PDF(Pubmed)
Abstract：
BACKGROUND: Rice (Oryza sativa L.) is one of the globally important staple food crops, and yield-related traits are prerequisites for improved breeding efficiency in rice. Here, we used six different genome-wide association study (GWAS) models for 198 accessions, with 553,229 single nucleotide markers (SNPs) to identify the quantitative trait nucleotides (QTNs) and candidate genes (CGs) governing rice yield.
RESULTS: Amongst the 73 different QTNs in total, 24 were co-localized with already reported QTLs or loci in previous mapping studies. We obtained fifteen significant QTNs, pathway analysis revealed 10 potential candidates within 100kb of these QTNs that are predicted to govern plant height, days to flowering, and plot yield in rice. Based on their superior allelic information in 20 elite and 6 inferior genotypes, we found a higher percentage of superior alleles in the elite genotypes in comparison to inferior genotypes. Further, we implemented expression analysis and enrichment analysis enabling the identification of 73 candidate genes and 25 homologues of Arabidopsis, 19 of which might regulate rice yield traits. Of these candidate genes, 40 CGs were found to be enriched in 60 GO terms of the studied traits for instance, positive regulator metabolic process (GO:0010929), intracellular part (GO:0031090), and nucleic acid binding (GO:0090079). Haplotype and phenotypic variation analysis confirmed that LOC_OS09G15770, LOC_OS02G36710 and LOC_OS02G17520 are key candidates associated with rice yield.
CONCLUSIONS: Overall, we foresee that the QTNs, putative candidates elucidated in the study could summarize the polygenic regulatory networks controlling rice yield and be useful for breeding high-yielding varieties.
RESULTS: Amongst the 73 different QTNs in total, 24 were co-localized with already reported QTLs or loci in previous mapping studies. We obtained fifteen significant QTNs, pathway analysis revealed 10 potential candidates within 100kb of these QTNs that are predicted to govern plant height, days to flowering, and plot yield in rice. Based on their superior allelic information in 20 elite and 6 inferior genotypes, we found a higher percentage of superior alleles in the elite genotypes in comparison to inferior genotypes. Further, we implemented expression analysis and enrichment analysis enabling the identification of 73 candidate genes and 25 homologues of Arabidopsis, 19 of which might regulate rice yield traits. Of these candidate genes, 40 CGs were found to be enriched in 60 GO terms of the studied traits for instance, positive regulator metabolic process (GO:0010929), intracellular part (GO:0031090), and nucleic acid binding (GO:0090079). Haplotype and phenotypic variation analysis confirmed that LOC_OS09G15770, LOC_OS02G36710 and LOC_OS02G17520 are key candidates associated with rice yield.
CONCLUSIONS: Overall, we foresee that the QTNs, putative candidates elucidated in the study could summarize the polygenic regulatory networks controlling rice yield and be useful for breeding high-yielding varieties.
摘要：
背景:水稻是全球重要的主食作物之一,和产量相关性状是提高水稻育种效率的前提。这里,我们使用了六种不同的全基因组关联研究（GWAS）模型，对198个种质，使用553,229个单核苷酸标记（SNP）来鉴定控制水稻产量的数量性状核苷酸（QTNs）和候选基因（CGs）。
结果：在总共73种不同的QTNs中，24个与先前作图研究中已经报道的QTL或基因座共定位。我们获得了15个显著的QTNs，途径分析显示，在这些QTNs的100kb内，有10个潜在的候选者被预测为控制植物高度，天开花，和水稻的地块产量。根据他们在20个精英和6个劣等基因型中的优越等位基因信息，我们发现，与劣等基因型相比，精英基因型中的优势等位基因百分比更高。Further,我们实施了表达分析和富集分析，从而鉴定了拟南芥的73个候选基因和25个同源物，其中19个可能调控水稻产量性状。在这些候选基因中，例如，发现40个CGs富含60个GO术语的研究性状，正调节代谢过程(GO:0010929)，细胞内部分（GO：0031090），和核酸结合(GO:0090079)。单倍型和表型变异分析证实，LOC_OS09G15770，LOC_OS02G36710和LOC_OS02G17520是与水稻产量相关的关键候选者。
结论：总体而言，我们预见到QTNs，研究中阐明的推定候选物可以总结控制水稻产量的多基因调控网络，并有助于育种高产品种。
结果：在总共73种不同的QTNs中，24个与先前作图研究中已经报道的QTL或基因座共定位。我们获得了15个显著的QTNs，途径分析显示，在这些QTNs的100kb内，有10个潜在的候选者被预测为控制植物高度，天开花，和水稻的地块产量。根据他们在20个精英和6个劣等基因型中的优越等位基因信息，我们发现，与劣等基因型相比，精英基因型中的优势等位基因百分比更高。Further,我们实施了表达分析和富集分析，从而鉴定了拟南芥的73个候选基因和25个同源物，其中19个可能调控水稻产量性状。在这些候选基因中，例如，发现40个CGs富含60个GO术语的研究性状，正调节代谢过程(GO:0010929)，细胞内部分（GO：0031090），和核酸结合(GO:0090079)。单倍型和表型变异分析证实，LOC_OS09G15770，LOC_OS02G36710和LOC_OS02G17520是与水稻产量相关的关键候选者。
结论：总体而言，我们预见到QTNs，研究中阐明的推定候选物可以总结控制水稻产量的多基因调控网络，并有助于育种高产品种。
