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Combined Analysis of BSA-Seq Based Mapping, RNA-Seq, and Metabolomic Unraveled Candidate Genes Associated with Panicle Grain Number in Rice (Oryza sativa L.).

ABSTRACT: Rice grain yield is a complex and highly variable quantitative trait consisting of several key components, including the grain weight, the effective panicles per unit area, and the grain number per panicle (GNPP). The GNPP is a significant contributor to grain yield controlled by multiple genes (QTL) and is crucial for improvement. Attempts have been made to find genes for this trait, which has always been a challenging and arduous task through conventional methods. We combined a BSA analysis, RNA profiling, and a metabolome analysis in the present study to identify new candidate genes involved in the GNPP. The F₂ population from crossing R4233 (high GNPP) and Ce679 (low GNPP) revealed a frequency distribution fitting two segregated genes. Three pools, including low, middle, and high GNPP, were constructed and a BSA analysis revealed six candidate regions spanning 5.38 Mb, containing 739 annotated genes. Further, a conjunctive analysis of BSA-Seq and RNA-Seq showed 31 differentially expressed genes (DEGs) in the candidate intervals. Subsequently, a metabolome analysis showed 1024 metabolites, with 71 significantly enriched, including 44 up and 27 downregulated in Ce679 vs. R4233. A KEGG enrichment analysis of these 31 DEGs and 71 differentially enriched metabolites (DEMs) showed two genes, Os12g0102100 and Os01g0580500, significantly enriched in the metabolic pathways' biosynthesis of secondary metabolites, cysteine and methionine metabolism, and fatty acid biosynthesis. Os12g0102100, which encodes for the alcohol dehydrogenase superfamily and a zinc-containing protein, is a novel gene whose contribution to the GNPP is not yet elucidated. This gene coding for mitochondrial trans-2-enoyl-CoA reductase is involved in the biosynthesis of myristic acid, also known as tetradecanoic acid. The Os01g0580500 coding for the enzyme 1-aminoclopropane-1-carboxylate oxidase (OsACO7) is responsible for the final step of the ethylene biosynthesis pathway through the conversion of 1-aminocyclopropane-1-carboxylic acid (ACC) into ethylene. Unlike Os12g0102100, this gene was significantly upregulated in R4233, downregulated in Ce679, and significantly enriched in two of the three metabolite pathways. This result pointed out that these two genes are responsible for the difference in the GNPP in the two cultivars, which has never been identified. Further validation studies may disclose the physiological mechanisms through which they regulate the GNPP in rice.

SUBMITTER: Ma Y

PROVIDER: S-EPMC9313402 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Grain number per spike, a pivotal agronomic trait dictating wheat yield, lacks a comprehensive understanding of its underlying mechanism in Pubing3228, despite the identification of certain pertinent genes. Thus, our investigation sought to ascertain molecular markers and candidate regions associated with grain number per spike through a high-density genetic mapping approach that amalgamates site-specific amplified fragment sequencing (SLAF-seq) and bulked segregation analysis (BSA). To facilitate this, we conducted a comparative analysis of two wheat germplasms, Pubing3228 and Jing4839, known to exhibit marked discrepancies in spike shape. By leveraging this methodology, we successfully procured 2,810,474 SLAF tags, subsequently resulting in the identification of 187,489 single nucleotide polymorphisms (SNPs) between the parental strains. We subsequently employed the SNP-index association algorithm alongside the extended distribution (ED) association algorithm to detect regions associated with the trait. The former algorithm identified 24 trait-associated regions, whereas the latter yielded 70. Remarkably, the intersection of these two algorithms led to the identification of 25 trait-associated regions. Amongst these regions, we identified 399 annotated genes, including three genes harboring non-synonymous mutant SNP loci. Notably, the APETALA2 (AP2) transcription factor families, which exhibited a strong correlation with spike type, were also annotated. Given these findings, it is plausible to hypothesize that these genes play a critical role in determining spike shape. In summation, our study contributes significant insights into the genetic foundation of grain number per spike. The molecular markers and candidate regions we have identified can be readily employed for marker-assisted breeding endeavors, ultimately leading to the development of novel wheat cultivars possessing enhanced yield potential. Furthermore, conducting further functional analyses on the identified genes will undoubtedly facilitate a comprehensive elucidation of the underlying mechanisms governing spike development in wheat.

Project description:BackgroundRice (Oryza sativa L.) yield is seriously influenced by panicle exsertion (PE) and the uppermost internode (UI) through panicle enclosure or energy transport during grain-filling stages. We evaluated the traits of PE and UI of 205 rice accessions in two independent environments and performed genome-wide association (GWAS) to explore the key genes controlling PE and UI, which could be used to improve panicle enclosure in rice breeding.ResultsIn this study, extensive genetic variation was found in both PE and UI among the 205 rice accessions, and 10.7% of accessions had panicle enclosure (PE/UI???0). Correlation analysis revealed that PE was significantly positively correlated with 1000-grain weight (1000-GW) but negatively correlated with heading date (HD), and UI was significantly positively correlated with HD but no significantly correlated with 1000-GW. A total of 22 and 24 quantitative trait loci (QTLs) were identified for PE and UI using GWAS, respectively. Eight loci for PE and nine loci for UI were simultaneously detected both in 2015 and in 2016, seven loci had adjacent physical positions between PE and UI, and ten loci for PE and seven loci for UI were located in previously reported QTLs. Further, we identified the CYP734A4 gene, encoding a cytochrome P450 monooxygenase, and the OsLIS-L1 gene, encoding a lissencephaly type-1-like protein, as causal genes for qPE14 and qUI14, and for qPE19, respectively. PE and UI were both significantly shorter in these two genes' mutants than in WT. Allelic Hap.1/2/4 of CYP734A4 and Hap.1/2/4 of OsLIS-L1 increased PE, UI, PE/UI, and 1000-GW, but Hap.3 of CYP734A4 and Hap.3 of OsLIS-L1 reduced them. In addition, six candidate genes were also detected for four key novel loci, qPE16, qPE21, qUI1, and qUI18, that seemed to be related to PE and UI.ConclusionsOur results provide new information on the genetic architecture of PE and UI in rice, confirming that the CYP734A4 and OsLIS-L1 genes participate in PE and UI regulation, which could improve our understanding of the regulatory mechanism of PE and UI for rice breeding in the future.

Dataset Information

Combined Analysis of BSA-Seq Based Mapping, RNA-Seq, and Metabolomic Unraveled Candidate Genes Associated with Panicle Grain Number in Rice (Oryza sativa L.).

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