Genetic dissection of yield traits in super hybrid rice Xieyou9308 using both unconditional and conditional genome-wide association mapping

Exploring genomic regions and genes modulating plant height and flag leaf morphology in rice

Plant height and flag leaf morphology critically affect plant yield because they determine above-ground plant biomass and photosynthate production. However, few genetic basis analyses and gene mining studies on plant height, flag leaf length, and flag leaf width have been performed, and there is little available information about the evolution and utilization of the underlying natural alleles. This study conducted a genome-wide association study (GWAS) using 689 rice accessions collected from diverse regions across the globe. The GWAS identified 73, 159, and 158 significant loci associated with plant height, flag leaf length, and flag leaf width, respectively. SD1HAP1 and NAL1A were also identified as superior alleles that could be used to improve plant architecture by reducing plant height and increasing flag leaf width, respectively. LEAF1 and its elite allele LEAF1G, which simultaneously modulated plant height and flag leaf morphology, were isolated, and the LEAF1 knockout lines showed reduced flag leaf length and plant height, whereas LEAF1G-complementary lines in the LEAF1A background had the opposite phenotypes. The results also showed that LEAF1G and SD1HAP1 evolved directly from wild rice and were mainly found in the Xian subgroup, whereas NAL1A might have originated from de novo mutation during domestication and was mainly found in the Geng subgroup. A joint haplotype analysis revealed that pyramiding SD1HAP1, NAL1A, and LEAF1G in Type I accessions optimized plant architecture, reduced plant height, and enlarged the flag leaves. In addition, genomic regions and genes that had been convergently selected for these traits were identified by combining a population genetics analysis with a GWAS. These findings provide valuable genetic targets for molecular breeding that will improve plant height and flag leaf morphology in rice.

Superior haplotypes of key drought-responsive genes reveal opportunities for the development of climate-resilient rice varieties

Haplotype-based breeding is an emerging and innovative concept that enables the development of designer crop varieties by exploiting and exploring superior alleles/haplotypes among target genes to create new traits in breeding programs. In this regard, whole-genome re-sequencing of 399 genotypes (landraces and breeding lines) from the 3000 rice genomes panel (3K-RG) is mined to identify the superior haplotypes for 95 drought-responsive candidate genes. Candidate gene-based association analysis reveals 69 marker-trait associations (MTAs) in 16 genes for single plant yield (SPY) under drought stress. Haplo-pheno analysis of these 16 genes identifies superior haplotypes for seven genes associated with the higher SPY under drought stress. Our study reveals that the performance of lines possessing superior haplotypes is significantly higher (p ≤ 0.05) as measured by single plant yield (SPY), for the OsGSK1-H4, OsDSR2-H3, OsDIL1-H22, OsDREB1C-H3, ASR3-H88, DSM3-H4 and ZFP182-H4 genes as compared to lines without the superior haplotypes. The validation results indicate that a superior haplotype for the DREB transcription factor (OsDREB1C) is present in all the drought-tolerant rice varieties, while it was notably absent in all susceptible varieties. These lines carrying the superior haplotypes can be used as potential donors in haplotype-based breeding to develop high-yielding drought-tolerant rice varieties.

Superior haplotypes towards development of low glycemic index rice with preferred grain and cooking quality

Increasing trends in the occurrence of diabetes underline the need to develop low glycemic index (GI) rice with preferred grain quality. In the current study, a diverse set of 3 K sub-panel of rice consisting of 150 accessions was evaluated for resistant starch and predicted glycemic index, including nine other quality traits under transplanted situation. Significant variations were noticed among the accessions for the traits evaluated. Trait associations had shown that amylose content possess significant positive and negative association with resistant starch and predicted glycemic index. Genome-wide association studies with 500 K SNPs based on MLM model resulted in a total of 41 marker-trait associations (MTAs), which were further confirmed and validated with mrMLM multi-locus model. We have also determined the allelic effect of identified MTAs for 11 targeted traits and found favorable SNPs for 8 traits. A total of 11 genes were selected for haplo-pheno analysis to identify the superior haplotypes for the target traits where haplotypes ranges from 2 (Os10g0469000-GC) to 15 (Os06g18720-AC). Superior haplotypes for RS and PGI, the candidate gene Os06g11100 (H4-3.28% for high RS) and Os08g12590 (H13-62.52 as intermediate PGI). The identified superior donors possessing superior haplotype combinations may be utilized in Haplotype-based breeding to developing next-generation tailor-made high quality healthier rice varieties suiting consumer preference and market demand.

Haplotype analysis of key genes governing grain yield and quality traits across 3K RG panel reveals scope for the development of tailor-made rice with enhanced genetic gains

Though several genes governing various major traits have been reported in rice, their superior haplotype combinations for developing ideal variety remains elusive. In this study, haplotype analysis of 120 previously functionally characterized genes, influencing grain yield (87 genes) and grain quality (33 genes) revealed significant variations in the 3K rice genome (RG) panel. For selected genes, meta-expression analysis using already available datasets along with co-expression network provided insights at systems level. Also, we conducted candidate gene based association study for the 120 genes and identified 21 strongly associated genes governing 10-grain yield and quality traits. We report superior haplotypes upon phenotyping the subset of 3K RG panel, SD1-H8 with haplotype frequency (HF) of 30.13% in 3K RG panel, MOC1-H9 (HF: 23.08%), IPA1-H14 (HF: 6.64%), DEP3-H2 (HF: 5.59%), DEP1-H2 (HF: 37.53%), SP1-H3 (HF: 5.05%), LAX1-H5 (HF: 1.56%), LP-H13 (3.64%), OSH1-H4 (5.52%), PHD1-H14 (HF: 15.21%), AGO7-H15 (HF: 3.33%), ROC5-H2 (31.42%), RSR1-H8 (HF: 4.20%) and OsNAS3-H2 (HF: 1.00%). For heading date, Ghd7-H8 (HF: 3.08%), TOB1-H10 (HF: 4.60%) flowered early, Ghd7-H14 (HF: 42.60%), TRX1-H9 (HF: 27.97%), OsVIL3-H14 (HF: 1.72%) for medium duration flowering, while Ghd7-H6 (HF: 1.65%), SNB-H9 (HF: 9.35%) were late flowering. GS5-H4 (HF: 65.84%) attributed slender, GS5-H5 (HF: 29.00%), GW2-H2 (HF: 4.13%) were medium slender and GS5-H9 (HF: 2.15%) for bold grains. Furthermore, haplotype analysis explained possible genetic basis for superiority of selected mega-varieties. Overall, this study suggests the possibility for developing next-generation tailor-made rice with superior haplotype combinations of target genes suiting future food and nutritional demands via haplotype-based breeding.

Evaluation and Recommendations for Routine Genotyping Using Skim Whole Genome Re-sequencing in Canola

Whole genome sequencing offers genome wide, unbiased markers, and inexpensive library preparation. With the cost of sequencing decreasing rapidly, many plant genomes of modest size are amenable to skim whole genome resequencing (skim WGR). The use of skim WGR in diverse sample sets without the use of imputation was evaluated in silico in 149 canola samples representative of global diversity. Fastq files with an average of 10x coverage of the reference genome were used to generate skim samples representing 0.25x, 0.5x, 1x, 2x, 3x, 4x, and 5x sequencing coverage. Applying a pre-defined list of SNPs versus de novo SNP discovery was evaluated. As skim WGR is expected to result in some degree of insufficient allele sampling, all skim coverage levels were filtered at a range of minimum read depths from a relaxed minimum read depth of 2 to a stringent read depth of 5, resulting in 28 list-based SNP sets. As a broad recommendation, genotyping pre-defined SNPs between 1x and 2x coverage with relatively stringent depth filtering is appropriate for a diverse sample set of canola due to a balance between marker number, sufficient accuracy, and sequencing cost, but depends on the intended application. This was experimentally examined in two sample sets with different genetic backgrounds: 1x coverage of 1,590 individuals from 84 Australian spring type four-parent crosses aimed at maximizing diversity as well as one commercial F1 hybrid, and 2x coverage of 379 doubled haploids (DHs) derived from a subset of the four-parent crosses. To determine optimal coverage in a simpler genetic background, the DH sample sequence coverage was further down sampled in silico. The flexible and cost-effective nature of the protocol makes it highly applicable across a range of species and purposes.