechnology".

Deadline for manuscript submissions: 31 January 2025 | Viewed by 59

Special Issue Editors

Department of Botany and Plant Sciences, University of California, Riverside, CA 92521, USA
Interests: statistical genomics; genetics; rice
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Guest Editor
College of Agronomy, Hebei Agricultural University, Baoding 071000, China
Interests: plant quantitative genetics

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Guest Editor
State Key Laboratory of Rice Biology and Breeding, China National Rice Research Institute, Hangzhou 310006, China
Interests: rice; genome

Special Issue Information

Dear Colleagues,

Genomic selection enhances hybrid rice breeding by intensifying selection and expediting breeding cycles. Beyond genomic data, technological advancements produce diverse omic datasets including transcriptomic, proteomic, and metabolomic data. Integrating these omics datasets can deepen our understanding of the genetic and biochemical foundations of agronomic traits. Multi-omics data enable the prediction of expected breeding values (EBVs) for agronomic traits and facilitate the selection of superior hybrids. However, research indicates that the optimal combinations of multi-omics data for prediction vary depending on the trait and population under consideration. Consequently, it is essential to evaluate the prediction accuracy of different omics datasets within specific populations and for targeted traits in rice breeding endeavors.

Dr. Shibo Wang
Dr. Yanru Cui
Dr. Lan Shen
Guest Editors

Manuscript Submission Information

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  • genomic selection
  • rice
  • multi-omics

Published Papers

This special issue is now open for submission.
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