Transcriptome-wide association analyses reveal the impact of regulatory variants on rice panicle architecture and causal gene regulatory networks.

Panicle architecture is a key determinant of rice grain yield and is mainly determined at the 1-2 mm young panicle stage. Here, we investigated the transcriptome of the 1-2 mm young panicles from 275 rice varieties and identified thousands of genes whose expression levels were associated with panicle traits. Multimodel association studies suggested that many small-effect genetic loci determine spikelet per panicle (SPP) by regulating the expression of genes associated with panicle traits. We found that alleles at cis-expression quantitative trait loci of SPP-associated genes underwent positive selection, with a strong preference for alleles increasing SPP. We further developed a method that integrates the associations of cis- and trans-expression components of genes with traits to identify causal genes at even small-effect loci and construct regulatory networks. We identified 36 putative causal genes of SPP, including SDT (MIR156j) and OsMADS17, and inferred that OsMADS17 regulates SDT expression, which was experimentally validated. Our study reveals the impact of regulatory variants on rice panicle architecture and provides new insights into the gene regulatory networks of panicle traits.

Fixation of hybrid sterility genes and favorable alleles of key yield-related genes with dominance contribute to the high yield of the Yongyou series of intersubspecific hybrid rice.

In rice, the Yongyou series of Xian-Geng intersubspecific hybrids have excellent production performance, as shown by their extremely high yield. However, the mechanisms underlying the success of these rice hybrids are unclear. In this study, three F2 populations are generated from three Yongyou hybrids to determine the genetic basis of the extremely high yield of intersubspecific hybrids. Genome constitution analysis reveals that the female and male parental lines belong to the Geng and Xian subspecies, respectively, although introgression of 20% of the Xian ancestry and 14% of the Geng ancestry are observed. Twenty-five percent of the hybrid genomes carries homozygous Xian or Geng fragments, which harbors hybrid sterility genes such as Sd, Sc, f5, and qS12 and favorable alleles of key yield-related genes, including NAL1, Ghd7, and Ghd8. None of the parents carries the S5+ killer of the S5 killer-protector system. Compatible allele combinations of hybrid sterility genes ensure the fertility of these intersubspecific hybrids and overcome the bottleneck in applying intersubspecific hybrids. Additive effects of favorable alleles of yield-related genes fixed in both parents enhances midparent values. Many QTLs for yield and its key component spikelets per panicle shows dominance and the net positive dominant effects lead to heterosis. These factors result in an extremely high yield of the hybrids. These findings will aid in the development of new intersubspecific rice hybrids with diverse genetic backgrounds.

An inferred functional impact map of genetic variants in rice.

Interpreting the functional impacts of genetic variants (GVs) is an important challenge for functional genomic studies in crops and next-generation breeding. Previous studies in rice (Oryza sativa) have focused mainly on the identification of GVs, whereas systematic functional annotation of GVs has not yet been performed. Here, we present a functional impact map of GVs in rice. We curated haplotype information for 17 397 026 GVs from sequencing data of 4726 rice accessions. We quantitatively evaluated the effects of missense mutations in coding regions in each haplotype based on the conservation of amino acid residues and obtained the effects of 918 848 non-redundant missense GVs. Furthermore, we generated high-quality chromatin accessibility (CA) data from six representative rice tissues and used these data to train deep convolutional neural network models to predict the impacts of 5 067 405 GVs for CA in regulatory regions. We characterized the functional properties and tissue specificity of the GV effects and found that large-effect GVs in coding and regulatory regions may be subject to selection in different directions. Finally, we demonstrated how the functional impact map could be used to prioritize causal variants in mapping populations. This impact map will be a useful resource for accelerating gene cloning and functional studies in rice, and can be freely queried in RiceVarMap V2.0 (http://ricevarmap.ncpgr.cn).