Deciphering highly similar multigene family transcripts from Iso-Seq data with IsoCon.
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ABSTRACT:
SUBMITTER: Sahlin K
PROVIDER: S-EPMC6214943 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundNowadays, both customers and producers prefer thin-tailed fat sheep. To effectively breed for this phenotype, it is important to identify candidate genes and uncover the genetic mechanism related to tail fat deposition in sheep. Accumulating evidence suggesting that post-transcriptional modification events of precursor-messenger RNA (pre-mRNA), including alternative splicing (AS) and alternative polyadenylation (APA), may regulate tail fat deposition in sheep. Differentially expressed transcripts (DETs) analysis is a way to identify candidate genes related to tail fat deposition. However, due to the technological limitation, post-transcriptional modification events in the tail fat of sheep and DETs between thin-tailed and fat-tailed sheep remains unclear.MethodsIn the present study, we applied pooled PacBio isoform sequencing (Iso-Seq) to generate transcriptomic data of tail fat tissue from six sheep (three thin-tailed sheep and three fat-tailed sheep). By comparing with reference genome, potential gene loci and novel transcripts were identified. Post-transcriptional modification events, including AS and APA, and lncRNA in sheep tail fat were uncovered using pooled Iso-Seq data. Combining Iso-Seq data with six RNA-sequencing (RNA-Seq) data, DETs between thin- and fat-tailed sheep were identified. Protein protein interaction (PPI) network, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were implemented to investigate the potential functions of DETs.ResultsIn the present study, we revealed the transcriptomic complexity of the tail fat of sheep, result in 9,001 potential novel gene loci, 17,834 AS events, 5,791 APA events, and 3,764 lncRNAs. Combining Iso-Seq data with RNA-Seq data, we identified hundreds of DETs between thin- and fat-tailed sheep. Among them, 21 differentially expressed lncRNAs, such as ENSOART00020036299, ENSOART00020033641, ENSOART00020024562, ENSOART00020003848 and 9.53.1 may regulate tail fat deposition. Many novel transcripts were identified as DETs, including 15.527.13 (DGAT2), 13.624.23 (ACSS2), 11.689.28 (ACLY), 11.689.18 (ACLY), 11.689.14 (ACLY), 11.660.12 (ACLY), 22.289.6 (SCD), 22.289.3 (SCD) and 22.289.14 (SCD). Most of the identified DETs have been enriched in GO and KEGG pathways related to extracellular matrix (ECM). Our result revealed the transcriptome complexity and identified many candidate transcripts in tail fat, which could enhance the understanding of molecular mechanisms behind tail fat deposition.
| S-EPMC8571958 | biostudies-literature
Project description:The Iso-Seq technology, based on PacBio sequencing, enables the generation of high-quality, full-length transcripts, providing insights into transcriptome complexity. In this study, total RNA from promastigotes of four Leishmania species (Leishmania braziliensis, Leishmania donovani, Leishmania infantum and Leishmania major) was sequenced using Single Molecule, Real-Time (SMRT) Sequencing (PacBio) methodology. The Iso-seq transcripts were categorized as either complete or truncated according to the presence or absence of the Spliced-Leader (SL) sequence at their 5'-end, respectively. Moreover, only transcripts having a poly-A+ at their 3'-end were considered. Supplied datasets represent valuable information that may help to uncover novel transcripts and alternative splicing events in a parasite that regulates its gene expression at the post-transcriptional level. A better knowledge of gene expression regulation in Leishmania will open avenues for the development of new drugs to treat leishmaniasis, a devastating disease that has worldwide distribution. Additionally, the bioinformatics pipeline followed here may guide the analysis of Iso-Seq data derived from related trypanosomatids like Trypanosoma cruzi (Chagas disease agent) and Trypanosoma brucei (sleeping disease). © 2023 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
| S-EPMC10698239 | biostudies-literature
Project description:Chinese sturgeon (Acipenser sinensis) is a critically endangered fish inhabiting the Yangtze River and Chinese coastal waters. Numerous research projects and conservation efforts have focused on artificial propagation and release to restore this endangered species. However, genomic and full-length transcriptomic sequencing of Chinese sturgeon has rarely been reported. In this study, a total of 10 Chinese sturgeon tissues were used for PacBio Iso-seq and RNA-seq analyses. A total of 19,538 full-length transcripts were obtained with sizes from 51 bp to 7,033 bp. Moreover, cluster analysis of gene families and phylogenetic analysis of 14 species were performed. Furthermore, lncRNAs and coding sequence (CDS) were identified in all Chinese sturgeon tissues. Finally, gene expression profiles and differentially expressed genes (DEGs) were analyzed among 10 tissues in Chinese sturgeon. Taken together, full-length transcripts and the gene expression profile from Chinese sturgeon tissues will provide gene sequences and expression information for future functional genomic study and be very helpful for comprehensive understanding of the genetic mechanism of endangerment in Chinese sturgeon.
| S-EPMC9950146 | biostudies-literature
Project description:BackgroundOur understanding of the pig transcriptome is limited. RNA transcript diversity among nine tissues was assessed using poly(A) selected single-molecule long-read isoform sequencing (Iso-seq) and Illumina RNA sequencing (RNA-seq) from a single White cross-bred pig.ResultsAcross tissues, a total of 67,746 unique transcripts were observed, including 60.5% predicted protein-coding, 36.2% long non-coding RNA and 3.3% nonsense-mediated decay transcripts. On average, 90% of the splice junctions were supported by RNA-seq within tissue. A large proportion (80%) represented novel transcripts, mostly produced by known protein-coding genes (70%), while 17% corresponded to novel genes. On average, four transcripts per known gene (tpg) were identified; an increase over current EBI (1.9 tpg) and NCBI (2.9 tpg) annotations and closer to the number reported in human genome (4.2 tpg). Our new pig genome annotation extended more than 6000 known gene borders (5' end extension, 3' end extension, or both) compared to EBI or NCBI annotations. We validated a large proportion of these extensions by independent pig poly(A) selected 3'-RNA-seq data, or human FANTOM5 Cap Analysis of Gene Expression data. Further, we detected 10,465 novel genes (81% non-coding) not reported in current pig genome annotations. More than 80% of these novel genes had transcripts detected in > 1 tissue. In addition, more than 80% of novel intergenic genes with at least one transcript detected in liver tissue had H3K4me3 or H3K36me3 peaks mapping to their promoter and gene body, respectively, in independent liver chromatin immunoprecipitation data.ConclusionsThese validated results show significant improvement over current pig genome annotations.
| S-EPMC6505119 | biostudies-literature
Project description:MotivationHigh-throughput sequencing enables expression analysis at the level of individual transcripts. The analysis of transcriptome expression levels and differential expression (DE) estimation requires a probabilistic approach to properly account for ambiguity caused by shared exons and finite read sampling as well as the intrinsic biological variance of transcript expression.ResultsWe present Bayesian inference of transcripts from sequencing data (BitSeq), a Bayesian approach for estimation of transcript expression level from RNA-seq experiments. Inferred relative expression is represented by Markov chain Monte Carlo samples from the posterior probability distribution of a generative model of the read data. We propose a novel method for DE analysis across replicates which propagates uncertainty from the sample-level model while modelling biological variance using an expression-level-dependent prior. We demonstrate the advantages of our method using simulated data as well as an RNA-seq dataset with technical and biological replication for both studied conditions.AvailabilityThe implementation of the transcriptome expression estimation and differential expression analysis, BitSeq, has been written in C++ and Python. The software is available online from http://code.google.com/p/bitseq/, version 0.4 was used for generating results presented in this article.
| S-EPMC3381971 | biostudies-literature
Project description:BackgroundA popular strategy to study alternative splicing in non-model organisms starts from sequencing the entire transcriptome, then assembling the reads by using de novo transcriptome assembly algorithms to obtain predicted transcripts. A similarity search algorithm is then applied to a related organism to infer possible function of these predicted transcripts. While some of these predictions may be inaccurate and transcripts with low coverage are often missed, we observe that it is possible to obtain a more complete set of transcripts to facilitate possible functional assignments by starting the search from the intermediate de Bruijn graph that contains all branching possibilities.ResultsWe develop an algorithm to extract similar transcripts in a related organism by starting the search from the de Bruijn graph that represents the transcriptome instead of from predicted transcripts. We show that our algorithm is able to recover more similar transcripts than existing algorithms, with large improvements in obtaining longer transcripts and a finer resolution of isoforms. We apply our algorithm to study salt and waterlogging tolerance in two Melilotus species by constructing new RNA-Seq libraries.ConclusionsWe have developed an algorithm to identify paths in the de Bruijn graph that correspond to similar transcripts in a related organism directly. Our strategy bypasses the transcript prediction step in RNA-Seq data and makes use of support from evolutionary information.
| S-EPMC6551239 | biostudies-literature
Project description:We have developed a new method, SOAPfuse, to identify fusion transcripts from paired-end RNA-Seq data. SOAPfuse applies an improved partial exhaustion algorithm to construct a library of fusion junction sequences, which can be used to efficiently identify fusion events, and employs a series of filters to nominate high-confidence fusion transcripts. Compared with other released tools, SOAPfuse achieves higher detection efficiency and consumed less computing resources. We applied SOAPfuse to RNA-Seq data from two bladder cancer cell lines, and confirmed 15 fusion transcripts, including several novel events common to both cell lines. SOAPfuse is available at http://soap.genomics.org.cn/soapfuse.html.
| S-EPMC4054009 | biostudies-literature
Project description:Prokaryotic transcripts constitute almost always uninterrupted intervals when mapped back to the genome. Split reads, i.e., RNA-seq reads consisting of parts that only map to discontiguous loci, are thus disregarded in most analysis pipelines. There are, however, some well-known exceptions, in particular, tRNA splicing and circularized small RNAs in Archaea as well as self-splicing introns. Here, we reanalyze a series of published RNA-seq data sets, screening them specifically for non-contiguously mapping reads. We recover most of the known cases together with several novel archaeal ncRNAs associated with circularized products. In Eubacteria, only a handful of interesting candidates were obtained beyond a few previously described group I and group II introns. Most of the atypically mapping reads do not appear to correspond to well-defined, specifically processed products. Whether this diffuse background is, at least in part, an incidental by-product of prokaryotic RNA processing or whether it consists entirely of technical artifacts of reverse transcription or amplification remains unknown.
| S-EPMC3849169 | biostudies-literature
Project description:RNA-Seq made possible the global identification of fusion transcripts, i.e. "chimeric RNAs". Even though various software packages have been developed to serve this purpose, they behave differently in different datasets provided by different developers. It is important for both users, and developers to have an unbiased assessment of the performance of existing fusion detection tools. Toward this goal, we compared the performance of 12 well-known fusion detection software packages. We evaluated the sensitivity, false discovery rate, computing time, and memory usage of these tools in four different datasets (positive, negative, mixed, and test). We conclude that some tools are better than others in terms of sensitivity, positive prediction value, time consumption and memory usage. We also observed small overlaps of the fusions detected by different tools in the real dataset (test dataset). This could be due to false discoveries by various tools, but could also be due to the reason that none of the tools are inclusive. We have found that the performance of the tools depends on the quality, read length, and number of reads of the RNA-Seq data. We recommend that users choose the proper tools for their purpose based on the properties of their RNA-Seq data.
| S-EPMC4748267 | biostudies-literature
Project description:BackgroundSeveral novel immunoglobulin-like transcripts (NILTs) which have previously been identified in the salmonid species rainbow trout (Oncorhynchus mykiss) contain either one or two extracellular Ig domains of the V-type. NILTs also possess either an immunoreceptor tyrosine-based activating motif (ITAM) or immunoreceptor tyrosine-based inhibitory motifs (ITIMs) in the cytoplasmic region resulting in different signalling abilities. Here we report for the first time the genomic organisation and structure of the multigene family of NILTs in Atlantic salmon (Salmo salar) using a BAC sequencing approach.ResultsWe have identified six novel Atlantic salmon NILT genes (Ssa-NILT1-6), two pseudogenes (Ssa-NILTp1 and Ssa-NILTp2) and seven genes encoding putative transposable elements in one BAC covering more than 200 kbp. Ssa-NILT1, 2, 4, 5 and 6 contain one Ig domain, all having a CX₃C motif, whereas Ssa-NILT3 contains two Ig domains, having a CX₆C motif in Ig1 and a CX₇C motif in Ig2. Atlantic salmon NILTs possess several ITIMs in the cytoplasmic region and the ITIM-bearing exons are in phase 0. A comparison of identity between the amino acid sequences of the CX₃C Ig domains from NILTs varies from 77% to 96%. Ssa-NILT1, 2, 3 and 4 were all confirmed to be expressed either by their presence in EST databases (Ssa-NILT1) or RT-PCR (Ssa-NILT2, 3, and 4) using cDNA as template. A survey of the repertoire of putative NILT genes in a single individual revealed three novel genes (Ssa-NILT7-9) represented by the Ig domain, which together with Ig domains from Ssa-NILT1-6 could be divided into different groups based on specific motifs.ConclusionsThis report reveals a tightly clustered, multigene NILT family in Atlantic salmon. By screening a highly redundant Atlantic salmon BAC library we have identified and characterised the genomic organisation of six genes encoding NILT receptors. The genes show similar characteristics to NILTs previously identified in rainbow trout, having highly conserved cysteines in the Ig domain and several inhibitory signalling motifs in the cytoplasmic region. In a single individual three unique NILT Ig domain sequences were discovered at the genomic DNA level, which were divided into two different groups based on a four residue motif after the third cysteine. Our results from the BAC screening and analysis on the repertoire of NILT genes in a single individual indicates that many genes of this expanding Ig containing NILT family are still to be discovered in fish.
| S-EPMC3022915 | biostudies-literature