Dataset Information

Profiling Alternative 3' Untranslated Regions in Sorghum using RNA-seq Data.

ABSTRACT: Sorghum is an important crop widely used for food, feed, and fuel. Transcriptome-wide studies of 3' untranslated regions (3'UTR) using regular RNA-seq remain scarce in sorghum, while transcriptomes have been characterized extensively using Illumina short-read sequencing platforms for many sorghum varieties under various conditions or developmental contexts. 3'UTR is a critical regulatory component of genes, controlling the translation, transport, and stability of messenger RNAs. In the present study, we profiled the alternative 3'UTRs at the transcriptome level in three genetically related but phenotypically contrasting lines of sorghum: Rio, BTx406, and R9188. A total of 1,197 transcripts with alternative 3'UTRs were detected using RNA-seq data. Their categorization identified 612 high-confidence alternative 3'UTRs. Importantly, the high-confidence alternative 3'UTR genes significantly overlapped with the genesets that are associated with RNA N6-methyladenosine (m6A) modification, suggesting a clear indication between alternative 3'UTR and m6A methylation in sorghum. Moreover, taking advantage of sorghum genetics, we provided evidence of genotype specificity of alternative 3'UTR usage. In summary, our work exemplifies a transcriptome-wide profiling of alternative 3'UTRs using regular RNA-seq data in non-model crops and gains insights into alternative 3'UTRs and their genotype specificity.

SUBMITTER: Tu M

PROVIDER: S-EPMC7649775 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Profiling Alternative 3' Untranslated Regions in Sorghum using RNA-seq Data.

Tu Min M Li Yin Y

Frontiers in genetics 20201026

<i>Sorghum</i> is an important crop widely used for food, feed, and fuel. Transcriptome-wide studies of 3' untranslated regions (3'UTR) using regular RNA-seq remain scarce in sorghum, while transcriptomes have been characterized extensively using Illumina short-read sequencing platforms for many sorghum varieties under various conditions or developmental contexts. 3'UTR is a critical regulatory component of genes, controlling the translation, transport, and stability of messenger RNAs. In the pr ...[more]

PMID: 33193635

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Project description:UNLABELLED: BACKGROUND:Second generation RNA sequencing technology (RNA-seq) offers the potential to interrogate genome-wide differential RNA splicing in cancer. However, since short RNA reads spanning spliced junctions cannot be mapped contiguously onto to the chromosomes, there is a need for methods to profile splicing from RNA-seq data. Before the invent of RNA-seq technologies, microarrays containing probe sequences representing exon-exon junctions of known genes have been used to hybridize cellular RNAs for measuring context-specific differential splicing. Here, we extend this approach to detect tumor-specific splicing in prostate cancer from a RNA-seq dataset. METHOD:A database, SPEventH, representing probe sequences of under a million non-redundant splice events in human is created with exon-exon junctions of optimized length for use as virtual microarray. SPEventH is used to map tens of millions of reads from matched tumor-normal samples from ten individuals with prostate cancer. Differential counts of reads mapped to each event from tumor and matched normal is used to identify statistically significant tumor-specific splice events in prostate. RESULTS:We find sixty-one (61) splice events that are differentially expressed with a p-value of less than 0.0001 and a fold change of greater than 1.5 in prostate tumor compared to the respective matched normal samples. Interestingly, the only evidence, EST (BF372485), in the public database for one of the tumor-specific splice event joining one of the intron in KLK3 gene to an intron in KLK2, is also derived from prostate tumor-tissue. Also, the 765 events with a p-value of less than 0.001 is shown to cluster all twenty samples in a context-specific fashion with few exceptions stemming from low coverage of samples. CONCLUSIONS:We demonstrate that virtual microarray experiments using a non-redundant database of splice events in human is both efficient and sensitive way to profile genome-wide splicing in biological samples and to detect tumor-specific splicing signatures in datasets from RNA-seq technologies. The signature from the large number of splice events that could cluster tumor and matched-normal samples into two tight separate clusters, suggests that differential splicing is yet another RNA phenotype, alongside gene expression and SNPs, that can be exploited for tumor stratification.

Dataset Information

Profiling Alternative 3' Untranslated Regions in Sorghum using RNA-seq Data.

Publications

Profiling Alternative 3' Untranslated Regions in Sorghum using RNA-seq Data.

Similar Datasets

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