A robust SNP barcode for typing Mycobacterium tuberculosis complex strains

Strain-specific genomic diversity in the Mycobacterium tuberculosis complex (MTBC) is an important factor in pathogenesis that may affect virulence, transmissibility, host response and emergence of drug resistance. Several systems have been proposed to classify MTBC strains into distinct lineages and families. Here, we investigate single-nucleotide polymorphisms (SNPs) as robust (stable) markers of genetic variation for phylogenetic analysis. We identify ~92k SNP across a global collection of 1,601 genomes. The SNP-based phylogeny is consistent with the gold-standard regions of difference (RD) classification system. Of the ~7k strain-specific SNPs identified, 62 markers are proposed to discriminate known circulating strains. This SNP-based barcode is the first to cover all main lineages, and classifies a greater number of sublineages than current alternatives. It may be used to classify clinical isolates to evaluate tools to control the disease, including therapeutics and vaccines whose effectiveness may vary by strain type

Safe and complete contig assembly via omnitigs

Contig assembly is the first stage that most assemblers solve when reconstructing a genome from a set of reads. Its output consists of contigs -- a set of strings that are promised to appear in any genome that could have generated the reads. From the introduction of contigs 20 years ago, assemblers have tried to obtain longer and longer contigs, but the following question was never solved: given a genome graph $G$ (e.g. a de Bruijn, or a string graph), what are all the strings that can be safely reported from $G$ as contigs? In this paper we finally answer this question, and also give a polynomial time algorithm to find them. Our experiments show that these strings, which we call omnitigs, are 66% to 82% longer on average than the popular unitigs, and 29% of dbSNP locations have more neighbors in omnitigs than in unitigs.Comment: Full version of the paper in the proceedings of RECOMB 201

An investigation of causes of false positive single nucleotide polymorphisms using simulated reads from a small eukaryote genome

Background: Single Nucleotide Polymorphisms (SNPs) are widely used molecular markers, and their use has increased massively since the inception of Next Generation Sequencing (NGS) technologies, which allow detection of large numbers of SNPs at low cost. However, both NGS data and their analysis are error-prone, which can lead to the generation of false positive (FP) SNPs. We explored the relationship between FP SNPs and seven factors involved in mapping-based variant calling - quality of the reference sequence, read length, choice of mapper and variant caller, mapping stringency and filtering of SNPs by read mapping quality and read depth. This resulted in 576 possible factor level combinations. We used error- and variant-free simulated reads to ensure that every SNP found was indeed a false positive. Results: The variation in the number of FP SNPs generated ranged from 0 to 36,621 for the 120 million base pairs (Mbp) genome. All of the experimental factors tested had statistically significant effects on the number of FP SNPs generated and there was a considerable amount of interaction between the different factors. Using a fragmented reference sequence led to a dramatic increase in the number of FP SNPs generated, as did relaxed read mapping and a lack of SNP filtering. The choice of reference assembler, mapper and variant caller also significantly affected the outcome. The effect of read length was more complex and suggests a possible interaction between mapping specificity and the potential for contributing more false positives as read length increases. Conclusions: The choice of tools and parameters involved in variant calling can have a dramatic effect on the number of FP SNPs produced, with particularly poor combinations of software and/or parameter settings yielding tens of thousands in this experiment. Between-factor interactions make simple recommendations difficult for a SNP discovery pipeline but the quality of the reference sequence is clearly of paramount importance. Our findings are also a stark reminder that it can be unwise to use the relaxed mismatch settings provided as defaults by some read mappers when reads are being mapped to a relatively unfinished reference sequence from e.g. a non-model organism in its early stages of genomic exploration

Phage typing or CRISPR typing for epidemiological surveillance of Salmonella Typhimurium?

Objective: Salmonella Typhimurium is the most dominant Salmonella serovar around the world. It is associated with foodborne gastroenteritis outbreaks but has recently been associated with invasive illness and deaths. Characterization of S. Typhimurium is therefore very crucial for epidemiological surveillance. Phage typing has been used for decades for subtyping of S. Typhimurium to determine the epidemiological relation among isolates. Recent studies however have suggested that high throughput clustered regular interspaced short palindromic repeats (CRISPR) typing has the potential to replace phage typing. This study aimed to determine the efficacy of highthroughput CRISPR typing over conventional phage typing in epidemiological surveillance and outbreak investigation of S. Typhimurium. Results: In silico analysis of whole genome sequences (WGS) of well-documented phage types of S. Typhimurium reveals the presence of different CRISPR type among strains belong to the same phage type. Furthermore, different phage types of S. Typhimurium share identical CRISPR type. Interestingly, identical spacers were detected among outbreak and non-outbreak associated DT8 strains of S. Typhimurium. Therefore, CRISPR typing is not useful for the epidemiological surveillance and outbreak investigation of S. Typhimurium and phage typing, until it is replaced by WGS, is still the gold standard method for epidemiological surveillance of S. Typhimurium

Extensive Copy-Number Variation of Young Genes across Stickleback Populations

MM received funding from the Max Planck innovation funds for this project. PGDF was supported by a Marie Curie European Reintegration Grant (proposal nr 270891). CE was supported by German Science Foundation grants (DFG, EI 841/4-1 and EI 841/6-1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Bacterial microevolution and the Pangenome

The comparison of multiple genome sequences sampled from a bacterial population reveals considerable diversity in both the core and the accessory parts of the pangenome. This diversity can be analysed in terms of microevolutionary events that took place since the genomes shared a common ancestor, especially deletion, duplication, and recombination. We review the basic modelling ingredients used implicitly or explicitly when performing such a pangenome analysis. In particular, we describe a basic neutral phylogenetic framework of bacterial pangenome microevolution, which is not incompatible with evaluating the role of natural selection. We survey the different ways in which pangenome data is summarised in order to be included in microevolutionary models, as well as the main methodological approaches that have been proposed to reconstruct pangenome microevolutionary history

Shigella sonnei genome sequencing and phylogenetic analysis indicate recent global dissemination from Europe

Shigella are human-adapted Escherichia coli that have gained the ability to invade the human gut mucosa and cause dysentery1,2, spreading efficiently via low-dose fecal-oral transmission3,4. Historically, S. sonnei has been predominantly responsible for dysentery in developed countries, but is now emerging as a problem in the developing world, apparently replacing the more diverse S. flexneri in areas undergoing economic development and improvements in water quality4-6. Classical approaches have shown S. sonnei is genetically conserved and clonal7. We report here whole-genome sequencing of 132 globally-distributed isolates. Our phylogenetic analysis shows that the current S. sonnei population descends from a common ancestor that existed less than 500 years ago and has diversified into several distinct lineages with unique characteristics. Our analysis suggests the majority of this diversification occurred in Europe, followed by more recent establishment of local pathogen populations in other continents predominantly due to the pandemic spread of a single, rapidly-evolving, multidrug resistant lineage

An expanded global inventory of allelic variation in the most extremely polymorphic region of Plasmodium falciparum merozoite surface protein 1 provided by short read sequence data.

BACKGROUND: Within Plasmodium falciparum merozoite surface protein 1 (MSP1), the N-terminal block 2 region is a highly polymorphic target of naturally acquired antibody responses. The antigenic diversity is determined by complex repeat sequences as well as non-repeat sequences, grouping into three major allelic types that appear to be maintained within populations by natural selection. Within these major types, many distinct allelic sequences have been described in different studies, but the extent and significance of the diversity remains unresolved. METHODS: To survey the diversity more extensively, block 2 allelic sequences in the msp1 gene were characterized in 2400 P. falciparum infection isolates with whole genome short read sequence data available from the Pf3K project, and compared with the data from previous studies. RESULTS: Mapping the short read sequence data in the 2400 isolates to a reference library of msp1 block 2 allelic sequences yielded 3815 allele scores at the level of major allelic family types, with 46% of isolates containing two or more of these major types. Overall frequencies were similar to those previously reported in other samples with different methods, the K1-like allelic type being most common in Africa, MAD20-like most common in Southeast Asia, and RO33-like being the third most abundant type in each continent. The rare MR type, formed by recombination between MAD20-like and RO33-like alleles, was only seen in Africa and very rarely in the Indian subcontinent but not in Southeast Asia. A combination of mapped short read assembly approaches enabled 1522 complete msp1 block 2 sequences to be determined, among which there were 363 different allele sequences, of which 246 have not been described previously. In these data, the K1-like msp1 block 2 alleles are most diverse and encode 225 distinct amino acid sequences, compared with 123 different MAD20-like, 9 RO33-like and 6 MR type sequences. Within each of the major types, the different allelic sequences show highly skewed geographical distributions, with most of the more common sequences being detected in either Africa or Asia, but not in both. CONCLUSIONS: Allelic sequences of this extremely polymorphic locus have been derived from whole genome short read sequence data by mapping to a reference library followed by assembly of mapped reads. The catalogue of sequence variation has been greatly expanded, so that there are now more than 500 different msp1 block 2 allelic sequences described. This provides an extensive reference for molecular epidemiological genotyping and sequencing studies, and potentially for design of a multi-allelic vaccine

Allele-specific miRNA-binding analysis identifies candidate target genes for breast cancer risk

Most breast cancer (BC) risk-associated single-nucleotide polymorphisms (raSNPs) identified in genome-wide association studies (GWAS) are believed to cis-regulate the expression of genes. We hypothesise that cis-regulatory variants contributing to disease risk may be affecting microRNA (miRNA) genes and/or miRNA binding. To test this, we adapted two miRNA-binding prediction algorithms-TargetScan and miRanda-to perform allele-specific queries, and integrated differential allelic expression (DAE) and expression quantitative trait loci (eQTL) data, to query 150 genome-wide significant ( P≤5×10-8 ) raSNPs, plus proxies. We found that no raSNP mapped to a miRNA gene, suggesting that altered miRNA targeting is an unlikely mechanism involved in BC risk. Also, 11.5% (6 out of 52) raSNPs located in 3'-untranslated regions of putative miRNA target genes were predicted to alter miRNA::mRNA (messenger RNA) pair binding stability in five candidate target genes. Of these, we propose RNF115, at locus 1q21.1, as a strong novel target gene associated with BC risk, and reinforce the role of miRNA-mediated cis-regulation at locus 19p13.11. We believe that integrating allele-specific querying in miRNA-binding prediction, and data supporting cis-regulation of expression, improves the identification of candidate target genes in BC risk, as well as in other common cancers and complex diseases.Funding Agency Portuguese Foundation for Science and Technology CRESC ALGARVE 2020 European Union (EU) 303745 Maratona da Saude Award DL 57/2016/CP1361/CT0042 SFRH/BPD/99502/2014 CBMR-UID/BIM/04773/2013 POCI-01-0145-FEDER-022184info:eu-repo/semantics/publishedVersio