Biology subjects

Aguilar-Ordonez, I.

Publications and source records attributed to Aguilar-Ordonez, I..

5 recordsLinked to original sources

bioRxiv2025

Ancestry, admixture, and pathogens in contemporaneous Neolithic farmers and foragers on the Island of Gotland

Two archaeological cultural complexes coexisted on Gotland for over 500 years, between [~]3300 and 2800 calBCE, i.e. the Neolithic Funnelbeaker culture (FBC), and the Pitted ware culture (PWC). The ancestry of the FBC farmers and PWC marine foragers largely aligns with European Neolithic Farmers and European Mesolithic foragers, respectively, but the direct interactions between the groups on Gotland is not understood. We present a Middle Neolithic (MN) high-coverage genome and a Late Neolithic (LN) low-coverage genome from the Ansarve FBC dolmen. We investigate ancestry, admixture, and pathogens among these MN farmers (n =6), foragers (n=19), and a LN individual. We find that recent gene-flow between farmers and foragers could have taken place, although most gene-flow happened prior to their coexistence on the island. We also find evidence of different Yersinia pestis strains in the three cultural groups, showing that the pestis was widespread among groups with different subsistence strategies.

genomics↗

bioRxiv2024

Whole genome sequencing of 76 Mexican Indigenous reveals recent selection signatures linked to pathogens and diet adaptation.

Whole genome scans for natural selection signatures across Mexican Indigenous (MI) Populations remain underrepresented in the literature. Here, we conducted the first comparative analysis of genetic adaptation in MI populations using whole genome sequencing (WGS) data from 76 individuals representing 27 different ethnic groups in Mexico. We divided the cohort into Northern, Central, and Southern populations and identified signals of natural selection within and across populations. We find evidence of adaptation to pathogenic environments in all our populations, including significant signatures in the Duffy blood group gene in Central MI populations. Despite each region exhibiting unique local adaptation profiles, selection signatures on ARHGAP15, VGLL4, LINGO2, SYNDIG1, and TFAP2B were common to all populations. Our results also suggest that selection signatures falling within enhancers or promoters are usually connected to non-coding features, with notable exceptions like ARHGAP15 and GTDC1. This paper provides new evidence on the selection landscape of Mexican Indigenous Populations and lays the foundation for additional work on Mexican phenotypic characterization. Significance statementPrevious research has identified distinct patterns of genomic adaptation across the different regions of Mexico, highlighting evidence of natural selection within metabolic and immune-related genes. However, the characterization of the Mexican selection landscape from a whole-genome perspective remains unexplored. Here, we conducted the first whole-genome scan for natural selection in 76 Mexican Indigenous individuals from 27 different ethnic groups divided into Northern, Central, and Southern populations. Our findings revealed distinct local adaptation profiles for each Mexican region, with different evidence of adaptation to pathogenic environments across these groups. In contrast, all populations had common selection signatures on ARHGAP15, VGLL4, LINGO2, SYNDIG1, and TFAP2B. This paper provides new evidence on the genetic basis of adaptation of Indigenous groups in Mexico. Moreover, it provides a foundation for additional work on Mexican phenotypic characterization.

evolutionary biology↗

bioRxiv2022

Reorganization of F-actin nanostructures is required for the late phases of SARS-CoV-2 replication in pulmonary cells.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is worldwide the main cause of the COVID-19 pandemic. After infection of human pulmonary cells, intracellular viral replication take place in different cellular compartments resulting in the destruction of the host cells and causing severe respiratory diseases. Although cellular trafficking of SARS-CoV-2 have been explored, little is known about the role of the cytoskeleton during viral replication in pulmonary cells. Here we show that SARS-CoV-2 infection induces dramatic changes of F-actin nanostructures overtime. Ring-like actin nanostructures are surrounding viral intracellular organelles, suggesting a functional interplay between F-actin and viral M clusters during particle assembly. Filopodia-like structures loaded with viruses to neighbour cells suggest these structures as mechanism for cell-to-cell virus transmission. Strikingly, gene expression profile analysis and PKN inhibitor treatments of infected pulmonary cells reveal a major role of alpha-actinins superfamily proteins in SARS-CoV-2 replication. Overall, our results highlight cell actors required for SARS-CoV2 replication that are promises for antiviral targets. TeaserImpairing regulation of actin filaments inhibits SARS-CoV-2 particle production in human pulmonary cells.

microbiology↗

bioRxiv2020

SPEAQeasy: a Scalable Pipeline for Expression Analysis and Quantification for R/Bioconductor-powered RNA-seq analyses

RNA sequencing (RNA-seq) is a common and widespread biological assay, and an increasing amount of data is generated with it. In practice, there are a large number of individual steps a researcher must perform before raw RNA-seq reads yield directly valuable information, such as differential gene expression data. Existing software tools are typically specialized, only performing one step-- such as alignment of reads to a reference genome-- of a larger workflow. The demand for a more comprehensive and reproducible workflow has led to the production of a number of publicly available RNA-seq pipelines. However, we have found that most require computational expertise to set up or share among several users, are not actively maintained, or lack features we have found to be important in our own analyses. In response to these concerns, we have developed a Scalable Pipeline for Expression Analysis and Quantification (SPEAQeasy), which is easy to install and share, and provides a bridge towards R/Bioconductor downstream analysis solutions. SPEAQeasy is user-friendly and lowers the computational-domain entry barrier for biologists and clinicians to RNA-seq data processing as the main input file is a table with sample names and their corresponding FASTQ files. SPEAQeasy is portable across computational frameworks (SGE, SLURM, local, docker integration) and different configuration files are provided.

bioinformatics↗

bioRxiv2018

ExtendAlign: a computational algorithm for delivering multiple global alignment results originated from local alignments.

In this work, we evaluated several tools used for the alignment of short sequences and found that most aligners execute reasonably well for identical sequences, whereas a variety of alignment errors emerge for dissimilar ones. Since alignments are essential in computational biology, we developed ExtendAlign, a post-analysis tool that corrects these errors and improves the alignment of dissimilar short sequences. We used simulated and biological data to show that ExtendAlign outperforms the other aligners in most metrics tested. ExtendAlign is useful for pinpointing the identity percentage for alignments of short sequences in the range of [~]35-50% similarity.

bioinformatics↗