Identification and allele mining of new candidate genes underlying rice grain weight and grain shape by genome-wide association study.

BACKGROUND: Grain weight and grain shape are important agronomic traits that affect the grain yield potential and grain quality of rice. Both grain weight and grain shape are controlled by multiple genes. The 3,000 Rice Genomes Project (3 K RGP) greatly facilitates the discovery of agriculturally important genetic variants and germplasm resources for grain weight and grain shape. RESULTS: Abundant natural variations and distinct phenotic differentiation among the subgroups in grain weight and grain shape were observed in a large population of 2,453 accessions from the 3 K RGP. A total of 21 stable quantitative trait nucleotides (QTNs) for the four traits were consistently identified in at least two of 3-year trials by genome-wide association study (GWAS), including six new QTNs (qTGW3.1, qTGW9, qTGW11, qGL4/qRLW4, qGL10, and qRLW1) for grain weight and grain shape. We further predicted seven candidate genes (Os03g0186600, Os09g0544400, Os11g0163600, Os04g0580700, Os10g0399700, Os10g0400100 and Os01g0171000) for the six new QTNs by high-density association and gene-based haplotype analyses. The favorable haplotypes of the seven candidate genes and five previously cloned genes in elite accessions with high TGW and RLW are also provided. CONCLUSIONS: Our results deepen the understanding of the genetic basis of grain weight and grain shape in rice and provide valuable information for improving rice grain yield and grain quality through molecular breeding.

Genetic background- and environment-independent QTL and candidate gene identification of appearance quality in three MAGIC populations of rice.

Many QTL have been identified for grain appearance quality by linkage analysis (LA) in bi-parental mapping populations and by genome-wide association study (GWAS) in natural populations in rice. However, few of the well characterized genes/QTL have been successfully applied in molecular rice breeding due to genetic background (GB) and environment effects on QTL expression and deficiency of favorable alleles. In this study, GWAS and LA were performed to identify QTL for five grain appearance quality-related traits using three multi-parent advanced generation inter-cross (MAGIC) populations. A total of 22 QTL on chromosomes 1-3, 5-8 were identified by GWAS for five traits in DC1, DC2 and 8way, and four combined populations DC12 (DC1+DC2), DC18 (DC1+8way), DC28 (DC2+8way) and DC128 (DC1+DC2+8way). And a total of 42 QTL were identified on all 12 chromosomes except 10 by LA in the three single populations. Among 20 QTL identified by GWAS in DC1, DC2 and 8way, 10, four and three QTL were commonly detected in DC18, DC28, and DC128, respectively. Similarly, among 42 QTL detected by LA in the three populations, four, one and two QTL were commonly detected in DC18, DC28, and DC128, respectively. There was no QTL mapped together in DC12 by both two mapping methods, indicating that GB could greatly affect the mapping results, and it was easier to map the common QTL among populations with similar GB. The 8way population was more powerful for QTL mapping than the DC1, DC2 and various combined populations. Compared with GWAS, LA can not only identify large-effect QTL, but also identify minor-effect ones. Among 11 QTL simultaneously detected by the two methods in different GBs and environments, eight QTL corresponded to known genes, including AqGL3b and AqGLWR3a for GL and GLWR, AqGW5a, AqGLWR5, AqDEC5 and AqPGWC5 for GW, GLWR, DEC and PGWC, and AqDEC6b and AqPGWC6b for DEC and PGWC, respectively. AqGL7, AqGL3c/AqGLWR3b, AqDEC6a/AqPGWC6a, and AqPGWC7 were newly identified and their candidate genes were analyzed and inferred. It was discussed to further improve grain appearance quality through designed QTL pyramiding strategy based on the stable QTL identified in the MAGIC populations.

Genomic Architecture of Yield Performance of an Elite Rice Hybrid Revealed by its Derived Recombinant Inbred Line and Their Backcross Hybrid Populations.

BACKGROUND: Since its development and wide adoption in China, hybrid rice has reached the yield plateau for more than three decades. To understand the genetic basis of heterosis in rice and accelerate hybrid rice breeding, the yield performances of the elite rice hybrid, Quan-you-si-miao (QYSM) were genetically dissected by whole-genome sequencing, large-scale phenotyping of 1061 recombined inbred lines (RILs) and 1061 backcross F1 (BCF1) hybrids derived from QYSM's parents across three environments and gene-based analyses. RESULTS: Genome-wide scanning of 13,847 segregating genes between the parents and linkage mapping based on 855 bins across the rice genome and phenotyping experiments across three environments resulted in identification of large numbers of genes, 639 main-effect QTLs (M-QTLs) and 2736 epistatic QTLs with significant additive or heterotic effects on the trait performances of the combined population consisting of RILs and BCF1 hybrids, most of which were environment-specific. The 324 M-QTLs affecting yield components included 32.7% additive QTLs, 38.0% over-dominant or dominant ones with strong and positive effects and 29.3% under-dominant or incomplete recessive ones with significant negative heterotic effects. 63.6% of 1403 genes with allelic introgression from subspecies japonica/Geng in the parents of QYSM may have contributed significantly to the enhanced yield performance of QYSM. CONCLUSIONS: The parents of QYSM and related rice hybrids in China carry disproportionally more additive and under-dominant genes/QTLs affecting yield traits. Further focus in indica/Xian rice breeding should shift back to improving inbred varieties, while breaking yield ceiling of Xian hybrids can be achieved by one or combinations of the three strategies: (1) by pyramiding favorable alleles of additive genes, (2) by eliminating or minimizing under-dominant loci, and (3) by pyramiding overdominant/dominant genes polymorphic, particularly those underlying inter-subspecific heterosis.