Biology subjects

Bitarello, B. D.

Publications and source records attributed to Bitarello, B. D..

7 recordsLinked to original sources

bioRxiv2026

Host Cellular Remodeling, Not Viral Transcriptional Inhibition, Drives Quorum Sensing Signal-Mediated Evasion of Viral Lysis in Gephyrocapsa huxleyi

Bacterial infochemicals can profoundly alter phytoplankton physiology, yet how these compounds influence viral infection outcomes remains poorly understood. The bacterial quorum sensing molecule 2-heptyl-4-quinolone (HHQ) enables the globally abundant coccolithophore, Gephyrocapsa huxleyi, to evade virus-induced mortality following infection by Emiliania huxleyi virus (EhV). HHQ reduced infectious virus production at 24 hours despite largely intact viral gene transcription, as revealed by RNA sequencing of host and viral responses during EhV-201 infection. Host transcriptomics instead revealed rapid and progressive HHQ-dependent physiological remodeling evidenced by changes in protein encoding genes associated with vesicular trafficking, and cytoskeletal organization. Transcriptional responses further implicated endolysosomal sorting, membrane remodeling, and protein modification as potential barriers to productive infection. These findings indicate that HHQ-mediated evasion of virus-induced mortality occurs downstream of viral entry and transcription, through remodeling of host processes required for virion assembly, maturation, trafficking, and release.

microbiology↗

bioRxiv2026

A hierarchical Bayesian framework accommodates intraspecific and interspecific variation in multivariate traits

Phylogenetic comparative methods are a critical tool in biology, providing the framework to test evolutionary hypotheses of phenotypic diversification. Accommodating intraspecific variation in multivariate analyses is critical for accurate evolutionary inference, but current methods that incorporate intraspecific variation either 1) assume that traits evolve independently or 2) that all taxa share the same intraspecific covariance structure. Violations of these assumptions can produce biased estimates of evolutionary parameters. Here, we introduce a hierarchical Bayesian framework for multivariate traits that jointly estimates taxon-specific intraspecific covariance structures alongside the underlying evolutionary process. This framework propagates uncertainty from sample size discrepancies and missing data, enabling the incorporation of highly variable morphological traits into phylogenetic analyses. Analysis of simulated data confirms that the model and implementation are well calibrated under the assumed generative model, including challenging datasets with more traits than individuals and substantial missing observations. Applied to perikymata spacing across the great ape clade, including modern humans and Neandertals, the framework recovers intraspecific covariance structures that differ among taxa and yields evolutionary rate estimates markedly more uniform across the tooth crown than those obtained when taxon means are fixed. Our method, which is applicable to other multivariate traits, provide a flexible, tractable approach to joint estimation of intraspecific variation and evolutionary process in multivariate traits.

evolutionary biology↗

bioRxiv2025

Principal Components Analysis fails to recover phylogenetic structure in hominins

ObjectivesPaleoanthropologists often utilize geometric morphometrics and principal components analysis (PCA) to interpret shape variation within the hominin fossil record. It is common practice to interpret proximity in principal components (PC) space among taxa as indicative of not just morphological, but also phylogenetic affinity. This interpretation, however, has not been directly evaluated for hominins. Materials and MethodsFirst, we inferred the posterior distribution of hominin phylogenetic trees and subsampled trees from this distribution. On these phylogenies, we simulated 2D and 3D geometric morphometric datasets and traditional morphological datasets, containing traits analogous to measurements of size or length, with varying numbers of landmarks or traits and evolutionary rates. On each dataset, we conducted a PCA and used neighbor-joining to infer evolutionary relationships from the PC scores of each taxon. We measure the difference between the PCA tree and sampled tree with subtree pruning and regrafting distance and Robinson-Foulds distance. ResultsPCA trees inferred from traditional morphometric data were identical to the sampled tree in 0.11% of datasets when we only considered PC axes 1 and 2, and in 2.9% of datasets when we considered all axes. No PCA tree inferred from any of the 2,400,000 shape datasets was identical to the sampled tree, regardless of the number of axes. DiscussionPhylogenetic interpretations of the hominin fossil record based on proximity in PC space are inherently flawed and likely to be erroneous. Arguments in the hominin systematics literature based on PCA should therefore be reevaluated using phylogenetically-informed alternatives.

evolutionary biology↗

bioRxiv2024

The effects of trait redundancy and information content on hominin phylogenetic inference

Paleoanthropological phylogenetic inference is based on characters assumed to be phylogenetically informative and independent. Yet, our understanding of whether these criteria are met in published character supermatrices is limited. We assess the phylogenetic information content (PHIC) of 107 discrete craniodental traits from a widely-used hominin character matrix. We compare test topologies -- inferred by permuting single traits or removing single traits, anatomical units (AUs), and operational taxonomic units -- to the baseline topology, inferred from the unmodified matrix. In this dataset, only 31 traits have some degree of PHIC: 23 uniquely informative traits -- sufficient, as a set, to closely approach the baseline topology -- and eight redundant traits. No single AU, nor the combination of mandibular and dentition AUs, contains sufficient PHIC to approach the baseline topology, and only the maxilla contains more PHIC than expected. Therefore, phylogenetic placements of fossil hominins represented by isolated AUs should be regarded as putative until better-preserved specimens and more informative traits can be incorporated. Given the ubiquity of discrete morphological data in paleontology and that most of the history of life on Earth was only recorded through fossils, our methods should be broadly applicable to phylogenetic inference involving other paleontological clades.

evolutionary biology↗

bioRxiv2021

Predicting skeletal stature using ancient DNA

ObjectivesAncient DNA provides an opportunity to separate the genetic and environmental bases of complex traits by allowing direct estimation of genetic values in ancient individuals. Here, we test whether genetic scores for height in ancient individuals are predictive of their actual height, as inferred from skeletal remains. We estimate the contributions of genetic and environmental variables to observed phenotypic variation as a first step towards quantifying individual sources of morphological variation. Materials and MethodsWe collected stature estimates and femur lengths from West Eurasian skeletal remains with published genome-wide ancient DNA data (n=167, dating from 33,000-850 BP). We also recorded genetic sex, genetic ancestry, date and paleoclimate data for each individual, and{delta} 13C and{delta} 15N stable isotope values where available (n=67). ResultsA polygenic score (PRS) for height predicts 6.8% of the variance in femur length in our data (n=117, SD=0.0068%, p<0.001), controlling for sex, ancestry, and date. This is consistent with the predictive power of height PRS in present-day populations and the low coverage of ancient samples. Comparatively, sex explains about 15% of the variance in femur length in our sample. Environmental effects also likely play a role in variation, independent of genetics, though with considerable uncertainty (longitude: R2=0.0317, SD=0.009, p=0.019). DiscussionPolygenic scores explain a small but significant proportion of the variance in height in ancient individuals, though not enough to make useful predictions of individual phenotypes. However, environmental variables also contribute to phenotypic outcomes and understanding their interaction with direct genetic predictions will provide a framework with which to model how plasticity and genetic changes ultimately combine to drive adaptation and evolution.

evolutionary biology↗

bioRxiv2020

Polygenic scores for height in admixed populations

Polygenic risk scores (PRS) use the results of genome-wide association studies (GWAS) to predict quantitative phenotypes or disease risk at an individual level. This provides a potential route to the use of genetic data in personalized medical care. However, a major barrier to the use of PRS is that the majority of GWAS come from cohorts of European ancestry. The predictive power of PRS constructed from these studies is substantially lower in non-European ancestry cohorts, although the reasons for this are unclear. To address this question, we investigate the performance of PRS for height in cohorts with admixed African and European ancestry, allowing us to evaluate ancestry-related differences in PRS predictive accuracy while controlling for environment and cohort differences. We first show that that the predictive accuracy of height PRS increases linearly with European ancestry and is largely explained by European ancestry segments of the admixed genomes. We show that differences in allele frequencies, recombination rate, and marginal effect sizes across ancestries all contribute to the decrease in predictive power, but none of these effects explain the decrease on its own. Finally, we demonstrate that prediction for admixed individuals can be improved by using a linear combination of PRS that includes ancestry-specific effect sizes, although this approach is at present limited by the small size of non-European ancestry discovery cohorts.

genomics↗

bioRxiv2017

Signatures of long-term balancing selection in human genomes

Balancing selection maintains advantageous diversity in populations through various mechanisms. While extensively explored from a theoretical perspective, an empirical understanding of its prevalence and targets lags behind our knowledge of positive selection. Here we describe the Non-Central Deviation (NCD), a simple yet powerful statistic to detect long-term balancing selection (LTBS) that quantifies how close frequencies are to expectations under LTBS, and provides the basis for a neutrality test. NCD can be applied to a single locus or genomic data, and can be implemented considering only polymorphisms (NCD1) or also considering fixed differences with respect to an outgroup (NCD2) species. Incorporating fixed differences improves power, and NCD2 has higher power to detect LTBS in humans under different frequencies of the balanced allele(s) than other available methods. Applied to genome-wide data from African and European human populations, in both cases using chimpanzee as an outgroup, NCD2 shows that, albeit not prevalent, LTBS affects a sizable portion of the genome: about 0.6% of analyzed genomic windows and 0.8% of analyzed positions. Significant windows (p < 0.0001) contain 1.6% of SNPs in the genome, which disproportionally fall within exons and change protein sequence, but are not enriched in putatively regulatory sites. These windows overlap about 8% of the protein-coding genes, and these have larger number of transcripts than expected by chance even after controlling for gene length. Our catalog includes known targets of LTBS but a majority of them (90%) are novel. As expected, immune-related genes are among those with the strongest signatures, although most candidates are involved in other biological functions, suggesting that LTBS potentially influences diverse human phenotypes.

genomics↗