In:
Science, American Association for the Advancement of Science (AAAS), Vol. 385, No. 6704 ( 2024-07-05)
Abstract:
The molecular basis of phenotypic variation has long been one of the core endeavors in genetics. In plants, most traits are cooperatively controlled by multiple genes. Besides the additive effects of each individual gene, there are often genetic interactions among genes leading to complex epistatic effects. Although many genes have been functionally identified, a global view of genetic architecture—including the number of genes affecting a trait as well as genetic effects and their interactions with each other—remains lacking in most plants. RATIONALE The advent of new genomics technologies and quantitative genetics methods has greatly facilitated the characterization of genetic architecture. Nonetheless, the power is strongly affected by size, diversity, and structure of the genetic population used. The allelic frequencies of most genes and their digenic combinations are highly skewed in natural populations. Less-structured experimental populations can give rise to more informative allelic combinations and are more suitable for genetic mapping, epistatic interaction detection, and genetic effect evaluation. However, to date, both genetic diversity and sample size of experimental populations in most plants are relatively limited and not sufficient to perform a powerful and reliable characterization. RESULTS We developed a large permanent population in rice [18,421 lines (18K-rice)], using an approach designed to reduce population structure. We generated reference-level genome assemblies for the founders and obtained high-density genotypes of all 18K-rice lines through whole-genome sequencing. In total, we mapped 1207 quantitative trait loci (QTL) for 16 agronomic traits and developed an integrated genomics method [rice genome-wide association study to gene (RiceG2G)] to prioritize causal genes. Out of 1207 QTL, 28.0% contained known genes. For panicle number and heading date we experimentally validated two newly identified causal genes, OsMADS22 and OsFTL1 . Furthermore, we constructed a genetic interactome using 18K-rice in which 170 masking genes were implicated in the cause of genetic background effects. We estimated that the additive and epistatic effects of the identified QTL collectively explained 49.9 and 2.2% of phenotypic variation, respectively. By contrast, the genomic heritability accounting for the additive and epistatic effects was estimated to be 56.2 and 8.8%, respectively. CONCLUSION The genetic mapping work suggests that previously identified quantitative trait genes are a small proportion of the total set in rice. Extensive quantitative and functional genomics studies for various traits are still required to further extend the gene list. Regarding overall genetic architecture, additive effects are the main force in shaping rice traits and the genotype-to-phenotype relationship becomes complex in the presence of numerous genetic interactions. Specially, masking alleles in epistasis pairs are prevalent in rice, making a significant genetic background effect. These findings advance our understanding of rice genetics and plants in general. An atlas of genetic architecture of rice traits using a large permanent population. A number of QTL and epistatic QTL pairs were identified, with additive and epistatic effects estimated.
Type of Medium:
Online Resource
ISSN:
0036-8075
,
1095-9203
DOI:
10.1126/science.adm8762
Language:
English
Publisher:
American Association for the Advancement of Science (AAAS)
Publication Date:
2024
detail.hit.zdb_id:
128410-1
detail.hit.zdb_id:
2066996-3
SSG:
11
Permalink
