Sensitivity of the polyDetect computational pipeline for phylogenetic analyses

Structural variations (SVs) are differences in genomic regions that are larger than 1 kilobase-pair (Kbp) between individuals, and can arise from errant DNA repair mechanisms, whole genome duplications, and transposable element activity across the genome. Recent advances, optimizations, and cost reductions in next generation sequencing technologies have facilitated the exponential increase in the amount of available short read genomic data. Here we present SaVor, a flexible, reproducible SV calling workflow that accepts single or multi-lane short-read paired-end Illumina sequence data, or BAM files as input to generate a consensus SV call-set based on user-provided merge parameters. We tested SaVor on 1,165 Arabidopsis thaliana whole genome sequences and benchmarked its performance on a set of SVs derived from the same accessions using Lumpy. Intersection calls i.e. SVs supported by 3 SV callers showed the highest precision (>0.91) while union calls supported by at least 1 caller showed the highest recall (>0.88). We found that the former suffers from decreased recall (<0.51) and the latter decreased precision (<0.57). Depending on the merge strategy, trade-offs in recall and precision need to be considered for downstream analyses of SV call-sets from short-read data. SaVor is an open-source Snakemake pipeline and is available on GitHub at https://github.com/ChabbyTMD/SaVor

Syncytin-2 is a membrane fusion protein involved in placenta development that is derived from the endogenous retrovirus envelope gene acquired in the common ancestral lineage of New World and Old World monkeys (OWMs). It is known that syncytin-2 is conserved between apes and OWMs, suggesting its functional importance; however, syncytin-2 of common marmosets (Callithrix jacchus) exhibits lower fusogenic activity than those of humans and OWMs in human cell lines. To obtain insight into the functional diversity of syncytin-2 genes in primates, we examined the syncytin-2 gene in New World monkeys (NWMs). We experimentally evaluated the cell fusion ability of syncytin-2 in humans, C.jacchus, and tufted capuchins (Sapajus apella). We found that the cell fusion ability of S.apella was lower than that of human syncytin-2. Chimeric syncytin-2 constructs revealed that the amino acid differences in the surface unit of S.apella syncytin-2 were responsible for the weak cell fusion activity. In addition, genomic sequence analyses of syncytin-2 revealed that the open reading frames (ORFs) of syncytin-2 were highly conserved in seven apes and 22 OWMs; however, the syncytin-2 ORFs of three of 12 NWM species were truncated. Our results suggest that syncytin-2 in several NWMs may be of less importance than in OWMs and apes, and other syncytin-like genes may be required for placental development in various NWM species.

Human and great ape milks contain a diverse array of milk oligosaccharides, but little is known about the milk oligosaccharides of other primates, and how they differ among taxa. Neutral and acidic oligosaccharides were isolated from the milk of three species of Old World or catarrhine monkeys (Cercopithecidae: rhesus macaque (Macaca mulatta), toque macaque (Macaca sinica) and Hamadryas baboon (Papio hamadryas)) and three of New World or platyrrhine monkeys (Cebidae: tufted capuchin (Cebus apella) and Bolivian squirrel monkey (Saimiri boliviensis); Atelidae: mantled howler (Alouatta palliata)). The milks of these species contained 6–8% total sugar, most of which was lactose: the estimated ratio of oligosaccharides to lactose in Old World monkeys (1:4 to 1:6) was greater than in New World monkeys (1:12 to 1:23). The chemical structures of the oligosaccharides were determined mainly by 1H-NMR spectroscopy. Oligosaccharides containing the type II unit (Gal(β1-4)GlcNAc) were found in the milk of the rhesus macaque, toque macaque, Hamadryas baboon and tufted capuchin, but oligosaccharides containing the type I unit (Gal(β1-3)GlcNAc), which have been found in human and many great ape milks, were absent from the milk of all species studied. Oligosaccharides containing Lewis x (Gal(β1-4)[Fuc(α1-3)]GlcNAc) and 3-fucosyl lactose (3-FL, Gal(β1-4)[Fuc(α1-3)]Glc) were found in the milk of the three cercopithecid monkey species, while 2-fucosyl lactose (5'-FL, Fuc(α1-2)Gal(β1-4)Glc) was absent from all species studied. All of these milks contained acidic oligosaccharides that had N-acetylneuraminic acid as part of their structures, but did not contain oligosaccharides that had N-glycolylneuraminic acid, in contrast to the milk or colostrum of great apes which contain both types of acidic oligosaccharides. Two GalNAc-containing oligosaccharides, lactose 3′-O-sulfate and lacto-N-novopentaose I (Gal(β1-3)[Gal(β1-4)GlcNAc(β1-6)]Gal(β1-4)Glc) were found only in the milk of rhesus macaque, hamadryas baboon and tufted capuchin, respectively. Further research is needed to determine the extent to which the milk oligosaccharide patterns observed among these taxa represent wider phylogenetic trends among primates and how much variation occurs among individuals or species.Electronic supplementary materialThe online version of this article (doi:10.1007/s10719-010-9315-0) contains supplementary material, which is available to authorized users.

BackgroundInsertion sequences (IS) are small transposable elements, commonly found in bacterial genomes. Identifying the location of IS in bacterial genomes can be useful for a variety of purposes including epidemiological tracking and predicting antibiotic resistance. However IS are commonly present in multiple copies in a single genome, which complicates genome assembly and the identification of IS insertion sites. Here we present ISMapper, a mapping-based tool for identification of the site and orientation of IS insertions in bacterial genomes, directly from paired-end short read data.ResultsISMapper was validated using three types of short read data: (i) simulated reads from a variety of species, (ii) Illumina reads from 5 isolates for which finished genome sequences were available for comparison, and (iii) Illumina reads from 7 Acinetobacter baumannii isolates for which predicted IS locations were tested using PCR. A total of 20 genomes, including 13 species and 32 distinct IS, were used for validation. ISMapper correctly identified 97 % of known IS insertions in the analysis of simulated reads, and 98 % in real Illumina reads. Subsampling of real Illumina reads to lower depths indicated ISMapper was able to correctly detect insertions for average genome-wide read depths >20x, although read depths >50x were required to obtain confident calls that were highly-supported by evidence from reads. All ISAba1 insertions identified by ISMapper in the A. baumannii genomes were confirmed by PCR. In each A. baumannii genome, ISMapper successfully identified an IS insertion upstream of the ampC beta-lactamase that could explain phenotypic resistance to third-generation cephalosporins. The utility of ISMapper was further demonstrated by profiling genome-wide IS6110 insertions in 138 publicly available Mycobacterium tuberculosis genomes, revealing lineage-specific insertions and multiple insertion hotspots.ConclusionsISMapper provides a rapid and robust method for identifying IS insertion sites directly from short read data, with a high degree of accuracy demonstrated across a wide range of bacteria.

CpG methylation, a key epigenetic mark involved in gene regulation, development, and other biological processes, is commonly analyzed using Whole-Genome Bisulfite Sequencing (WGBS). However, bisulfite treatment causes significant DNA degradation. Enzymatic Methyl-seq (EM-seq) offers a short-read alternative that preserves DNA integrity but requires conversion steps, limiting its compatibility with downstream analyses. Third-generation sequencing technologies, such as Oxford Nanopore Technologies (ONT) and PacBio, enable direct detection of DNA modifications without altering the DNA, providing simultaneous genome and epigenome information. This work presents a comprehensive dataset combining long- and short-read sequencing data, including ONT, PacBio, Enzymatic Methyl-seq, and WGBS, for two agronomically relevant species: pig (Sus scrofa) and quail (Coturnix japonica). Data quality evaluation reveals high nucleotide quality scores for PacBio and short reads, robust alignment rates for long reads, and inter-method correlations in CpG methylation calling ranging from 0.76 to 0.99. This dataset is a valuable resource for training methylation callers and represents the first combined methylation dataset for these species, providing an essential benchmark for assessing emerging sequencing technologies.

Simple SummaryLeishmaniasis is a parasitic disease caused by flagellated protozoa of the genus Leishmania. Multiple genome sequencing platforms have been employed to complete Leishmania genomes at the expense of high cost. This study proposes an integrative bioinformatic workflow for assembling only the short-read data of Leishmania orientalis isolate PCM2 from Thailand and produce an acceptable-quality genome for further genomic analysis. This workflow gives extensive information required for identifying strain-specific markers and virulence-associated genes useful for drug and vaccine development before a more exhaustive and expensive investigation.Background: Leishmania orientalis (formerly named Leishmania siamensis) has been neglected for years in Thailand. The genomic study of L. orientalis has gained much attention recently after the release of the first high-quality reference genome of the isolate LSCM4. The integrative approach of multiple sequencing platforms for whole-genome sequencing has proven effective at the expense of considerably expensive costs. This study presents a preliminary bioinformatic workflow including the use of multi-step de novo assembly coupled with the reference-based assembly method to produce high-quality genomic drafts from the short-read Illumina sequence data of L. orientalis isolate PCM2. Results: The integrating multi-step de novo assembly by MEGAHIT and SPAdes with the reference-based method using the L. enriettii genome and salvaging the unmapped reads resulted in the 30.27 Mb genomic draft of L. orientalis isolate PCM2 with 3367 contigs and 8887 predicted genes. The results from the integrated approach showed the best integrity, coverage, and contig alignment when compared to the genome of L. orientalis isolate LSCM4 collected from the northern province of Thailand. Similar patterns of gene ratios and frequency were observed from the GO biological process annotation. Fifty GO terms were assigned to the assembled genomes, and 23 of these (accounting for 61.6% of the annotated genes) showed higher gene counts and ratios when results from our workflow were compared to those of the LSCM4 isolate. Conclusions: These results indicated that our proposed bioinformatic workflow produced an acceptable-quality genome of L. orientalis strain PCM2 for functional genomic analysis, maximising the usage of the short-read data. This workflow would give extensive information required for identifying strain-specific markers and virulence-associated genes useful for drug and vaccine development before a more exhaustive and expensive investigation.

Haplotypes, defined as the sequence of alleles on one chromosome, are crucial for many genetic analyses. As experimental determination of haplotypes is extremely expensive, haplotypes are traditionally inferred using computational approaches from genotype data, i.e. the mixture of the genetic information from both haplotypes. Best performing approaches for haplotype inference rely on Hidden Markov Models, with the underlying assumption that the haplotypes of a given individual can be represented as a mosaic of segments from other haplotypes in the same population. Such algorithms use this model to predict the most likely haplotypes that explain the observed genotype data conditional on reference panel of haplotypes. With rapid advances in short read sequencing technologies, sequencing is quickly establishing as a powerful approach for collecting genetic variation information. As opposed to traditional genotyping-array technologies that independently call genotypes at polymorphic sites, short read sequencing often collects haplotypic information; a read spanning more than one polymorphic locus (multi-single nucleotide polymorphic read) contains information on the haplotype from which the read originates. However, this information is generally ignored in existing approaches for haplotype phasing and genotype-calling from short read data. In this article, we propose a novel framework for haplotype inference from short read sequencing that leverages multi-single nucleotide polymorphic reads together with a reference panel of haplotypes. The basis of our approach is a new probabilistic model that finds the most likely haplotype segments from the reference panel to explain the short read sequencing data for a given individual. We devised an efficient sampling method within a probabilistic model to achieve superior performance than existing methods. Using simulated sequencing reads from real individual genotypes in the HapMap data and the 1000 Genomes projects, we show that our method is highly accurate and computationally efficient. Our haplotype predictions improve accuracy over the basic haplotype copying model by ∼20% with comparable computational time, and over another recently proposed approach Hap-SeqX by ∼10% with significantly reduced computational time and memory usage. Publicly available software is available at http://genetics.cs.ucla.edu/harsh bpasaniuc@mednet.ucla.edu or eeskin@cs.ucla.edu.

We are far from developing an informed synthesis regarding the evolution of New World Monkeys – probably decades away. For even with the important strides made over the past 30–40 years regarding platyrrhine ecology and behavior, there are large gaps in our knowledge of the evolutionary and historical context. The scarceness of fossils is but one factor. Equally critical is our incomplete knowledge of largescale changes to the continent of South America (SAM), pertinent to the evolution of its fauna. An objective of this paper is to review some of this information as a basis for interpreting the platyrrhines from an ecophylogenetic point of view in space and time. Our goal is to integrate information on living and extinct forms in order to identify community or regional patterns of platyrrhine evolution, rather than examining the moderns and fossils as distinct entities or evolutionary problems. In keeping with the South American emphasis of this volume, we do not consider the primate fauna of the Middle American mainland but have elected to examine the Caribbean subfossil monkeys for reasons that will become clear below. We suggest that the casual way of thinking about New World Monkeys (NWM) as a monolithic radiation inhabiting a rainforest wonderland – South America – is a model that needs to be changed. The continent is about 2.5 times the size of today’s Amazonian rainforest in area, it contains diverse landscapes and habitats, and the Amazonian region changed vastly during the Cenozoic (e.g., Bigarella and Ferreira 1985). At present, more of the continent is grassland than rainforest (Fig. 4.1a), and the grasslands have been flourishing for 20–30 million years (see below). The first primates to arrive did not encounter the Amazonia we know, for it may have begun to take on its present character only about 15 Ma (Campbell et al. 2006). Thus, even though the NWM have a monophyletic, unitary origin, their

Whole genome sequencing provides the highest resolution for characterizing pathogen evolution, epidemiology, and diagnostics. Genome assemblies contain information on the identity and potential phenotypes of a pathogen. Likewise, variant calling can inform on transmission patterns and evolutionary relationships. Recent improvements in Oxford Nanopore long-read sequencing have made its use attractive for genomic epidemiology. However, the accuracy and optimal strategy for analysis of Nanopore reads remains to be determined. We compared the use of Illumina short reads and Oxford Nanopore long reads for genome assembly and variant calling of phytopathogenic bacteria. We generated short- and long-read datasets for diverse phytopathogenic Agrobacterium strains. We then analyzed these data using multiple pipelines designed for either short or long reads and compared the results. We found that assemblies made from long reads were more complete than those made from short-read data and contained few sequence errors. Variant calling pipelines differed in their ability to accurately call variants and infer genotypes from long reads. Results suggest that computationally fragmenting long reads can improve the accuracy of variant calling in population-level studies. Using fragmented long reads, pipelines designed for short reads were more accurate at recovering genotypes than pipelines designed for long reads. Further, short- and long-read datasets can be analyzed together with the same pipelines. These findings show that Oxford Nanopore sequencing is accurate and can be sufficient for microbial pathogen genomics and epidemiology. Ultimately, this enhances the ability of researchers and clinicians to understand and mitigate the spread of pathogens.

Alu elements are the largest family of short tandem interspersed elements (SINEs) in human who have arisen to a copy number with an excess of 500 000 copies per haploid human genome and mobilize through an RNAse polymerase III derived transcript in a process termed “retroposition.” Several features make Alu insertions a powerful tool used in population genetic studies: the polymorphic nature of many Alu insertions, the stability of an Alu insertion event and, furthermore, the ancestral state of an Alu insertion is known to be the absence (complete and exact) of the Alu element at a particular locus and the presence of an Alu insertion at the site that forward mutational change. Here we report on the distribution of six polymorphic Alu insertions in a general Moroccan population and in the Arab and Berber populations from Morocco and their relationships with other populations previously studied. Our results show that there is a small difference between Arabs and Berbers and that the Arab population was closer to African populations than Berber population which is closest to Europeans.

CCR5 chemokine receptor gene evolution in New World monkeys (Platyrrhini, Primates): implication on resistance to lentiviruses

The growth hormone (GH) gene family represents an erratic and complex evolutionary pattern, involving many evolutionary events, such as multiple gene duplications, positive selection, the birth-and-death process and gene conversions. In the present study, we cloned and sequenced GH-like genes from three species of New World monkeys (NWM). Phylogenetic analysis strongly suggest monophyly for NWM GH-like genes with respect to those of Old World monkeys (OWM) and hominoids, indicating that independent gene duplications have occurred in NWM GH-like genes. There are three main clusters of genes in putatively functional NWM GH-like genes, according to our gene tree. Comparison of the ratios of nonsynonymous and synonymous substitutions revealed that these three clusters of genes evolved under different kinds of selective pressures. Detailed analysis of the evolution of pseudogenes showed that the evolutionary pattern of this gene family in platyrrhines is in agreement with the so-called birth-and-death process.

Detection of KMT2A Partial Tandem Duplication in Myeloid Samples By Pacbio® Long Read Sequencing

Copy Number Alterations (CNAs) such as deletions and duplications; compose a larger percentage of genetic variations than single nucleotide polymorphisms or other structural variations in cancer genomes that undergo major chromosomal re-arrangements. It is, therefore, imperative to identify cancer-specific somatic copy number alterations (SCNAs), with respect to matched normal tissue, in order to understand their association with the disease. We have devised an accurate, sensitive, and easy-to-use tool, COPS, COpy number using Paired Samples, for detecting SCNAs. We rigorously tested the performance of COPS using short sequence simulated reads at various sizes and coverage of SCNAs, read depths, read lengths and also with real tumor:normal paired samples. We found COPS to perform better in comparison to other known SCNA detection tools for all evaluated parameters, namely, sensitivity (detection of true positives), specificity (detection of false positives) and size accuracy. COPS performed well for sequencing reads of all lengths when used with most upstream read alignment tools. Additionally, by incorporating a downstream boundary segmentation detection tool, the accuracy of SCNA boundaries was further improved. Here, we report an accurate, sensitive and easy to use tool in detecting cancer-specific SCNAs using short-read sequence data. In addition to cancer, COPS can be used for any disease as long as sequence reads from both disease and normal samples from the same individual are available. An added boundary segmentation detection module makes COPS detected SCNA boundaries more specific for the samples studied. COPS is available at ftp://115.119.160.213 with username “cops” and password “cops”.

Quantitative monitoring of emerging antimicrobial resistance genes (ARGs) using short-read sequences remains challenging due to the high frequency of amino acid functional domains and motifs shared with related but functionally distinct (non-target) proteins. To facilitate ARG monitoring efforts using unassembled short reads, we present novel ROCker models for mcr, mph, erm, and lnu ARG families, as well as models for variants of special public health concern within these families, including mcr-1, mphA, ermB, lnuF, lnuB, and lnuG genes. For this, we curated target gene sequence sets for model training and built these models using the recently updated ROCker V2 pipeline (Gerhardt et al., in review). To validate our models, we simulated reads from the whole genome of ARG-carrying isolates spanning a range of common read lengths and used them to challenge the filtering efficacy of ROCker versus common static filtering approaches, such as similarity searches using BLASTx with various e-value thresholds or hidden Markov models. ROCker models consistently showed F1 scores up to 10× higher (31% higher on average) and lower false-positive (by 30%, on average) and false-negative (by 16%, on average) rates based on 250 bp reads compared to alternative methods. The ROCker models and all related reference materials and data are freely available through http://enve-omics.ce.gatech.edu/rocker/models, further expanding the available model collection previously developed for other genes. Their application to short-read metagenomes, metatranscriptomes, and PCR amplicon data should facilitate more accurate classification and quantification of unassembled short-read sequences for these ARG families and specific genes.IMPORTANCEAntimicrobial resistance gene families encoding erm and mph genes confer resistance to the macrolide class of antimicrobials, which are used to treat a wide range of infections. Similarly, the mcr gene family confers resistance to polymyxin E (colistin), a drug of last resort for many serious drug-resistant bacterial infections, and the lnu gene family confers resistance to lincomycin, which is reserved for patients allergic to penicillin or where bacteria have developed resistance to other antimicrobials. Assessing the prevalence of these genes in clinical or environmental samples and monitoring their spread to new pathogens are thus important for quantifying the associated public health risk. However, detecting these and other resistance genes in short-read sequence data is technically challenging. Our ROCker bioinformatic pipeline achieves reliable detection and typing of broad-range target gene sequences in complex data sets, thus contributing toward solving an important problem in ongoing surveillance efforts of antimicrobial resistance.