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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2025

Clustering of plasmid genomes for genomic epidemiology by using rearrangement distances, with pling

Integration of plasmids into genomic epidemiology is challenging, because there are no clearly defined evolving-units (equivalent to species), and because plasmids appear to evolve as much by structural change (rearrangements, insertions and deletions) as by mutation (1). Further, plasmids transfer horizontally between bacterial hosts (2), and thus a model beyond just a phylogeny is needed to integrate their genetic information with that of their hosts. Pling (3) is a tool designed to measure a genetic distance between plasmids that is related to how they empirically appear to evolve, by measuring the distance between two plasmids as the minimum number of structural changes needed to change one plasmid into the other (ignoring SNP differences). Having done this, it constructs a relatedness network of the plasmids under study, and then clusters them into groups that are credibly recently related. We give here a protocol for running pling, and how we integrate its information with plasmid typing and SNP information. Together, these provide a system for deciding which plasmids are worth treating as "the same plasmid" for the purposes of epidemiology, quantifying their relatedness in terms of rearrangements and SNPs, and then seeing how they are distributed across the host phylogeny.

bioinformatics↗
bioRxiv2018

The Staphylococcus aureus Two-Component System AgrAC Displays Four Distinct Genomic Arrangements That Delineate Genomic Virulence Factor Signatures

Two-component systems (TCSs) consist of a histidine kinase and a response regulator. Here, we evaluated the conservation of the AgrAC TCS among 149 completely sequenced S. aureus strains. It is composed of four genes: agrBDCA. We found that: i) AgrAC system (agr) was found in all but one of the 149 strains; ii) The agr positive strains were further classified into four agr types based on AgrD protein sequences, iii) the four agr types not only specified the chromosomal arrangement of the agr genes but also the sequence divergence of AgrC histidine kinase protein, which confers signal specificity, iv) the sequence divergence was reflected in distinct structural properties especially in the transmembrane region and second extracellular binding domain, and v) there was a strong correlation between the agr type and the virulence genomic profile of the organism. Taken together, these results demonstrate that bioinformatic analysis of the agr locus leads to a classification system that correlates with the presence of virulence factors and protein structural properties.

microbiology↗
bioRxiv2018

The genomic and proteomic landscape of the rumen microbiome revealed by comprehensive genome-resolved metagenomics

Ruminants provide essential nutrition for billions of people worldwide. The rumen is a specialised stomach adapted to the breakdown of plant-derived complex polysaccharides, and collectively the rumen microbiota encode the thousands of enzymes responsible. Here we present a comprehensive analysis of over 6.5 terabytes of Illumina and Nanopore sequence data, including assembly of 4941 metagenome-assembled genomes, and several single-contig, whole-chromosome assemblies of novel rumen bacteria. We also present the largest dataset of predicted proteins from the rumen, and provide rich annotation against public datasets. Together these data will form an essential part of future studies of rumen microbiome structure and function.

microbiology↗
bioRxiv2026

Genomic Insights into Bacterial Communities of Coenocytic Algae Using Metagenome Assembled Genomes

Coenocytic algae are organisms that undergo karyokinesis without cytokinesis, resulting in multinucleated cells. Most research on bacterial communities in coenocytic algae has used 16S rRNA sequencing, primarily focusing on the order Bryopsidales of green coenocytic algae. Recent studies have analyzed metagenome-assembled genomes (MAGs) from algal hosts across multiple taxa, such as Chlorophyta, Phaeophyta, and Rhodophyta, revealing more about bacterial biosynthetic machinery and potential symbiotic relationships. Given the cosmopolitan distribution of coenocytic algae, such as Bryopsis, Caulerpa, Codium, and the yellow-green alga Vaucheria, and their unique morphology, there is a need to better understand their associated bacterial communities. To address this, filaments of Vaucheria bursata LB2067 were sequenced using the Illumina NovaSeq instrument, and all publicly available short- and long-read datasets from coenocytic algae were screened for MAG recovery. All recovered MAGs from both Bryopsidales and Vaucheriales showed a high dominance of Pseudomonadota at the phylum level, but no consistent patterns at the order or family levels. High completeness of specific KEGG pathways, such as bidirectional polyphosphate metabolism and riboflavin biosynthesis, was prevalent in MAGs from coenocytic orders compared to non-coenocytic ones. Notably, N-acetylglutaminylglutamine amide (NAGGN) biosynthetic gene clusters (BGCs) were found only in MAGs from coenocytic orders, whereas polysaccharide utilization loci (PULs) were present in all MAGs analyzed. These results indicate that bacterial communities associated with coenocytic algae are complex, with diverse survival strategies adapted to challenging and variable environments.

microbiology↗
bioRxiv2026

Microhomology-Driven Genomic Alterations in Cancer Genomes: Patterns, Prevalence, and Clinical Implications.

Homologous recombination deficiency (HRD) can force cancer cells to rely on alternative DNA repair pathways, including microhomology-mediated end joining (MMEJ), an error-prone mechanism that can generate deletions with microhomology at repair junctions. Because such patterns may reflect DNA repair defects with clinical relevance, this study aimed to assess the biological and prognostic significance of microhomology-associated deletions and optimize their detection parameters to improve patient stratification and inform targeted therapeutic strategies, including PARP inhibition. We optimized the microhomology length threshold (Mlt parameter) using signal-to-noise ratios and survival models. We evaluated the utility of whole-exome (WES) versus whole-genome sequencing (WGS). We then investigated how Loss of Function (LoF) alterations affect microhomology-associated deletion burden and assessed their prognostic significance across an ovarian cancer (OV) cohort and a TCGA Pan-Cancer dataset. Applying an Mlt = 2 threshold maximized the precision and statistical reliability of microhomology-associated deletion identification. WGS yielded higher reproducibility, whereas WES proved insufficient for accurate estimation. Inactivation of tumor suppressor genes, including RB1 and CCDC122, was associated with increased microhomology-associated deletion burden. Importantly, higher burden correlated with extended overall survival in ovarian cancer. Furthermore, while baseline microhomology-associated deletion burden varies by tumor type, Pan-Cancer analysis identified candidate gene-level alterations, including FDX1 and PDE8B, whose LoF increased microhomology-associated deletion burden across tumors. Precise parameterization combined with WGS resolution highlights the extent to which specific gene losses affect deletion burden consistent with MMEJ-mediated repair. Identifying these genetic vulnerabilities and the resulting deletion burden may provide a candidate prognostic biomarker and foundation for personalized therapies.

bioinformatics↗
bioRxiv2014

Revealing missing isoforms encoded in the human genome by integrating genomic, transcriptomic and proteomic data

Biological and biomedical research relies on comprehensive understanding of protein-coding transcripts. However, the total number of human proteins is still unknown due to the prevalence of alternative splicing and is much larger than the number of human genes.\n\nIn this paper, we detected 31,566 novel transcripts with coding potential by filtering our ab initio predictions with 50 RNA-seq datasets from diverse tissues/cell lines. PCR followed by MiSeq sequencing showed that at least 84.1% of these predicted novel splice sites could be validated. In contrast to known transcripts, the expression of these novel transcripts were highly tissue-specific. Based on these novel transcripts, at least 36 novel proteins were detected from shotgun proteomics data of 41 breast samples. We also showed L1 retrotransposons have a more significant impact on the origin of new transcripts/genes than previously thought. Furthermore, we found that alternative splicing is extraordinarily widespread for genes involved in specific biological functions like protein binding, nucleoside binding, neuron projection, membrane organization and cell adhesion. In the end, the total number of human transcripts with protein-coding potential was estimated to be at least 204,950.\n\nAuthor summaryThe identification of all human proteins is an important and open problem. In this report we first develop an ab initio predictor to collect candidate gene models as many as possible. Next, comprehensive sets of RNA-seq data from diverse tissues and cell lines are used to select confident transcripts. Experimental validation of a subset of predictions confirms a high accuracy for the predicted coding transcript set and has added about 30,000 new protein-coding transcripts to the existing corpus of knowledge in this area. This is significant progress given that the existing protein-coding transcript number in public databases is about 60,000. Our newly found transcripts are more tissue specific. Based on our results, we show that L1's high impact on gene origin and genes with high number of transcripts are enriched in specific functions. At last, we estimate that the total number of human protein-coding transcripts is in excess of 200,000.

Genomics↗
bioRxiv2016

Genome-wide identification and characterisation of HOT regions in the human genome

HOT (high-occupancy target) regions, which are bound by a surprisingly large number of transcription factors, are considered to be among the most intriguing findings of recent years. An improved understanding of the roles that HOT regions play in biology would be afforded by knowing the constellation of factors that constitute these domains and by identifying HOT regions across the spectrum of human cell types. We characterised and validated HOT regions in embryonic stem cells (ESCs) and produced a catalogue of HOT regions in a broad range of human cell types. We found that HOT regions are associated with genes that control and define the developmental processes of the respective cell and tissue types. We also showed evidence of the developmental persistence of HOT regions at primitive enhancers and demonstrate unique signatures of HOT regions that distinguish them from typical enhancers and super-enhancers. Finally, we performed an epigenetic analysis to reveal the dynamic epigenetic regulation of HOT regions upon H1 differentiation. Taken together, our results provide a resource for the functional exploration of HOT regions and extend our understanding of the key roles of HOT regions in development and differentiation.

Genomics↗
bioRxiv2017

First landscape of binding to chromosomes for a domesticated mariner transposase in the human genome: diversity of genomic targets of SETMAR isoforms in two colorectal cell lines

Setmar is a 3-exons gene coding a SET domain fused to a Hsmar1 transposase. Its different transcripts theoretically encode 8 isoforms with SET moieties differently spliced. In vitro, the largest isoform binds specifically to Hsmar1 DNA ends and with no specificity to DNA when it is associated with hPso4. In colon cell lines, we found they bind specifically to two chromosomal targets depending probably on the isoform, Hsmar1 ends and sites with no conserved motifs. We also discovered that the isoforms profile was different between cell lines and patient tissues, suggesting the isoforms encoded by this gene in healthy cells and their functions are currently not investigated.

genomics↗
bioRxiv2021

De Novo Whole Genome Assembly of the Roborovski Dwarf Hamster (Phodopus roborovskii) Genome, an Animal Model for Severe/Critical COVID-19

The Roborovski dwarf hamster Phodopus roborovskii belongs to the Phodopus genus, one of seven within Cricetinae subfamily. Like other rodents such as mice, rats or ferrets, hamsters can be important animal models for a range of diseases. Whereas the Syrian hamster from the genus Mesocricetus is now widely used as a model for mild to moderate COVID-19, Roborovski dwarf hamster show a severe to lethal course of disease upon infection with the novel human coronavirus SARS-CoV-2.

genomics↗
bioRxiv2017

A genome-wide resource for high-throughput genomic tagging of yeast ORFs

Here we describe a C-SWAT library for high-throughput tagging of Saccharomyces cerevisiae ORFs. It consists of 5661 strains with an acceptor module inserted after each ORF, which can be efficiently replaced with tags or regulatory elements. We validate the library with targeted sequencing and demonstrate its use by tagging the yeast proteome with bright fluorescent proteins, determining how sequences downstream of ORFs influence protein expression and localizing previously undetected proteins.

genomics↗
bioRxiv2019

Mapping gene regulatory networks of primary CD4+ T cells using single-cell genomics and genome engineering

Gene regulatory programs controlling the activation and polarization of CD4+ T cells are incompletely mapped and the interindividual variability in these programs remain unknown. We sequenced the transcriptomes of ~160k CD4+ T cells from 9 donors following pooled CRISPR perturbation targeting 140 regulators. We identified 134 regulators that affect T cell functionalization, including IRF2 as a positive regulator of Th2 polarization. Leveraging correlation patterns between cells, we mapped 194 pairs of interacting regulators, including known (e.g. BATF and JUN) and novel interactions (e.g. ETS1 and STAT6). Finally, we identified 80 natural genetic variants with effects on gene expression, 48 of which are modified by a perturbation. In CD4+ T cells, CRISPR perturbations can influence in vitro polarization and modify the effects of trans and cis regulatory elements on gene expression.

genomics↗
bioRxiv2019

Towards establishing internal validity for correlated gene expression measures in imaging genomics of functional networks: why distance corrections and external face validity alone fall short. Reply to "Distance is not everything in imaging genomics of functional networks: reply to a commentary on Correlated gene expression supports synchronous activity in brain networks"

The primary claim of the Richiardi et. al. 2015 Science article1 is that a measure of correlated gene expression, significant strength fraction (SSF), is related to resting state fMRI (rsfMRI) networks. However, there is still debate about this claim and whether spatial proximity, in the form of contiguous clusters, accounts entirely, or only partially, for SSF2,3. Here, thirteen distributed networks were simulated by combining 34 contiguous clusters randomly placed throughout cortex, with resulting edge distance distributions similar to rsfMRI networks. Cluster size was modulated (6-15mm radius) to test its influence on SSF false positive rate (SSF-FPR) among the simulated noise networks. The contribution of rsfMRI networks on SSF-FPR was examined by comparing simulations using: 1) all cortical samples 2) all samples with non-rsfMRI cluster centers and 3) only non-rsfMRI samples. Results show that SSF-FPR is influenced only by cluster size (r>0.9, p<0.001), not by rsfMRI samples. Simulations using 14mm radius clusters most resembled rsfMRI networks. When thresholding at p<10-4, the SSF-FPR was 0.47. Genes that maximize SF have high global spatial autocorrelation. In conclusion, SSF is unrelated to rsfMRI networks. The main conclusion of Richiardi et. al. 2015 is based on a finding that is [~]50% likely to be a false positive, not less than 0.01% as originally reported in the article1. We discuss why distance corrections alone and external face validity are insufficient to establish a trustworthy relationship between correlated gene expression measures and rsfMRI networks, and propose more rigorous approaches to preclude common pitfalls in related studies.

neuroscience↗
bioRxiv2021

Coordination of phage genome degradation versus host genome protection by a bifunctional restriction-modification enzyme visualized by CryoEM

Restriction enzymes that combine DNA methylation and cleavage activities into a single polypeptide or protein assemblage and that modify just one DNA strand for host protection are capable of more efficient adaptation towards novel target sites. However, they must solve the problem of discrimination between newly replicated and unmodified host sites (needing methylation) and invasive foreign site (needing to lead to cleavage). One solution to this problem might be that the activity that occurs at any given site is dictated by the oligomeric state of the bound enzyme. Methylation requires just a single bound site and is relatively slow, while cleavage requires that multiple unmethylated target sites (often found in incoming, foreign DNA) be brought together into an enzyme-DNA complex to license rapid cleavage. To validate and visualize the basis for such a mechanism, we have determined the catalytic behavior of a bifunctional Type IIL restriction-modification ( RM) enzyme (DrdV) and determined its high-resolution structure at several different stages of assembly and coordination with multiple bound DNA targets using CryoEM. The structures demonstrate a mechanism of cleavage by which an initial dimer is formed between two DNA-bound enzyme molecules, positioning the single endonuclease domain from each enzyme against the others DNA and requiring further oligomerization through differing protein-protein contacts of additional DNA-bound enzyme molecules to enable cleavage. The analysis explains how endonuclease activity is licensed by the presence of multiple target-containing DNA duplexes and provides a clear view of the assembly through 3D space of a DNA-bound RM enzyme synapse that leads to rapid cleavage of foreign DNA.

biochemistry↗
bioRxiv2022

cLD: Rare-variant disequilibrium between genomic regions identifies novel genomic interactions

Linkage disequilibrium (LD) is a fundamental concept in genetics; critical for studying genetic associations and molecular evolution. However, LD measurements are only reliable for common genetic variants, leaving low-frequency variants unanalyzed. In this work, we introduce cumulative LD (cLD), a stable statistic that captures the rare-variant LD between genetic regions, which reflects more biological interactions between variants, in addition to lack of recombination. We derived the theoretical variance of cLD using delta methods to demonstrate its higher stability than LD for rare variants. This property is also verified by bootstrapped simulations using real data. In application, we find cLD reveals an increased genetic association between genes in 3D chromatin interactions, a phenomenon recently reported negatively by calculating standard LD between common variants. Additionally, we show that cLD is higher between gene pairs reported in interaction databases, identifies unreported protein-protein interactions, and reveals interacting genes distinguishing case/control samples in association studies.

bioinformatics↗
bioRxiv2023

eGADA: enhanced Genomic Alteration Detection Algorithm, a fast genomic segmentation algorithm

eGADA is an enhanced version of GADA, which is a fast segmentation algorithm utilizing the Sparse Bayesian Learning (or Relevance Vector Machine) technique from Tipping 2001. It can be applied to array intensity data, NGS sequencing coverage data, or any sequential data that displays characteristics of stepwise functions. Improvements by eGADA over GADA include: a) a customized Red-Black tree to expedite the final backward elimination step of GADA; b) code in C++, which is safer and better structured than C; c) use Boost libraries extensively to provide user-friendly help and commandline argument processing; d) user-friendly input and output formats; e) export a dynamic library eGADA.so (packaged via Boost.Python) that offers API to Python; f) other bug fixes/optimization. The code is published at https://github.com/polyactis/eGADA.

bioinformatics↗
bioRxiv2024

Genomic insights on the potential role of the accessory genome in the emergence of a novel geographically restricted K. pneumoniae lineage as a high-risk clone

Klebsiella pneumoniae causes life-threatening nosocomial infections and is featured by a remarkable propensity for multidrug resistance acquisition. Infections caused by multidrug- (MDR) and extensively drug-resistant (XDR) strains lead to a limitation of therapeutic options and an increase in persistent infections, and they are usually represented by high-risk lineages. Based on these features and their relevance to global public health, most of the studies focused on such high-risk clones, and little is known about the epidemiological and evolutionary dynamics of new/geographically restricted lineages. This study aimed to unveil the antimicrobial resistance and virulence genetic repertoire of a clinical XDR K. pneumoniae (Kp199) strain belonging to geographically-restricted ST, not linked to any known clonal complex. Its intrinsic (gyrA, parC, ramR, soxR and soxS mutations) and acquired resistome agreed with the observed XDR phenotype. An extensive arsenal of both antibiotic and heavy metal resistance genes was observed, as well as genes involved with resistance to several antiseptics currently used in clinical settings. The co-occurrence of blaKPC-2 and blaNDM-1 carbapenemase genes in Kp199 was an alarming finding since it could contribute to increased carbapenem resistance. Kp199 virulome was associated with bacterial survival and replication during infections. This study raises concern about a novel, geographically restricted K. pneumoniae lineage harbouring a huge resistome and virulome, which may strongly contribute to its successful establishment as an epidemic lineage. Therefore, our findings underscore the importance of vigilant surveillance and control measures to mitigate the threat posed by the potential emergence of new high-risk pandemic clones.

microbiology↗
bioRxiv2019

The genomic architecture of blood metabolites based on a decade of genome-wide analyses

Metabolomics examines the small molecules involved in cellular metabolism. Approximately 50% of total phenotypic differences in metabolite levels is due to genetic variance, but heritability estimates differ across metabolite classes and lipid species. We performed a review of all genetic association studies, and identified > 800 class-specific metabolite loci that influence metabolite levels. In a twin-family cohort (N = 5,117), these metabolite loci were leveraged to simultaneously estimate total heritability (h2total), and the proportion of heritability captured by known metabolite loci (h2Metabolite-hits) for 309 lipids and 52 organic acids. Our study revealed significant differences in h2Metabolite-hits among different classes of lipids and organic acids. Furthermore, phosphatidylcholines with a high degree of unsaturation had higher h2Metabolite-hits estimates than phosphatidylcholines with a low degree of unsaturation. This study highlights the importance of common genetic variants for metabolite levels, and elucidates the genetic architecture of metabolite classes and lipid species.

genetics↗
bioRxiv2020

Diminutive, degraded but dissimilar: Wolbachia genomes from filarial nematodes do not conform to a single paradigm

Wolbachia are alpha-proteobacteria symbionts infecting a large range of arthropod species and two different families of nematodes. Interestingly, these endosymbionts are able to induce diverse phenotypes in their hosts: they are reproductive parasites within many arthropods, nutritional mutualists within some insects and obligate mutualists within their filarial nematode hosts. Defining Wolbachia "species" is controversial and so they are commonly classified into 16 different phylogenetic lineages, termed supergroups, named A to S. However, available genomic data remains limited and not representative of the full Wolbachia diversity; indeed, of the 24 complete genomes and 55 draft genomes of Wolbachia available to date, 84% belong to supergroups A and B, exclusively composed of Wolbachia from arthropods. For the current study, we took advantage of a recently developed DNA enrichment method to produce four complete genomes and two draft genomes of Wolbachia from filarial nematodes. Two complete genomes, wCtub and wDcau, are the smallest Wolbachia genomes sequenced to date (863,988bp and 863,427bp, respectively), as well as the first genomes representing supergroup J. These genomes confirm the validity of this supergroup, a controversial clade due to weaknesses of the multi-locus system typing (MLST) approach. We also produced the first draft Wolbachia genome from a supergroup F filarial nematode representative (wMhie), two genomes from supergroup D (wLsig and wLbra) and the complete genome of wDimm from supergroup C. Our new data confirm the paradigm of smaller Wolbachia genomes from filarial nematodes containing low levels of transposable elements and the absence of intact bacteriophage sequences, unlike many Wolbachia from arthropods, where both are more abundant. However, we observe differences among the Wolbachia genomes from filarial nematodes: no global co-evolutionary pattern, strong synteny between supergroup C and supergroup J Wolbachia, and more transposable elements observed in supergroup D Wolbachia compared to the other supergroups. Metabolic pathway analysis indicates several highly conserved pathways (haem and nucleotide biosynthesis for example) as opposed to more variable pathways, such as vitamin B biosynthesis, which might be specific to certain host-symbiont associations. Overall, there appears to be no single Wolbachia- filarial nematode pattern of co-evolution or symbiotic relationship. Graphical abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY RepositoriesData generated are available in GenBank: BioProject PRJNA593581; BioSample SAMN13482485 for wLsig, Wolbachia endosymbiont of Litomosoides sigmodontis (genome: CP046577); Biosample SAMN15190311 for the nematode host Litomosoides sigmodontis (genome: JABVXW000000000); BioSample SAMN13482488 for wDimm, Wolbachia endosymbiont of Dirofilaria (D.) immitis (genome: CP046578); Biosample SAMN15190314 for the nematode host Dirofilaria (D.) immitis (genome: JABVXT000000000); BioSample SAMN13482046 for wCtub, Wolbachia endosymbiont of Cruorifilaria tuberocauda (genome: CP046579); Biosample SAMN15190313 for the nematode host Cruorifilaria tuberocauda (genome: JABVXU000000000); BioSample SAMN13482057 for wDcau, Wolbachia endosymbiont of Dipetalonema caudispina (genome: CP046580); Biosample SAMN15190312 for the nematode host Dipetalonema caudispina (genome: JABVXV000000000); BioSample SAMN13482459 for wLbra, Wolbachia endosymbiont of Litomosoides brasiliensis (genome: WQM000000000); Biosample SAMN15190311 for the nematode host Litomosoides brasiliensis (genome: JABVXW000000000); BioSample SAMN13482487 for wMhie, Wolbachia endosymbiont of Madathamugadia hiepei (genome: WQMP00000000); Biosample SAMN15190315 for the nematode host Madathamugadia hiepei (genome: JABVXS000000000). The raw data are available in GenBank as Sequence Read Archive (SRA): SRR10903008 to SRR10903010; SRR10902913 to SRR10902914; SRR10900508 to SRR10900511; SRR10898805 to SRR10898806. Data summaryThe authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files. Eleven Supplementary tables and two supplementary files are available with the online version of this article. Impact StatementWolbachia are endosymbiotic bacteria infecting a large range of arthropod species and two different families of nematodes, characterized by causing diverse phenotypes in their hosts, ranging from reproductive parasitism to mutualism. While available Wolbachia genomic data are increasing, they are not representative of the full Wolbachia diversity; indeed, 84% of Wolbachia genomes available on the NCBI database to date belong to the two main studied clades (supergroups A and B, exclusively composed of Wolbachia from arthropods). The present study presents the assembly and analysis of four complete genomes and two draft genomes of Wolbachia from filarial nematodes. Our genomics comparisons confirm the paradigm that smaller Wolbachia genomes from filarial nematodes contain low levels of transposable elements and the absence of intact bacteriophage sequences, unlike many Wolbachia from arthropods. However, data show disparities among the Wolbachia genomes from filarial nematodes: no single pattern of co-evolution, stronger synteny between some clades (supergroups C and supergroup J) and more transposable elements in another clade (supergroup D). Metabolic pathway analysis indicates both highly conserved and more variable pathways, such as vitamin B biosynthesis, which might be specific to certain host-symbiont associations. Overall, there appears to be no single Wolbachia-filarial nematode pattern of symbiotic relationship.

genomics↗