# Large-Scale Rice Mutant Establishment and High-Throughput Mutant Manipulation Help Advance Rice Functional Genomics

## TL;DR

This paper reviews large-scale rice mutant libraries and DNA barcoding techniques to improve understanding of rice gene functions for crop improvement.

## Contribution

The paper emphasizes DNA barcoding integration for high-throughput mutant analysis in rice functional genomics.

## Key findings

- Million rice mutant lines have been established, but only 5–10% of gene functions are identified due to low-throughput methods.
- DNA barcoding enables scalable and precise pooled analysis of mutants for gene function assignment.
- Combining DNA barcoding with high-throughput phenotyping and OMICS accelerates gene function discovery.

## Abstract

Rice (Oryza sativa L.) is a stable food for over half of the world population, contributing 50–80% of the daily calorie intake. The completion of rice genome sequencing marks a significant milestone in understanding functional genomics, yet the systematic identification of gene functions remains a bottleneck for rice improvement. Large-scale mutant libraries in which the functions of genes are lost or gained (e.g., through chemical/physical treatments, T-DNA, transposons, RNAi, CRISPR/Cas9) have proven to be powerful tools for the systematic linking of genotypes to phenotypes. So far, using different mutagenesis approaches, a million mutant lines have been established and about 5–10% of the predicted rice gene functions have been identified due to the high demands of labor and low-throughput utilization. DNA-barcoding-based large-scale mutagenesis offers unprecedented precision and scalability in functional genomics. This review summarizes large-scale loss-of-function and gain-of-function mutant library development approaches and emphasizes the integration of DNA barcoding for pooled analysis. Unique DNA barcodes can be tagged to transposons/retrotransposons, DNA constructs, miRNA/siRNA, gRNA, and cDNA, allowing for pooling analysis and the assignment of functions to genes that cause phenotype alterations. In addition, the integration of high-throughput phenotyping and OMICS technologies can accelerate the identification of gene functions.