Making ubiquitin specific

Luteinizing hormone stimulates ingression of mural granulosa cells within the mouse preovulatory follicle

Luteinizing hormone (LH) induces ovulation by acting on its receptors in the mural granulosa cells that surround a mammalian oocyte in an ovarian follicle. However, much remains unknown about how activation of the LH receptor modifies the structure of the follicle such that the oocyte is released and the follicle remnants are transformed into the corpus luteum. The present study shows that the preovulatory surge of LH stimulates LH receptor-expressing granulosa cells, initially located almost entirely in the outer layers of the mural granulosa, to rapidly extend inwards, intercalating between other cells. The cellular ingression begins within 30 minutes of the peak of the LH surge, and the proportion of LH receptor-expressing cell bodies in the inner half of the mural granulosa layer increases until the time of ovulation, which occurs at about 10 hours after the LH peak. During this time, many of the initially flask-shaped cells appear to detach from the basal lamina, acquiring a rounder shape with multiple filipodia. Starting at about 4 hours after the LH peak, the mural granulosa layer at the apical surface of the follicle where ovulation will occur begins to thin, and the basolateral surface develops invaginations and constrictions. Our findings raise the question of whether LH stimulation of granulosa cell ingression may contribute to these changes in the follicular structure that enable ovulation.

Accurate sequencing of DNA motifs able to form alternative (non-B) structures

Approximately 13% of the human genome at certain motifs have the potential to form noncanonical (non-B) DNA structures (e.g., G-quadruplexes, cruciforms, and Z-DNA), which regulate many cellular processes but also affect the activity of polymerases and helicases. Because sequencing technologies use these enzymes, they might possess increased errors at non-B structures. To evaluate this, we analyzed error rates, read depth, and base quality of Illumina, Pacific Biosciences (PacBio) HiFi, and Oxford Nanopore Technologies (ONT) sequencing at non-B motifs. All technologies showed altered sequencing success for most non-B motif types, although this could be owing to several factors, including structure formation, biased GC content, and the presence of homopolymers. Single-nucleotide mismatch errors had low biases in HiFi and ONT for all non-B motif types but were increased for G-quadruplexes and Z-DNA in all three technologies. Deletion errors were increased for all non-B types but Z-DNA in Illumina and HiFi, as well as only for G-quadruplexes in ONT. Insertion errors for non-B motifs were highly, moderately, and slightly elevated in Illumina, HiFi, and ONT, respectively. Additionally, we developed a probabilistic approach to determine the number of false positives at non-B motifs depending on sample size and variant frequency, and applied it to publicly available data sets (1000 Genomes, Simons Genome Diversity Project, and gnomAD). We conclude that elevated sequencing errors at non-B DNA motifs should be considered in low-read-depth studies (single-cell, ancient DNA, and pooled-sample population sequencing) and in scoring rare variants. Combining technologies should maximize sequencing accuracy in future studies of non-B DNA.

Complete telomere-to-telomere de novo assembly of the Plasmodium falciparum genome through long-read (>11 kb), single molecule, real-time sequencing

The application of next-generation sequencing to estimate genetic diversity of Plasmodium falciparum, the most lethal malaria parasite, has proved challenging due to the skewed AT-richness [∼80.6% (A + T)] of its genome and the lack of technology to assemble highly polymorphic subtelomeric regions that contain clonally variant, multigene virulence families (Ex: var and rifin). To address this, we performed amplification-free, single molecule, real-time sequencing of P. falciparum genomic DNA and generated reads of average length 12 kb, with 50% of the reads between 15.5 and 50 kb in length. Next, using the Hierarchical Genome Assembly Process, we assembled the P. falciparum genome de novo and successfully compiled all 14 nuclear chromosomes telomere-to-telomere. We also accurately resolved centromeres [∼90–99% (A + T)] and subtelomeric regions and identified large insertions and duplications that add extra var and rifin genes to the genome, along with smaller structural variants such as homopolymer tract expansions. Overall, we show that amplification-free, long-read sequencing combined with de novo assembly overcomes major challenges inherent to studying the P. falciparum genome. Indeed, this technology may not only identify the polymorphic and repetitive subtelomeric sequences of parasite populations from endemic areas but may also evaluate structural variation linked to virulence, drug resistance and disease transmission.

Evaluation of an Optimal Epidemiological Typing Scheme for Legionella pneumophila with Whole-Genome Sequence Data Using Validation Guidelines

Sequence-based typing (SBT), analogous to multilocus sequence typing (MLST), is the current "gold standard" typing method for investigation of legionellosis outbreaks caused by Legionella pneumophila However, as common sequence types (STs) cause many infections, some investigations remain unresolved. In this study, various whole-genome sequencing (WGS)-based methods were evaluated according to published guidelines, including (i) a single nucleotide polymorphism (SNP)-based method, (ii) extended MLST using different numbers of genes, (iii) determination of gene presence or absence, and (iv) a kmer-based method. L. pneumophila serogroup 1 isolates (n = 106) from the standard "typing panel," previously used by the European Society for Clinical Microbiology Study Group on Legionella Infections (ESGLI), were tested together with another 229 isolates. Over 98% of isolates were considered typeable using the SNP- and kmer-based methods. Percentages of isolates with complete extended MLST profiles ranged from 99.1% (50 genes) to 86.8% (1,455 genes), while only 41.5% produced a full profile with the gene presence/absence scheme. Replicates demonstrated that all methods offer 100% reproducibility. Indices of discrimination range from 0.972 (ribosomal MLST) to 0.999 (SNP based), and all values were higher than that achieved with SBT (0.940). Epidemiological concordance is generally inversely related to discriminatory power. We propose that an extended MLST scheme with ∼50 genes provides optimal epidemiological concordance while substantially improving the discrimination offered by SBT and can be used as part of a hierarchical typing scheme that should maintain backwards compatibility and increase discrimination where necessary. This analysis will be useful for the ESGLI to design a scheme that has the potential to become the new gold standard typing method for L. pneumophila.

The TraDIS toolkit: sequencing and analysis for dense transposon mutant libraries

Summary: Transposon insertion sequencing is a high-throughput technique for assaying large libraries of otherwise isogenic transposon mutants providing insight into gene essentiality, gene function and genetic interactions. We previously developed the Transposon Directed Insertion Sequencing (TraDIS) protocol for this purpose, which utilizes shearing of genomic DNA followed by specific PCR amplification of transposon-containing fragments and Illumina sequencing. Here we describe an optimized high-yield library preparation and sequencing protocol for TraDIS experiments and a novel software pipeline for analysis of the resulting data. The Bio-Tradis analysis pipeline is implemented as an extensible Perl library which can either be used as is, or as a basis for the development of more advanced analysis tools. This article can serve as a general reference for the application of the TraDIS methodology.

Availability and implementation: The optimized sequencing protocol is included as supplementary information. The Bio-Tradis analysis pipeline is available under a GPL license at https://github.com/sanger-pathogens/Bio-Tradis

Contact:parkhill@sanger.ac.uk

Supplementary information:Supplementary data are available at Bioinformatics online.

Genome specialization and decay of the strangles pathogen, Streptococcus equi, is driven by persistent infection

Strangles, the most frequently diagnosed infectious disease of horses worldwide, is caused by Streptococcus equi. Despite its prevalence, the global diversity and mechanisms underlying the evolution of S. equi as a host-restricted pathogen remain poorly understood. Here, we define the global population structure of this important pathogen and reveal a population replacement in the late 19th or early 20th Century. Our data reveal a dynamic genome that continues to mutate and decay, but also to amplify and acquire genes despite the organism having lost its natural competence and become host-restricted. The lifestyle of S. equi within the horse is defined by short-term acute disease, strangles, followed by long-term infection. Population analysis reveals evidence of convergent evolution in isolates from post-acute disease samples as a result of niche adaptation to persistent infection within a host. Mutations that lead to metabolic streamlining and the loss of virulence determinants are more frequently found in persistent isolates, suggesting that the pathogenic potential of S. equi reduces as a consequence of long-term residency within the horse post-acute disease. An example of this is the deletion of the equibactin siderophore locus that is associated with iron acquisition, which occurs exclusively in persistent isolates, and renders S. equi significantly less able to cause acute disease in the natural host. We identify several loci that may similarly be required for the full virulence of S. equi, directing future research toward the development of new vaccines against this host-restricted pathogen.

Deep sequencing of norovirus genomes defines evolutionary patterns in an urban tropical setting

Norovirus is a highly transmissible infectious agent that causes epidemic gastroenteritis in susceptible children and adults. Norovirus infections can be severe and can be initiated from an exceptionally small number of viral particles. Detailed genome sequence data are useful for tracking norovirus transmission and evolution. To address this need, we have developed a whole-genome deep-sequencing method that generates entire genome sequences from small amounts of clinical specimens. This novel approach employs an algorithm for reverse transcription and PCR amplification primer design using all of the publically available norovirus sequence data. Deep sequencing and de novo assembly were used to generate norovirus genomes from a large set of diarrheal patients attending three hospitals in Ho Chi Minh City, Vietnam, over a 2.5-year period. Positive-selection analysis and direct examination of protein changes in the virus over time identified codons in the regions encoding proteins VP1, p48 (NS1-2), and p22 (NS4) under positive selection and expands the known targets of norovirus evolutionary pressure.

IMPORTANCE The high transmissibility and rapid evolutionary rate of norovirus, combined with a short-lived host immune responses, are thought to be the reasons why the virus causes the majority of pediatric viral diarrhea cases. The evolutionary patterns of this RNA virus have been described in detail for only a portion of the virus genome and never for a virus from a detailed urban tropical setting. We provide a detailed sequence description of the noroviruses circulating in three Ho Chi Minh City hospitals over a 2.5-year period. This study identified patterns of virus change in known sites of host immune response and identified three additional regions of the virus genome under selection that were not previously recognized. In addition, the method described here provides a robust full-genome sequencing platform for community-based virus surveillance.

Strand-specific RNA-Seq reveals widespread and developmentally regulated transcription of natural antisense transcripts in Plasmodium falciparum

BACKGROUND

Advances in high-throughput sequencing have led to the discovery of widespread transcription of natural antisense transcripts (NATs) in a large number of organisms, where these transcripts have been shown to play important roles in the regulation of gene expression. Likewise, the existence of NATs has been observed in Plasmodium but our understanding towards their genome-wide distribution remains incomplete due to the limited depth and uncertainties in the level of strand specificity of previous datasets.

RESULTS

To gain insights into the genome-wide distribution of NATs in P. falciparum, we performed RNA-ligation based strand-specific RNA sequencing at unprecedented depth. Our data indicate that 78.3% of the genome is transcribed during blood-stage development. Moreover, our analysis reveals significant levels of antisense transcription from at least 24% of protein-coding genes and that while expression levels of NATs change during the intraerythrocytic developmental cycle (IDC), they do not correlate with the corresponding mRNA levels. Interestingly, antisense transcription is not evenly distributed across coding regions (CDSs) but strongly clustered towards the 3'-end of CDSs. Furthermore, for a significant subset of NATs, transcript levels correlate with mRNA levels of neighboring genes.Finally, we were able to identify the polyadenylation sites (PASs) for a subset of NATs, demonstrating that at least some NATs are polyadenylated. We also mapped the PASs of 3443 coding genes, yielding an average 3' untranslated region length of 523 bp.

CONCLUSIONS

Our strand-specific analysis of the P. falciparum transcriptome expands and strengthens the existing body of evidence that antisense transcription is a substantial phenomenon in P. falciparum. For a subset of neighboring genes we find that sense and antisense transcript levels are intricately linked while other NATs appear to be regulated independently of mRNA transcription. Our deep strand-specific dataset will provide a valuable resource for the precise determination of expression levels as it separates sense from antisense transcript levels, which we find to often significantly differ. In addition, the extensive novel data on 3' UTR length will allow others to perform searches for regulatory motifs in the UTRs and help understand post-translational regulation in P. falciparum.