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PubMed2025

Validation of a genome-wide polygenic score for body mass index in South Asians.

Obesity is a complex disorder, manifested by the interaction of inherited and environmental factors and modulated by a person's lifestyle habits. India has witnessed more than a two-fold increase in the number of overweight adults in the last 30 years. The polygenic risk score (PRS) quantitatively measures an individual's risk for common diseases. The PRS for obesity have been validated in the Caucasian population but not in the South Asian (SAS) population. In this study, we benchmarked and validated the existing genome-wide PRS model of obesity with 2.1 million variants in the SAS population. We analyzed a total of 14,263 individuals from three different South Asian cohorts. We compared the risk score with the body mass index (BMI) categories (underweight, normal weight, overweight, and obese) in all three cohorts. High PRS was associated with increased BMI in all the three cohorts. This study also compared validation results from another population-specific PRS model for the BMI. We conclude that high PRS is associated with high BMI in South Asians. Our study suggests that the PRS score can perhaps be an early predictor of overweight and obesity in the South Asian population.

South Asian↗
PubMed2024

ONCOLINER: A new solution for monitoring, improving, and harmonizing somatic variant calling across genomic oncology centers.

The characterization of somatic genomic variation associated with the biology of tumors is fundamental for cancer research and personalized medicine, as it guides the reliability and impact of cancer studies and genomic-based decisions in clinical oncology. However, the quality and scope of tumor genome analysis across cancer research centers and hospitals are currently highly heterogeneous, limiting the consistency of tumor diagnoses across hospitals and the possibilities of data sharing and data integration across studies. With the aim of providing users with actionable and personalized recommendations for the overall enhancement and harmonization of somatic variant identification across research and clinical environments, we have developed ONCOLINER. Using specifically designed mosaic and tumorized genomes for the analysis of recall and precision across somatic SNVs, insertions or deletions (indels), and structural variants (SVs), we demonstrate that ONCOLINER is capable of improving and harmonizing genome analysis across three state-of-the-art variant discovery pipelines in genomic oncology.

Humans↗
PubMed2026

VirBinn improves viral genome binning from metagenomic Hi-C through graph diffusion.

MOTIVATION: Metagenomic Hi-C provides in situ proximity signals that can improve genome binning and enable virus-host-association analysis. However, viral genome recovery remains difficult because virus-virus Hi-C contact matrices are extremely sparse. Viral genomes are small, often low-abundance, and frequently assemble into short contigs, leaving many true within-genome links unobserved and causing viral bins to fragment. RESULTS: We present VirBinn, a graph-diffusion framework for viral binning from metagenomic Hi-C. VirBinn enhances virus-virus connectivity through two complementary mechanisms: random-walk-with-restart enhancement on the sparse virus-virus contact graph and host-guided diffusion that propagates viral seeds through the host network to infer indirect virus-virus associations. The enhanced views are integrated and clustered using Leiden community detection to produce viral metagenome-assembled genomes (vMAGs). On dataset-specific simulation benchmarks with ground truth, VirBinn consistently recovers more high-quality vMAGs than Hi-C-based and shotgun-based baselines and substantially increases the number of near-complete genomes. On four real metagenomic Hi-C datasets spanning human gut, pig gut, sheep gut (long-read assembly), and wastewater, VirBinn yields more high-completeness vMAGs under CheckV and produces bins with strong within-cluster contact support. Finally, host linkage analysis using reconstructed host MAGs reveals habitat-specific host-association patterns and plausible host taxonomic profiles. AVAILABILITY AND IMPLEMENTATION: VirBinn is available at https://github.com/dyxstat/VirBinn. The scripts to reproduce the results and figures in this article are available at https://github.com/dyxstat/Reproduce_VirBinn.

Genome, Viral↗
PubMed2006

Integrated prediction of the helical membrane protein interactome in yeast.

At least a quarter of all genes in most genomes contain putative transmembrane (TM) helices, and helical membrane protein interactions are a major component of the overall cellular interactome. However, current experimental techniques for large-scale detection of protein-protein interactions are biased against membrane proteins. Here, we define protein-protein interaction broadly as co-complexation, and develop a weighted-voting procedure to predict interactions among yeast helical membrane proteins by optimally combining evidence based on diverse genome-wide information such as sequence, function, localization, abundance, regulation, and phenotype. We use logistic regression to simultaneously optimize the weights of all evidence sources for best discrimination based on a set of known helical membrane protein interactions. The resulting integrated classifier not only significantly outperforms classifiers based on any single genomic feature, but also does better than a benchmark Naïve Bayes classifier (using a simplifying assumption of conditional independence among features). Finally, we apply the optimized classifier genome-wide, and construct a comprehensive map of predicted helical membrane protein interactome in yeast. This can serve as a guide for prioritizing further experimental validation efforts.

Membrane Proteins↗
PubMed2025

Sawfish: improving long-read structural variant discovery and genotyping with local haplotype modeling.

MOTIVATION: Structural variants (SVs) play an important role in evolutionary and functional genomics but are challenging to characterize. High-accuracy, long-read sequencing can substantially improve SV characterization when coupled with effective calling methods. While state-of-the-art long-read SV callers are highly accurate, further improvements are achievable by systematically modeling local haplotypes during SV discovery and genotyping. RESULTS: We describe sawfish, an SV caller for mapped high-quality long reads incorporating systematic SV haplotype modeling to improve accuracy and resolution. Assessment against the draft Genome in a Bottle (GIAB) SV benchmark from the T2T-HG002-Q100 diploid assembly shows that sawfish has the highest accuracy among state-of-the-art long-read SV callers across every tested SV size group. Additionally, sawfish maintains the highest accuracy at every tested depth level from 10- to 32-fold coverage, such that other callers required at least 30-fold coverage to match sawfish accuracy at 15-fold coverage. Sawfish also shows the highest accuracy in the GIAB challenging medically relevant genes benchmark, demonstrating improvements in both comprehensive and medically relevant contexts.When joint-genotyping seven samples from CEPH-1463, sawfish has over 9000 more pedigree-concordant calls than other state-of-the-art SV callers, with the highest proportion of concordant SVs (81%). Sawfish's quality model enables selection for an even higher proportion of concordant SVs (88%), while still calling nearly 5000 more pedigree-concordant SVs than other callers. These results demonstrate that sawfish improves on the state-of-the-art for long-read SV calling accuracy across both individual and joint-sample analyses. AVAILABILITY AND IMPLEMENTATION: Sawfish source code, pre-compiled Linux binaries, and documentation are released on GitHub: https://github.com/PacificBiosciences/sawfish.

Haplotypes↗
PubMed2001

Promoter prediction in the human genome.

Computational prediction of eukaryotic poIII promoters has been one of the most elusive problems despite considerable effort devoted to the study. Researchers have looked for various types of signals around the transcriptional start site (TSS), viz. oligo-nucleotide statistics, potential binding sites for core factors, clusters of binding sites, proximity to CpG islands etc. The proximity of CpG islands to gene starts is now a well established fact, although until recently, it was based on very little genomic data. In this work we explore the possibility of enhancing the promoter prediction accuracy by combining CpG island information with a few other, biologically motivated, seemingly independent signals, that cover most of the known knowledge. We benchmarked the method on a much larger genomic datasets compared to previous studies. We were able to improve slightly upon current prediction accuracy. Furthermore, we observe that CpG islands are the most dominant signals and the other signals do not improve the prediction. This suggests that the computational prediction of promoters for genes with no associated CpG-island (typically having tissue-specific expression) looking only at the immediate neighborhood of the TSS may not even be possible. We suggest some biological experiments and studies to better understand the biology of transcription.

Binding Sites↗
PubMed2005

Structural similarity to bridge sequence space: finding new families on the bridges.

Structures for protein domains have increased rapidly in recent years owing to advances in structural biology and structural genomics projects. New structures are often similar to those solved previously, and such similarities can give insights into function by linking poorly understood families to those that are better characterized. They also allow the possibility of combing information to find still more proteins adopting a similar structure and sometimes a similar function, and to reprioritize families in structural genomics pipelines. We explore this possibility here by preparing merged profiles for pairs of structurally similar, but not necessarily sequence-similar, domains within the SMART and Pfam database by way of the Structural Classification of Proteins (SCOP). We show that such profiles are often able to successfully identify further members of the same superfamily and thus can be used to increase the sensitivity of database searching methods like HMMer and PSI-BLAST. We perform detailed benchmarks using the SMART and Pfam databases with four complete genomes frequently used as annotation benchmarks. We quantify the associated increase in structural information in Swissprot and discuss examples illustrating the applicability of this approach to understand functional and evolutionary relationships between protein families.

Protein Conformation↗
PubMed2025

Evaluating Language Models for Biomedical Fact-Checking: A Benchmark Dataset for Cancer Variant Interpretation Verification.

Accurate interpretation of genomic variants is critical for precision oncology but remains slow and dependent on specialized expertise. Public knowledgebases such as the Clinical Interpretation of Variants in Cancer (CIViC) help by curating literature-backed variant interpretations in a structured form, yet verification and review have become major bottlenecks. To address this, we developed CIViC-Fact, a benchmark dataset and pipeline for testing automated systems that verify the accuracy of cancer variant claims. CIViC-Fact links structured claims to sentence-level supporting or refuting evidence from full-text articles, and includes expert annotations and explanations. We evaluated multiple language models. Proprietary models performed well without training, but a smaller open-source model, fine-tuned on CIViC-Fact, achieved the highest accuracy (89%). Applying our fact-checking pipeline to real CIViC entries showed that reviewing less than 20% of content, focusing on flagged entries, would be sufficient to catch over half of all errors. This AI-assisted triage greatly accelerates the review process without replacing or reducing expert insight, ensuring that existing careful oversight remains in place while curators can work more efficiently. CIViC-Fact provides a realistic, high-consequence framework for biomedical fact-checking and a path toward more rigorous and efficient knowledgebase curation.

Journal Article↗
PubMed2004

Mitochondrial substitution rates are extraordinarily elevated and variable in a genus of flowering plants.

Plant mitochondrial (mt) genomes have long been known to evolve slowly in sequence. Here we show remarkable departure from this pattern of conservative evolution in a genus of flowering plants. Substitution rates at synonymous sites vary substantially among lineages within Plantago. At the extreme, rates in Plantago exceed those in exceptionally slow plant lineages by approximately 4,000-fold. The fastest Plantago lineages set a new benchmark for rapid evolution in a DNA genome, exceeding even the fastest animal mt genome by an order of magnitude. All six mt genes examined show similarly elevated divergence in Plantago, implying that substitution rates are highly accelerated throughout the genome. In contrast, substitution rates show little or no elevation in Plantago for each of four chloroplast and three nuclear genes examined. These results, combined with relatively modest elevations in rates of nonsynonymous substitutions in Plantago mt genes, indicate that major, reversible changes in the mt mutation rate probably underlie the extensive variation in synonymous substitution rates. These rate changes could be caused by major changes in any number of factors that control the mt mutation rate, from the production and detoxification of oxygen free radicals in the mitochondrion to the efficacy of mt DNA replication and/or repair.

Animals↗
PubMed2026

Variant harmonization critically determines polygenic score transferability for lipid traits in Samoan populations.

Dyslipidemia is a significant risk factor for cardiovascular disease (CVD), the leading cause of death in Samoa. Polygenic scores (PGSs) for lipid traits offer promise for improved CVD risk prediction; however, their performance in Pacific Islander populations-comprising only 0.002% of genome-wide association study (GWAS) participants as of 2024-remains unknown. We evaluated the transferability of multi-ancestry PGS for LDL cholesterol (LDL-C), HDL cholesterol (HDL-C), triglycerides (TGs), and total cholesterol (TC) in 4,342 Samoan adults across five cohorts spanning 1990-2010. PGSs from Graham et al. and Kanoni et al. multi-ancestry meta-analyses were harmonized with genome-wide imputed genotypes using a Samoan-specific reference panel, and performance was assessed via incremental R2 from linear mixed models with bootstrapped confidence intervals. HDL-C showed the highest performance (incremental R2 5.0%-15.0%), followed by TC (5.0%-10.7%), LDL-C (5.7%-8.6%), and TG (3.5%-7.0%). Critically, meaningful LDL-C performance was achieved only with the genome-wide PRS-CS score (99.6%-99.7% variant matching), while a curated pruning-and-thresholding score achieved ∼9% matching and near-zero performance. These findings establish systematic lipid PGS benchmarks in Samoans, demonstrating meaningful transferability when genome-wide variant coverage is ensured, and highlight variant harmonization as a critical precondition for PGS deployment in underrepresented populations.

Pacific Islanders↗
PubMed2001

In silico structural and functional analysis of the human cytomegalovirus (HHV5) genome.

The open reading frames of human cytomegalovirus (human herpesvirus-5, HHV5) encode some 213 unique proteins with mostly unknown functions. Using the threading program, ProCeryon, we calculated possible matches between the amino acid sequences of these proteins and the Protein Data Bank library of three-dimensional structures. Thirty-six proteins were fully identified in terms of their structure and, often, function; 65 proteins were recognized as members of narrow structural/functional families (e.g. DNA-binding factors, cytokines, enzymes, signaling particles, cell surface receptors etc.); and 87 proteins were assigned to broad structural classes (e.g. all-beta, 3-layer-alphabetaalpha, multidomain, etc.). Genes encoding proteins with similar folds, or containing identical structural traits (extreme sequence length, runs of unstructured (Pro and/or Gly-rich) residues, transmembrane segments, etc.) often formed tandem clusters throughout the genome. In the course of this work, benchmarks on about 20 known folds were used to optimize adjustable parameters of threading calculations, i.e. gap penalty weights used in sequence/structure alignments; new scores obtained as simple combinations of existing scoring functions; and number of threading runs conducive to meaningful results. An introduction of summed, per-residue-normalized scores has been essential for discovery of subdomains (EGF-like, SH2, SH3) in longer protein sequences, such as the eight "open sandwich" cytokine domains, 60-70 amino acids long and having the 3beta1alpha fold with one or two disulfide bridges, present in otherwise unrelated proteins.

Amino Acid Sequence↗
PubMed2005

Consolidating the set of known human protein-protein interactions in preparation for large-scale mapping of the human interactome.

BACKGROUND: Extensive protein interaction maps are being constructed for yeast, worm, and fly to ask how the proteins organize into pathways and systems, but no such genome-wide interaction map yet exists for the set of human proteins. To prepare for studies in humans, we wished to establish tests for the accuracy of future interaction assays and to consolidate the known interactions among human proteins. RESULTS: We established two tests of the accuracy of human protein interaction datasets and measured the relative accuracy of the available data. We then developed and applied natural language processing and literature-mining algorithms to recover from Medline abstracts 6,580 interactions among 3,737 human proteins. A three-part algorithm was used: first, human protein names were identified in Medline abstracts using a discriminator based on conditional random fields, then interactions were identified by the co-occurrence of protein names across the set of Medline abstracts, filtering the interactions with a Bayesian classifier to enrich for legitimate physical interactions. These mined interactions were combined with existing interaction data to obtain a network of 31,609 interactions among 7,748 human proteins, accurate to the same degree as the existing datasets. CONCLUSION: These interactions and the accuracy benchmarks will aid interpretation of current functional genomics data and provide a basis for determining the quality of future large-scale human protein interaction assays. Projecting from the approximately 15 interactions per protein in the best-sampled interaction set to the estimated 25,000 human genes implies more than 375,000 interactions in the complete human protein interaction network. This set therefore represents no more than 10% of the complete network.

Algorithms↗
PubMed2026

Genome-wide association studies reveal genetic variants associated with antineoplastic monoterpenoid indole alkaloid accumulation in Catharanthus roseus.

Catharanthus roseus produces pharmacologically important monoterpenoid indole alkaloids (MIAs), yet their natural accumulation is low, limiting therapeutic exploitation. To dissect the genetic basis of natural variation in MIA accumulation, we integrated phenotypic, chemotypic, and genomic analyses of 93 C. roseus accessions sampled from six locations across India, including New Delhi, Lucknow, Jodhpur, Bangalore, and two locations in Gujarat: Navsari and Bardoli. Morphological characterization showed limited differentiation among locations, whereas accessions from Gujarat tended to be taller compared to other locations and more frequently white-flowered. Quantitative HPLC profiling revealed substantial accession- and location-dependent variation in total indole alkaloid levels, with Gujarat accessions showing the highest accumulation, largely driven by vindoline and catharanthine. Genotyping-by-sequencing generated 10,801 high-quality variants comprising 10,087 SNPs and 714 InDels corresponding to an average density of 19.34 variants per Mbp of the genome, revealing three genetic subgroups with overall admixed ancestry and weak geographic stratification. Genome-wide association study (GWAS) using five benchmark models identified 47 variants potentially associated with catharanthine, vindoline, and vinblastine content. These putative candidate loci were located near genes implicated in hormone signaling, mitochondrial function, nitrogen metabolism, and RNA processing, suggesting complex regulatory control of MIA biosynthesis. Notably, two missense variants in a carboxylesterase-like gene were associated with vindoline accumulation, and highly significant intergenic SNP clusters suggested putative regulatory hotspots for vinblastine biosynthesis. These results provide GWAS-based insights into the genetic architecture of MIA metabolism in C. roseus and nominate candidate variants for precision breeding and metabolic engineering to enhance pharmaceutical alkaloid production.

Catharanthus roseus↗
PubMed2006

Close sequence comparisons are sufficient to identify human cis-regulatory elements.

Cross-species DNA sequence comparison is the primary method used to identify functional noncoding elements in human and other large genomes. However, little is known about the relative merits of evolutionarily close and distant sequence comparisons. To address this problem, we identified evolutionarily conserved noncoding regions in primate, mammalian, and more distant comparisons using a uniform approach (Gumby) that facilitates unbiased assessment of the impact of evolutionary distance on predictive power. We benchmarked computational predictions against previously identified cis-regulatory elements at diverse genomic loci and also tested numerous extremely conserved human-rodent sequences for transcriptional enhancer activity using an in vivo enhancer assay in transgenic mice. Human regulatory elements were identified with acceptable sensitivity (53%-80%) and true-positive rate (27%-67%) by comparison with one to five other eutherian mammals or six other simian primates. More distant comparisons (marsupial, avian, amphibian, and fish) failed to identify many of the empirically defined functional noncoding elements. Our results highlight the practical utility of close sequence comparisons, and the loss of sensitivity entailed by more distant comparisons. We derived an intuitive relationship between ancient and recent noncoding sequence conservation from whole-genome comparative analysis that explains most of the observations from empirical benchmarking. Lastly, we determined that, in addition to strength of conservation, genomic location and/or density of surrounding conserved elements must also be considered in selecting candidate enhancers for in vivo testing at embryonic time points.

Animals↗
PubMed2025

A telomere-to-telomere reference genome assembly of the red silk cotton tree (Bombax ceiba).

Bombax ceiba, an important ornamental tree and potential fiber resource in the textile industry, is widely distributed in tropical and subtropical regions. In this study, we assembled a nearly gap-free telomere-to-telomere (T2T) genome of B. ceiba using Illumina, PacBio High-fidelity (HiFi), ONT ultra-long, and Hi-C sequencing technologies. The genome spanned approximately 807.89 Mb, with a scaffold N50 of 16.58 Mb, and 754.68 Mb (93.41%) of genomic sequences were anchored onto 48 pseudo-chromosomes. Benchmarking Universal Single-Copy Orthologs (BUSCO) analysis revealed a completeness of 99.40%, identifying 1,378 single-copy and 213 duplicated genes out of 1,614. The genome contained 67.72% (547.11 Mb) repeat regions, with 39,708 predicted protein-coding genes. Collectively, our study provides valuable genomic data for investigating the evolutionary history of the Malvaceae family.

Genome, Plant↗
PubMed2026

Genome-resolved assessment of archaeal diversity in full-scale anaerobic digesters reveals variability in mcrA primer coverage.

AIMS: Methanogenic archaea are key players in anaerobic digestion, driving methane production in biogas reactors. This study aimed to assess the diversity of methanogenic archaea in full-scale anaerobic digesters using genome-resolved metagenomics and to systematically evaluate the taxonomic coverage of commonly used mcrA-targeted qPCR primer sets against this genomic framework. METHODS AND RESULTS: Methanogenic diversity was assessed using 113 dereplicated archaeal metagenome-assembled genomes (MAGs) recovered from 109 full-scale anaerobic digesters treating diverse substrates. Genome-resolved analyses revealed a diverse archaeal community spanning multiple phyla, dominated by Halobacteriota and Methanobacteriota, with additional representatives from Methanobacteriota_B, Thermoplasmatota, and Thermoproteota. The presence of the mcrA gene was identified in a subset 55 MAGs, which were subsequently used as the genomic framework to evaluate six commonly used mcrA qPCR primer sets in silico. This subset clustered into nine phylogenetic groups and formed the basis for the primer coverage analysis. The evaluation revealed marked differences in taxonomic coverage among primer sets. Most primers preferentially detected Methanobacteriales and Methanosarcinales, while underrepresenting or excluding other methanogenic lineages, including H₂-dependent methylotrophic Methanomassiliicoccaceae. CONCLUSIONS: Commonly used mcrA primer sets differ substantially in their ability to capture methanogenic diversity, with some showing broad representation of reactor-associated methanogens and others exhibiting strong lineage-specific biases. Genome-resolved metagenomics provides an effective framework for benchmarking primer performance and supports the selection and improvement of molecular tools for more accurate monitoring of anaerobic digestion systems.

Archaea↗
PubMed2026

An encyclopedia of human enhancer-gene regulatory interactions.

Identifying transcriptional enhancers and their target genes is essential for understanding gene regulation and the effect of human genetic variation on disease1-6. Here we create and evaluate a resource of more than 92 million enhancer-gene regulatory interactions across 1,458 biosamples covering 369 cell types and tissues, by integrating predictive models, chromatin states, three-dimensional contacts and large-scale genetic perturbations generated by the ENCODE Consortium7. We first create a systematic benchmarking pipeline to compare predictive models, assembling a dataset of 10,356 element-gene pairs measured in CRISPR perturbation experiments, more than 30,000 fine-mapped expression quantitative trait loci and 569 fine-mapped genome-wide association study (GWAS) variants linked to a probable causal gene. Using this framework, we develop ENCODE-rE2G, a predictive model achieving state-of-the-art performance across several prediction tasks, demonstrating that iterative perturbations and supervised machine learning can build increasingly accurate predictive models of enhancer regulation. Using ENCODE-rE2G, we build an encyclopedia of enhancer-gene regulatory interactions in the human genome, revealing global properties of enhancer networks, identifying differences in regulatory complexity across genes and improving analyses linking noncoding variants to target genes and cell types for common complex diseases. By interpreting the model, we find that beyond enhancer activity and three-dimensional enhancer-promoter contacts, additional features that guide enhancer-promoter communication include promoter class and enhancer-enhancer synergy. These genome-wide maps of enhancer-gene regulatory interactions, benchmarking software, predictive models and insights about enhancer function provide a valuable resource for future studies of gene regulation and human genetics.

Humans↗
PubMed2025

A high-quality chromosome-level genome assembly and annotation of the giant freshwater prawn (Macrobrachium rosenbergii).

The giant freshwater prawn, Macrobrachium rosenbergii, is native to Southeast Asia and is used in aquacultural practices worldwide. It is considered advantageous because of its rapid growth, high nutritional value, and economic benefits. As one of the three major freshwater aquaculture shrimp sources in China, a high-quality genome resource is of great significance for promoting the germplasm improvement of varieties. This study presents a high-quality chromosome-level genome assembly of M. rosenbergii that was generated by combining PacBio, MGI, and Hi-C reads. The assembled genome was 2.96 Gb in size, with a contig N50 of 0.64 Mb and a scaffold N50 of 55.76 Mb, which was positioned on 59 pseudo-chromosomes. The Benchmarking Universal Single-Copy Orthologs (BUSCO) analysis for genome assembly reached 94.37%. In total, 27,111 protein-coding genes were identified, of which 25,470 were functionally annotated. These results provide a foundation for future research into adaptive evolution, genomics, and molecular breeding in M. rosenbergii.

Animals↗