Biology subjects

Colonna, V.

Publications and source records attributed to Colonna, V..

17 recordsLinked to original sources

bioRxiv2025

Scalable PBWT Queries with Minimum-Length SMEMConstraints

Detecting long shared ancestry tracts in large haplotype panels is central to IBD analysis, imputation, and local ancestry inference, and can be approximated computationally by finding Set-Maximal Exact Matches (SMEMs) between sequences. The Positional Burrows-Wheeler Transform (PBWT) provides an efficient index for these panels, yet current methods often enumerate all SMEMs, producing a large number of short, uninformative matches. We introduce Positional Boyer- Moore-Li (PBML), which restricts enumeration to SMEMs occurring in at least k haplotypes and spanning at least L sites (kL-SMEMs). PBML is the first algorithm for computing KL-SMEMs on top of a single compressed run-length encoded PBWT index reusable for any (k, L) without rebuilding. On the 1000 Genomes Project, PBML achieves 4.6x faster query time than {micro}-PBWT and 2.4x over Durbins PBWT with lower memory, scaling to 15.9x over {micro}-PBWT at 16 threads. On a 10,000-haplotype panel from the Tennessee BIG Initiative, a diverse admixed cohort, PBML outperforms {micro}-PBWT by up to 4.7x in k-SMEM finding. By applying both thresholds during traversal, PBML extracts biologically informative, population-shared segments while filtering millions of short matches, a capability not available in current tools. On the BIG panel, in about 10 seconds PBML finds 2,441 long tracts at (k = 50, L = 5000) shared by an average of 60 haplotypes against 1000 queries, significantly reducing the 4.8 million unfiltered SMEMs shared on average by 2 haplotypes. These results establish PBML as a scalable tool for targeted long-range shared ancestry detection in large, diverse panels.

bioinformatics↗

bioRxiv2025

Identity-by-descent captures Shared Environmental Factors at Biobank Scale

Genealogical ties leave traces beyond shared genetic material: relatives tend to share environmental exposures and cultural practices that persist across generations. Using genomic and electronic health record data from 13,143 individuals in the Biorepository for Integrative Genomics, we applied a hierarchical community detection algorithm to group individuals into four major communities and 17 subcommunities based on the proportion of their genome shared identical by descent (IBD). This approach captured a fine-scale demographic structure beyond traditional ancestry classifications. By integrating neighborhood-level geographic data with census-derived environmental metrics, we revealed unequal exposure to environmental stressors between subcommunities, which correlated with differential rates of health conditions, including elevated respiratory condition prevalence in subcommunities under greater pollution burden. Through an interventional mediation analysis we found that excess risk at the subcommunity-level substantially exceeded what measured environmental factors alone could explain. thus showing the contribution of unmeasured shared exposures that IBD-based grouping captures. Subcommunity-level disparities persisted in sensitivity analyses adjusting for self-reported race, indicating that IBD-based clustering captures health-relevant information beyond demographic categories commonly used as proxies for social determinants of health. We implemented an open-source dashboard for interactive exploration of IBD-defined communities, disease prevalence, and environmental exposures. Together, we demonstrate that IBD-based clustering jointly captures genetic and environmental determinants of health, offering a scalable framework for precision health and population genetics that translates biobank data into actionable insights.

genomics↗

bioRxiv2024

Creating a biomedical knowledge base by addressing GPT inaccurate responses and benchmarking context

We created GNQA, a generative pre-trained transformer (GPT) knowledge base driven by a performant retrieval augmented generation (RAG) with a focus on aging, dementia, Alzheimers and diabetes. We uploaded a corpus of three thousand peer reviewed publications on these topics into the RAG. To address concerns about inaccurate responses and GPT hallucinations, we implemented a context provenance tracking mechanism that enables researchers to validate responses against the original material and to get references to the original papers. To assess the effectiveness of contextual information we collected evaluations and feedback from both domain expert users and citizen scientists on the relevance of GPT responses. A key innovation of our study is automated evaluation by way of a RAG assessment system (RAGAS). RAGAS combines human expert assessment with AI-driven evaluation to measure the effectiveness of RAG systems. When evaluating the responses to their questions, human respondents give a "thumbs-up" 76% of the time. Meanwhile, RAGAS scores 90% on answer relevance on questions posed by experts. And when GPT-generates questions, RAGAS scores 74% on answer relevance. With RAGAS we created a benchmark that can be used to continuously assess the performance of our knowledge base. Full GNQA functionality is embedded in the free GeneNetwork.org web service, an open-source system containing over 25 years of experimental data on model organisms and human. The code developed for this study is published under a free and open-source software license at https://git.genenetwork.org/gn-ai/tree/README.md.

scientific communication and education↗

bioRxiv2024

Pangenome reconstruction in rats enhances genotype-phenotype mapping and novel variant discovery

The HXB/BXH family of recombinant inbred rat strains is a unique genetic resource that has been extensively phenotyped over 25 years, resulting in a vast dataset of quantitative molecular and physiological phenotypes. We built a pangenome graph from 10x Genomics Linked-Read data for 31 recombinant inbred rats to study genetic variation and association mapping. The pangenome includes 0.2Gb of sequence that is not present the reference mRatBN7.2, confirming the capture of substantial additional variation. We validated variants in challenging regions, including complex structural variants resolving into multiple haplotypes. Phenome-wide association analysis of validated SNPs uncovered variants associated with glucose/insulin levels and hippocampal gene expression. We propose an interaction between Pirl1l1, chromogranin expression, TNF- levels, and insulin regulation. This study demonstrates the utility of linked-read pangenomes for comprehensive variant detection and mapping phenotypic diversity in a widely used rat genetic reference panel.

genomics↗

bioRxiv2023

A revamped rat reference genome improves the discovery of genetic diversity in laboratory rats

The seventh iteration of the reference genome assembly for Rattus norvegicus-- mRatBN7.2--corrects numerous misplaced segments and reduces base-level errors by approximately 9-fold and increases contiguity by 290-fold compared to its predecessor. Gene annotations are now more complete, significantly improving the mapping precision of genomic, transcriptomic, and proteomics data sets. We jointly analyzed 163 short-read whole genome sequencing datasets representing 120 laboratory rat strains and substrains using mRatBN7.2. We defined [~]20.0 million sequence variations, of which 18.7 thousand are predicted to potentially impact the function of 6,677 genes. We also generated a new rat genetic map from 1,893 heterogeneous stock rats and annotated transcription start sites and alternative polyadenylation sites. The mRatBN7.2 assembly, along with the extensive analysis of genomic variations among rat strains, enhances our understanding of the rat genome, providing researchers with an expanded resource for studies involving rats.

genomics↗

bioRxiv2023

Building pangenome graphs

Pangenome graphs can represent all variation between multiple reference genomes, but current approaches to build them exclude complex sequences or are based upon a single reference. In response, we developed the PanGenome Graph Builder (PGGB), a pipeline for constructing pangenome graphs without bias or exclusion. PGGB uses all-to-all alignments to build a variation graph in which we can identify variation, measure conservation, detect recombination events, and infer phylogenetic relationships.

bioinformatics↗

bioRxiv2022

Recombination between heterologous human acrocentric chromosomes

The short arms of the human acrocentric chromosomes 13, 14, 15, 21, and 22 share large homologous regions, including the ribosomal DNA repeats and extended segmental duplications (Floutsakou et al. 2013; van Sluis et al. 2019). While the complete assembly of these regions in the Telomere-to-Telomere consortiums CHM13 provided a model of their homology (Nurk et al. 2022), it remained unclear if these patterns were ancestral or maintained by ongoing recombination exchange. Here, we show that acrocentric chromosomes contain pseudo-homologous regions (PHRs) indicative of recombination between non-homologs. Considering an all-to-all comparison of the high-quality human pangenome from the Human Pangenome Reference Consortium (HPRC) (Liao et al. 2022), we find that contigs from all of the acrocentric short arms form a community similar to those formed by single chromosomes or the sex chromosome pair. A variation graph (Garrison et al. 2018) constructed from centromere-spanning acrocentric contigs indicates the presence of regions where most contigs appear nearly identical between heterologous CHM13 acrocentrics. Except on chromosome 15, we observe faster decay of linkage disequilibrium in the PHRs than in the corresponding short and long arms, indicating higher rates of recombination (N. Li and Stephens 2003; Huttley et al. 1999). The PHRs include sequences previously shown to lie at the breakpoint of Robertsonian translocations (Jarmuz-Szymczak et al. 2014), and we show that their arrangement is compatible with crossover in inverted duplications on chromosomes 13, 14, and 21. The ubiquity of signals of recombination between heterologous chromosomes seen in the HPRC draft pangenomes acrocentric assemblies suggests that these shared sequences form the basis for recurrent Robertsonian translocations, providing sequence and population-based confirmation of hypotheses first developed cytogenetically fifty years ago (Hamerton et al. 1975).

genomics↗

bioRxiv2022

A Draft Human Pangenome Reference

The Human Pangenome Reference Consortium (HPRC) presents a first draft human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individuals. These assemblies cover more than 99% of the expected sequence and are more than 99% accurate at the structural and base-pair levels. Based on alignments of the assemblies, we generated a draft pangenome that captures known variants and haplotypes, reveals novel alleles at structurally complex loci, and adds 119 million base pairs of euchromatic polymorphic sequence and 1,529 gene duplications relative to the existing reference, GRCh38. Roughly 90 million of the additional base pairs derive from structural variation. Using our draft pangenome to analyze short-read data reduces errors when discovering small variants by 34% and boosts the detected structural variants per haplotype by 104% compared to GRCh38-based workflows, and by 34% compared to using previous diversity sets of genome assemblies.

genomics↗

bioRxiv2022

Private and sub-family specific mutations of founder haplotypes in the BXD family reveal phenotypic consequences relevant to health and disease

The BXD family of recombinant inbred mice were developed by crossing and inbreeding progeny of C57BL/6J and DBA/2J strains. This family is the largest and most extensively phenotyped mammalian experimental genetic resource. Although used in genetics for 52 years, we do not yet have comprehensive data on DNA variants segregating in the BXDs. Using linked-read whole-genome sequencing, we sequenced 152 members of the family at about 40X coverage and quantified most variants. We identified 6.25 million polymorphism segregating at a near-optimal minor allele frequency of 0.42. We also defined two other major variants: strain-specific de novo singleton mutations and epoch-specific de novo polymorphism shared among subfamilies of BXDs. We quantified per-generation mutation rates of de novo variants and demonstrate how founder-derived, strain-specific, and epoch-specific variants can be analyzed jointly to model genome-phenome causality. This integration enables forward and reverse genetics at scale, rapid production of any of more than 10,000 diallel F1 hybrid progeny to test predictions across diverse environments or treatments. Combined with five decades of phenome data, the BXD family and F1 hybrids are a major resource for systems genetics and experimental precision medicine.

genomics↗

bioRxiv2022

LAMC2 marks a tumor-initiating cell population with an aggressive signature in pancreatic cancer

Tumor-initiating cells (TIC), also known as cancer stem cells, are considered a specific subpopulation of cells necessary for cancer initiation and metastasis. Here, we report a LAMC2-positive cell population, which is endowed with enhanced self-renewal capacity, and is sufficient for tumor initiation, differentiation, and driving metastasis. Mechanistically, mRNA profiling of these cells indicate a prominent squamous signature, and differentially activated pathways critical for tumor growth and metastasis, including deregulation of the TGF-{beta} signaling pathway. Treatment with Vactosertib, a new small molecule inhibitor of transforming growth factor-{beta} (TGF-{beta}) type I receptor (activin receptor-like kinase-5, ALK5), completely abrogated the lung metastasis, primarily originating from LAMC2 expressing cells. Our results prompt further study of this TIC population in pancreatic cancer and exploration as a potential therapeutic target and/or biomarker.

cancer biology↗

bioRxiv2022

A novel quantitative trait locus implicates Msh3 in the propensity for genome-wide short tandem repeat expansions in mice

Short tandem repeats (STRs) are a class of rapidly mutating genetic elements characterized by repeated units of 1 or more nucleotides. We leveraged whole genome sequencing data for 152 recombinant inbred (RI) strains from the BXD family derived from C57BL/6J and DBA/2J mice to study the effects of genetic background on genome-wide patterns of new mutations at STRs. We defined quantitative phenotypes describing the numbers and types of germline STR mutations in each strain and identified a locus on chromosome 13 associated with the propensity of STRs to expand. Several dozen genes lie in the QTL region, including Msh3, a known modifier of STR stability at pathogenic repeat expansions in mice and humans. Detailed analysis of the locus revealed a cluster of variants near the 5 end of Msh3, including multiple protein-coding variants within the DNA mismatch recognition domain of MSH3, and a retrotransposon insertion overlapping an annotated exon. Additionally, gene expression analysis demonstrates co-localization of this QTL with expression QTLs for multiple nearby genes, including Msh3. Our results suggest a novel role for Msh3 in regulating genome-wide patterns of germline STR mutations and demonstrate that inherited genetic variation can contribute to variability in accumulation of new mutations across individuals.

genomics↗

bioRxiv2021

SVJAM: Joint Analysis of Structural Variants Using Linked Read Sequencing Data

Linked-read whole genome sequencing methods, such as the 10x Chromium, attach a unique molecular barcode to each high molecular weight DNA molecule. The samples are then sequenced using short-read technology. During analysis, sequence reads sharing the same barcode are aligned to adjacent genomic locations. The pattern of barcode sharing between genomic regions allows the discovery of large structural variants (SVs) in the range of 1 Kb to a few Mb. Most SV calling methods for these data, such as LongRanger, analyze one sample at a time and often produces inconsistent results for the same genomic location across multiple samples. We developed a method, SVJAM, for joint calling of SVs, using data from 152 members of the BXD family of recombinant inbred strains of mice. Our method first collects candidate SV regions from single sample analysis, such as those produced by LongRanger. We then retrieve barcode overlapping data from all samples for each region. These data are organized as a high dimensional matrix. The dimension of this matrix is then reduced using principal component analysis. Samples projected onto a two dimensional space formed by the first two principal components forms two or three clusters based on their genotype, representing the reference, alternative, or heterozygotic alleles. We developed a novel distance measure for hierarchical clustering and rotating the axes to find the optimal clustering results. We also developed an algorithm to decide whether the pattern of sample distribution is best fitted with one, two, or three genotypes. For each sample, we calculate its membership score for each genotype. We compared results produced by SVJAM with LongRanger and few methods that rely on PacBio or Oxford Nanopore data. In a comparison of SVJAM with SV detected using long-read sequencing data for the DBA/2J strain, we found that our results recovered many SVs missed by LongRanger. We also found many SVs called by LongRanger were assigned with an incorrect SV type. Our algorithm also consistently identified heterozygotic regions.

genomics↗

bioRxiv2020

Succinct dynamic variation graphs

MotivationPangenomics is a growing field within computational genomics. Many pangenomic analyses use bidirected sequence graphs as their core data model. However, implementing and correctly using this data model can be difficult, and the scale of pangenomic data sets can be challenging to work at. These challenges have impeded progress in this field. ResultsHere we present a stack of two C++ libraries, libbdsg and libhandlegraph, which use a simple, field-proven interface, designed to expose elementary features of these graphs while preventing common graph manipulation mistakes. The libraries also provide a Python binding. Using a diverse collection of pangenome graphs, we demonstrate that these tools allow for efficient construction and manipulation of large genome graphs with dense variation. For instance, the speed and memory usage is up to an order of magnitude better than the prior graph implementation in the vg toolkit, which has now transitioned to using libbdsgs implementations. Availabilitylibhandlegraph and libbdsg are available under an MIT License from https://github.com/vgteam/libhandlegraph and https://github.com/vgteam/libbdsg. Contacterik.garrison@ucsc.edu

bioinformatics↗

bioRxiv2019

Inter-individual genomic heterogeneity within European population isolates

A number of studies carried out since the early 70s has investigated the effects of isolation on genetic variation within and among human populations in diverse geographical contexts. However, no extensive analysis has been carried out on the heterogeneity among genomes within isolated populations. This issue is worth exploring since events of recent admixture and/or subdivision could potentially disrupt the genetic homogeneity which is to be expected when isolation is prolonged and constant over time. Here, we analyze literature data relative to 87,818 autosomal single-nucleotide polymorphisms, which were obtained from a total of 28 European populations. Our results challenge the traditional paradigm of population isolates as genetically (and genomically) uniform entities. In fact, focusing on the distribution of variance of intra-population diversity measures across individuals, we show that the inter-individual heterogeneity of isolated populations is at least comparable to the open ones. More in particular, three small and highly inbred isolates (Sappada, Sauris and Timau in Northeastern Italy) were found to be characterized by levels of this parameter largely exceeding that of all other populations, possibly due to relatively recent events of genetic introgression. Finally, we propose a way to monitor the effects of inter-individual heterogeneity in disease-gene association studies.

genomics↗

bioRxiv2019

Genomics and transcriptomics to unravel sex determination pathway and its evolution in sand flies

BackgroundPhlebotomine sand flies (Diptera, Nematocera) are important vectors of several pathogens, including Leishmania parasites, causing serious diseases of humans and dogs. Despite their importance as disease vectors, most aspects of sand fly biology remain unknown including the molecular bases of their reproduction and sex determination, aspects also relevant for the development of novel vector control strategies.\n\nResultsUsing a comparative genomics/transcriptomics approach, we identified the sex determining genes in phlebotomine sand flies and proposed the first model for the sex determination cascade of these insects. For all the genes identified, we produced manually curated gene models, developmental gene expression profile and performed evolutionary molecular analysis. We identified and characterized, for the first time in a Nematocera species, the transformer (tra) homolog which exhibits both conserved and novel features. The analysis of the tra locus in sand flies and its expression pattern suggest that this gene is able to autoregulate its own splicing, as observed in the fruit fly Ceratitis capitata and several other insect species.\n\nConclusionsOur results permit to fill the gap about sex determination in sand flies, contribute to a better understanding of this developmental pathway in Nematocera and open the way for the identification of sex determining orthologs in other species of this important Diptera sub-order. Furthermore, the sex determination genes identified in our work also provide the opportunity of future biotech applications to control natural population of sand flies, reducing their impact on public health.

genomics↗

bioRxiv2018

Genomic diversity and novel genome-wide association with fruit morphology in Capsicum, from 746k polymorphic sites.

BackgroundCapsicum is one of the major vegetable crops grown world-wide. Current subdivision in clades and species is based on morphological traits and coarse sets of genetic markers. Fruits broad variability has been driven by breeding programs and has been mainly studied by linkage analysis.\n\nResultsWe discovered 746k variable sites by sequencing 1.8% of the genome in a collection of 373 accessions belonging to 11 Capsicum species from 51 countries. We describe genomic variation at population-level, confirm major subdivision in clades and species, and show that the known subdivision of C. annuum in two groups separates large and bulky fruits form small ones. In C. annuum, we identify four novel loci associated with phenotypes determining the fruit shape, including a non-synonymous mutation in the gene Longifolia 1-like (CA03g16080).\n\nConclusionsOur collection covers all the economically important species of Capsicum widely used in breeding programs, and represent the widest and largest study so far in terms of the number of species and genetic variants analyzed. We identified a large set of markers that can be used for population genetic studies and genetic association analyses. Our results foster fine genetic association studies and foresee genomic variability at population-level.

genetics↗

bioRxiv2018

Positive selection in Europeans and East-Asians at the ABCA12 gene

Natural selection acts on genetic variants by increasing the frequency of alleles responsible for a cellular function that is favorable in a certain environment. In a previous genome-wide scan for positive selection in contemporary humans, we identified a signal of positive selection in European and Asians at the genetic variant rs10180970. The variant is located in the second intron of the ABCA12 gene, which is implicated in the lipid barrier formation and down-regulated by UVB radiation. We studied the signal of selection in the genomic region surrounding rs10180970 in a larger dataset that includes DNA sequences from ancient samples. We also investigated the functional consequences of gene expression of the alleles of rs10180970 and another genetic variant in its proximity in healthy volunteers exposed to similar UV radiation.\n\nWe confirmed the selection signal and refine its location that extends over 35 kb and includes the first intron, the first two exons and the transcription starting site of ABCA12. We found no obvious effect of rs10180970 alleles on ABCA12 gene expression. We reconstructed the trajectory of the T allele over the last 80,000 years to discover that it was specific to H. sapiens and frequent among non-Africans already 45,000 years ago.

genomics↗