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Multi-platform analysis reveals a complex transcriptome architecture of a circovirus.

ABSTRACT: In this study, we used Pacific Biosciences RS II long-read and Illumina HiScanSQ short-read sequencing technologies for the characterization of porcine circovirus type 1 (PCV-1) transcripts. Our aim was to identify novel RNA molecules and transcript isoforms, as well as to determine the exact 5'- and 3'-end sequences of previously described transcripts with single base-pair accuracy. We discovered a novel 3'-UTR length isoform of the Cap transcript, and a non-spliced Cap transcript variant. Additionally, our analysis has revealed a 3'-UTR isoform of Rep and two 5'-UTR isoforms of Rep' transcripts, and a novel splice variant of the longer Rep' transcript. We also explored two novel long transcripts, one with a previously identified splice site, and a formerly undetected mRNA of ORF3. Altogether, our methods have identified nine novel RNA molecules, doubling the size of PCV-1 transcriptome that had been known before. Additionally, our investigations revealed an intricate pattern of transcript overlapping, which might produce transcriptional interference between the transcriptional machineries of adjacent genes, and thereby may potentially play a role in the regulation of gene expression in circoviruses.

SUBMITTER: Moldovan N

PROVIDER: S-EPMC5927800 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

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Multi-platform analysis reveals a complex transcriptome architecture of a circovirus.

Moldován Norbert N Balázs Zsolt Z Tombácz Dóra D Csabai Zsolt Z Szűcs Attila A Snyder Michael M Boldogkői Zsolt Z

Virus research 20170524

In this study, we used Pacific Biosciences RS II long-read and Illumina HiScanSQ short-read sequencing technologies for the characterization of porcine circovirus type 1 (PCV-1) transcripts. Our aim was to identify novel RNA molecules and transcript isoforms, as well as to determine the exact 5'- and 3'-end sequences of previously described transcripts with single base-pair accuracy. We discovered a novel 3'-UTR length isoform of the Cap transcript, and a non-spliced Cap transcript variant. Addi ...[more]

PMID: 28549855

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Project description:BackgroundTo understand the genetic architecture of complex traits and bridge the genotype-phenotype gap, it is useful to study intermediate -omics data, e.g. the transcriptome. The present study introduces a method for simultaneous quantification of the contributions from single nucleotide polymorphisms (SNPs) and transcript abundances in explaining phenotypic variance, using Bayesian whole-omics models. Bayesian mixed models and variable selection models were used and, based on parameter samples from the model posterior distributions, explained variances were further partitioned at the level of chromosomes and genome segments.ResultsWe analyzed three growth-related traits: Body Weight (BW), Feed Intake (FI), and Feed Efficiency (FE), in an F2 population of 440 mice. The genomic variation was covered by 1806 tag SNPs, and transcript abundances were available from 23,698 probes measured in the liver. Explained variances were computed for models using pedigree, SNPs, transcripts, and combinations of these. Comparison of these models showed that for BW, a large part of the variation explained by SNPs could be covered by the liver transcript abundances; this was less true for FI and FE. For BW, the main quantitative trait loci (QTLs) are found on chromosomes 1, 2, 9, 10, and 11, and the QTLs on 1, 9, and 10 appear to be expression Quantitative Trait Locus (eQTLs) affecting gene expression in the liver. Chromosome 9 is the case of an apparent eQTL, showing that genomic variance disappears, and that a tri-modal distribution of genomic values collapses, when gene expressions are added to the model.ConclusionsWith increased availability of various -omics data, integrative approaches are promising tools for understanding the genetic architecture of complex traits. Partitioning of explained variances at the chromosome and genome-segment level clearly separated regulatory and structural genomic variation as the areas where SNP effects disappeared/remained after adding transcripts to the model. The models that include transcripts explained more phenotypic variance and were better at predicting phenotypes than a model using SNPs alone. The predictions from these Bayesian models are generally unbiased, validating the estimates of explained variances.

Project description:Large-scale sequencing efforts have documented extensive genetic variation within the human genome. However, our understanding of the origins, global distribution, and functional consequences of this variation is far from complete. While regulatory variation influencing gene expression has been studied within a handful of populations, the breadth of transcriptome differences across diverse human populations has not been systematically analyzed. To better understand the spectrum of gene expression variation, alternative splicing, and the population genetics of regulatory variation in humans, we have sequenced the genomes, exomes, and transcriptomes of EBV transformed lymphoblastoid cell lines derived from 45 individuals in the Human Genome Diversity Panel (HGDP). The populations sampled span the geographic breadth of human migration history and include Namibian San, Mbuti Pygmies of the Democratic Republic of Congo, Algerian Mozabites, Pathan of Pakistan, Cambodians of East Asia, Yakut of Siberia, and Mayans of Mexico. We discover that approximately 25.0% of the variation in gene expression found amongst individuals can be attributed to population differences. However, we find few genes that are systematically differentially expressed among populations. Of this population-specific variation, 75.5% is due to expression rather than splicing variability, and we find few genes with strong evidence for differential splicing across populations. Allelic expression analyses indicate that previously mapped common regulatory variants identified in eight populations from the International Haplotype Map Phase 3 project have similar effects in our seven sampled HGDP populations, suggesting that the cellular effects of common variants are shared across diverse populations. Together, these results provide a resource for studies analyzing functional differences across populations by estimating the degree of shared gene expression, alternative splicing, and regulatory genetics across populations from the broadest points of human migration history yet sampled.

Project description:BackgroundThe Lolium-Festuca complex incorporates species from the Lolium genera and the broad leaf fescues, both belonging to the subfamily Pooideae. This subfamily also includes wheat, barley, oat and rye, making it extremely important to world agriculture. Species within the Lolium-Festuca complex show very diverse phenotypes, and many of them are related to agronomically important traits. Analysis of sequenced transcriptomes of these non-model species may shed light on the molecular mechanisms underlying this phenotypic diversity.ResultsWe have generated de novo transcriptome assemblies for four species from the Lolium-Festuca complex, ranging from 52,166 to 72,133 transcripts per assembly. We have also predicted a set of proteins and validated it with a high-confidence protein database from three closely related species (H. vulgare, B. distachyon and O. sativa). We have obtained gene family clusters for the four species using OrthoMCL and analyzed their inferred phylogenetic relationships. Our results indicate that VRN2 is a candidate gene for differentiating vernalization and non-vernalization types in the Lolium-Festuca complex. Grouping of the gene families based on their BLAST identity enabled us to divide ortholog groups into those that are very conserved and those that are more evolutionarily relaxed. The ratio of the non-synonumous to synonymous substitutions enabled us to pinpoint protein sequences evolving in response to positive selection. These proteins may explain some of the differences between the more stress tolerant Festuca, and the less stress tolerant Lolium species.ConclusionsOur data presents a comprehensive transcriptome sequence comparison between species from the Lolium-Festuca complex, with the identification of potential candidate genes underlying some important phenotypical differences within the complex (such as VRN2). The orthologous genes between the species have a very high %id (91,61%) and the majority of gene families were shared for all of them. It is likely that the knowledge of the genomes will be largely transferable between species within the complex.

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Multi-platform analysis reveals a complex transcriptome architecture of a circovirus.

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Multi-platform analysis reveals a complex transcriptome architecture of a circovirus.

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