Biology subjects

Chacon-Duque, J. C.

Publications and source records attributed to Chacon-Duque, J. C..

5 recordsLinked to original sources

bioRxiv2026

MitoDate: a Nextflow pipeline for molecular clock dating and phylogenetic inference using ancient mitogenomes

SummaryAncient DNA studies are increasingly targeting samples that are beyond the limit of radiocarbon dating (>50 thousand years old) and are often difficult or impossible to date using other geochronological methods. In cases where complete mitochondrial genomes (mitogenomes) can be recovered from such samples, Bayesian molecular clock dating approaches are routinely used as an alternative method for estimating their age. However, molecular clock dating of ancient mitogenomes lacks a standardised, reproducible computational framework, and existing approaches rely heavily on graphical interfaces that limit automation and scalability. To address these gaps, we developed MitoDate, an automated Nextflow pipeline for reproducible molecular clock dating of ancient mitochondrial genomes. The workflow standardises Bayesian time-calibrated phylogenetic inference within a portable, containerised framework, reducing manual intervention and improving analytical consistency. Availability and implementationMitoDate is implemented in Nextflow and is freely available at https://github.com/CpgSthlm/MitoDate. The pipeline is distributed with containerised dependencies and detailed documentation, including example datasets and usage guidelines.

bioinformatics↗

bioRxiv2026

DNAharvester: A Nextflow Pipeline for Analysing Highly Degraded DNA from Ancient and Historical Specimens

Ancient DNA (aDNA) research has advanced rapidly with the development of high-throughput sequencing, enabling genome-wide analyses of large collections of prehistoric specimens. However, analysing palaeontological and archaeological material with highly degraded DNA constitutes a major bioinformatic challenge. DNA from such samples is characterised by short fragment lengths, low endogenous content, post-mortem damage, and cross-species contamination, which can increase spurious mapping and reference bias, affecting downstream population genetic inferences. We present DNAharvester, a modular and reproducible pipeline designed specifically for processing highly degraded DNA from ancient and historical specimens. DNAharvester integrates metagenomic filtering, competitive mapping, adaptive aligner selection (incorporating BWA-aln, BWA-mem, and Bowtie2), and systematic evaluation of reference bias and spurious mapping. By incorporating flexible mapping and filtering strategies, the pipeline can be adapted to varying sample preservation, focusing on maximising authentic data recovery. DNAharvester features subworkflows for iterative assembly of mitogenomes, identification of genomic repeats and CpG sites, taxonomic classification, microbial/pathogen screening, genetic sex determination, and variant calling. To accommodate varying sequencing depths, the pipeline supports diploid variant calling, genotype likelihood estimation, and pseudo-haploid random allele calling. Implemented in Nextflow, DNAharvester provides a highly scalable, containerised framework that enhances reproducibility, portability, and robustness in aDNA analyses. We validated the pipeline using simulated and empirical datasets, demonstrating its ability to systematically mitigate complex background contamination while preserving authentic genomic signals. By streamlining complex bioinformatic tasks through simple configuration files, DNAharvester establishes a standardised approach for analysing aDNA datasets and makes genomic analyses of ancient remains accessible to the broader research community.

bioinformatics↗

bioRxiv2025

Recovering ecological interactions by mining non-target data from whole genome re-sequencing projects

The study of parasitic species can shed light on aspects of their hosts ecology. Such interactions are however often unknown or understudied due to the difficulty to detect and/or quantify many infections. Whole-genome sequencing and re-sequencing data have been generated at an increasing rate and reduced costs over the last two decades. Projects based on whole organisms, like whole insect specimens, provide genomic material for the target taxon, but may also include sequencing reads from associated microbes and other parasites. Here, we screened for the presence of non-host reads in a collection of whole-genome (re-) sequence projects from the Glanville fritillary butterfly, Melitaea cinxia, a model organism in research on the ecology and evolution of species in spatially structured and fragmented landscapes. We identified infections with different bacteria and eukaryotic parasites, which are shared between populations and underly both previously known and new biotic interactions for this butterfly species. The bacterial symbiont Wolbachia, usually common in insects, was found at relatively low prevalence, while Spiroplasma was ubiquitous across samples from several European populations of the butterfly. Additionally, we confirmed expected rates of larval parasitism by at least two parasitoid wasps. Such results provide proof of principle that key ecological interactions can be uncovered efficiently from existing data, an important first step to characterising the role host-associated organisms play in shaping the ecology and evolutionary history of their host species.

ecology↗

bioRxiv2020

Prediction Of Eye, Hair And Skin Color In Admixed Populations Of Latin America

We report an evaluation of prediction accuracy for eye, hair and skin pigmentation based on genomic and phenotypic data for over 6,500 admixed Latin Americans (the CANDELA dataset). We examined the impact on prediction accuracy of three main factors: (i) The methods of prediction, including classical statistical methods and machine learning approaches, (ii) The inclusion of non-genetic predictors, continental genetic ancestry and pigmentation SNPs in the prediction models, and (iii) Compared two sets of pigmentation SNPs: the commonly-used HIrisPlex-S set (developed in Europeans) and novel SNP sets we defined here based on genome-wide association results in the CANDELA sample. We find that Random Forest or regression are globally the best performing methods. Although continental genetic ancestry has substantial power for prediction of pigmentation in Latin Americans, the inclusion of pigmentation SNPs increases prediction accuracy considerably, particularly for skin color. For hair and eye color, HIrisPlex-S has a similar performance to the CANDELA-specific prediction SNP sets. However, for skin pigmentation the performance of HIrisPlex-S is markedly lower than the SNP set defined here, including predictions in an independent dataset of Native American data. These results reflect the relatively high variation in hair and eye color among Europeans for whom HIrisPlex-S was developed, whereas their variation in skin pigmentation is comparatively lower. Furthermore, we show that the dataset used in the training of prediction models strongly impacts on the portability of these models across Europeans and Native Americans.

genetics↗

bioRxiv2018

Latin Americans show wide-spread Converso ancestry and the imprint of local Native ancestry on physical appearance

Historical records and genetic analyses indicate that Latin Americans trace their ancestry mainly to the admixture of Native Americans, Europeans and Sub-Saharan Africans1. Using novel haplotype-based methods here we infer the sub-populations involved in admixture for over 6,500 Latin Americans and evaluate the impact of sub-continental ancestry on the physical appearance of these individuals. We find that pre-Columbian Native genetic structure is mirrored in Latin Americans and that sources of non-Native ancestry, and admixture timings, match documented migratory flows. We also detect South/East Mediterranean ancestry across Latin America, probably stemming from the clandestine colonial migration of Christian converts of non-European origin (Conversos). Furthermore, we find that Central Andean ancestry impacts on variation of facial features in Latin Americans, particularly nose morphology, possibly relating to environmental adaptation during the evolution of Native Americans.

genetics↗