Biology subjects

Rohlfs, R.

Publications and source records attributed to Rohlfs, R..

7 recordsLinked to original sources

bioRxiv2026

A Pan-pangenome illuminates complex structural variation and selection in humans, chimpanzees, and bonobos

Complete, haplotype-resolved genome assemblies have provided unprecedented insight into the evolution of structurally complex, rapidly evolving regions of human genomes1-6; however, population-scale pangenome resources of our closest relatives, chimpanzees and bonobos (genus, Pan), are necessary to ascertain the origins and evolutionary context of these loci. Here, we sequence and assemble 58 haplotypes from four distinct Pan clades to high contiguity (median contig NG50=54 Mb), including eight near-T2T genomes. These genomes reveal previously intractable genetic variation increasing estimates of genome-wide genetic diversity 6-37% across populations compared to short-read estimates7. We identify recurrent structural polymorphisms across species impacting genes associated with immune response and host-pathogen interaction and find that structural variants (SVs) are 170- to 260-fold more likely than single nucleotide variants (SNVs) to exhibit high-impact effects across species. Contrasting SV patterns across primates we find that transposable element mutation rates differ by as much as threefold between species. We show that human disease-associated short tandem repeat (TR) loci have uniquely expanded in humans sensitizing our species to these TR-expansion disorders. Physically phased haplotypes enable reconstruction of genome-wide genealogical histories, uncovering ancient, functional genetic variation maintained by balancing selection, as well as signatures of recent adaptation in chimpanzee subspecies. Several malaria-associated loci exhibit ancient structural polymorphism, including the African great ape-specific glycophorin (GYP) gene expansion. We characterize the sequence, structure, and composition of diverse glycophorin haplotypes in humans and chimpanzees. We identify independent malaria-protective GYPA-B fusion events in humans and novel chimpanzee glycophorin genes resulting from both ancient and recent fusion events demonstrating parallel adaptations to pathogen resistance across hominins. Together, our resource highlights the critical importance of nonhuman primate population-scale pangenomics for understanding the evolution of complex genome structures and the biodiversity of our endangered closest living relatives.

evolutionary biology↗

bioRxiv2026

A Statistical Framework to Infer the Mutation Model of Tandem Repeat Variants

Tandem Repeats (TRs) have complex mutational patterns that depend on many properties of the analyzed loci. An accurate characterization of the mutation model that defines the evolution of each TR is fundamental to understand the genetic diversity patterns of each TR. Here we propose a computational method that leverages the rich information contained in the ancestral recombination graph (ARG) to estimate the mutation process that drives the evolution of one loci containing a TR variant. Our method is called TRAMA, Tandem Repeat ARG-based Mutation Analysis. TRAMA uses the genealogical history estimated at each loci, which is contained in the ARG, to estimate the parameters that define the mutation of a TR under two different mutational models: The Stepwise Mutation Model (SMM) and the Two-Phase Mutation Model (TPM). First we show that TRAMA can provide estimates of the mutation rate of a TR evolving under the SMM that are accurate or have a slight underestimation when the mutation rate is higher than 10-5. Then, we show that TRAMA can provide reasonable estimates of the parameters that define the TPM under certain conditions. We also show that TRAMA can do an accurate selection of the mutational model that better explains the genetic diversity patterns of a loci from two competing models: TPM and SMM. Then, we show that estimates of the mutation rate under the SMM are similar when using the true genealogical history compared to using a genealogical history estimated using an ARG inference program, SINGER. We also discuss potential extensions of our methodology to perform a more accurate characterization of the mutation model driving the evolution of TRs.

evolutionary biology↗

bioRxiv2026

Comparative genomics of Tandem Repeat variation in apes

Tandem repeats (TRs) are highly mutable DNA elements that influence gene regulation1, protein structure2, and disease3. Until recently, their repetitive nature has hindered accurate TR sequencing and genotyping, resulting in sparse comparative data across species. In addition, we lack population-aware approaches to analyze TR conservation, divergence, and mutational dynamics. Here, leveraging telomere-to-telomere primate genomes and long-read data from 46 humans and 23 chimpanzees, we constructed a catalog of homologous TR loci, and developed an analytical framework to jointly analyze TR variation within- and between-species. Across primates, TR diversity and conservation vary strongly with genomic context, with coding and 5 UTR TRs exhibiting reduced polymorphism and constraint across species, consistent with stabilizing selection. Yet, while TRs are depleted in coding sequence, they are enriched in 5 UTRs, suggesting functional roles that outweighs mutational risks. TR heterozygosity varies across motif lengths and is concordant with both evolutionary and trio-based mutation rate estimates4. Introducing an HKA-like approach to control for locus-specific mutation rates, we identified TRs with signatures of directional and balancing selection. These candidates are significantly enriched in genes involved in nervous system development and synaptic function, highlighting TRs as potential contributors to neural evolution. Further, TR divergence correlates with gene expression divergence, particularly for promoter-related TRs and expression in organoids related to neurodevelopment, implicating a subset of regulatory TRs as candidates for adaptive expression evolution. Finally, trait-associated TRs display longer alleles and higher diversity in humans compared to chimpanzees, consistent with lineage-specific runaway mutations and/or directional selection5. Together, our results establish a comparative framework for TR evolutionary analyses, revealing how mutational processes and selection jointly shape repeat variation, and supporting their role as both conserved functional elements and as drivers of evolutionary innovation.

evolutionary biology↗

bioRxiv2025

Ectopic, hepatic GLP-1R agonism enhances the weight loss efficacy of GLP-1 analogues.

ObjectiveUnimolecular triagonists drive substantial weight loss in patients with obesity (PwO) by engaging the glucagon-like peptide 1 (GLP-1) and glucose dependent insulinotropic polypeptide (GIP) receptors to reduce food intake (FI) and the hepatic glucagon (Gcg) receptor to enhance energy expenditure (EE). However, their development has been challenged by deleterious cardiovascular (CV) effects including increased heart rate (HR), elongated QTc, and arrhythmia mediated by GcgR agonism. GLP-1R monoagonists on the other hand improve both obesity and CV outcomes with negligible effects on EE. We sought to imbue peptide GLP-1R agonists with an EE enhancing effect by combining them with ectopic GLP-1R expression and agonism in hepatocytes. MethodsWe used an attenuated adenovirus (AAV) to induce the expression of a functional, liver-specific GLP-1R combined with traditional peptide agonist treatment to drive greater body weight loss via reduced energy intake and increased energy expenditure. ResultsAgonism of the ectopic GLP-1R with either semaglutide, a low internalization GLP-1R agonist (Sema584), or a dual GLP-1R/GIPR agonist in wild-type (WT) diet induced obese (DIO) mice led to enhanced EE and improved weight loss compared to agonist treatment alone. ConclusionsThis represents a novel mechanism for achieving polypharmacy to treat obesity. HighlightsO_LIA Glp1r encoding AAV induces expression of a functional receptor mouse livers. C_LIO_LIEndogenous GLP-1R does not mediate semaglutide clearance. C_LIO_LIEctopic GLP-1R mediates semaglutide clearance. C_LIO_LIEctopic, hepatic Glp1r plus semaglutide enhances weight loss in mice. C_LIO_LIEctopic, hepatic Glp1r plus a dual incretin agonist enhances weight loss in mice. C_LI

zoology↗

bioRxiv2024

TRACKing Tandem Repeats: a customizable pipeline for identification and cross-species comparisons

SummaryTRACK is a user-friendly command-line pipeline designed to consolidate the discovery and comparison of tandem repeats (TRs) across species. TRACK facilitates the cataloging and filtering of TRs based on reference genomes or T2T transcripts, and applies reciprocal LiftOver and sequence alignment methods to identify putative homologous TRs between species. For further streamlined analyses, TRACK can be used to genotype TRs and subsequently estimate and plot basic population genetic statistics. By integrating existing tools into one integrated workflow, TRACK enhances TR analysis accessibility and reproducibility, while offering flexibility for the user. AvailabilityThe TRACK toolkit with step-by-step tutorial is freely available at https://github.com/caroladam/track.

genomics↗

bioRxiv2024

py_ped_sim - A flexible forward genetic simulator for complex family pedigree analysis

BackgroundLarge-scale family pedigrees are commonly used across medical, evolutionary, and forensic genetics. These pedigrees are tools for identifying genetic disorders, tracking evolutionary patterns, and establishing familial relationships via forensic genetic identification. However, there is a lack of software to accurately simulate different pedigree structures along with genomes corresponding to those individuals in a family pedigree. This limits simulation-based evaluations of methods that use pedigrees. ResultsWe have developed a python command-line-based tool called py_ped_sim that facilitates the simulation of pedigree structures and the genomes of individuals in a pedigree. py_ped_sim represents pedigrees as directed acyclic graphs, enabling conversion between standard pedigree formats and integration with the forward population genetic simulator, SLiM. Notably, py_ped_sim allows the simulation of varying numbers of offspring for a set of parents, with the capacity to shift the distribution of sibship sizes over generations. We additionally add simulations for events of misattributed paternity, which offers a way to simulate half-sibling relationships. We validated the accuracy of our software by simulating genomes onto diverse family pedigree structures, showing that the estimated kinship coefficients closely approximated expected values. Conclusionspy_ped_sim is a user-friendly and open-source solution for simulating pedigree structures and conducting pedigree genome simulations. It empowers medical, forensic, and evolutionary genetics researchers to gain deeper insights into the dynamics of genetic inheritance and relatedness within families.

bioinformatics↗

bioRxiv2023

Decreased accuracy of forensic DNA mixture analysis for groups with lower genetic diversity

Forensic investigation of DNA samples from multiple contributors has become commonplace. These complex analyses use statistical frameworks accounting for multiple levels of uncertainty in allelic contributions from different individuals, particularly for samples containing few molecules of DNA. These methods have been thoroughly tested along some axes of variation, but less attention has been paid to accuracy across human genetic variation. Here, we quantify the accuracy of DNA mixture analysis over 244 human groups. We find higher false inclusion rates for mixtures with more contributors, and for groups with lower genetic diversity. Even for two-contributor mixtures where one contributor is known and the reference group is correctly specified, false inclusion rates are 1e-5 or higher for 56 out of 244 groups. This means that, depending on multiple testing, some false inclusions may be expected. These false positives could be lessened with more selective and conservative use of DNA mixture analysis. HIGHLIGHTSO_LIGroups with lower genetic diversity have higher mixture analysis false positive rates. C_LIO_LIAnalyses with mis-specified references have somewhat higher false positive rates. C_LIO_LIMixture analysis accuracy decreases with more mixture contributors. C_LI GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=198 HEIGHT=200 SRC="FIGDIR/small/554311v2_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@157c28aorg.highwire.dtl.DTLVardef@a4ff05org.highwire.dtl.DTLVardef@62caa0org.highwire.dtl.DTLVardef@1e4ce92_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗