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September 22, 2019  |  

PLEK: a tool for predicting long non-coding RNAs and messenger RNAs based on an improved k-mer scheme.

High-throughput transcriptome sequencing (RNA-seq) technology promises to discover novel protein-coding and non-coding transcripts, particularly the identification of long non-coding RNAs (lncRNAs) from de novo sequencing data. This requires tools that are not restricted by prior gene annotations, genomic sequences and high-quality sequencing.We present an alignment-free tool called PLEK (predictor of long non-coding RNAs and messenger RNAs based on an improved k-mer scheme), which uses a computational pipeline based on an improved k-mer scheme and a support vector machine (SVM) algorithm to distinguish lncRNAs from messenger RNAs (mRNAs), in the absence of genomic sequences or annotations. The performance of PLEK was evaluated on well-annotated mRNA and lncRNA transcripts. 10-fold cross-validation tests on human RefSeq mRNAs and GENCODE lncRNAs indicated that our tool could achieve accuracy of up to 95.6%. We demonstrated the utility of PLEK on transcripts from other vertebrates using the model built from human datasets. PLEK attained >90% accuracy on most of these datasets. PLEK also performed well using a simulated dataset and two real de novo assembled transcriptome datasets (sequenced by PacBio and 454 platforms) with relatively high indel sequencing errors. In addition, PLEK is approximately eightfold faster than a newly developed alignment-free tool, named Coding-Non-Coding Index (CNCI), and 244 times faster than the most popular alignment-based tool, Coding Potential Calculator (CPC), in a single-threading running manner.PLEK is an efficient alignment-free computational tool to distinguish lncRNAs from mRNAs in RNA-seq transcriptomes of species lacking reference genomes. PLEK is especially suitable for PacBio or 454 sequencing data and large-scale transcriptome data. Its open-source software can be freely downloaded from https://sourceforge.net/projects/plek/files/.

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September 22, 2019  |  

Single Molecule Sequencing: new outlooks for solving genome assembly and transcripts identification challenges

In this review, we introduce a novel sequencing technology, named Single Molecule Real Time sequencing. Also called Single Molecule Sequencing, as it do not requires any amplification, this new technology is able to pro- duce much longer reads than previous NGS technologies such as Illumina. This read size improvements, which can reach 150 fold, will solve many challenges caused by the actual NGS technologies. Short NGS reads, reach- ing a maximum size of 300 bp, make it hard to reconstitute a whole genome and are always leading to fragmented genome assembly. It is also difficult to correctly infer transcript quantification and identification when there is a high isoforms diversity. Despite their higher error rate, long reads have shown very promising result concerning these actual issues. We show that longer reads can produce less fragmented assembly, with a better quality, but also sequence from start to end mRNA, making it much more easier to infer correct transcript quantification, and even allow new intron structure and so new isoforms discovery.

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September 22, 2019  |  

Cataloguing over-expressed genes in Epstein Barr Virus immortalized lymphoblastoid cell lines through consensus analysis of PacBio transcriptomes corroborates hypomethylation of chromosome 1

The ability of Epstein Barr Virus (EBV) to transform resting cell B-cells into immortalized lymphoblastoid cell lines (LCL) provides a continuous source of peripheral blood lymphocytes that are used to model conditions in which these lymphocytes play a key role. Here, the PacBio generated transcriptome of three LCLs from a parent-daughter trio (SRAid:SRP036136) provided by a previous study [1] were analyzed using a kmer-based version of YeATS (KEATS). The set of over-expressed genes in these cell lines were determined based on a comparison with the PacBio transcriptome of twenty tissues pro- vided by another study (hOPTRS) [2]. MIR155 long non-coding RNA (MIR155HG), Fc fragment of IgE receptor II (FCER2), T-cell leukemia/lymphoma 1A (TCL1A), and germinal center associated signaling and motility (GCSAM) were genes having the highest expression counts in the three LCLs with no expression in hOPTRS. Other over-expressed genes, having low expression in hOPTRS, were membrane spanning 4-domains A1 (MS4A1) and ribosomal protein S2 pseudogene 55 (RPS2P55). While some of these genes are known to be over-expressed in LCLs, this study provides a comprehensive cataloguing of such genes. A recent work involving a patient with EBV-positive large B-cell lymphoma was “unusually lacking various B-cell markers”, but over-expressing CD30 [3] – a gene ranked 79 among uniquely expressed genes here. Hypomethylation of chromosome 1 observed in EBV immortalized LCLs [4, 5] is also corroborated here by mapping the genes to chromosomes. Extending previous work identifying un-annotated genes [6], 80 genes were identified which are expressed in the three LCLs, not in hOPTRS, and missing in the GENCODE, RefSeq and RefSeqGene databases. KEATS introduces a method of determining expression counts based on a partitioning of the known annotated genes, has runtimes of a few hours on a personal workstation and provides detailed reports enabling proper debugging.

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September 22, 2019  |  

Capturing a long look at our genetic library.

Long-read sequencing, coupled to cDNA capture, provides an unrivaled view of the transcriptome of chromosome 21, revealing surprises about the splicing of long noncoding RNAs. Copyright © 2018. Published by Elsevier Inc.

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September 22, 2019  |  

Introduction to isoform sequencing using Pacific Biosciences technology (Iso-Seq)

Alternative RNA splicing is a known phenomenon, but we still do not have a complete catalog of isoforms that explain variability in the human transcriptome. We have made significant progress in developing methods to study variability of the transcriptome, but we are far away of having a complete picture of the transcriptome. The initial methods to study gene expression were based on cloning of cDNAs and Sanger sequencing. The strategy was labor-intensive and expensive. With the development of microarrays, different methods based on exon arrays and tiling arrays provided valuable information about RNA expression. However, the microarray presented significant limitations. Most of the limitations became apparent by 2005, but it was not until 2008 that an alternative method to study the transcriptome was developed. RNA Sequencing using next-generation sequencing (RNA-Seq) quickly became the technology of choice for gene expression profiling. Recently, the precision and sensitivity of RNA-Seq have come into question, especially for transcriptome reconstruction. This chapter will describe a relatively new method, “Isoform Sequencing (Iso-Seq). Iso-Seq was developed by Pacific Biosciences (PacBio), and it is capable of identifying new isoforms with extraordinary precision due to its long-read technology. The technique to create libraries is straightforward, and the PacBio RS II instrument generates the information in hours. The bioinformatics analysis is performed using the freely available SMRT® Portal software. The SMRT Portal is easy to use and capable of performing all the steps necessary to analyze the raw data and to generate high-quality full-length isoforms. For the universal acceptance of the Iso-Seq method, the capacity of the SMRT Cells needs to improve at least 10- to 100-fold to make the system affordable and attractive to users.

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September 22, 2019  |  

JAFFA: High sensitivity transcriptome-focused fusion gene detection.

Genomic instability is a hallmark of cancer and, as such, structural alterations and fusion genes are common events in the cancer landscape. RNA sequencing (RNA-Seq) is a powerful method for profiling cancers, but current methods for identifying fusion genes are optimised for short reads. JAFFA (https://github.com/Oshlack/JAFFA/wiki) is a sensitive fusion detection method that outperforms other methods with reads of 100 bp or greater. JAFFA compares a cancer transcriptome to the reference transcriptome, rather than the genome, where the cancer transcriptome is inferred using long reads directly or by de novo assembling short reads.

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September 22, 2019  |  

Complex rearrangements and oncogene amplifications revealed by long-read DNA and RNA sequencing of a breast cancer cell line.

The SK-BR-3 cell line is one of the most important models for HER2+ breast cancers, which affect one in five breast cancer patients. SK-BR-3 is known to be highly rearranged, although much of the variation is in complex and repetitive regions that may be underreported. Addressing this, we sequenced SK-BR-3 using long-read single molecule sequencing from Pacific Biosciences and develop one of the most detailed maps of structural variations (SVs) in a cancer genome available, with nearly 20,000 variants present, most of which were missed by short-read sequencing. Surrounding the important ERBB2 oncogene (also known as HER2), we discover a complex sequence of nested duplications and translocations, suggesting a punctuated progression. Full-length transcriptome sequencing further revealed several novel gene fusions within the nested genomic variants. Combining long-read genome and transcriptome sequencing enables an in-depth analysis of how SVs disrupt the genome and sheds new light on the complex mechanisms involved in cancer genome evolution.© 2018 Nattestad et al.; Published by Cold Spring Harbor Laboratory Press.

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September 22, 2019  |  

Revealing missing human protein isoforms based on Ab initio prediction, RNA-seq and proteomics.

Biological and biomedical research relies on comprehensive understanding of protein-coding transcripts. However, the total number of human proteins is still unknown due to the prevalence of alternative splicing. In this paper, we detected 31,566 novel transcripts with coding potential by filtering our ab initio predictions with 50 RNA-seq datasets from diverse tissues/cell lines. PCR followed by MiSeq sequencing showed that at least 84.1% of these predicted novel splice sites could be validated. In contrast to known transcripts, the expression of these novel transcripts were highly tissue-specific. Based on these novel transcripts, at least 36 novel proteins were detected from shotgun proteomics data of 41 breast samples. We also showed L1 retrotransposons have a more significant impact on the origin of new transcripts/genes than previously thought. Furthermore, we found that alternative splicing is extraordinarily widespread for genes involved in specific biological functions like protein binding, nucleoside binding, neuron projection, membrane organization and cell adhesion. In the end, the total number of human transcripts with protein-coding potential was estimated to be at least 204,950.

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September 22, 2019  |  

Sixteen diverse laboratory mouse reference genomes define strain-specific haplotypes and novel functional loci.

We report full-length draft de novo genome assemblies for 16 widely used inbred mouse strains and find extensive strain-specific haplotype variation. We identify and characterize 2,567 regions on the current mouse reference genome exhibiting the greatest sequence diversity. These regions are enriched for genes involved in pathogen defence and immunity and exhibit enrichment of transposable elements and signatures of recent retrotransposition events. Combinations of alleles and genes unique to an individual strain are commonly observed at these loci, reflecting distinct strain phenotypes. We used these genomes to improve the mouse reference genome, resulting in the completion of 10 new gene structures. Also, 62 new coding loci were added to the reference genome annotation. These genomes identified a large, previously unannotated, gene (Efcab3-like) encoding 5,874 amino acids. Mutant Efcab3-like mice display anomalies in multiple brain regions, suggesting a possible role for this gene in the regulation of brain development.

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September 22, 2019  |  

Shorter unreported sequences in a RACE-Seq study involving seven tissues confirms ~150 novel transcripts identified in MCF-7 cell line PacBio transcriptome, leaving ~100 non-redundant transcripts exclusive to the cancer cell line.

PacBio sequencing generates much longer reads compared to second-generation sequencing technologies, with a trade-off of lower throughput, higher error rate and more cost per base. The PacBio transcriptome of the breast cancer cell line MCF-7 was found to have ~300 transcripts un-annotated in the current GENCODE (v25) or RefSeq, and missing in the liver, heart and brain PacBio transcriptomes [1]. RACE-sequencing (RACE-seq [2]) extends a well-established method of characterizing cDNA molecules generated by rapid amplification of cDNA ends (RACE [3]) using high-throughput sequencing technologies, reducing costs compared to PacBio. Here, shorter fragments of ~150 transcripts were found to be present in seven tissues analyzed in a recent RACE-seq study (Accid:ERP012249) [4]. These transcripts were not among the ~2500 novel transcripts reported in that study, tested separately here using the genomic coordinates provided, although “all curated novel isoforms were incorporated into the human GENCODE set (v22)” in that study. Non-redundancy analysis of the exclusive transcripts identified one transcript mapping to Chr1 with seven different splice variants, and erroneously mapped to Chr15 (PAC clone 15q11-q13) from the Prader-Willi/Angelman Syndrome region (Accid:AC004137.1). Finally, there are ~100 non-redundant transcripts missing in the seven tissues, in addition to other three tissues analyzed previously. Their absence in GENCODE and RefSeq databases rule them out as commonly transcribed regions, further increasing their likelihood as biomarkers.

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September 22, 2019  |  

SQANTI: extensive characterization of long-read transcript sequences for quality control in full-length transcriptome identification and quantification.

High-throughput sequencing of full-length transcripts using long reads has paved the way for the discovery of thousands of novel transcripts, even in well-annotated mammalian species. The advances in sequencing technology have created a need for studies and tools that can characterize these novel variants. Here, we present SQANTI, an automated pipeline for the classification of long-read transcripts that can assess the quality of data and the preprocessing pipeline using 47 unique descriptors. We apply SQANTI to a neuronal mouse transcriptome using Pacific Biosciences (PacBio) long reads and illustrate how the tool is effective in characterizing and describing the composition of the full-length transcriptome. We perform extensive evaluation of ToFU PacBio transcripts by PCR to reveal that an important number of the novel transcripts are technical artifacts of the sequencing approach and that SQANTI quality descriptors can be used to engineer a filtering strategy to remove them. Most novel transcripts in this curated transcriptome are novel combinations of existing splice sites, resulting more frequently in novel ORFs than novel UTRs, and are enriched in both general metabolic and neural-specific functions. We show that these new transcripts have a major impact in the correct quantification of transcript levels by state-of-the-art short-read-based quantification algorithms. By comparing our iso-transcriptome with public proteomics databases, we find that alternative isoforms are elusive to proteogenomics detection. SQANTI allows the user to maximize the analytical outcome of long-read technologies by providing the tools to deliver quality-evaluated and curated full-length transcriptomes.© 2018 Tardaguila et al.; Published by Cold Spring Harbor Laboratory Press.

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September 22, 2019  |  

Full-length mRNA sequencing uncovers a widespread coupling between transcription initiation and mRNA processing.

The multifaceted control of gene expression requires tight coordination of regulatory mechanisms at transcriptional and post-transcriptional level. Here, we studied the interdependence of transcription initiation, splicing and polyadenylation events on single mRNA molecules by full-length mRNA sequencing.In MCF-7 breast cancer cells, we find 2700 genes with interdependent alternative transcription initiation, splicing and polyadenylation events, both in proximal and distant parts of mRNA molecules, including examples of coupling between transcription start sites and polyadenylation sites. The analysis of three human primary tissues (brain, heart and liver) reveals similar patterns of interdependency between transcription initiation and mRNA processing events. We predict thousands of novel open reading frames from full-length mRNA sequences and obtained evidence for their translation by shotgun proteomics. The mapping database rescues 358 previously unassigned peptides and improves the assignment of others. By recognizing sample-specific amino-acid changes and novel splicing patterns, full-length mRNA sequencing improves proteogenomics analysis of MCF-7 cells.Our findings demonstrate that our understanding of transcriptome complexity is far from complete and provides a basis to reveal largely unresolved mechanisms that coordinate transcription initiation and mRNA processing.

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September 22, 2019  |  

High-resolution comparative analysis of great ape genomes.

Genetic studies of human evolution require high-quality contiguous ape genome assemblies that are not guided by the human reference. We coupled long-read sequence assembly and full-length complementary DNA sequencing with a multiplatform scaffolding approach to produce ab initio chimpanzee and orangutan genome assemblies. By comparing these with two long-read de novo human genome assemblies and a gorilla genome assembly, we characterized lineage-specific and shared great ape genetic variation ranging from single- to mega-base pair-sized variants. We identified ~17,000 fixed human-specific structural variants identifying genic and putative regulatory changes that have emerged in humans since divergence from nonhuman apes. Interestingly, these variants are enriched near genes that are down-regulated in human compared to chimpanzee cerebral organoids, particularly in cells analogous to radial glial neural progenitors. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

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September 22, 2019  |  

A single-molecule long-read survey of the human transcriptome.

Global RNA studies have become central to understanding biological processes, but methods such as microarrays and short-read sequencing are unable to describe an entire RNA molecule from 5′ to 3′ end. Here we use single-molecule long-read sequencing technology from Pacific Biosciences to sequence the polyadenylated RNA complement of a pooled set of 20 human organs and tissues without the need for fragmentation or amplification. We show that full-length RNA molecules of up to 1.5 kb can readily be monitored with little sequence loss at the 5′ ends. For longer RNA molecules more 5′ nucleotides are missing, but complete intron structures are often preserved. In total, we identify ~14,000 spliced GENCODE genes. High-confidence mappings are consistent with GENCODE annotations, but >10% of the alignments represent intron structures that were not previously annotated. As a group, transcripts mapping to unannotated regions have features of long, noncoding RNAs. Our results show the feasibility of deep sequencing full-length RNA from complex eukaryotic transcriptomes on a single-molecule level.

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September 22, 2019  |  

A survey of transcriptome complexity in Sus scrofa using single-molecule long-read sequencing.

Alternative splicing (AS) and fusion transcripts produce a vast expansion of transcriptomes and proteomes diversity. However, the reliability of these events and the extend of epigenetic mechanisms have not been adequately addressed due to its limitation of uncertainties about the complete structure of mRNA. Here we combined single-molecule real-time sequencing, Illumina RNA-seq and DNA methylation data to characterize the landscapes of DNA methylation on AS, fusion isoforms formation and lncRNA feature and further to unveil the transcriptome complexity of pig. Our analysis identified an unprecedented scale of high-quality full-length isoforms with over 28,127 novel isoforms from 26,881 novel genes. More than 92,000 novel AS events were detected and intron retention predominated in AS model, followed by exon skipping. Interestingly, we found that DNA methylation played an important role in generating various AS isoforms by regulating splicing sites, promoter regions and first exons. Furthermore, we identified a large of fusion transcripts and novel lncRNAs, and found that DNA methylation of the promoter and gene body could regulate lncRNA expression. Our results significantly improved existed gene models of pig and unveiled that pig AS and epigenetic modify were more complex than previously thought.

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