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Genomics

Explore bioRxiv genomics preprints on sequencing, gene expression and genetic variation. Read source abstracts and verify methods in the manuscript; preprints are not peer reviewed.

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bioRxiv2023

Comparative genomics analysis of three conserved plasmid families in the Western Hemisphere soft tick-borne relapsing fever borreliae provides insight into variation in genome structure and antigenic variation systems

Borrelia spirochetes, causative agents of Lyme disease and relapsing fever (RF), have a uniquely complex genome consisting of a linear chromosome and circular and linear plasmids. The plasmids harbor genes important for the vector-host life cycle of these tick-borne bacteria. The role of Lyme disease causing Borrelia plasmids is more refined compared to RF spirochetes because of limited plasmid-resolved genomes for RF spirochetes. We recently addressed this limitation and found that three linear plasmid families (F6, F27, and F28) were syntenic across all species. Given this conservation, we further investigated the three plasmid families. The F6 family, also known as the megaplasmid, contained regions of repetitive DNA. The F27 was the smallest, encoding genes with unknown function. The F28 family encoded the expression locus for antigenic variation in all species except Borrelia hermsii and Borrelia anserina. Taken together, this work provides a foundation for future investigations to identify essential plasmid-localized genes that drive the vector-host life cycle of RF Borrelia. IMPORTANCEBorrelia spp. spirochetes are arthropod-borne bacteria found globally and infect humans and other vertebrates. RF borreliae are understudied and misdiagnosed pathogens because of the vague clinical presentation of disease and the elusive feeding behavior of argasid ticks. Consequently, genomics resources for RF spirochetes have been limited. Analyses of Borrelia plasmids have been challenging because they are often highly fragmented and unassembled. By utilizing Oxford Nanopore Technologies, we recently generated plasmid-resolved genomes for seven Borrelia spp. found in the Western Hemisphere. This current study is a more in-depth investigation into the linear plasmids that were conserved and syntenic across species. This analysis determined differences in genome structure and, importantly, in antigenic variation systems between species. This work is an important step in identifying crucial plasmid-borne genetic elements essential for the life cycle of RF spirochetes.

microbiology↗

bioRxiv2023

Population genomic analyses reveal extensive genomic regions within selective sweeps associated with adaptation and demographic history of a wheat fungal pathogen

Plant pathogens can quickly evolve in response to the changing host and environment, resulting in destructive epidemics. The fungus Puccinia striiformis f. sp. tritici (Pst), causing wheat stripe rust disease worldwide, is one such pathogen. In the arms race between pathogens and hosts, changes in host populations exerted continuous selective forces on the dynamics of pathogens. However, the footprints of these selection forces and the demography of Pst remain poorly explored, limited our understanding the evolutionary processes that shape the spread and evolution of pathogens. In this study, we revealed several features of worldwide Pst populations through population genomic analyses. There might be limited gene flow between Pst populations from China and other countries. A slower rate of linkage disequilibrium decay was detected comparing to rust fungi with known sexual reproduction. Furthermore, we detected extensive hard and soft sweeps associated with Pst adaptation. Genes within the selective sweeps were enriched in secreted proteins and effectors and showed functions related to pathogenicity or virulence, temperature tolerance, and fungicide resistance implying that Chinese Pst populations suffered positive selection pressures from host and abiotic factors. Moreover, demographic history indicated Pst populations experienced strong bottlenecks at the beginning of the wheat domestication around 10,000 years ago and during modern agriculture around 100 years ago, suggesting that the crop domestication and breeding programs could continuously contribute to the decline of pathogen effective population sizes. Our results provided insights into the evolution of the Pst genome and highlighted the role of modern agriculture on pathogen demography. Author SummaryWheat stripe rust, as a pathogen of wheat, is capable of inducing significant yield reduction on a global scale. Traditional epidemiological investigations have elucidated the causative agent behind this disease, the wheat stripe rust pathogen, as an organism exhibiting swift adaptive evolution in response to its environment. However, the precise mechanisms underpinning its adaptive strategies and the ensuing alterations in population dynamics remain relatively unexplored. In our research, we have undertaken an analysis encompassing wheat stripe rust samples throughout the world. Employing population genomics methods, we have sought to discern the genomic footprints corresponding to the adaptive process within the pathogen. These genomic footprints have illuminated the operation of positive selection pressures caused by both the host plant and the ecological context. Concurrently, it have provided insights into the population size that the wheat stripe rust pathogen has undergone over millennia. Notably, its change in population size revealed the demographic history associated with wheat domestication.

microbiology↗

bioRxiv2023

Fine-Tuning GBS Data with Comparison of Reference and Mock Genome Approaches for Advancing Genomic Selection in Less Studied Farmed Species

BackgroundDiversifying animal cultivation demands efficient genotyping for enabling genomic selection, but non-model species lack efficient genotyping solutions. The aim of this study was to optimize a genotyping-by-sequencing (GBS) double-digest RAD-sequencing (ddRAD) pipeline. Bovine data was used to automate the bioinformatic analysis. The application of the optimization was demonstrated on non-model European whitefish data. ResultsDdRAD data generation was designed for a reliable estimation of relatedness and is scalable to up to 384 samples. The GBS sequencing yielded approximately one million reads for each of the around 100 assessed samples. Optimizing various strategies to create a de-novo reference genome for variant calling (mock reference) showed that using three samples outperformed other building strategies with single or very large number of samples. Adjustments to most pipeline tuning parameters had limited impact on high-quality data, except for the identity criterion for merging mock reference genome clusters. For each species, over 15k GBS variants based on the mock reference were obtained and showed comparable results with the ones called using an existing reference genome. Repeatability analysis showed high concordance over replicates, particularly in bovine while in European whitefish data repeatability did not exceed earlier observations. ConclusionsThe proposed cost-effective ddRAD strategy, coupled with an efficient bioinformatics workflow, enables broad adoption of ddRAD GBS across diverse farmed species. While beneficial, a reference genome is not obligatory. The integration of Snakemake streamlines the pipeline usage on computer clusters and supports customization. This user-friendly solution facilitates genotyping for both model and non-model species.

bioinformatics↗

bioRxiv2023

Genomic sequencing should extend to diverse priority pathogens for effective study and surveillance of antimicrobial resistance: a systematic review of whole-genome sequencing studies from India

BackgroundAntimicrobial resistance (AMR) is a public health emergency in many low and middle-income countries, including India. To effectively tackle AMR, we need rapid diagnostics, effective surveillance and new antimicrobial drugs. Whole-genome sequencing of pathogens is the first definite step towards achieving these goals. MethodsIn this work, we review all the studies published till date that report whole-genome sequences of select priority AMR pathogens from India. We searched PubMed and Web of Science databases for the studies that involved whole-genome sequencing of AMR priority pathogens from India. For the top two highly sequenced pathogens, S. typhi and K. pneumoniae, we performed phylogenetic analyses to understand the geo-climatic distribution of genetically diverse strains. ResultsOur search reveals 94 studies that report 2547 unique whole-genome sequences. We find that most sequences are limited to select priority pathogens isolated from a couple of geo-climatic zones of India. Our phylogenetic analyses show that available data does not indicate systematic differences between the genomes of isolates from different geo-climatic zones. Our search also reveals complete absence of travel-related studies tracking possible movement of AMR pathogens within country. Lastly, we find very few studies that sequence AMR pathogens isolated from food, soil or other environments. ConclusionTogether, these observations suggest that lndia should prioritize sequencing of diverse AMR pathogens from clinics as well as from environments and travellers rather than extending the geo-climatic range of already-sequenced pathogens. Our recommendations can be potentially valuable for other low and middle-income countries with limited resources, high prevalence of AMR and diverse geo-climatic conditions.

microbiology↗

bioRxiv2023

Unraveling Coinfection Dynamics into 100 Whole Genome of Diarrheal Pathogens: A Genome-to-Systems Biology Approach with Plesiomonas shigelloides

Diarrhea is the second leading cause of mortality among infants under the age of five. One of the main causes of this disease is multipathogenic infections, which can make the conditions of patients even worse. Plesiomonas shigelloides (P. shigelloides) is one of the pathogenic bacteria that contributes to the pathophysiology of diarrhea and may be implicated in coinfection with other diarrheal pathogens. Therefore, the purpose of this study is to investigate the hypothetical proteins to explore the genetic insights of P. shigelloides and its relationships with common diarrheal diseases. For this reason, we used 16S rRNA sequencing together with several biochemical tests to identify the bacteria that we isolated from diarrheal patients (8 years). Afterwards, the whole genome of P. shigelloides was sequenced, assembled and annotated in order to obtain the genomic insights of P. shigelloides. In addition, the common virulence genes of ten (10) common diarrhea-causing bacteria were identified from 100 whole genome sequences. Finally, the system biology approach was applied to predict the coinfection pattern between P. shigelloides and the virulence genes of 10 bacteria. The complete genome sequencing analysis of this bacterium revealed 899 hypothetical proteins from which 33 hypothetical proteins shared the clusters with the 109 virulence genes of 10 distinct diarrheal pathogens, forming a strong interaction based on biological processes, molecular functions, subcellular localization, or pathways. All diarrhea causing bacteria were found to have P. shigelloides microbial interactions; however, V. cholerae exhibited the strongest relationships, while C. difficile showed the weakest. The results of this investigation clearly imply that P. shigelloides shares a coinfection pattern with other bacteria that cause diarrhea. Finally, the findings from the complete genome provide new avenues for researchers to pursue their investigation of the pathophysiology of diarrhea.

systems biology↗

bioRxiv2023

Chloroplast genome-based genetic resources for Japan's threatened subalpine forests via genome skimming

The Japanese subalpine zone is dominated by a distinct and ecologically important conifer rich forest biome, subalpine coniferous forests, that are an outlier of the extensive boreal forests of Eurasia. While being relatively intact compared to other forest biomes in Japan, subalpine coniferous forests are under significant threat from deer browsing, global warming and small populations size effects. However, there is a severe lack of genetic resources available for the study of this biomes major constituent plant species. This study aims to develop chloroplast genome-based genetic resources for 12 widespread subalpine tree and shrub species via genome skimming of whole genomic DNA using short reads (100-150 bp in length). For 10 species, whole chloroplast genomes were assembled via de novo-based methods from 4-10 individuals per species sampled from across their ranges in Japan and, for non-Japanese endemic species, elsewhere in northeast Asia. A total of 566 single nucleotide polymorphisms for Japanese samples and 768 for all samples (varying from 2 to 202 per species) were identified which were distributed in geographically restricted lineages in most species. In addition, between 9 to 58 polymorphic simple sequence repeat regions were identified per species. For two Ericaceae species (Rhododendron brachycarpum and Vaccinium vitis-idaea) characterized by large chloroplast genomes, de novo assembly failed, but single nucleotide polymorphisms could be identified using reference mapping. This data will be useful for genetic studies of the taxonomic relationship of populations within Japan and to other parts of northeast Asia, investigating phylogeographic patterns within species, conservation genetics and has potential application for studies of environmental and ancient DNA.

genetics↗

bioRxiv2023

A high-quality genome assembly of the ghost moth Druceiella hillmani provides new evidence of genome size augmentation in Hepialidae

Ghost moths are an unusual family of primitive moths (Lepidoptera: Hepialidae) known for their large body size and crepuscular adult activity. These moths represent an ancient lineage, frequently have soil dwelling larvae, and are adapted to high elevations, deserts, and other extreme environments. Despite being rather speciose with more than 700 species, there is a dearth of genomic resources for the family. Here, we present the first high quality, publicly available hepialid genome, generated from an Andean species of ghost moth, Druceiella hillmani. Our genome assembly has a length of 2,586 Mbp with contig N50 of 28.1 Mb and N50 of 29, and BUSCO completeness of 97.1%, making it one of the largest genomes in the order Lepidoptera. Our assembly is a vital resource for future research on ghost moth genomics.

evolutionary biology↗

bioRxiv2024

Genome-wide conditional degron libraries for functional genomics

The yeast knockout library, comprised of strains carrying precise deletions of individual open reading frames (ORFs), has been a vital resource to understand gene function. However, accumulation of suppressor mutations in knockout strains can lead to erroneous functional annotations. Moreover, the library is limited to non-essential ORFs, and must be complemented with hypomorphic alleles of essential ORFs for genome- wide studies. To address these limitations, we constructed genome-wide libraries of conditional alleles based on the auxin-inducible degron (AID) system for conditional degradation of AID-tagged proteins. First, we determined that N-terminal tagging is at least twice more likely to inadvertently impair protein function across the proteome. We thus constructed two genome-wide libraries with over 5600 essential and non-essential proteins fused at the C-terminus with an AID tag and an optional fluorescent protein. Almost 90% of AID- tagged proteins were degraded in the presence of the auxin analog 5-Ph-IAA, with initial protein abundance and tag accessibility as limiting factors. Genome-wide screens for DNA damage response factors with the AID libraries revealed a role for the glucose signaling factor GSF2 in resistance to hydroxyurea, highlighting how these resources extend the toolbox for functional genomics in yeast.

systems biology↗

bioRxiv2024

Impact of genome assemblies, genotyping methods, variant types, ploidy levels and population structures on genomic prediction in switchgrass

Genomic prediction, the use of genetic information for predicting traits, has accelerated the breeding processes and provided mechanistic insights into the genetic bases of complex traits. While substantial efforts have been devoted to optimize genomic prediction, there remain areas that need to be further explored, including the impact of genome assemblies, genotyping approaches, variant types, allelic complexities, polyploidy levels, and population structures. Here, we assess the impact of these factors on the prediction of 20 complex traits in switchgrass (Panicum virgatum L.), a perennial biofuel feedstock. We found that short read-based genome assembly perform comparably to or even better than long read-based assembly in trait prediction; exome capture-based models have higher prediction accuracy than genotyping-by-sequencing-based models for 13 traits; bi-allelic insertion/deletions are as useful as bi-allelic single nucleotide polymorphisms in trait prediction, whereas multi-allelic variants outperform bi-allelic ones for 15 traits. Models built for tetraploids have higher prediction accuracy than those for octoploids for most traits. Traits of individuals with higher within-population genetic distances tend to have higher prediction accuracy. Finally, integrating different types of variants can improve the prediction accuracy. By exploring these factors, anthesis date prediction models built using multi-allelic insertion/deletions derived from exome capture led to the largest number of orthologs of benchmark flowering time genes compared to other models. Our study provides insights into the factors influencing genomic prediction outcomes that inform best practices for future studies and for improving agronomic traits in switchgrass and other species through selective breeding.

plant biology↗

bioRxiv2024

Accelerating whole-genome alignment in the age of complete genome assemblies

Recent advancements in long-read sequencing and assembly methods have ushered in an era of high-quality genome assemblies. Modern assemblies commonly feature megabase-long sequences frequently spanning entire chromosomes. The increase in the assembly contiguity and the reduced number of assembly contigs also implies that whole-genome alignment is no longer an embarrassingly parallel problem. The conventional method of aligning sequences of the query genome in parallel is to utilize a single thread per sequence. This results in poor CPU utilization and long runtimes. In this work, we designed optimizations to accelerate whole-genome alignment on multi-core processors and implemented them in a commonly used aligner, minimap2. Our improvements include a fine-grained parallel chaining method and a fast mechanism for differentiating primary and secondary chains. Our approach accelerates alignment of human, plant, and primate genomes by 1.6x to 7.2x without compromising accuracy.

bioinformatics↗

bioRxiv2024

Gfa2bin enables graph-based GWAS by converting genome graphs to pan-genomic genotypes

Variation graphs offer superior representation of genomic diversity compared to traditional linear reference genomes, capturing complex features that are otherwise inaccessible to analysis. It seems self-evident that integrating these graphs with genome-wide association studies (GWAS) should enable more comprehensive understanding of genetic landscapes, potentially uncovering novel associations between genetic variations and traits. This approach takes full advantage of rich genomic information, thereby providing deeper insights into the genetic base of complex traits. Our tool, gfa2bin, offers multiple methods to (i) genotype variation graphs and (ii) convert the genotypes to well-established data formats for genome-wide association studies (GWAS). We demonstrate that variation graphs are feasible alternatives to traditional linear references for GWAS. Our case study using Arabidopsis thaliana and 1,695 traits shows that our approach complements SNP-based approaches, often identifying additional associations, with all associations having on average higher significance compared to SNP-based approaches. gfa2bin is implemented in Rust. Commented source code is available under MIT license at https://github.com/MoinSebi/gfa2bin. Examples of how to run gfa2bin are provided in the documentation. We added several Python scripts and a Snakemake pipeline for easy processing of our tool using larger data sets. In addition, we recommend using packing (https://github.com/MoinSebi/packing) for reduced storage and preprocessing (normalization) of sequence-to-graph alignments coverage.

bioinformatics↗

bioRxiv2025

PlantVarFilter: A Comprehensive Pipeline for Variant Filtering and Genome-Wide Association Analysis in Plant Genomics

Genomic variant analysis is fundamental to understanding the genetic basis of phenotypic traits in plants. However, the increasing volume and complexity of variant data pose significant challenges for effective filtering, annotation, and downstream analysis. Here, we present PlantVarFilter, a comprehensive Python-based pipeline designed to facilitate efficient filtering of plant genomic variants, precise gene annotation, and integration with trait data for genome-wide association studies (GWAS). PlantVarFilter supports multiple input formats, including compressed VCF and GFF3 files, enabling scalable processing of large datasets. It implements consequence-based filtering to prioritize biologically relevant variants and provides seamless annotation of variants with gene features and trait associations. The toolkit includes statistical GWAS modules based on t-tests and linear regression models, coupled with automated generation of visual summary plots such as Manhattan plots and variant consequence distributions. Our pipeline aims to empower plant geneticists and breeders with an easy-to-use, extensible framework for variant-trait association analysis, accelerating discovery in agricultural genomics. The current release demonstrates robust performance on real-world plant datasets, highlighting its potential as a valuable resource for the genomics community.

bioinformatics↗

bioRxiv2025

The power to resolve relationships: identifying incongruence and precision of reduced representation and genome-wide data in phylogenomics and population genomics

Target capture of ultraconserved elements (UCEs) and taxon-specific probes are widely used reduced-representation methods in phylogenomics and, increasingly, in population genomics for their ability to retrieve hundreds to thousands of homologous loci across divergent taxa. Meanwhile, declining costs and improved computational methods have made genome resequencing more accessible for non-model species, enabling the generation of datasets that can address evolutionary and ecological questions from micro- to macroevolutionary scales. Whether target capture approaches to likewise generate datasets that can address questions across broad hierarchical scales remains unclear. Here, we assess the efficacy of data collection (i.e., single nucleotide polymorphism (SNP) retention), predicted genetic variation across samples (i.e., heterozygosity), and phylogenetic congruence between data generated using reduced-representation methods and genome resequencing, leveraging publicly available datasets from plants and animals. We found that SNP retention varied by locus type, with genome-wide datasets retaining the highest proportion of SNPs and UCEs the lowest proportion. Heterozygosity also differed, with Benchmarking Universal Single-Copy Orthologs (BUSCOs) producing the lowest estimates, followed by UCEs; the inclusion of supercontig flanking regions raised heterozygosity values moderately. Across all phylogenetic trees, UCE datasets had the lowest bootstrap support, followed by BUSCOs and single copy orthologous genes. Population structure analyses frequently underestimated the number of ancestral populations in reduced-representation datasets, often identifying fewer populations than genome-wide datasets and assigning samples to different clusters. These discrepancies underscore the challenges of relying solely on reduced-representation methods for robust inferences of genetic diversity, phylogenetic relationships, and population structure.

evolutionary biology↗

bioRxiv2025

Genomic selection for accelerated heartwood formation in Pedunculate oak (Quercus robur L.) using whole-genome sequencing

Heartwood traits in trees are critical for timber quality but are notoriously difficult to phenotype due to their late expression and the need for destructive sampling. In this proof-of-concept study, we demonstrate that combining genome-wide association studies (GWAS) with Bayesian genomic prediction models provides an effective strategy to overcome these challenges. By using GWAS to preselect trait associated SNPs and integrating them into predictive models, we substantially improve the accuracy of genomic predictions for heartwood related traits in oaks. Our approach allows for reliable selection of superior genotypes at the seedling stage, long before heartwood traits can be directly measured, thus enabling early and cost-effective breeding decisions. We also identify the number of rings in sapwood as a genetically controlled, easily measured proxy trait that enhances selection strategies for heartwood content. Together, these findings provide a scalable framework for integrating genomics into operational tree breeding programs and demonstrate how combining GWAS and genomic prediction can accelerate the improvement of complex wood traits in long lived forest tree species.

genetics↗

bioRxiv2025

Atypical plastid genome evolution: Cereus Mill. from distinct environments harbor one of the largest plastid genomes in Cactaceae

BackgroundCactaceae has successfully radiated in xeric habitats across the Americas, presenting very distinct morphologies and evolutionary patterns within tribes. This study presents the complete plastomes of C. jamacaru subsp. jamacaru and C. hildmannianus subsp. hildmannianus, which inhabit distinct habitats, providing insights into their genomic structure and evolutionary history, with implications for conservation. Methods and ResultsChloroplast genomes of the two Cereus were assembled and analyzed to investigate plastome evolution in Cactoideae. Fresh cladodes were collected and their mesophyll manually extracted, chloroplasts were extracted from the mesophyll, and cpDNA sequenced using Illumina MiSeq. De novo assembly and annotation were conducted using BLAST, Expasy, and tRNAScan as validation tools. We compared the genome structure, gene content, codon usage, and RNA editing predictions between tribes. The genome was 141.884 and 141.600 bp for C. jamacaru and C. hildmannianus, respectively, and dotplot analysis confirmed highly syntenic plastomes. The genes trnV-GAC, trnV-UAC, rpl23, ndhA, ndhE, ndhG, ndhI, and ndhK were lost, and ndhB, ndhC, ndhF, and rpl33 are pseudogenes. The tRNAval losses indicate putative superwobbling or nuclear-coded tRNA import from cytosol. We identified an insertion in rps18 for both Cereus, suggesting that intron retention may be in course for these species. We identified [~]190 single sequence repeats and 50 tandem repeats for each species, and eight exclusive RNA editing sites. Synteny analysis revealed rearrangements distinguishing taxa within Cactoideae. Phylogenetic results supported Cereus monophyly, corroborating existing classifications, and clarifies unresolved relationships, enhancing understanding of phylogenetic relationships within Cactaceae. ConclusionsOur results provide evidence on the evolutionary patterns and putative signatures of adaptation to distinct environments, providing insights into genomic evolution and conservation of Cereus.

evolutionary biology↗

bioRxiv2025

Darwin21 Genome Database: A Curated Whole-Genome Repository of Endophytic Bacteria from Desert Plants

Microbial communities associated with desert plants play a pivotal role in enhancing host survival under extreme environmental stressors, including drought, salinity, and nutrient limitation. The Darwin21 Endophytic Microbial Collection is one of the largest curated repositories of 2,500 cultivable endophytic bacteria isolated from 23 native desert plant species across Saudi Arabia, Jordan, and Pakistan. Representing a broad spectrum of arid microhabitats from inland deserts and mountain wadis to coastal mangroves and date palm oases, the collection supports integrative studies on microbial ecology and plant-microbe interactions in water-limited ecosystems. A central component of this initiative is the Darwin21 Genome Database, which currently hosts whole-genome sequences (WGS) of 534 endophytic bacterial isolates annotated with extensive ecological metadata, assembly statistics, functional traits, and host associations. The database interface provides tools for genome exploration, metadata filtering, and functional gene mining, enabling users to identify taxa and traits of agronomic interest, particularly for applications in sustainable agriculture and sustainable desert revegetation. By combining genomic, ecological, and functional data, the Darwin21 Genome Database serves as a foundational platform for the development of targeted microbial inoculants and fosters data-driven research into desert microbiomes and plant resilience mechanisms. Database URLhttps://www.genomedatabase.org/ O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=156 SRC="FIGDIR/small/672100v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@1703432org.highwire.dtl.DTLVardef@172fce7org.highwire.dtl.DTLVardef@39bd1borg.highwire.dtl.DTLVardef@ae3fef_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

Hi-C informed kernel association test: integrating 3-dimensional genome structure into variant-set association for whole-genome sequencing data

Variant-set association analysis is a powerful strategy for genetic studies of whole genome sequence (WGS) data, especially for rare variants. By aggregating variant signals, variant-set analysis can improve statistical power, result interpretability, and study replicability. Motivated by evidence that three-dimensional (3D) genome architecture plays a critical role in regulating gene transcription, several works have incorporated 3D genome architecture into gene-based association tests and demonstrated great promise. In this work, we extend the idea of 3D-genome guided test from gene-centric to gene-agnostic, whole-genome testing by introducing a Hi-C informed kernel association test. We present a principled procedure that converts Hi-C contact confidence into borrowing weights and integrates these weights into genetic similarity kernels so that higher-confidence interacting loci contribute more to the association test of the target variant set. We use a controlling parameter to adaptively determine the appropriate degree of information borrowing from its interacting loci during association testing. We assess the performance of the Hi-C informed test using simulations and illustrate its advantage in detecting rare-variant sets using WGS data from the ARIC study in the Trans-Omics for Precision Medicine (TOPMed) program.

bioinformatics↗

bioRxiv2025

Deciphering the global genomic landscape of C. neoformans: Population dynamics, molecular epidemiology and genomic signatures of pathogenicity

The study investigates global genomic surveillance of Cryptococcus neoformans over three decades to elucidate genetic diversity, incorporating serotypes, molecular types, STs and mating types, phylogenomics, virulence-associated determinants, antifungal resistance, and pangenome profiles. Across 139 study genomes, the isolates exhibited nineteen distinct sequence types (STs), among which ST5 (63%) was the most prevalent. The predominance of MAT mating type 91% mirrors enhanced virulence, environmental adaptability and clonal expansion, enabling its persistence without MATa (9%) counterparts. The phylogenomic analysis revealed, there is no distinct clustering of isolates from clinical and environmental settings, indicating a high level of genome conservation across sources. Core-accessory genome partitioning and ortholog-based clustering revealed clonal population dominance of the VNI lineage across continents, alongside clear divergence from the VNIV lineage. Virulence gene analysis highlighted conserved expression of capsular genes, phospholipase gene, iron acquisition genes and superoxide dismutase genes, while point mutations and aneuploidy in ERG11 and AFR1 suggested potential azole-resistance mechanisms. This study delivers a holistic assessment of global genomic diversity in the C. neoformans population, emphasising evolutionary conservation, lineage-specific divergence, and adaptability to environment, host and anti-fungal treatments.

bioinformatics↗