Reference genomes for BALB/c Nude and NOD/SCID mouse models.

Mouse xenograft models play a vital role in tumor studies for research as well as for screening of drugs for the pharmaceutical industry. In particular, models with compromised immunity are favorable to increase the success of transplantation, such as, e.g. NOD/SCID and BALB/c Nude strains. The genomic sequence and alterations of many of these models still remain elusive and might hamper a model's further optimization or proper adapted usage. This can be in respect to treatments (e.g. NOD/SCID sensitivity to radiation), experiments or analysis of derived sequencing data of such models. Here we present the genome assemblies for the NOD/SCID and BALB/c Nude strains to overcome this short-coming for the future and improve our understanding of these models in the process. We highlight as well first insights into observed genomic differences for these models compared to the C57BL/6 reference genome. Genome assemblies for both are close to full-chromosome representations and provided with liftover annotations from the GRCm39 reference genome.

Exploiting parallelization in positional Burrows-Wheeler transform (PBWT) algorithms for efficient haplotype matching and compression.

Summary: The positional Burrows-Wheeler transform (PBWT) data structure allows for efficient haplotype data matching and compression. Its performance makes it a powerful tool for bioinformatics. However, existing algorithms do not exploit parallelism due to inner dependencies. We introduce a new method to break the dependencies and show how to fully exploit modern multi-core processors. Availability and implementation: Source code and applications are available at https://github.com/rwk-unil/parallel_pbwt. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

Integrated multi-omics reveals anaplerotic rewiring in methylmalonyl-CoA mutase deficiency.

Methylmalonic aciduria (MMA) is an inborn error of metabolism with multiple monogenic causes and a poorly understood pathogenesis, leading to the absence of effective causal treatments. Here we employ multi-layered omics profiling combined with biochemical and clinical features of individuals with MMA to reveal a molecular diagnosis for 177 out of 210 (84%) cases, the majority (148) of whom display pathogenic variants in methylmalonyl-CoA mutase (MMUT). Stratification of these data layers by disease severity shows dysregulation of the tricarboxylic acid cycle and its replenishment (anaplerosis) by glutamine. The relevance of these disturbances is evidenced by multi-organ metabolomics of a hemizygous Mmut mouse model as well as through identification of physical interactions between MMUT and glutamine anaplerotic enzymes. Using stable-isotope tracing, we find that treatment with dimethyl-oxoglutarate restores deficient tricarboxylic acid cycling. Our work highlights glutamine anaplerosis as a potential therapeutic intervention point in MMA.

Repeat Detector: versatile sizing of expanded tandem repeats and identification of interrupted alleles from targeted DNA sequencing.

Targeted DNA sequencing approaches will improve how the size of short tandem repeats is measured for diagnostic tests and preclinical studies. The expansion of these sequences causes dozens of disorders, with longer tracts generally leading to a more severe disease. Interrupted alleles are sometimes present within repeats and can alter disease manifestation. Determining repeat size mosaicism and identifying interruptions in targeted sequencing datasets remains a major challenge. This is in part because standard alignment tools are ill-suited for repetitive and unstable sequences. To address this, we have developed Repeat Detector (RD), a deterministic profile weighting algorithm for counting repeats in targeted sequencing data. We tested RD using blood-derived DNA samples from Huntington's disease and Fuchs endothelial corneal dystrophy patients sequenced using either Illumina MiSeq or Pacific Biosciences single-molecule, real-time sequencing platforms. RD was highly accurate in determining repeat sizes of 609 blood-derived samples from Huntington's disease individuals and did not require prior knowledge of the flanking sequences. Furthermore, RD can be used to identify alleles with interruptions and provide a measure of repeat instability within an individual. RD is therefore highly versatile and may find applications in the diagnosis of expanded repeat disorders and in the development of novel therapies.

An anti-influenza combined therapy assessed by single cell RNA-sequencing.

Influenza makes millions of people ill every year, placing a large burden on the healthcare system and the economy. To develop a treatment against influenza, we combined virucidal sialylated cyclodextrins with interferon lambda and demonstrated, in human airway epithelia, that the two compounds inhibit the replication of a clinical H1N1 strain more efficiently when administered together rather than alone. We investigated the mechanism of action of the combined treatment by single cell RNA-sequencing analysis and found that both the single and combined treatments impair viral replication to different extents across distinct epithelial cell types. We showed that each cell type comprises multiple sub-types, whose proportions are altered by H1N1 infection, and assessed the ability of the treatments to restore them. To the best of our knowledge this is the first study investigating the effectiveness of an antiviral therapy against influenza virus by single cell transcriptomic studies.

Towards mouse genetic-specific RNA-sequencing read mapping.

Genetic variations affect behavior and cause disease but understanding how these variants drive complex traits is still an open question. A common approach is to link the genetic variants to intermediate molecular phenotypes such as the transcriptome using RNA-sequencing (RNA-seq). Paradoxically, these variants between the samples are usually ignored at the beginning of RNA-seq analyses of many model organisms. This can skew the transcriptome estimates that are used later for downstream analyses, such as expression quantitative trait locus (eQTL) detection. Here, we assessed the impact of reference-based analysis on the transcriptome and eQTLs in a widely-used mouse genetic population: the BXD panel of recombinant inbred lines. We highlight existing reference bias in the transcriptome data analysis and propose practical solutions which combine available genetic variants, genotypes, and genome reference sequence. The use of custom BXD line references improved downstream analysis compared to classical genome reference. These insights would likely benefit genetic studies with a transcriptomic component and demonstrate that genome references need to be reassessed and improved.

Dissection of the macrophage response towards infection by the Leishmania-viral endosymbiont duo and dynamics of the type I interferon response.

Leishmania RNA virus 1 (LRV1) is a double-stranded RNA virus found in some strains of the human protozoan parasite Leishmania, the causative agent of leishmaniasis, a neglected tropical disease. Interestingly, the presence of LRV1 inside Leishmania constitutes an important virulence factor that worsens the leishmaniasis outcome in a type I interferon (IFN)-dependent manner and contributes to treatment failure. Understanding how macrophages respond toward Leishmania alone or in combination with LRV1 as well as the role that type I IFNs may play during infection is fundamental to oversee new therapeutic strategies. To dissect the macrophage response toward infection, RNA sequencing was performed on murine wild-type and Ifnar-deficient bone marrow-derived macrophages infected with Leishmania guyanensis (Lgy) devoid or not of LRV1. Additionally, macrophages were treated with poly I:C (mimetic virus) or with type I IFNs. By implementing a weighted gene correlation network analysis, the groups of genes (modules) with similar expression patterns, for example, functionally related, coregulated, or the members of the same functional pathway, were identified. These modules followed patterns dependent on Leishmania, LRV1, or Leishmania exacerbated by the presence of LRV1. Not only the visualization of how individual genes were embedded to form modules but also how different modules were related to each other were observed. Thus, in the context of the observed hyperinflammatory phenotype associated to the presence of LRV1, it was noted that the biomarkers tumor-necrosis factor α (TNF-α) and the interleukin 6 (IL-6) belonged to different modules and that their regulating specific Src-family kinases were segregated oppositely. In addition, this network approach revealed the strong and sustained effect of LRV1 on the macrophage response and genes that had an early, late, or sustained impact during infection, uncovering the dynamics of the IFN response. Overall, this study contributed to shed light and dissect the intricate macrophage response toward infection by the Leishmania-LRV1 duo and revealed the crosstalk between modules made of coregulated genes and provided a new resource that can be further explored to study the impact of Leishmania on the macrophage response.

XSI-a genotype compression tool for compressive genomics in large biobanks.

MOTIVATION: Generation of genotype data has been growing exponentially over the last decade. With the large size of recent datasets comes a storage and computational burden with ever increasing costs. To reduce this burden, we propose XSI, a file format with reduced storage footprint that also allows computation on the compressed data and we show how this can improve future analyses. RESULTS: We show that xSqueezeIt (XSI) allows for a file size reduction of 4-20× compared with compressed BCF and demonstrate its potential for 'compressive genomics' on the UK Biobank whole-genome sequencing genotypes with 8× faster loading times, 5× faster run of homozygozity computation, 30× faster dot products computation and 280× faster allele counts. AVAILABILITY AND IMPLEMENTATION: The XSI file format specifications, API and command line tool are released under open-source (MIT) license and are available at https://github.com/rwk-unil/xSqueezeIt. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Sex-Biased Control of Inflammation and Metabolism by a Mitochondrial Nod-Like Receptor.

Mitochondria regulate steroid hormone synthesis, and in turn sex hormones regulate mitochondrial function for maintaining cellular homeostasis and controlling inflammation. This crosstalk can explain sex differences observed in several pathologies such as in metabolic or inflammatory disorders. Nod-like receptor X1 (NLRX1) is a mitochondria-associated innate receptor that could modulate metabolic functions and attenuates inflammatory responses. Here, we showed that in an infectious model with the human protozoan parasite, Leishmania guyanensis, NLRX1 attenuated inflammation in females but not in male mice. Analysis of infected female and male bone marrow derived macrophages showed both sex- and genotype-specific differences in both inflammatory and metabolic profiles with increased type I interferon production, mitochondrial respiration, and glycolytic rate in Nlrx1-deficient female BMDMs in comparison to wild-type cells, while no differences were observed between males. Transcriptomics of female and male BMDMs revealed an altered steroid hormone signaling in Nlrx1-deficient cells, and a "masculinization" of Nlrx1-deficient female BMDMs. Thus, our findings suggest that NLRX1 prevents uncontrolled inflammation and metabolism in females and therefore may contribute to the sex differences observed in infectious and inflammatory diseases.

External Quality Assessment of SARS-CoV-2 Sequencing: an ESGMD-SSM Pilot Trial across 15 European Laboratories.

This first pilot trial on external quality assessment (EQA) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) whole-genome sequencing, initiated by the European Society of Clinical Microbiology and Infectious Diseases (ESCMID) Study Group for Genomic and Molecular Diagnostics (ESGMD) and the Swiss Society for Microbiology (SSM), aims to build a framework between laboratories in order to improve pathogen surveillance sequencing. Ten samples with various viral loads were sent out to 15 clinical laboratories that had free choice of sequencing methods and bioinformatic analyses. The key aspects on which the individual centers were compared were the identification of (i) single nucleotide polymorphisms (SNPs) and indels, (ii) Pango lineages, and (iii) clusters between samples. The participating laboratories used a wide array of methods and analysis pipelines. Most were able to generate whole genomes for all samples. Genomes were sequenced to various depths (up to a 100-fold difference across centers). There was a very good consensus regarding the majority of reporting criteria, but there were a few discrepancies in lineage and cluster assignments. Additionally, there were inconsistencies in variant calling. The main reasons for discrepancies were missing data, bioinformatic choices, and interpretation of data. The pilot EQA was overall a success. It was able to show the high quality of participating laboratories and provide valuable feedback in cases where problems occurred, thereby improving the sequencing setup of laboratories. A larger follow-up EQA should, however, improve on defining the variables and format of the report. Additionally, contamination and/or minority variants should be a further aspect of assessment.

Quantification of the spread of SARS-CoV-2 variant B.1.1.7 in Switzerland.

BACKGROUND: In December 2020, the United Kingdom (UK) reported a SARS-CoV-2 Variant of Concern (VoC) which is now named B.1.1.7. Based on initial data from the UK and later data from other countries, this variant was estimated to have a transmission fitness advantage of around 40-80 % (Volz et al., 2021; Leung et al., 2021; Davies et al., 2021). AIM: This study aims to estimate the transmission fitness advantage and the effective reproductive number of B.1.1.7 through time based on data from Switzerland. METHODS: We generated whole genome sequences from 11.8 % of all confirmed SARS-CoV-2 cases in Switzerland between 14 December 2020 and 11 March 2021. Based on these data, we determine the daily frequency of the B.1.1.7 variant and quantify the variant's transmission fitness advantage on a national and a regional scale. RESULTS: We estimate B.1.1.7 had a transmission fitness advantage of 43-52 % compared to the other variants circulating in Switzerland during the study period. Further, we estimate B.1.1.7 had a reproductive number above 1 from 01 January 2021 until the end of the study period, compared to below 1 for the other variants. Specifically, we estimate the reproductive number for B.1.1.7 was 1.24 [1.07-1.41] from 01 January until 17 January 2021 and 1.18 [1.06-1.30] from 18 January until 01 March 2021 based on the whole genome sequencing data. From 10 March to 16 March 2021, once B.1.1.7 was dominant, we estimate the reproductive number was 1.14 [1.00-1.26] based on all confirmed cases. For reference, Switzerland applied more non-pharmaceutical interventions to combat SARS-CoV-2 on 18 January 2021 and lifted some measures again on 01 March 2021. CONCLUSION: The observed increase in B.1.1.7 frequency in Switzerland during the study period is as expected based on observations in the UK. In absolute numbers, B.1.1.7 increased exponentially with an estimated doubling time of around 2-3.5 weeks. To monitor the ongoing spread of B.1.1.7, our plots are available online.

Unsupervised Analysis of Flow Cytometry Data in a Clinical Setting Captures Cell Diversity and Allows Population Discovery.

Data obtained with cytometry are increasingly complex and their interrogation impacts the type and quality of knowledge gained. Conventional supervised analyses are limited to pre-defined cell populations and do not exploit the full potential of data. Here, in the context of a clinical trial of cancer patients treated with radiotherapy, we performed longitudinal flow cytometry analyses to identify multiple distinct cell populations in circulating whole blood. We cross-compared the results from state-of-the-art recommended supervised analyses with results from MegaClust, a high-performance data-driven clustering algorithm allowing fast and robust identification of cell-type populations. Ten distinct cell populations were accurately identified by supervised analyses, including main T, B, dendritic cell (DC), natural killer (NK) and monocytes subsets. While all ten subsets were also identified with MegaClust, additional cell populations were revealed (e.g. CD4+HLA-DR+ and NKT-like subsets), and DC profiling was enriched by the assignment of additional subset-specific markers. Comparison between transcriptomic profiles of purified DC populations and publicly available datasets confirmed the accuracy of the unsupervised clustering algorithm and demonstrated its potential to identify rare and scarcely described cell subsets. Our observations show that data-driven analyses of cytometry data significantly enrich the amount and quality of knowledge gained, representing an important step in refining the characterization of immune responses.

Blood virosphere in febrile Tanzanian children.

Viral infections are the leading cause of childhood acute febrile illnesses motivating consultation in sub-Saharan Africa. The majority of causal viruses are never identified in low-resource clinical settings as such testing is either not part of routine screening or available diagnostic tools have limited ability to detect new/unexpected viral variants. An in-depth exploration of the blood virome is therefore necessary to clarify the potential viral origin of fever in children. Metagenomic next-generation sequencing is a powerful tool for such broad investigations, allowing the detection of RNA and DNA viral genomes. Here, we describe the blood virome of 816 febrile children (<5 years) presenting at outpatient departments in Dar es Salaam over one-year. We show that half of the patients (394/816) had at least one detected virus recognized as causes of human infection/disease (13.8% enteroviruses (enterovirus A, B, C, and rhinovirus A and C), 12% rotaviruses, 11% human herpesvirus type 6). Additionally, we report the detection of a large number of viruses (related to arthropod, vertebrate or mammalian viral species) not yet known to cause human infection/disease, highlighting those who should be on the radar, deserve specific attention in the febrile paediatric population and, more broadly, for surveillance of emerging pathogens.Trial registration: ClinicalTrials.gov identifier: NCT02225769.

Setting the basis of best practices and standards for curation and annotation of logical models in biology-highlights of the [BC]2 2019 CoLoMoTo/SysMod Workshop.

The fast accumulation of biological data calls for their integration, analysis and exploitation through more systematic approaches. The generation of novel, relevant hypotheses from this enormous quantity of data remains challenging. Logical models have long been used to answer a variety of questions regarding the dynamical behaviours of regulatory networks. As the number of published logical models increases, there is a pressing need for systematic model annotation, referencing and curation in community-supported and standardised formats. This article summarises the key topics and future directions of a meeting entitled 'Annotation and curation of computational models in biology', organised as part of the 2019 [BC]2 conference. The purpose of the meeting was to develop and drive forward a plan towards the standardised annotation of logical models, review and connect various ongoing projects of experts from different communities involved in the modelling and annotation of molecular biological entities, interactions, pathways and models. This article defines a roadmap towards the annotation and curation of logical models, including milestones for best practices and minimum standard requirements.

Virosaurus A Reference to Explore and Capture Virus Genetic Diversity.

The huge genetic diversity of circulating viruses is a challenge for diagnostic assays for emerging or rare viral diseases. High-throughput technology offers a new opportunity to explore the global virome of patients without preconception about the culpable pathogens. It requires a solid reference dataset to be accurate. Virosaurus has been designed to offer a non-biased, automatized and annotated database for clinical metagenomics studies and diagnosis. Raw viral sequences have been extracted from GenBank, and cleaned up to remove potentially erroneous sequences. Complete sequences have been identified for all genera infecting vertebrates, plants and other eukaryotes (insect, fungus, etc.). To facilitate the analysis of clinically relevant viruses, we have annotated all sequences with official and common virus names, acronym, genotypes, and genomic features (linear, circular, DNA, RNA, etc.). Sequences have been clustered to remove redundancy at 90% or 98% identity. The analysis of clustering results reveals the state of the virus genetic landscape knowledge. Because herpes and poxviruses were under-represented in complete genomes considering their potential diversity in nature, we used genes instead of complete genomes for those in Virosaurus.

Predicting combinations of immunomodulators to enhance dendritic cell-based vaccination based on a hybrid experimental and computational platform.

Dendritic cell (DC)-based vaccines have been largely used in the adjuvant setting for the treatment of cancer, however, despite their proven safety, clinical outcomes still remain modest. In order to improve their efficacy, DC-based vaccines are often combined with one or multiple immunomodulatory agents. However, the selection of the most promising combinations is hampered by the plethora of agents available and the unknown interplay between these different agents. To address this point, we developed a hybrid experimental and computational platform to predict the effects and immunogenicity of dual combinations of stimuli once combined with DC vaccination, based on the experimental data of a variety of assays to monitor different aspects of the immune response after a single stimulus. To assess the stimuli behavior when used as single agents, we first developed an in vitro co-culture system of T cell priming using monocyte-derived DCs loaded with whole tumor lysate to prime autologous peripheral blood mononuclear cells in the presence of the chosen stimuli, as single adjuvants, and characterized the elicited response assessing 18 different phenotypic and functional traits important for an efficient anti-cancer response. We then developed and applied a prediction algorithm, generating a ranking for all possible dual combinations of the different single stimuli considered here. The ranking generated by the prediction tool was then validated with experimental data showing a strong correlation with the predicted scores, confirming that the top ranked conditions globally significantly outperformed the worst conditions. Thus, the method developed here constitutes an innovative tool for the selection of the best immunomodulatory agents to implement in future DC-based vaccines.

Three-dimensional chromatin interactions remain stable upon CAG/CTG repeat expansion.

Expanded CAG/CTG repeats underlie 13 neurological disorders, including myotonic dystrophy type 1 (DM1) and Huntington's disease (HD). Upon expansion, disease loci acquire heterochromatic characteristics, which may provoke changes to chromatin conformation and thereby affect both gene expression and repeat instability. Here, we tested this hypothesis by performing 4C sequencing at the DMPK and HTT loci from DM1 and HD-derived cells. We find that allele sizes ranging from 15 to 1700 repeats displayed similar chromatin interaction profiles. This was true for both loci and for alleles with different DNA methylation levels and CTCF binding. Moreover, the ectopic insertion of an expanded CAG repeat tract did not change the conformation of the surrounding chromatin. We conclude that CAG/CTG repeat expansions are not enough to alter chromatin conformation in cis. Therefore, it is unlikely that changes in chromatin interactions drive repeat instability or changes in gene expression in these disorders.

New genome assembly of the barn owl (Tyto alba alba).

New genomic tools open doors to study ecology, evolution, and population genomics of wild animals. For the Barn owl species complex, a cosmopolitan nocturnal raptor, a very fragmented draft genome was assembled for the American species (Tyto furcata pratincola) (Jarvis et al. 2014). To improve the genome, we assembled de novo Illumina and Pacific Biosciences (PacBio) long reads sequences of its European counterpart (Tyto alba alba). This genome assembly of 1.219 Gbp comprises 21,509 scaffolds and results in a N50 of 4,615,526 bp. BUSCO (Universal Single-Copy Orthologs) analysis revealed an assembly completeness of 94.8% with only 1.8% of the genes missing out of 4,915 avian orthologs searched, a proportion similar to that found in the genomes of the zebra finch (Taeniopygia guttata) or the collared flycatcher (Ficedula albicollis). By mapping the reads of the female American barn owl to the male European barn owl reads, we detected several structural variants and identified 70 Mbp of the Z chromosome. The barn owl scaffolds were further mapped to the chromosomes of the zebra finch. In addition, the completeness of the European barn owl genome is demonstrated with 94 of 128 proteins missing in the chicken genome retrieved in the European barn owl transcripts. This improved genome will help future barn owl population genomic investigations.

Integrated proteogenomic deep sequencing and analytics accurately identify non-canonical peptides in tumor immunopeptidomes.

Efforts to precisely identify tumor human leukocyte antigen (HLA) bound peptides capable of mediating T cell-based tumor rejection still face important challenges. Recent studies suggest that non-canonical tumor-specific HLA peptides derived from annotated non-coding regions could elicit anti-tumor immune responses. However, sensitive and accurate mass spectrometry (MS)-based proteogenomics approaches are required to robustly identify these non-canonical peptides. We present an MS-based analytical approach that characterizes the non-canonical tumor HLA peptide repertoire, by incorporating whole exome sequencing, bulk and single-cell transcriptomics, ribosome profiling, and two MS/MS search tools in combination. This approach results in the accurate identification of hundreds of shared and tumor-specific non-canonical HLA peptides, including an immunogenic peptide derived from an open reading frame downstream of the melanoma stem cell marker gene ABCB5. These findings hold great promise for the discovery of previously unknown tumor antigens for cancer immunotherapy.

Contribution of exome sequencing to the identification of genes involved in the response to clopidogrel in cardiovascular patients.

BACKGROUND: On-clopidogrel platelet reactivity (PR) is associated with the risk of thrombotic or bleeding event in selected populations of high-risk patients. PR is a highly heritable phenotype and a few variants of cytochrome genes, essentially CYP2C19, are associated with PR but only explain 5% to 12% of the variability. OBJECTIVE: The aim of this study is to delineate genetic determinants of on-clopidogrel PR using high-throughput sequencing. METHODS: We performed a whole exome sequencing of 96 low- and matched high-PR patients in a discovery cohort. Exomes from genes with variants significantly associated with PR were sequenced in 96 low- and matched high-PR patients from an independent replication cohort. RESULTS: We identified 585 variants in 417 genes with an adjusted P value < .05. In the replication cohort, all top variants including CYP2C8, CYP2C18, and CYP2C19 from the discovery population were found again. An original network analysis identified several candidate genes of potential interest such as a regulator of PI3K, a key actor in the downstream signaling pathway of the P2Y12 receptor. CONCLUSION: This study emphasizes the role of CYP-related genes as major regulators of clopidogrel response, including the poorly investigated CYP2C8 and CYP2C18.