Dataset Information

Identification, Analysis, and Confirmation of Seed Storability-Related Loci in Dongxiang Wild Rice (Oryza rufipogon Griff.).

ABSTRACT: Dongxiang wild rice (Oryza rufipogon Griff.) (DXWR) has strong seed storability and identifying its elite gene resources may facilitate genetic improvements in rice seed storability. In this study, we developed two backcross inbred lines (BILs) populations, with DXWR as a common donor parent and two rice varieties (F6 and R974) as recipient parents. Bulked segregant analysis via whole genome sequencing (BSA-seq) was used to identify seed storability-related loci in the DXWR and F6 population. Two main genomic regions containing 18,550,000-20,870,000 bp on chromosome 4 and 7,860,000-9,780,000 bp on chromosome 9 were identified as candidate loci of DXWR seed storability; these overlapped partially with seed storability-related quantitative trait loci (QTLs) discovered in previous studies, suggesting that these loci may provide important regions for isolating the responsible genes. In total, 448 annotated genes were predicted within the identified regions, of which 274 and 82 had nonsynonymous and frameshift mutations, respectively. We detected extensive metabolic activities and cellular processes during seed storability and confirmed the effects of the seed storability-related candidate loci using four BILs from DXWR and R974. These results may facilitate the cloning of DXWR seed storability-related genes, thereby elucidating rice seed storability and its improvement potential.

SUBMITTER: Zhao M

PROVIDER: S-EPMC8622159 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BACKGROUND:Low phosphorus availability is a major factor restricting rice growth. Dongxiang wild rice (Oryza rufipogon Griff.) has many useful genes lacking in cultivated rice, including stress resistance to phosphorus deficiency, cold, salt and drought, which is considered to be a precious germplasm resource for rice breeding. However, the molecular mechanism of regulation of phosphorus deficiency tolerance is not clear. RESULTS:In this study, cDNA libraries were constructed from the leaf and root tissues of phosphorus stressed and untreated Dongxiang wild rice seedlings, and transcriptome sequencing was performed with the goal of elucidating the molecular mechanisms involved in phosphorus stress response. The results indicated that 1184 transcripts were differentially expressed in the leaves (323 up-regulated and 861 down-regulated) and 986 transcripts were differentially expressed in the roots (756 up-regulated and 230 down-regulated). 43 genes were up-regulated both in leaves and roots, 38 genes were up-regulated in roots but down-regulated in leaves, and only 2 genes were down-regulated in roots but up-regulated in leaves. Among these differentially expressed genes, the detection of many transcription factors and functional genes demonstrated that multiple regulatory pathways were involved in phosphorus deficiency tolerance. Meanwhile, the differentially expressed genes were also annotated with gene ontology terms and key pathways via functional classification and Kyoto Encyclopedia of Gene and Genomes pathway mapping, respectively. A set of the most important candidate genes was then identified by combining the differentially expressed genes found in the present study with previously identified phosphorus deficiency tolerance quantitative trait loci. CONCLUSION:The present work provides abundant genomic information for functional dissection of the phosphorus deficiency resistance of Dongxiang wild rice, which will be help to understand the biological regulatory mechanisms of phosphorus deficiency tolerance in Dongxiang wild rice.

Project description:BackgroundMicroRNAs (miRNAs) is a class of non-coding RNAs involved in post- transcriptional control of gene expression, via degradation and/or translational inhibition. Six-hundred sixty-one rice miRNAs are known that are important in plant development. However, flowering-related miRNAs have not been characterized in Oryza rufipogon Griff. It was approved by supervision department of Guangdong wild rice protection. We analyzed flowering-related miRNAs in O. rufipogon using high-throughput sequencing (deep sequencing) to understand the changes that occurred during rice domestication, and to elucidate their functions in flowering.ResultsThree O. rufipogon sRNA libraries, two vegetative stage (CWR-V1 and CWR-V2) and one flowering stage (CWR-F2) were sequenced using Illumina deep sequencing. A total of 20,156,098, 21,531,511 and 20,995,942 high quality sRNA reads were obtained from CWR-V1, CWR-V2 and CWR-F2, respectively, of which 3,448,185, 4,265,048 and 2,833,527 reads matched known miRNAs. We identified 512 known rice miRNAs in 214 miRNA families and predicted 290 new miRNAs. Targeted functional annotation, GO and KEGG pathway analyses predicted that 187 miRNAs regulate expression of flowering-related genes. Differential expression analysis of flowering-related miRNAs showed that: expression of 95 miRNAs varied significantly between the libraries, 66 are flowering-related miRNAs, such as oru-miR97, oru-miR117, oru-miR135, oru-miR137, et al. 17 are early-flowering -related miRNAs, including osa-miR160f, osa-miR164d, osa-miR167d, osa-miR169a, osa-miR172b, oru-miR4, et al., induced during the floral transition. Real-time PCR revealed the same expression patterns as deep sequencing. miRNAs targets were confirmed for cleavage by 5'-RACE in vivo, and were negatively regulated by miRNAs.ConclusionsThis is the first investigation of flowering miRNAs in wild rice. The result indicates that variation in miRNAs occurred during rice domestication and lays a foundation for further study of phase change and flowering in O. rufipogon. Complicated regulatory networks mediated by multiple miRNAs regulate the expression of flowering genes that control the induction of flowering.

Dataset Information

Identification, Analysis, and Confirmation of Seed Storability-Related Loci in Dongxiang Wild Rice (Oryza rufipogon Griff.).

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets