RFGB

Rice Functional Genomic and Breeding (RFGB) toolkit, version 2.0 includes five major modules, which are: Phenotype, Haplotype, SNP & InDel, Restore Sequence, and Germplasm. Their functions are described with the embedded 3K-RG data as example. Four tips of iceberg for user cases of RFGB v2.0 with corresponding technical routes were presented including: 1) exploring favorable donors for higher zinc concentration in milled grains, 2) shortlisting candidate genes for grain length with near isogenic lines, 3) mining favorable haplotypes for seedling vigor traits under paddy direct seeding system, and 4) variations and restore sequence seeking for a leaf rolling QTL region.水稻功能基因组与育种（Rice Functional Genomic and Breeding，缩写RFGB）工具包v2.0包含五大核心模块，分别为表型（Phenotype）、单倍型（Haplotype）、单核苷酸多态性与插入缺失多态性（SNP & InDel）、恢复序列（Restore Sequence）以及种质资源（Germplasm）模块。其功能以内嵌的3K-RG（3000份水稻基因组）数据作为示例进行说明。本工具包还展示了RFGB v2.0的四大典型应用案例（犹如科研应用冰山一角），并配套对应技术路线，具体包括：1）筛选精米锌富集性状的优异供体材料；2）借助近等基因系筛选粒长性状候选基因；3）挖掘稻田旱直播栽培体系下幼苗活力性状的优异单倍型；4）针对卷叶数量性状位点（Quantitative Trait Locus，QTL）区域开展变异与恢复序列挖掘。

搜集汇总

背景与挑战

背景概述

RFGB数据集是一个水稻功能基因组与育种工具包，包含表型、单倍型、SNP与InDel、恢复序列和种质资源五个核心模块。它以3K水稻基因组数据为基础，旨在促进水稻重要性状等位基因的大规模挖掘，并作为全球公共数据库支持水稻育种技术创新。