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April 21, 2020

Long-Read Sequencing Emerging in Medical Genetics

The wide implementation of next-generation sequencing (NGS) technologies has revolutionized the field of medical genetics. However, the short read lengths of currently used sequencing approaches pose a limitation for identification of structural variants, sequencing repetitive regions, phasing alleles and distinguishing highly homologous genomic regions. These limitations may significantly contribute to the diagnostic gap in patients with genetic disorders who have undergone standard NGS, like whole exome or even genome sequencing. Now, the emerging long-read sequencing (LRS) technologies may offer improvements in the characterization of genetic variation and regions that are difficult to assess with the currently prevailing NGS approaches. LRS has so far mainly been used to investigate genetic disorders with previously known or strongly suspected disease loci. While these targeted approaches already show the potential of LRS, it remains to be seen whether LRS technologies can soon enable true whole genome sequencing routinely. Ultimately, this could allow the de novo assembly of individual whole genomes used as a generic test for genetic disorders. In this article, we summarize the current LRS-based research on human genetic disorders and discuss the potential of these technologies to facilitate the next major advancements in medical genetics.

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April 21, 2020

Divergent evolutionary trajectories following speciation in two ectoparasitic honey bee mites.

Multispecies host-parasite evolution is common, but how parasites evolve after speciating remains poorly understood. Shared evolutionary history and physiology may propel species along similar evolutionary trajectories whereas pursuing different strategies can reduce competition. We test these scenarios in the economically important association between honey bees and ectoparasitic mites by sequencing the genomes of the sister mite species Varroa destructor and Varroa jacobsoni. These genomes were closely related, with 99.7% sequence identity. Among the 9,628 orthologous genes, 4.8% showed signs of positive selection in at least one species. Divergent selective trajectories were discovered in conserved chemosensory gene families (IGR, SNMP), and Halloween genes (CYP) involved in moulting and reproduction. However, there was little overlap in these gene sets and associated GO terms, indicating different selective regimes operating on each of the parasites. Based on our findings, we suggest that species-specific strategies may be needed to combat evolving parasite communities. © The Author(s) 2019.

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April 21, 2020

Improved annotation of the domestic pig genome through integration of Iso-Seq and RNA-seq data.

Our 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. Across 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. These validated results show significant improvement over current pig genome annotations.

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April 21, 2020

De novo transcriptome assembly of the cubomedusa Tripedalia cystophora, including the analysis of a set of genes involved in peptidergic neurotransmission.

The phyla Cnidaria, Placozoa, Ctenophora, and Porifera emerged before the split of proto- and deuterostome animals, about 600 million years ago. These early metazoans are interesting, because they can give us important information on the evolution of various tissues and organs, such as eyes and the nervous system. Generally, cnidarians have simple nervous systems, which use neuropeptides for their neurotransmission, but some cnidarian medusae belonging to the class Cubozoa (box jellyfishes) have advanced image-forming eyes, probably associated with a complex innervation. Here, we describe a new transcriptome database from the cubomedusa Tripedalia cystophora.Based on the combined use of the Illumina and PacBio sequencing technologies, we produced a highly contiguous transcriptome database from T. cystophora. We then developed a software program to discover neuropeptide preprohormones in this database. This script enabled us to annotate seven novel T. cystophora neuropeptide preprohormone cDNAs: One coding for 19 copies of a peptide with the structure pQWLRGRFamide; one coding for six copies of a different RFamide peptide; one coding for six copies of pQPPGVWamide; one coding for eight different neuropeptide copies with the C-terminal LWamide sequence; one coding for thirteen copies of a peptide with the RPRAamide C-terminus; one coding for four copies of a peptide with the C-terminal GRYamide sequence; and one coding for seven copies of a cyclic peptide, of which the most frequent one has the sequence CTGQMCWFRamide. We could also identify orthologs of these seven preprohormones in the cubozoans Alatina alata, Carybdea xaymacana, Chironex fleckeri, and Chiropsalmus quadrumanus. Furthermore, using TBLASTN screening, we could annotate four bursicon-like glycoprotein hormone subunits, five opsins, and 52 other family-A G protein-coupled receptors (GPCRs), which also included two leucine-rich repeats containing G protein-coupled receptors (LGRs) in T. cystophora. The two LGRs are potential receptors for the glycoprotein hormones, while the other GPCRs are candidate receptors for the above-mentioned neuropeptides.By combining Illumina and PacBio sequencing technologies, we have produced a new high-quality de novo transcriptome assembly from T. cystophora that should be a valuable resource for identifying the neuronal components that are involved in vision and other behaviors in cubomedusae.

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April 21, 2020

Experimental validation of in silico predicted RAD locus frequencies using genomic resources and short read data from a model marine mammal.

Restriction site-associated DNA sequencing (RADseq) has revolutionized the study of wild organisms by allowing cost-effective genotyping of thousands of loci. However, for species lacking reference genomes, it can be challenging to select the restriction enzyme that offers the best balance between the number of obtained RAD loci and depth of coverage, which is crucial for a successful outcome. To address this issue, PredRAD was recently developed, which uses probabilistic models to predict restriction site frequencies from a transcriptome assembly or other sequence resource based on either GC content or mono-, di- or trinucleotide composition. This program generates predictions that are broadly consistent with estimates of the true number of restriction sites obtained through in silico digestion of available reference genome assemblies. However, in practice the actual number of loci obtained could potentially differ as incomplete enzymatic digestion or patchy sequence coverage across the genome might lead to some loci not being represented in a RAD dataset, while erroneous assembly could potentially inflate the number of loci. To investigate this, we used genome and transcriptome assemblies together with RADseq data from the Antarctic fur seal (Arctocephalus gazella) to compare PredRAD predictions with empirical estimates of the number of loci obtained via in silico digestion and from de novo assemblies.PredRAD yielded consistently higher predicted numbers of restriction sites for the transcriptome assembly relative to the genome assembly. The trinucleotide and dinucleotide models also predicted higher frequencies than the mononucleotide or GC content models. Overall, the dinucleotide and trinucleotide models applied to the transcriptome and the genome assemblies respectively generated predictions that were closest to the number of restriction sites estimated by in silico digestion. Furthermore, the number of de novo assembled RAD loci mapping to restriction sites was similar to the expectation based on in silico digestion.Our study reveals generally high concordance between PredRAD predictions and empirical estimates of the number of RAD loci. This further supports the utility of PredRAD, while also suggesting that it may be feasible to sequence and assemble the majority of RAD loci present in an organism’s genome.

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April 21, 2020

Genome sequence and transcriptomic profiles of a marine bacterium, Pseudoalteromonas agarivorans Hao 2018.

Members of the marine genus Pseudoalteromonas have attracted great interest because of their ability to produce a large number of biologically active substances. Here, we report the complete genome sequence of Pseudoalteromonas agarivorans Hao 2018, a strain isolated from an abalone breeding environment, using second-generation Illumina and third-generation PacBio sequencing technologies. Illumina sequencing offers high quality and short reads, while PacBio technology generates long reads. The scaffolds of the two platforms were assembled to yield a complete genome sequence that included two circular chromosomes and one circular plasmid. Transcriptomic data for Pseudoalteromonas were not available. We therefore collected comprehensive RNA-seq data using Illumina sequencing technology from a fermentation culture of P. agarivorans Hao 2018. Researchers studying the evolution, environmental adaptations and biotechnological applications of Pseudoalteromonas may benefit from our genomic and transcriptomic data to analyze the function and expression of genes of interest.

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October 23, 2019

Development of a Novel Reference Transcriptome for Scleractinian Coral Porites lutea Using Single-Molecule Long-Read Isoform Sequencing (Iso-Seq)

Elevation in seawater temperature associated with global climate change has caused coral bleaching problems and posed a significant threat to coral health and survival worldwide. Several studies have explored the effects of thermal stress on changes in gene expression levels of both coral hosts and their algal endosymbionts and provided evidences suggesting that corals could acclimatize to environmental stressors through differential regulation of their gene expression (Desalvo et al., 2008, 2010; Császár et al., 2009; Rodriguez-Lanetty et al., 2009; Polato et al., 2010; Meyer et al., 2011; Kenkel et al., 2013). Such information is crucial for understanding the adaptive capacity of the coral holobionts (Hughes et al., 2003). The availability of transcriptome data from a number of coral species and their associated Symbiodinium allows us to probe the molecular stress response of the organisms to heat stress (Traylor-Knowles et al., 2011; Moya et al., 2012; Kenkel et al., 2013; Shinzato et al., 2014; Kitchen et al., 2015; Anderson et al., 2016; Davies et al., 2016). Here, we report the first reference transcriptome for a scleractinian coral Porites lutea, one of the dominant reef-builders in the Indo-West Pacific (Yeemin et al., 2009). We applied both short-read Ion S5 RNA sequencing and long-read Pacific Biosciences (PacBio) isoform sequencing (Iso-seq) to generate transcriptome sequences of P. lutea under normal and heat stress conditions. The key advantage of PacBio’s Iso-seq technology lies within its ability to capture full-length mRNA sequences. These full-length transcripts enable the identification of novel genes/isoforms and the detection of alternative splice variants, which have been shown to be overrepresented in stress responses (Iida et al., 2004; Reddy et al., 2013; Liu and Guo, 2017). We envision that this reference transcriptome will provide a coral research community a valuable resource for investigating changes in gene expression under various biotic/abiotic stress conditions.

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October 23, 2019

Alternative splicing profile and sex-preferential gene expression in the female and male Pacific abalone Haliotis discus hannai.

In order to characterize the female or male transcriptome of the Pacific abalone and further increase genomic resources, we sequenced the mRNA of full-length complementary DNA (cDNA) libraries derived from pooled tissues of female and male Haliotis discus hannai by employing the Iso-Seq protocol of the PacBio RSII platform. We successfully assembled whole full-length cDNA sequences and constructed a transcriptome database that included isoform information. After clustering, a total of 15,110 and 12,145 genes that coded for proteins were identified in female and male abalones, respectively. A total of 13,057 putative orthologs were retained from each transcriptome in abalones. Overall Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analyzed in each database showed a similar composition between sexes. In addition, a total of 519 and 391 isoforms were genome-widely identified with at least two isoforms from female and male transcriptome databases. We found that the number of isoforms and their alternatively spliced patterns are variable and sex-dependent. This information represents the first significant contribution to sex-preferential genomic resources of the Pacific abalone. The availability of whole female and male transcriptome database and their isoform information will be useful to improve our understanding of molecular responses and also for the analysis of population dynamics in the Pacific abalone.

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October 23, 2019

The genome of common long-arm octopus Octopus minor.

The common long-arm octopus (Octopus minor) is found in mudflats of subtidal zones and faces numerous environmental challenges. The ability to adapt its morphology and behavioral repertoire to diverse environmental conditions makes the species a promising model for understanding genomic adaptation and evolution in cephalopods.The final genome assembly of O. minor is 5.09 Gb, with a contig N50 size of 197 kb and longest size of 3.027 Mb, from a total of 419 Gb raw reads generated using the Pacific Biosciences RS II platform. We identified 30,010 genes; 44.43% of the genome is composed of repeat elements. The genome-wide phylogenetic tree indicated the divergence time between O. minor and Octopus bimaculoides was estimated to be 43 million years ago based on single-copy orthologous genes. In total, 178 gene families are expanded in O. minor in the 14 bilaterian species.We found that the O. minor genome was larger than that of closely related O. bimaculoides, and this difference could be explained by enlarged introns and recently diversified transposable elements. The high-quality O. minor genome assembly provides a valuable resource for understanding octopus genome evolution and the molecular basis of adaptations to mudflats.

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September 22, 2019

TACO produces robust multisample transcriptome assemblies from RNA-seq.

Accurate transcript structure and abundance inference from RNA sequencing (RNA-seq) data is foundational for molecular discovery. Here we present TACO, a computational method to reconstruct a consensus transcriptome from multiple RNA-seq data sets. TACO employs novel change-point detection to demarcate transcript start and end sites, leading to improved reconstruction accuracy compared with other tools in its class. The tool is available at http://tacorna.github.io and can be readily incorporated into RNA-seq analysis workflows.

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September 22, 2019

The transcriptome of human pluripotent stem cells.

Human Embryonic Stem Cells (hESCs) are in vitro derivatives of the inner cell mass of the blastocyst and are characterized by an undifferentiated and pluripotent state that can be perpetuated in time, indefinitely. hESCs provide a unique opportunity to both dissect the molecular mechanisms that are predisposed to the maintenance of pluripotency and model the ability to initiate differentiation and cell commitment within the developing embryo. To fully understand these mechanisms, it is necessary to accurately identify the specific transcriptome of hESCs. Many distinct gene annotation methods, such as cDNA and EST sequencing and RNA-Seq, have been used to identify the transcriptome of hESCs. Lately, we developed a new tool (IDP) to integrate the hybrid sequencing data to characterize a more reliable and comprehensive hESC transcriptome with discoveries of many novel transcripts. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

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September 22, 2019

Leveraging multiple transcriptome assembly methods for improved gene structure annotation.

The performance of RNA sequencing (RNA-seq) aligners and assemblers varies greatly across different organisms and experiments, and often the optimal approach is not known beforehand.Here, we show that the accuracy of transcript reconstruction can be boosted by combining multiple methods, and we present a novel algorithm to integrate multiple RNA-seq assemblies into a coherent transcript annotation. Our algorithm can remove redundancies and select the best transcript models according to user-specified metrics, while solving common artifacts such as erroneous transcript chimerisms.We have implemented this method in an open-source Python3 and Cython program, Mikado, available on GitHub.

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September 22, 2019

Evaluating approaches to find exon chains based on long reads.

Transcript prediction can be modeled as a graph problem where exons are modeled as nodes and reads spanning two or more exons are modeled as exon chains. Pacific Biosciences third-generation sequencing technology produces significantly longer reads than earlier second-generation sequencing technologies, which gives valuable information about longer exon chains in a graph. However, with the high error rates of third-generation sequencing, aligning long reads correctly around the splice sites is a challenging task. Incorrect alignments lead to spurious nodes and arcs in the graph, which in turn lead to incorrect transcript predictions. We survey several approaches to find the exon chains corresponding to long reads in a splicing graph, and experimentally study the performance of these methods using simulated data to allow for sensitivity/precision analysis. Our experiments show that short reads from second-generation sequencing can be used to significantly improve exon chain correctness either by error-correcting the long reads before splicing graph creation, or by using them to create a splicing graph on which the long-read alignments are then projected. We also study the memory and time consumption of various modules, and show that accurate exon chains lead to significantly increased transcript prediction accuracy.The simulated data and in-house scripts used for this article are available at http://www.cs.helsinki.fi/group/gsa/exon-chains/exon-chains-bib.tar.bz2.

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September 22, 2019

neoantigenR: An annotation based pipeline for tumor neoantigen identification from sequencing data

Studies indicate that more than 90% of human genes are alternatively spliced, suggesting the complexity of the transcriptome assembly and analysis. The splicing process is often disrupted, resulting in both functional and non-functional end-products (Sveen et al. 2016) in many cancers. Harnessing the immune system to fight against malignant cancers carrying aberrantly mutated or spliced products is becoming a promising approach to cancer therapy. Advances in immune checkpoint blockade have elicited adaptive immune responses with promising clinical responses to treatments against human malignancies (Tumor Neoantigens in Personalized Cancer Immunotherapy 2017). Emerging data suggest that recognition of patient-specific mutation-associated cancer antigens (i.e. from alternative splicing isoforms) may allow scientists to dissect the immune response in the activity of clinical immunotherapies (Schumacher and Schreiber 2015). The advent of high-throughput sequencing technology has provided a comprehensive view of both splicing aberrations and somatic mutations across a range of human malignancies, allowing for a deeper understanding of the interplay of various disease mechanisms. Meanwhile, studies show that the number of transcript isoforms reported to date may be limited by the short-read sequencing due to the inherit limitation of transcriptome reconstruction algorithms, whereas long-read sequencing is able to significantly improve the detection of alternative splicing variants since there is no need to assemble full-length transcripts from short reads. The analysis of these high-throughput long-read sequencing data may permit a systematic view of tumor specific peptide epitopes (also known as neoantigens) that could serve as targets for immunotherapy (Tumor Neoantigens in Personalized Cancer Immunotherapy 2017). Currently, there is no software pipeline available that can efficiently produce mutation-associated cancer antigens from raw high-throughput sequencing data on patient tumor DNA (The Problem with Neoantigen Prediction 2017). In addressing this issue, we introduce a R package that allows the discoveries of peptide epitope candidates, which are the tumor-specific peptide fragments containing potential functional neoantigens. These peptide epitopes consist of structure variants including insertion, deletions, alternative sequences, and peptides from nonsynonymous mutations. Analysis of these precursor candidates with widely used tools such as netMHC allows for the accurate in-silico prediction of neoantigens. The pipeline named neoantigeR is currently hosted in https://github.com/ICBI/neoantigeR.

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September 22, 2019

A near complete snapshot of the Zea mays seedling transcriptome revealed from ultra-deep sequencing.

RNA-sequencing (RNA-seq) enables in-depth exploration of transcriptomes, but typical sequencing depth often limits its comprehensiveness. In this study, we generated nearly 3 billion RNA-Seq reads, totaling 341 Gb of sequence, from a Zea mays seedling sample. At this depth, a near complete snapshot of the transcriptome was observed consisting of over 90% of the annotated transcripts, including lowly expressed transcription factors. A novel hybrid strategy combining de novo and reference-based assemblies yielded a transcriptome consisting of 126,708 transcripts with 88% of expressed known genes assembled to full-length. We improved current annotations by adding 4,842 previously unannotated transcript variants and many new features, including 212 maize transcripts, 201 genes, 10 genes with undocumented potential roles in seedlings as well as maize lineage specific gene fusion events. We demonstrated the power of deep sequencing for large transcriptome studies by generating a high quality transcriptome, which provides a rich resource for the research community.

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