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bioRxiv2025

Discovery and biosynthesis of biffamycin A, a novel glycotetrapeptide antibiotic

The clinical deployment of antibiotics is undermined by antimicrobial resistance. Without new agents to treat antibiotic resistant bacterial infections, mortality rates are predicted to reach 10 million people per year by 2050. Most antibiotics are derived from natural products (NPs) produced by bacteria; however, this resource was abandoned by industry because of high rediscovery rates. We are amid a natural product renaissance fuelled by inexpensive access to genome sequencing and sophisticated bioinformatic tools, which have highlighted that most of the biosynthetic pathways for NPs are not expressed in the laboratory. Here, we engineered the expression of a silent biosynthetic gene cluster harboured by an environmental isolate of Streptomyces albidoflavus. By using a bioinformatics-guided approach, we isolated and structurally characterised a novel glycopeptide antibiotic (GPA) named biffamycin A, which is the smallest GPA known and harbours unprecedented 5-chloro-4-methoxy tryptophan and 3-hydroxy(-O_SCPLOWDC_SCPLOW-mannoysl)-O_SCPLOWDC_SCPLOW-lysine moieties. Biffamycin A possesses antimycobacterial and antistaphylococcal bioactivity, including methicillin-vancomycin-resistant Staphylococcus aureus.

biochemistry↗

bioRxiv2025

Mobilizable adipose stromal cells fuel regenerative adipogenesis in injured muscle

Skeletal muscle regeneration is a highly orchestrated process involving the dynamic interplay of multiple cell types. Among these, fibro-adipogenic progenitors (FAPs), a population of resident mesenchymal stromal cells (MSCs), are essential for creating a supportive microenvironment that promotes satellite cell differentiation and modulates immune responses. Our recent work revealed that adipose stromal cells (ASCs) from subcutaneous adipose tissue (ScAT) infiltrate the injured muscle within the first 24h post-injury, contributing significantly to the regenerative process. Consequently, the FAP population in the regenerating muscle comprises both resident FAPs and infiltrated ASCs. In the present study, using single cell RNA-seq in a mouse model with trackable KikGR+ ASCs and bioinformatics analyses, we identify Limch1+/Prg4+ ASCs as the primary Mobilizable ASCs (Mob-ASCs) that migrate to and infiltrate the injury site. Notably, this migration is detectable as early as 14 hours post-injury. We demonstrate that these cells are pre-activated within the ScAT, primed to initiate both migratory and regenerative programs. Intriguingly, bioinformatic inference of key activated transcription factors suggested that adipogenesis is also activated in these cells. Leveraging supervised machine learning, we tracked the fate of Mob-ASCs within the regenerating muscle post-injury, where they continue to execute these programs. Importantly, these cells lineage is cued towards a fate of adipogenesis. In vivo, we observed transient generation of adipocytes with a peak at 7-9 days post-injury to which infiltrated ASCs contributed. In vitro, conditioned media assays further revealed that adipocytes derived from ASCs--but not those from FAPs--enhance myoblasts fusion. Collectively, our findings establish Limch1+/Prg4+ ASCs as the Mobilizable ASC population and suggest that their transient adipogenic differentiation is beneficial for muscle regeneration.

physiology↗

bioRxiv2025

Enhanced Multiplexed Single-Cell RNA-Sequencing for Accurate Detection of Treatment Effects Without Batch Correction in the Avian Embryonic Model

Single-cell RNA sequencing has revolutionized our ability to explore cellular heterogeneity and is a powerful tool to study the impact of environmental perturbations on multiple cell states. However, environmental perturbations can be subtle, and the associated biological effects could be masked by experimental noise and bioinformatic processing, especially when the samples are generated separately. Multiplexing strategies have been developed to label each sample and process them together to reduce experimental noise, but existing multiplexing methods often fall short for non-human and non-mouse models in established single-cell RNA sequencing protocols like the BD Rhapsody technology. To address this gap, we combined Lipid Modified Oligonucleotide (LMO) cell tagging with the BD Rhapsody platform to achieve efficient and scalable multiplexing of early embryonic chick cells under different environmental conditions. This species-agnostic LMO approach overcomes limitations of antibody-based multiplexing methods that are often restricted to human and mouse systems, and the only multiplexing option available with the BD Rhapsody system. In our study, we successfully compartmentalized and multiplexed chick embryonic cells under different treatment conditions, analyzing up to 40,000 viable cells per experiment. This strategy minimized experimental noise, eliminating the need for bioinformatics-based batch correction. As a result, we were able to achieve high-quality transcriptomic profiling with minimal loss of critical biological information and identified subtle biological differences that were masked when using data integration pipelines. Our workflow provides an adaptable, robust solution for LMO-tagged single-cell analyses of complex non-human models with the BD Rhapsody technology and opens new avenues for developmental biology research by accurately capturing treatment-induced effects in embryonic tissues.

developmental biology↗

bioRxiv2025

RawBench: A Comprehensive Benchmarking Framework for Raw Nanopore Signal Analysis Techniques

Nanopore sequencing technologies continue to advance rapidly, offering critical benefits such as real-time analysis, the ability to sequence extremely long DNA fragments (up to millions of bases in a single read), and the option to selectively stop sequencing a molecule before completion. Traditionally, the raw electrical signals generated during sequencing are converted into DNA sequences through a process called basecalling, which typically relies on large neural network models. While accurate, these models are computationally intensive and often require high-end GPUs to process the vast volume of raw signal data. This presents a significant challenge for real-time processing, particularly on edge devices with limited computational resources, ultimately restricting the scalability and deployment of nanopore sequencing in resourceconstrained settings. Raw signal analysis has emerged as a promising alternative to these resource-intensive approaches. While attempts have been made to benchmark conventional basecalling methods, existing evaluation frameworks 1) overlook raw signal analysis techniques, 2) lack the flexibility to accommodate new raw signal analysis tools easily, and 3) fail to include the latest improvements in nanopore datasets. Our goal is to provide an extensible benchmarking framework that enables designing and comparing new methods for raw signal analysis. To this end, we introduce RawBench, the first flexible framework for evaluating raw nanopore signal analysis techniques. RawBench provides modular evaluation of three core pipeline components: 1) reference genome encoding (using different pore models), 2) signal encoding (through various segmentation methods), and 3) representation matching (via different data structures). We extensively evaluate raw signal analysis techniques in terms of 1) quality and performance for read mapping, quality and performance for read classification, and 3) quality of raw signal analysis-assisted basecalling. Our evaluations show that raw signal analysis can achieve competitive quality while significantly reducing resource requirements, particularly in settings where real-time processing or edge deployment is necessary. CCS ConceptsComputing methodologies [->] Bioinformatics; Evaluation methodologies; * Applied computing [->] Computational genomics. ACM Reference FormatFurkan Eris, Ulysse McConnell, Can Firtina, and Onur Mutlu. 2025. RawBench: A Comprehensive Benchmarking Framework for Raw Nanopore Signal Analysis Techniques. In Proceedings of the 16th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (BCB 25), October 11-15, 2025, Philadelphia, PA, USA. ACM, New York, NY, USA, 12 pages. https://doi.org/10.1145/3765612.3767302

genomics↗

bioRxiv2025

Statistical and Evolutionary Analysis of Sequenced DNA from Breast Cancer FFPE Specimens

BackgroundDespite the introduction of instant freezing of tumor specimens, formalin-fixed paraffin-embedded (FFPE) blocks of tissue are still commonplace in clinical practice and constitute an important reference for genetic epidemiology of cancer. We carried out a study of a collection of breast tumors paired with lymph-node metastases and analyzed using advanced computational methods, to determine how much information can be obtained from mid-depth whole-exome bulk DNA sequencing. MethodsWe gathered 15 paired (primary and an involved lymph node) excised breast tumors of different molecular subtypes (HER2+, triple negative, luminal A and luminal B HER2-), from the National Research Institute of Oncology, Krakow (Poland) Branch. FFPE specimens contained typical artifacts, manifesting themselves in spurious DNA variant calls. We used several bioinformatics tools to remove the artifacts and analyzed the exomic data, using both commercial and original in-house computational techniques. ResultsWe used several of recent bioinformatics tools to remove the FFPE artifacts and found a serious dispersal of outcomes. After calibration, a series of analyses was performed, including copy number study, resulting in ploidy levels ranging from 1 to 5 (average of 2.5). Positive association was found between the frequency of oncogenes relative to tumor suppressor genes and DNA copy number. In addition, we carried out analyses of the clonal structure of the data using original computational methods based on evolutionary modeling. Interesting results concerning clonal structure, early tumor expansion, and interdependence of the primary tumor and lymph node metastases have been obtained. ConclusionsDespite the imperfections of the FFPE data, many important features of molecular evolution of tumor DNA can be recovered from routine clinical samples.

evolutionary biology↗

bioRxiv2025

The Initial Detection of a Diversity of Viruses Associated with Ladybirds and Other Biocontrol Agents Prompts Interesting Ecological Insights

Predatory insects such as ladybirds, green lacewings, and an aphid-feeding gall midge have been commercialized and deployed worldwide to deal with the challenge of pest control. However, no information is available on their viruses which could interfere with the efficiency of biocontrol. To start filling this gap, this study employed an integrative bioinformatics approach starting from 21 publicly available RNA-seq libraries from 6 countries of 8 natural enemy species used to control aphids. A total of 41 putative novel viruses were identified and classified into 16 families and 1 genus. In addition, 13 known viruses were detected, including aphid and phytopathogenic viruses, and a virus from the invasive harlequin ladybird. The Aphid lethal paralysis virus was detected in several species at different trophic levels, including plants, aphid vectors, predatory insects, and insectivorous vertebrates. Thus, an ecosystem perspective on viruses across trophic levels is proposed because feeding may facilitate the spread of viruses between distant taxonomic species, such as invertebrate and vertebrate insectivorous predators. In conclusion, a simple assessment of the viral diversity in eight predatory insects of agricultural relevance, using a bioinformatics approach, has revealed a potential interspecies viral flux that deserves research attention. Further studies on viruses circulating in agricultural insect species are essential to improve biological control strategies based on trophic interactions, to conserve biodiversity, and to develop knowledge on the evolution of viral entities and their role as members of an agroecological system.

microbiology↗

bioRxiv2025

Serine recombinases are conserved genetic markers of antiphage defense systems

Renewed interest in phage therapy has highlighted a need to understand how bacteria subvert phage infection through antiphage defense systems. Traditionally, strategies to identify antiphage defense systems lack throughput or have limitations for bacterial species where antiphage defense systems are understudied. Herein, we developed a bioinformatic pipeline that uses a small serine recombinase to identify known and unknown antiphage defense systems. Using this approach to query reference genomes and metagenomes, we show that small serine recombinase genes are genetically linked to antiphage defense systems and serve as bait for finding these systems across diverse bacterial phyla. Using co-transcription predictions and statistical analysis of protein domain abundances, we experimentally validated our bioinformatic approach by discovering that KAP P-loop NTPases are fused to putative antiphage domains and reinforce prokaryotic Schlafen proteins as a new class of antiphage defense. Our work shows that small serine recombinases are a reliable genetic marker for the discovery of antiphage defenses across diverse bacterial phyla.

microbiology↗

bioRxiv2025

Human colonization with Phytobacter co-harbouring blaIMP-4 and mcr-9.1 highlights its potential as emerging human pathogen.

Phytobacter is a recently delineated, frequently misidentified genus within the order Enterobacterales. Following two rare cases of patient colonization with multidrug resistant Phytobacter in Ireland, this study presents a genus-wide genomic analysis that aims to define the pathogenic potential of Phytobacter species, with emphasis on their role as emerging human pathogens and reservoirs of carbapenemases. Two carbapenemase-encoding isolates were recovered from rectal swabs in Ireland in 2024 and were initially identified as Phytobacter by MALDI-ToF. Whole-genome sequencing with in silico species typing (dDDH, ANI) provided definitive taxonomic resolution. A genus-wide maximum-likelihood core-genome phylogeny was reconstructed, and the plasmidome and resistome were bioinformatically profiled across all available Phytobacter genomes. Phenotypic susceptibility of the Irish isolates was determined through minimum inhibitory concentration (MIC) testing. The Irish isolates (P. diazotrophicus E787336 and P. ursingii E980862) are the first reported Phytobacter strains carrying both plasmid-borne blaIMP-4 and mcr-9.1 in the genus. MIC testing confirmed resistance to aztreonam, aminoglycosides, cephalosporins, fluoroquinolones, and the {beta}-lactam/{beta}-lactamase inhibitor combination piperacillin-tazobactam. Across 34 Phytobacter genomes examined, 22 distinct plasmid replicon types were identified in 22 isolates, often shared across species. The genus-wide resistome encompassed 71 genes, more than half predicted to be acquired, with carbapenemases detected in 26.5% (9/34) of the genomes. In summary, Phytobacter harbors a diverse, plasmid-borne resistome including carbapenemases, with documented cases of human colonization and infection. These findings support its recognition as an emerging pathogen and reservoir of antimicrobial resistance, underscoring the need for improved clinical identification, genomic surveillance, and preparedness for limited treatment options. Author summarySince Phytobacter was first characterized in 2007, this bacterial genus has mainly been associated with plant growth promotion. More recently, however, increasing reports of human infections have raised concerns about its potential as emerging bacterial pathogen. These are further underscored by the description of multidrug resistant isolates capable to withstand different classes of antimicrobials, including carbapenems which are often used as a last line of treatment. Following the rare finding of multidrug resistant Phytobacter in two patients in Ireland, we combined bioinformatics and laboratory testing to characterize the antimicrobial resistance profile of this overlooked bacterial genus. Our results uncover the variety of resistance determinants, including to carbapenems, which is encoded in the genomes of Phytobacter. This shows its potential as hidden reservoir of drug resistance and emerging bacterial pathogen. We encourage improved clinical recognition and monitoring of Phytobacter to better anticipate infections with limited therapeutic options.

genomics↗

bioRxiv2025

Integrative transcriptomic analysis identifies miR-642a-5p as a regulator of POFUT1 expression in colon cancer

BackgroundColorectal cancer (CRC) is one of the most common and deadly cancers worldwide, underscoring the urgent need for novel biomarkers and therapeutic targets. Protein O-fucosyltransferase 1 (POFUT1) is increasingly recognized as an oncogenic driver in CRC, but the upstream regulatory mechanisms responsible for its overexpression remain poorly understood. ObjectiveWe aimed to identify a reproducible miRNA signature potentially regulating POFUT1 in colon cancer by combining multiple computational approaches and intersecting their outcomes to retain the most significant candidates and to validate biologically the most promising miRNA to confirm its regulatory potential. MethodsWe implemented an integrative, multi-step bioinformatics framework that combined multiple linear regression with stepwise selection, penalized regression models (LASSO and Elastic Net), and Random Forest analysis for non-linear feature evaluation. miRNAs showing a consistent inverse association with POFUT1 across these complementary methods were retained as final candidates. The most significant miRNA was then validated in vitro by mimic transfection, real-time quantitative PCR, and dual-luciferase reporter assays performed in colon cancer cell lines. ResultsFive miRNAs (miR-92b, miR-484, miR-574, miR-642a, and miR-3940) were consistently identified as negative contributors to POFUT1 expression across all analytical approaches. Among these, miR-642a exhibited the strongest negative correlation (r = - 0.44) with POFUT1. It was therefore selected for biological validation to confirm its regulatory interaction. Overexpression of miR-642a-5p through mimic transfection significantly reduced POFUT1 transcript levels by approximately 46 % in HCT 116, 50 % in SW480, and 22 % in SW620 cells compared with controls. Dual-luciferase reporter assays confirmed direct binding of miR-642a-5p to two predicted sites within the POFUT1 3'UTR, resulting in a decrease of luciferase activity by 40-50 %. ConclusionThis study combines bioinformatics screening based on multiple linear regression and machine learning models, with experimental validation to identify miRNAs regulating POFUT1 expression in colon cancer. This integrative strategy allows the identification of a miRNA signature related to POFUT1 and provides novel insights into its post-transcriptional control. It may serve as a foundation for future diagnostic or therapeutic strategies in CRC.

cancer biology↗

bioRxiv2025

Miniature inverted-repeat transposable elements mobilize diverse antibiotic resistance genes in Enterobacteriaceae

Miniature inverted-repeat transposable elements (MITEs) are nonautonomous mobile genetic elements (MGEs) that can be mobilized by transposases provided by the relevant autonomous MGEs. MITEs originating from Tn3-family transposons were previously termed Tn3-derived inverted-repeat miniature elements (TIMEs). Composite transposon-like structures bounded by two copies of TIME, called TIME-COMPs, were shown to mobilize the intervening sequences. However, their association with antibiotic resistance genes (ARGs) has not yet been systematically studied. This study thus aimed to identify new TIME-COMP-like structures containing ARGs in the genomic sequences of the clinically important bacterial family Enterobacteriaceae in public databases. TIME-COMP-like structures were first searched for in the plasmid database PLSDB, focusing on small plasmids, using a self-against-self blastn approach to identify repeated elements. Then, newly and previously identified MITEs (including TIMEs) were searched for in the NCBI core nucleotide database to identify TIME-COMP-like structures located on other replicons. Bioinformatic analysis identified multiple previously unreported TIME-COMPs containing ARGs, which are bounded by directly or inversely oriented TIMEs, namely, IS101, MITESen1, and a novel 244-bp TIME termed TIME244. TIME244 contains a putative resolution site related to that of Tn21. These TIMEs were predominantly detected in plasmids and very rarely in chromosomes. The ARGs embedded in newly identified TIME-COMPs were blaKPC-2, floR, qnrS1, and tet(A). Notably, the blaKPC-2 carbapenemase gene was found in TIME-COMPs bounded by TIME244 and a TIME-COMP bounded by IS101. These findings highlight a potential role for TIMEs in the spread of diverse ARGs. IMPACT STATEMENTBacterial miniature inverted-repeat transposable elements (MITEs) are a group of short (50 bp-500 bp) nonautonomous transposable elements that are thought to have originated from insertion sequences or transposons. Although MITEs can theoretically mobilize antibiotic resistance genes (ARGs) in the presence of transposases, only a few studies have reported their association with ARGs, probably due to difficulties in identifying MITEs in genomic sequences. This study provides evidence, based on bioinformatic analysis of public Enterobacteriaceae genomes, that a subset of MITEs, called Tn3-derived inverted-repeat miniature elements (TIMEs), mobilizes ARGs by forming composite transposon-like structures. A novel 244-bp TIME, designated TIME244, was present in more than 100 Enterobacteriaceae plasmids in the current RefSeq database, suggesting its further transmission in bacterial populations through horizontal gene transfer. This study reveals that TIMEs were often overlooked when analyzing the genetic contexts of ARGs in previous studies. These findings highlight the importance of TIMEs in bacterial gene acquisition and underscore the need for new tools that can detect TIMEs in bacterial genomes for ARG surveillance. DATA SUMMARYAccession numbers of sequence data analyzed in this study are provided within the article or in supplementary data files.

microbiology↗

bioRxiv2025

Astrocytic RNA degradation suppresses calcium signaling to support synapse function and restrain anxiety

How astrocytes achieve their diverse roles in the brain at the molecular level is poorly understood. In this study, we leverage mouse models, electrophysiology, calcium imaging, behavioral assays, and bioinformatic approaches to demonstrate that astrocyte activity and astrocyte-mediated mouse behavior depends on the highly conserved and selective RNA turnover pathway-nonsense-mediated RNA decay (NMD). Conditional deletion of the core NMD gene, Upf2, in mature astrocytes leads to enhanced basal Ca2+ signaling coupled with synapse dysfunction and elevated anxiety. Restoring basal Ca2+ signaling in NMD-deficient astrocytes rescued synaptic transmission and minimized anxiety-associated behavior. Molecular bioinformatic analysis identified specific NMD target transcripts in astrocytes as candidates influencing calcium signaling pathways and neuro-glia interactions that support brain function. Our study is the first to demonstrate specific roles for NMD in astrocytes.

neuroscience↗

bioRxiv2025

Overexpression of TPM4 promotes cancer progression through EMT in anaplastic thyroid cancer

Anaplastic thyroid cancer (ATC) is an undifferentiated tumour originating from thyroid follicular epithelium and represents the most malignant subtype of thyroid cancer. However, the mechanisms underlying ATC development are not fully understood. This study aimed to investigate the mechanisms driving ATC invasion and metastasis to provide novel insights into its aggressive behavior. Through an integrated bioinformatics analysis of the GEO database, we identified Tropomyosin 4 (TPM4) as a differentially expressed gene in ATC. Bioinformatic correlation and pathway enrichment analyses suggested that TPM4 expression is potentially linked to tumor cell invasion and lymph node metastasis. We showed that TPM4 was highly expressed in both ATC tissues and cell lines, and its expression levels were positively correlated with enhanced cell migration and invasion. Mechanistic studies indicated that TPM4 likely enhances tumour cell migration and invasion by facilitating cytoskeletal remodeling and promoting the epithelial-mesenchymal transition (EMT). Our findings suggest that TPM4 represents a promising diagnostic and therapeutic biomarker for ATC.

cancer biology↗

bioRxiv2017

HiMAP: robust Phylogenomics from Highly Multiplexed Amplicon sequencing

High-throughput sequencing has fundamentally changed how molecular phylogenetic datasets are assembled, and phylogenomic datasets commonly contain 50-100-fold more loci than those generated using traditional Sanger-based approaches. Here, we demonstrate a new approach for building phylogenomic datasets using single tube, highly multiplexed amplicon sequencing, which we name HiMAP (Highly Multiplexed Amplicon-based Phylogenomics), and present bioinformatic pipelines for locus selection based on genomic and transcriptomic data resources and post-sequencing consensus calling and alignment. This method is inexpensive and amenable to sequencing a large number (hundreds) of taxa simultaneously, requires minimal hands-on time at the bench (<1/2 day), and data analysis can be accomplished without the need for read mapping or assembly. We demonstrate this approach by sequencing 878 amplicons in single reactions for 82 species of tephritid fruit flies across seven genera (384 individuals), including some of the most economically-important agricultural insect pests. The resulting dataset (>150,000 bp concatenated alignment) contained >40,000 phylogenetically informative characters, and although some discordance was observed between analyses, it provided unparalleled resolution of many phylogenetic relationships in this group. Most notably, we found high support for the generic status of Zeugodacus and the sister relationship between Dacus and Zeugodacus. We discuss HiMAP, with regard to its molecular and bioinformatic strengths, and the insight the resulting dataset provides into relationships of this diverse insect group.

genomics↗

bioRxiv2017

Coupling MALDI-TOF mass spectrometry protein and specialized metabolite analyses to rapidly discriminate bacterial function

For decades, researchers have lacked the ability to rapidly correlate microbial identity with bacterial metabolism. Since specialized metabolites are critical to bacterial function and survival in the environment, we designed a data acquisition and bioinformatics technique (IDBac) that utilizes in situ matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to analyze protein and specialized metabolite spectra of single bacterial colonies from agar plates. We demonstrated the power of our approach by discriminating between two Bacillus subtilis colonies in under 30 minutes, which differ by a single genomic mutation, solely on the basis of their differential ability to produce cyclic peptide antibiotics surfactin and plipastatin. Next, we employed our IDBac technique to detect subtle intra-species differences in the production of metal scavenging acyl-desferrioxamines in a group of eight freshwater Micromonospora isolates that share >99% sequence similarity in the 16S rRNA gene. Finally, we employed our method to simultaneously extract protein and specialized metabolite MS profiles from unidentified species of Lake Michigan sponge-associated bacteria cultivated on an agar plate. In just 3 hours, we created hierarchical protein MS groupings of 11 environmental isolates (10 MS replicates each, for a total of 110 samples) that accurately mirrored phylogenetic groupings. We further distinguished isolates within these groupings, which share nearly identical 16S rRNA gene sequence identity, based on inter- and intra-species differences in specialized metabolite production. To our knowledge, IDBac is the first attempt to couple in situ MS analyses of protein content and specialized metabolite production to allow the distinction of closely related bacterial colonies.\n\nSignificanceMass spectrometry is a powerful technique that has been used to identify bacteria via protein content, and to assess bacterial function in an environment via analysis of specialized metabolites. However, until now these analyses have operated independently, and this has resulted in the inability to rapidly connect bacterial phylogenetic identity with patterns of specialized metabolism. To bridge this gap, we designed a MALDI-TOF mass spectrometry data acquisition and bioinformatics pipeline (IDBac) to discriminate both intact protein and specialized metabolite spectra directly from bacterial cells grown on agar. To our knowledge, this is the first technique that organizes bacteria into highly similar phylogenetic groups and allows for comparison of metabolic differences of hundreds of isolates in just a few hours.

microbiology↗

bioRxiv2017

An interlaboratory study of complex variant detection

Next-generation sequencing (NGS) is widely used and cost-effective. Depending on the specific methods, NGS can have limitations detecting certain technically challenging variant types even though they are both prevalent in patients and medically important. These types are underrepresented in validation studies, hindering the uniform assessment of test methodologies by laboratory directors and clinicians. Specimens containing such variants can be difficult to obtain; thus, we evaluated a novel solution to this problem in which a diverse set of technically challenging variants was synthesized and introduced into a known genomic background. This specimen was sequenced by 7 laboratories using 10 different NGS workflows. The specimen was compatible with all 10 workflows and presented biochemical and bioinformatic challenges similar to those of patient specimens. Only 10 of 22 challenging variants were correctly identified by all 10 workflows, and only 3 workflows detected all 22. Many, but not all, of the sensitivity limitations were bioinformatic in nature. We conclude that Synthetic controls can provide an efficient and informative mechanism to augment studies with technically challenging variants that are difficult to obtain otherwise. Data from such specimens can facilitate inter-laboratory methodologic comparisons and can help establish standards that improve communication between clinicians and laboratories.

genetics↗

bioRxiv2017

A de novo approach to disentangle partner identity and function in holobiont systems

BackgroundStudy of meta-transcriptomic datasets involving non-model organisms represents bioinformatic challenges. The production of chimeric sequences and our inability to distinguish the taxonomic origins of the sequences produced are inherent and recurrent difficulties in de novo assembly analyses. The study of holobiont transcriptomes shares similarities with meta-transcriptomic, and hence, is also affected by challenges invoked above. Here we propose an innovative approach to tackle such difficulties which was applied to the study of marine holobiont models as a proof of concept.\n\nResultsWe considered three holobionts models, of which two transcriptomes were previously assembled and published, and a yet unpublished transcriptome, to analyze their raw reads and assign them to the host and/or to the symbiont(s) using Short Read Connector, a k-mer based similarity method. We were able to define four distinct categories of reads for each holobiont transcriptome: host reads, symbiont reads, shared reads and unassigned reads. The result of the independent assemblies for each category within a transcriptome led to a significant diminution of de novo assembled chimeras compared to classical assembly methods. Combining independent functional and taxonomic annotations of each partners transcriptome is particularly convenient to explore the functional diversity of an holobiont. Finally, our strategy allowed to propose new functional annotations for two well-studied holobionts and a first transcriptome from a planktonic Radiolaria-Dinophyta system forming widespread symbiotic association for which our knowledge is limited. Conclusions\n\nIn contrast to classical assembly approaches, our bioinformatic strategy not only allows biologists to studying separately host and symbiont data from a holobiont mixture, but also generates improved transcriptome assemblies. The use of Short Read Connector has proven to be an effective way to tackle meta-transcriptomic challenges to study holobiont systems composed of either well-studied or poorly characterized symbiotic lineages such as the newly sequenced marine plankton Radiolaria-Dinophyta symbiosis and ultimately expand our knowledge about these marine symbiotic associations.

genomics↗

bioRxiv2018

Identification, expression analysis and molecular modeling of Iron deficiency specific clone 3 (Ids3) like gene in hexaploid wheat

Graminaceous plants secrete iron (Fe) chelators called mugineic acid family phytosiderophores (MAs) from their roots for solubilisation and mobilization of unavailable ferric (Fe3+) ions from the soil. The hydroxylated forms of these phytosiderophores have been found more efficient in chelation and subsequent uptake of minerals from soil which are available in very small quantities. The genes responsible for hydroxylation of phytosiderophores have been recognized as iron deficiency-specific clone 2 (Ids2) and iron deficiency-specific clone 3 (Ids3) in barley but their presence is not reported earlier in hexaploid wheat. Hence, the present investigation was done with the aim:(i) to search for the putative Hordeum vulgare Ids3 (HvIds3) ortholog in hexaploid wheat, (ii) physical mapping of HvIds3 ortholog on wheat chromosome using cytogenetic stocks developed in the background of wheat cultivar Chinese Spring and (iii) to analyze the effect of iron starvation on the expression pattern of this ortholog at transcription level. In the present investigation, a putative ortholog of HvIds3 gene was identified in hexaploid wheat using different bioinformatics tools. Further, protein structure of TaIDS3 was modelled using homology modeling and also evaluated modelled structure behavior on nanoseconds using molecular dynamics based approach. Additionally, the ProFunc results also predict the functional similarity between the proteins of HvIds3 and its wheat ortholog (TaIds3). The physical mapping study with the use of cytogenetic stocks confines TaIds3 in the telomeric region of chromosome 7AS which supports the results obtained by bioinformatics analysis. The relative expression analysis of TaIds3 indicated that the detectable expression of TaIds3 induces after 5th day of Fe-starvation and increases gradually up to 15th day and thereafter decreases till 35th day of Fe-starvation. This reflects that Fe deficiency directly regulates the induction of TaIds3 in the roots of hexaploid wheat.

genomics↗

bioRxiv2018

Best Practices for Benchmarking Germline Small Variant Calls in Human Genomes

Assessing accuracy of NGS variant calling is immensely facilitated by a robust benchmarking strategy and tools to carry it out in a standard way. Benchmarking variant calls requires careful attention to definitions of performance metrics, sophisticated comparison approaches, and stratification by variant type and genome context. The Global Alliance for Genomics and Health (GA4GH) Benchmarking Team has developed standardized performance metrics and tools for benchmarking germline small variant calls. This team includes representatives from sequencing technology developers, government agencies, academic bioinformatics researchers, clinical laboratories, and commercial technology and bioinformatics developers for whom benchmarking variant calls is essential to their work. Benchmarking variant calls is a challenging problem for many reasons:\n\nO_LIEvaluating variant calls requires complex matching algorithms and standardized counting because the same variant may be represented differently in truth and query callsets.\nC_LIO_LIDefining and interpreting resulting metrics such as precision (aka positive predictive value = TP/(TP+FP)) and recall (aka sensitivity = TP/(TP+FN)) requires standardization to draw robust conclusions about comparative performance for different variant calling methods.\nC_LIO_LIPerformance of NGS methods can vary depending on variant types and genome context; and as a result understanding performance requires meaningful stratification.\nC_LIO_LIHigh-confidence variant calls and regions that can be used as \"truth\" to accurately identify false positives and negatives are difficult to define, and reliable calls for the most challenging regions and variants remain out of reach.\nC_LI\n\nWe have made significant progress on standardizing comparison methods, metric definitions and reporting, as well as developing and using truth sets. Our methods are publicly available on GitHub (https://github.com/ga4gh/benchmarking-tools) and in a web-based app on precisionFDA, which allow users to compare their variant calls against truth sets and to obtain a standardized report on their variant calling performance. Our methods have been piloted in the precisionFDA variant calling challenges to identify the best-in-class variant calling methods within high-confidence regions. Finally, we recommend a set of best practices for using our tools and critically evaluating the results.

genomics↗