September 22, 2019 |
Meet some code-breakers of noncoding RNAs.
The regulome—the part of the genome that regulates function—includes noncoding RNAs with varied functions yet to be deciphered.
Auto Tag: Wellcome Trust Sanger Institute
September 22, 2019 |
Molecular genetic diversity and characterization of conjugation genes in the fish parasite Ichthyophthirius multifiliis.
Ichthyophthirius multifiliis is the etiologic agent of “white spot”, a commercially important disease of freshwater fish. As a parasitic ciliate, I. multifiliis infects numerous host species across a broad geographic range. Although Ichthyophthirius outbreaks are difficult to control, recent sequencing of the I. multifiliis genome has revealed a number of potential metabolic pathways for therapeutic intervention, along with likely vaccine targets for disease prevention. Nonetheless, major gaps exist in our understanding of both the life cycle and population structure of I. multifiliis in the wild. For example, conjugation has never been described in this species, and it is unclear whether I. multifiliis undergoes sexual reproduction, despite the presence of a germline micronucleus. In addition, no good methods exist to distinguish strains, leaving phylogenetic relationships between geographic isolates completely unresolved. Here, we compared nucleotide sequences of SSUrDNA, mitochondrial NADH dehydrogenase subunit I and cox-1 genes, and 14 somatic SNP sites from nine I. multifiliis isolates obtained from four different states in the US since 1995. The mitochondrial sequences effectively distinguished the isolates from one another and divided them into at least two genetically distinct groups. Furthermore, none of the nine isolates shared the same composition of the 14 somatic SNP sites, suggesting that I. multifiliis undergoes sexual reproduction at some point in its life cycle. Finally, compared to the well-studied free-living ciliates Tetrahymena thermophila and Paramecium tetraurelia, I. multifiliis has lost 38% and 29%, respectively, of 16 experimentally confirmed conjugation-related genes, indicating that mechanistic differences in sexual reproduction are likely to exist between I. multifiliis and other ciliate species. Copyright © 2015 Elsevier Inc. All rights reserved.
September 22, 2019 |
Separation and parallel sequencing of the genomes and transcriptomes of single cells using G&T-seq.
Parallel sequencing of a single cell’s genome and transcriptome provides a powerful tool for dissecting genetic variation and its relationship with gene expression. Here we present a detailed protocol for G&T-seq, a method for separation and parallel sequencing of genomic DNA and full-length polyA(+) mRNA from single cells. We provide step-by-step instructions for the isolation and lysis of single cells; the physical separation of polyA(+) mRNA from genomic DNA using a modified oligo-dT bead capture and the respective whole-transcriptome and whole-genome amplifications; and library preparation and sequence analyses of these amplification products. The method allows the detection of thousands of transcripts in parallel with the genetic variants captured by the DNA-seq data from the same single cell. G&T-seq differs from other currently available methods for parallel DNA and RNA sequencing from single cells, as it involves physical separation of the DNA and RNA and does not require bespoke microfluidics platforms. The process can be implemented manually or through automation. When performed manually, paired genome and transcriptome sequencing libraries from eight single cells can be produced in ~3 d by researchers experienced in molecular laboratory work. For users with experience in the programming and operation of liquid-handling robots, paired DNA and RNA libraries from 96 single cells can be produced in the same time frame. Sequence analysis and integration of single-cell G&T-seq DNA and RNA data requires a high level of bioinformatics expertise and familiarity with a wide range of informatics tools.
September 22, 2019 |
L_RNA_scaffolder: scaffolding genomes with transcripts.
Generation of large mate-pair libraries is necessary for de novo genome assembly but the procedure is complex and time-consuming. Furthermore, in some complex genomes, it is hard to increase the N50 length even with large mate-pair libraries, which leads to low transcript coverage. Thus, it is necessary to develop other simple scaffolding approaches, to at least solve the elongation of transcribed fragments.We describe L_RNA_scaffolder, a novel genome scaffolding method that uses long transcriptome reads to order, orient and combine genomic fragments into larger sequences. To demonstrate the accuracy of the method, the zebrafish genome was scaffolded. With expanded human transcriptome data, the N50 of human genome was doubled and L_RNA_scaffolder out-performed most scaffolding results by existing scaffolders which employ mate-pair libraries. In these two examples, the transcript coverage was almost complete, especially for long transcripts. We applied L_RNA_scaffolder to the highly polymorphic pearl oyster draft genome and the gene model length significantly increased.The simplicity and high-throughput of RNA-seq data makes this approach suitable for genome scaffolding. L_RNA_scaffolder is available at http://www.fishbrowser.org/software/L_RNA_scaffolder.
September 22, 2019 |
Evaluation of PacBio sequencing for full-length bacterial 16S rRNA gene classification.
Currently, bacterial 16S rRNA gene analyses are based on sequencing of individual variable regions of the 16S rRNA gene (Kozich, et al Appl Environ Microbiol 79:5112-5120, 2013).This short read approach can introduce biases. Thus, full-length bacterial 16S rRNA gene sequencing is needed to reduced biases. A new alternative for full-length bacterial 16S rRNA gene sequencing is offered by PacBio single molecule, real-time (SMRT) technology. The aim of our study was to validate PacBio P6 sequencing chemistry using three approaches: 1) sequencing the full-length bacterial 16S rRNA gene from a single bacterial species Staphylococcus aureus to analyze error modes and to optimize the bioinformatics pipeline; 2) sequencing the full-length bacterial 16S rRNA gene from a pool of 50 different bacterial colonies from human stool samples to compare with full-length bacterial 16S rRNA capillary sequence; and 3) sequencing the full-length bacterial 16S rRNA genes from 11 vaginal microbiome samples and compare with in silico selected bacterial 16S rRNA V1V2 gene region and with bacterial 16S rRNA V1V2 gene regions sequenced using the Illumina MiSeq.Our optimized bioinformatics pipeline for PacBio sequence analysis was able to achieve an error rate of 0.007% on the Staphylococcus aureus full-length 16S rRNA gene. Capillary sequencing of the full-length bacterial 16S rRNA gene from the pool of 50 colonies from stool identified 40 bacterial species of which up to 80% could be identified by PacBio full-length bacterial 16S rRNA gene sequencing. Analysis of the human vaginal microbiome using the bacterial 16S rRNA V1V2 gene region on MiSeq generated 129 operational taxonomic units (OTUs) from which 70 species could be identified. For the PacBio, 36,000 sequences from over 58,000 raw reads could be assigned to a barcode, and the in silico selected bacterial 16S rRNA V1V2 gene region generated 154 OTUs grouped into 63 species, of which 62% were shared with the MiSeq dataset. The PacBio full-length bacterial 16S rRNA gene datasets generated 261 OTUs, which were grouped into 52 species, of which 54% were shared with the MiSeq dataset. Alpha diversity index reported a higher diversity in the MiSeq dataset.The PacBio sequencing error rate is now in the same range of the previously widely used Roche 454 sequencing platform and current MiSeq platform. Species-level microbiome analysis revealed some inconsistencies between the full-length bacterial 16S rRNA gene capillary sequencing and PacBio sequencing.
September 22, 2019 |
G&T-seq: parallel sequencing of single-cell genomes and transcriptomes.
The simultaneous sequencing of a single cell’s genome and transcriptome offers a powerful means to dissect genetic variation and its effect on gene expression. Here we describe G&T-seq, a method for separating and sequencing genomic DNA and full-length mRNA from single cells. By applying G&T-seq to over 220 single cells from mice and humans, we discovered cellular properties that could not be inferred from DNA or RNA sequencing alone.
September 22, 2019 |
Transcriptional diversity during lineage commitment of human blood progenitors.
Blood cells derive from hematopoietic stem cells through stepwise fating events. To characterize gene expression programs driving lineage choice, we sequenced RNA from eight primary human hematopoietic progenitor populations representing the major myeloid commitment stages and the main lymphoid stage. We identified extensive cell type-specific expression changes: 6711 genes and 10,724 transcripts, enriched in non-protein-coding elements at early stages of differentiation. In addition, we found 7881 novel splice junctions and 2301 differentially used alternative splicing events, enriched in genes involved in regulatory processes. We demonstrated experimentally cell-specific isoform usage, identifying nuclear factor I/B (NFIB) as a regulator of megakaryocyte maturation-the platelet precursor. Our data highlight the complexity of fating events in closely related progenitor populations, the understanding of which is essential for the advancement of transplantation and regenerative medicine. Copyright © 2014, American Association for the Advancement of Science.
September 22, 2019 |
Meeting report: 31st International Mammalian Genome Conference, Mammalian Genetics and Genomics: From Molecular Mechanisms to Translational Applications.
High on the Heidelberg hills, inside the Advanced Training Centre of the European Molecular Biology Laboratory (EMBL) campus with its unique double-helix staircase, scientists gathered for the EMBL conference “Mammalian Genetics and Genomics: From Molecular Mechanisms to Translational Applications,” organized in cooperation with the International Mammalian Genome Society (IMGS) and the Mouse Molecular Genetics (MMG) group. The conference attracted 205 participants from 30 countries, representing 6 of the 7 continents-all except Antarctica. It was a richly diverse group of geneticists, clinicians, and bioinformaticians, with presentations by established and junior investigators, including many trainees. From the 24th-27th of October 2017, they shared exciting advances in mammalian genetics and genomics research, from the introduction of cutting-edge technologies to descriptions of translational studies involving highly relevant models of human disease.
September 22, 2019 |
The state of play in higher eukaryote gene annotation.
A genome sequence is worthless if it cannot be deciphered; therefore, efforts to describe – or ‘annotate’ – genes began as soon as DNA sequences became available. Whereas early work focused on individual protein-coding genes, the modern genomic ocean is a complex maelstrom of alternative splicing, non-coding transcription and pseudogenes. Scientists – from clinicians to evolutionary biologists – need to navigate these waters, and this has led to the design of high-throughput, computationally driven annotation projects. The catalogues that are being produced are key resources for genome exploration, especially as they become integrated with expression, epigenomic and variation data sets. Their creation, however, remains challenging.
September 22, 2019 |
Genomics and host specialization of honey bee and bumble bee gut symbionts.
Gilliamella apicola and Snodgrassella alvi are dominant members of the honey bee (Apis spp.) and bumble bee (Bombus spp.) gut microbiota. We generated complete genomes of the type strains G. apicola wkB1(T) and S. alvi wkB2(T) (isolated from Apis), as well as draft genomes for four other strains from Bombus. G. apicola and S. alvi were found to occupy very different metabolic niches: The former is a saccharolytic fermenter, whereas the latter is an oxidizer of carboxylic acids. Together, they may form a syntrophic network for partitioning of metabolic resources. Both species possessed numerous genes [type 6 secretion systems, repeats in toxin (RTX) toxins, RHS proteins, adhesins, and type IV pili] that likely mediate cell-cell interactions and gut colonization. Variation in these genes could account for the host fidelity of strains observed in previous phylogenetic studies. Here, we also show the first experimental evidence, to our knowledge, for this specificity in vivo: Strains of S. alvi were able to colonize their native bee host but not bees of another genus. Consistent with specific, long-term host association, comparative genomic analysis revealed a deep divergence and little or no gene flow between Apis and Bombus gut symbionts. However, within a host type (Apis or Bombus), we detected signs of horizontal gene transfer between G. apicola and S. alvi, demonstrating the importance of the broader gut community in shaping the evolution of any one member. Our results show that host specificity is likely driven by multiple factors, including direct host-microbe interactions, microbe-microbe interactions, and social transmission.
September 22, 2019 |
Accurate characterization of the IFITM locus using MiSeq and PacBio sequencing shows genetic variation in Galliformes.
Interferon inducible transmembrane (IFITM) proteins are effectors of the immune system widely characterized for their role in restricting infection by diverse enveloped and non-enveloped viruses. The chicken IFITM (chIFITM) genes are clustered on chromosome 5 and to date four genes have been annotated, namely chIFITM1, chIFITM3, chIFITM5 and chIFITM10. However, due to poor assembly of this locus in the Gallus Gallus v4 genome, accurate characterization has so far proven problematic. Recently, a new chicken reference genome assembly Gallus Gallus v5 was generated using Sanger, 454, Illumina and PacBio sequencing technologies identifying considerable differences in the chIFITM locus over the previous genome releases.We re-sequenced the locus using both Illumina MiSeq and PacBio RS II sequencing technologies and we mapped RNA-seq data from the European Nucleotide Archive (ENA) to this finalized chIFITM locus. Using SureSelect probes capture probes designed to the finalized chIFITM locus, we sequenced the locus of a different chicken breed, namely a White Leghorn, and a turkey.We confirmed the Gallus Gallus v5 consensus except for two insertions of 5 and 1 base pair within the chIFITM3 and B4GALNT4 genes, respectively, and a single base pair deletion within the B4GALNT4 gene. The pull down revealed a single amino acid substitution of A63V in the CIL domain of IFITM2 compared to Red Jungle fowl and 13, 13 and 11 differences between IFITM1, 2 and 3 of chickens and turkeys, respectively. RNA-seq shows chIFITM2 and chIFITM3 expression in numerous tissue types of different chicken breeds and avian cell lines, while the expression of the putative chIFITM1 is limited to the testis, caecum and ileum tissues.Locus resequencing using these capture probes and RNA-seq based expression analysis will allow the further characterization of genetic diversity within Galliformes.
September 22, 2019 |
Ensembl 2018
The Ensembl project has been aggregating, processing, integrating and redistributing genomic datasets since the initial releases of the draft human genome, with the aim of accelerating genomics research through rapid open distribution of public data. Large amounts of raw data are thus transformed into knowledge, which is made available via a multitude of channels, in particular our browser (http://www.ensembl.org). Over time, we have expanded in multiple directions. First, our resources describe multiple fields of genomics, in particular gene annotation, comparative genomics, genetics and epigenomics. Second, we cover a growing number of genome assemblies; Ensembl Release 90 contains exactly 100. Third, our databases feed simultaneously into an array of services designed around different use cases, ranging from quick browsing to genome-wide bioinformatic analysis. We present here the latest developments of the Ensembl project, with a focus on managing an increasing number of assemblies, supporting efforts in genome interpretation and improving our browser.
September 22, 2019 |
Single-cell multiomics: multiple measurements from single cells.
Single-cell sequencing provides information that is not confounded by genotypic or phenotypic heterogeneity of bulk samples. Sequencing of one molecular type (RNA, methylated DNA or open chromatin) in a single cell, furthermore, provides insights into the cell’s phenotype and links to its genotype. Nevertheless, only by taking measurements of these phenotypes and genotypes from the same single cells can such inferences be made unambiguously. In this review, we survey the first experimental approaches that assay, in parallel, multiple molecular types from the same single cell, before considering the challenges and opportunities afforded by these and future technologies. Copyright © 2016. Published by Elsevier Ltd.
September 22, 2019 |
Long reads: their purpose and place.
In recent years long-read technologies have moved from being a niche and specialist field to a point of relative maturity likely to feature frequently in the genomic landscape. Analogous to next generation sequencing, the cost of sequencing using long-read technologies has materially dropped whilst the instrument throughput continues to increase. Together these changes present the prospect of sequencing large numbers of individuals with the aim of fully characterizing genomes at high resolution. In this article, we will endeavour to present an introduction to long-read technologies showing: what long reads are; how they are distinct from short reads; why long reads are useful and how they are being used. We will highlight the recent developments in this field, and the applications and potential of these technologies in medical research, and clinical diagnostics and therapeutics.
September 22, 2019 |
Event analysis: Using transcript events to improve estimates of abundance in RNA-seq data.
Alternative splicing leverages genomic content by allowing the synthesis of multiple transcripts and, by implication, protein isoforms, from a single gene. However, estimating the abundance of transcripts produced in a given tissue from short sequencing reads is difficult and can result in both the construction of transcripts that do not exist, and the failure to identify true transcripts. An alternative approach is to catalog the events that make up isoforms (splice junctions and exons). We present here the Event Analysis (EA) approach, where we project transcripts onto the genome and identify overlapping/unique regions and junctions. In addition, all possible logical junctions are assembled into a catalog. Transcripts are filtered before quantitation based on simple measures: the proportion of the events detected, and the coverage. We find that mapping to a junction catalog is more efficient at detecting novel junctions than mapping in a splice aware manner. We identify 99.8% of true transcripts while iReckon identifies 82% of the true transcripts and creates more transcripts not included in the simulation than were initially used in the simulation. Using PacBio Iso-seq data from a mouse neural progenitor cell model, EA detects 60% of the novel junctions that are combinations of existing exons while only 43% are detected by STAR. EA further detects ~5,000 annotated junctions missed by STAR. Filtering transcripts based on the proportion of the transcript detected and the number of reads on average supporting that transcript captures 95% of the PacBio transcriptome. Filtering the reference transcriptome before quantitation, results in is a more stable estimate of isoform abundance, with improved correlation between replicates. This was particularly evident when EA is applied to an RNA-seq study of type 1 diabetes (T1D), where the coefficient of variation among subjects (n = 81) in the transcript abundance estimates was substantially reduced compared to the estimation using the full reference. EA focuses on individual transcriptional events. These events can be quantitate and analyzed directly or used to identify the probable set of expressed transcripts. Simple rules based on detected events and coverage used in filtering result in a dramatic improvement in isoform estimation without the use of ancillary data (e.g., ChIP, long reads) that may not be available for many studies. Copyright © 2018 Newman et al.