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A global view of the complexity of the porcine transcriptome using a full-sib pair with extreme phenotypes in growth and fat deposit by deep RNA sequencing

ABSTRACT: A global view of the complexity of the porcine transcriptome using a full-sib pair with extreme phenotypes in growth and fat deposit by deep RNA sequencing

PROVIDER: PRJNA136243 | ENA |

REPOSITORIES: ENA

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A global view of the complexity of the porcine transcriptome using a full-sib pair with extreme phenotypes in growth and fat deposit by deep RNA sequencing (small RNA)

Project description:Pig is the important animal model for human obesity and diseases. However, the complexity of the porcine transcriptome is not yet fully elucidated. Here we have used massively parallel high-throughput sequencing of cDNA (RNA-seq) to generate a high-resolution map of the porcine miRNA in liver (LI), longissimus dorsi (LD) and abdominal fat (AF) from a F2 female full-sib pair with extreme phenotypes on growth and fat deposit. Through small RNA sequencing and on the basis of miRbase15.0, we detected a total of 184 mature miRNAs and 164 unique porcine novel miRNAs. Some conserved miRNAs, such as miR-122, miR-1, miR-206 and let-7 family showed high expression level in this study. Finally, we identified 10, 20 and 63 differentially expressed miRNAs, respectively, in LI, LD and AF. This high resolution and comprehensive transcriptome analysis significantly enhances the current genome annotation of pigs. examining the complexity of pig transcriptome in three organs from a female full-sib pair

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A global view of the complexity of the porcine transcriptome using a full-sib pair with extreme phenotypes in growth and fat deposit by deep RNA sequencing (mRNA)

Project description:Pig is an important animal model for human obesity and diseases. However, the complexity of the porcine transcriptome is not yet fully elucidated. Here we have used massively parallel high-throughput sequencing of cDNA (RNA-Seq) to generate a high-resolution map of the porcine transcriptome and miRNA in liver (LI), longissimus dorsi (LD) and abdominal fat (AF) from an F2 female full-sib pair with extreme phenotypes in growth and fat deposit. On the basis of the porcine annotated genes against the UCSC database, we identified 21,414 annotated genes in our RNA-Seq analysis and 48,045-122,931 novel transcript fragments, which could be clustered into 17,085-29,499 novel transcriptional active regions (nTARs). We found that ~18.8% of the detected known genes showed alternative splicing patterns, and alternative 3’ splicing was the most common type of alternative splicing events in pigs. We also detected that more than 22.7% of the known genes identified here were extended at their 5’ and/or 3’ end. We identified 2,796, 1,551 and 835 differentially expressed genes (DEGs), respectively, in AF, LI and LD between the two individuals. Examining the complexity of the pig transcriptome in three organs (liver, abdominal fat, longissimus dorsi muscle) from a female full-sib pair.

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A global view of the complexity of the porcine transcriptome using a full-sib pair with extreme phenotypes in growth and fat deposit by deep RNA sequencing (small RNA)

2010-12-20 | GSE25923 | GEO

A global view of the complexity of the porcine transcriptome using a full-sib pair with extreme phenotypes in growth and fat deposit by deep RNA sequencing (mRNA)

2011-01-12 | GSE26382 | GEO

A global view of the complexity of the porcine transcriptome using a full-sib pair with extreme phenotypes in growth and fat deposit by deep RNA sequencing

Project description:This SuperSeries is composed of the SubSeries listed below.

2011-01-12 | GSE26572 | GEO

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Project description:A global view of the complexity of the porcine transcriptome using a full-sib pair with extreme phenotypes in growth and fat deposit by deep RNA sequencing (mRNA)

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Project description:A global view of the complexity of the porcine transcriptome using a full-sib pair with extreme phenotypes in growth and fat deposit by deep RNA sequencing (small RNA)

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Project description:High throughput RNA sequencing (RNA-seq) using cDNA has played a key role in delineating transcriptome complexity, including alternative transcription initiation, splicing, polyadenylation and base modification. However, the reads derived from current RNA-seq technologies are usually short and deprived of information on modification during reverse transcription, compromising their potential in defining transcriptome complexity. Here we applied a direct RNA sequencing method with ultra-long reads from Oxford Nanopore Technologies (ONT) to study the transcriptome complexity in C. elegans. We sequenced native poly-A tailed mRNAs by generating approximately six million reads from embryos, L1 larvae and young adult animals, with average read lengths ranging from 900 to 1,100 bps across stages. Around half of the reads represent full-length transcripts, judged by the presence of a splicing-leader or their full coverage of an existing transcript. To take advantage of the full-length transcripts in defining transcriptome complexity, we devised a novel algorithm to predict novel isoforms or group them with exiting isoforms using their mapping tracks rather than the existing intron/exon structures, which allowed us to identify roughly 57,000 novel isoforms and recover at least 26,000 out of the 33,500 existing isoforms. Intriguingly, stage-specific expression at the level of gene and isoform demonstrates little correlation. Finally, we observed an elevated level of modification in all bases in the coding region relative to the UTR. Taken together, the ONT long reads are expected to deliver new insights into RNA processing and modification and their underlying biology.

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