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Alves, J. M.

Publications and source records attributed to Alves, J. M..

16 recordsLinked to original sources
bioRxiv2026

Cold acclimation reprograms hepatic lipid composition toward n-3 HUFAs to uncouple adipose-derived lipid flux from steatosis

While cold exposure drives lipid flux from adipose tissue to the liver, this enhanced inter-organ crosstalk does not result in sustained hepatic steatosis during prolonged acclimation, indicating that factors beyond lipid flux shape metabolic outcome. To interrogate this adaptation, we performed integrated lipidomic and metabolic profiling across tissues and circulating lipoproteins over the course of cold acclimation. We showed that cold acclimation induces systemic reprogramming of lipid quality in mice, characterized by enrichment of n-3 highly unsaturated fatty acids (HUFAs) as a consequence of upregulation of fatty acid desaturases (FADS1 and 2) in the liver and white adipose tissue, thus increasing hepatic n-3/n-6 ratio. Cold-induced increase in n-3 HUFAs cause the suppression of SCD1-mediated desaturation, thus yielding a depletion of monounsaturated fatty acids (MUFAs) in the liver, along with the suppression of lipogenic markers. Notably, this high-HUFA/low-MUFA lipid signature is present in both hepatic free fatty acid and triglyceride pools, indicating that lipid remodeling occurs upstream of triglyceride synthesis. Lipidomic analysis revealed that the remodeled triglycerides are incorporated into very-low-density and intermediate density lipoproteins (VLDL and IDL), thereby propagating hepatic lipid reprogramming to the circulation. Thus, by selectively increasing endogenous n-3 HUFA availability, cold adaptation suppresses hepatic DNL and MUFA-driven triglyceride assembly, buffering lipid accumulation despite sustained fatty acid influx and reshaping systemic lipid distribution with potential cardiometabolic impact.

biochemistry↗
bioRxiv2026

The genome sequence of Pavonine herpesvirus 1, a novel Mardivirus infecting peafowl

Avian alphaherpesviruses of the genus Mardivirus include several economically important pathogens, such as the tumour-causing Mareks disease virus (MDV-1) of chickens. However, the diversity of related viruses in wild and non-model avian hosts remains poorly characterised. Here, we describe the genome of Pavonine herpesvirus 1 (PaHv1), a novel Mardivirus infecting peafowl (Pavo spp.). Through de novo assembly of reads generated from whole-genome sequencing of 370 captive peafowl, we generated a single viral genomic scaffold of 134,149 bp in length and an estimated total genome size of [~]146 kbp following reconstruction of terminal repeat regions. PaHv1 exhibits canonical Mardivirus UL-IRL-IRS-US genomic architecture and encodes 169 open reading frames, of which 82 have clear orthologs in other Mardivirus species. Comparative genomic analyses revealed strong syntenic concordance between PaHv1, MDV-1, MDV-2 and Meleagrid alphaherpesvirus 1 (HVT), but with notable absences of the Meq oncogene, viral interleukin-8 (vIL8), and a truncated pp38 gene - genes known to underpin oncogenicity and virulence in MDV-1. Phylogenetic analysis places PaHv1 firmly within the Mardivirus genus as a sister to the poultry-associated MDV-1 and MDV-2 viruses, but distinct from a previously described Phasianid herpesvirus with a partial DNA terminase sequence. PaHv1 was detected predominantly in feather-derived samples, consistent with replication or persistence in the feather follicle epithelium. Taken together, these findings identify PaHv1 as a novel, likely non-oncogenic Mardivirus, expanding our understanding of herpesvirus diversity, evolution and host association in galliform birds. ImportanceHerpesviruses cause several economically important diseases in domesticated birds, including Mareks disease, duck plague and infectious laryngotracheitis. Despite this, our understanding of herpesviruses infecting wild and semi-wild birds remains limited. Here, we present the genome of Pavonine herpesvirus 1 (PaHv1), a virus in the Mardivirus genus which infects peafowl. Based on comparative genomics with other Mardivirus species, we note the absence of several genes important for the high virulence of Mareks Disease Virus, such as the Meq oncogene, viral interleukin-8 and a truncated pp38. This, taken together with absence of clinical disease in preliminary observations, suggests that PaHv1 causes either a subclinical infection or one with mild symptoms. Our work expands the known evolutionary breadth of avian herpesviruses in the Mardivirus genus. In addition, PaHv1 may provide a useful starting point for the development of novel vaccine vectors for pathogenic herpesvirus infections.

genomics↗
bioRxiv2025

Gene flow weakens genomic clines while selection maintains adaptive loci: two decades of evolution in Drosophila melanogaster natural populations

Spatial genetic clines suggest local adaptation, but whether they persist or erode over evolutionary time remains largely unknown. Here, we use a unique genomic time series collected over several decades to quantify how gene flow and selection jointly shape spatial genomic structure. We analyzed pooled whole-genome sequencing from 16 natural populations of Drosophila melanogaster sampled along the North American east coast between 1997 and 2023, spanning hundreds of generations. We find pronounced homogenization of populations over time, accompanied by a genome-wide loss of clinal variants. Polymorphisms that remained clinal were less steep on chromosome 3R, reflecting declines in the frequency and clinality of major chromosomal inversions. Genomic context modulates this process: clinal SNPs are preferentially lost in regions of high recombination, whereas remaining clines are increasingly concentrated in coding and splice-associated sites. Despite widespread erosion of spatial structure, we detect signatures of selection shared across space at detoxification loci, including cytochrome P450 genes linked to insecticide resistance. Together, our results show widespread homogenization of neutral spatial variation consistent with gene flow, while spatially varying selection has preserved a subset of functionally important loci.

evolutionary biology↗
bioRxiv2025

Single-cell phylodynamics reveal rapid late-stage colorectal cancer expansions

Single-cell whole-genome sequencing of 335 cells from seven colorectal cancers, coupled with Bayesian phylodynamic modeling, revealed tumors often originate decades before diagnosis, remain indolent, and expand rapidly within two years. Strong spatial structuring with minimal interregional mixing was observed, while substitution rates varied widely and were decoupled from growth. Our findings highlight extended evolutionary stasis and sudden expansion, informing strategies for early detection and intervention.

evolutionary biology↗
bioRxiv2025

MHC-I diversity enables rapid adaptation during viral pandemic in wild rabbit populations

Emerging diseases can have devastating consequences for wild species, with long-term effects depending on the ability of the host to evolve resistance. Here, we show that major histocompatibility complex (MHC) genes provided standing genetic variation that enabled rabbits to mount a rapid evolutionary response to the myxoma virus pandemic that began in the 1950s. Using historical and modern specimens starting in 1865 and spanning the pandemic, we found strong parallel shifts in MHC-I allele frequencies across Australia, Britain and France, alongside population-specific signals. These evolutionary shifts appear to have altered antigen presentation to T cells. Our results provide evidence that MHC-I is under strong selection in natural populations during a pandemic, and that the high polymorphism of MHC may have contributed to the evolutionary rescue of these populations.

evolutionary biology↗
bioRxiv2025

Intraline genomic heterogeneity of the triple-negative breast cancer MDA-MB-231 cell line

Cancer cell lines are valuable models for studying tumor biology, yet their genomic evolution during culture can compromise experimental reproducibility. We conducted a detailed genomic analysis of the triple-negative breast cancer cell line MDA-MB-231, examining sublines obtained from different sources, at various time points, and across distinct passages. We introduce the concept of intraline heterogeneity (ILH) to highlight the genomic variability observed among these sublines. Our analyses revealed extensive genomic diversity, including differences in single nucleotide variants (SNVs) and copy number alterations (CNAs). In particular, CNAs exhibited remarkable heterogeneity, with pronounced chromosomal gains and losses between sublines, underscoring the impact of genomic instability on ILH. These findings suggest that ILH may influence experimental outcomes, emphasizing the importance of considering passage-specific genomic characterization to ensure consistency and reliability in cancer research.

genomics↗
bioRxiv2025

Leopard Cats Occupied Human Settlements in China for 3,500 years before the Arrival of Domestic cats in 600-900 CE around the Tang Dynasty

The earliest cats in human settlements in China were not domestic cats (Felis catus), but native leopard cats (Prionailurus bengalensis). To trace when and how domestic cats arrived in East Asia, we analyzed 22 feline bones from 14 sites across China spanning 5,000 years. Nuclear and mitochondrial genomes revealed that leopard cats began occupying anthropogenic scenes around 5,400 years ago and last appeared in 150 CE. Following several centuries gap of archeological feline remains, the first known domestic cat (706-883 CE) in China was identified in Shaanxi during the Tang Dynasty. Genomic analysis suggested a white or partially white coat and a link to a contemporaneous domestic cat from Kazakhstan, indicating a likely dispersal route via the Silk Road. The two felids once independently occupied ancient anthropogenic environments in China but followed divergent paths and reached different destinations in human-animal interactions.

evolutionary biology↗
bioRxiv2024

Genomic Insights Guiding Personalized First-Line Immunotherapy Response in Lung and Bladder Tumors

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, particularly in advanced non-small cell lung cancer (NSCLC) and muscle-invasive bladder cancer (MIBC). However, identifying reliable predictive biomarkers for ICI response remains a significant challenge. In this study, we analyzed real-world cohorts of advanced NSCLC and MIBC patients treated with ICIs as first-line therapy. Tumor samples underwent Whole Genome Sequencing (WGS) to identify specific somatic variants and assess tumor mutational burden (TMB). Additionally, mutational signature extraction and pathway enrichment analyses were performed to uncover the underlying mechanisms of ICI response. We also characterized HLA-I haplotypes and investigated LINE-1 retrotransposition. Distinct mutation patterns were identified in patients who responded to treatment, suggesting potential biomarkers for predicting ICI effectiveness. In NSCLC, tumor mutational burden (TMB) did not differ significantly between responders and non-responders, while in MIBC, higher TMB was linked to better responses. Specific mutational signatures and HLA haplotypes were associated with ICI response in both cancers. Pathway analysis showed that NSCLC responders had active inflammatory and immune pathways, while non-responders had pathways such related to FGFR3 and neural crest differentiation associated to resistance mechanisms. In MIBC, responders had alterations in DNA repair, leading to more neoantigens and a stronger ICI response. Importantly, for the first time, we found that LINE-1 activation was positively linked to ICI response, especially in MIBC. These findings reveal promising biomarkers and mechanistic insights, offering a new perspective on predicting ICI response and opening up exciting possibilities for more personalized immunotherapy strategies in NSCLC and MIBC.

genomics↗
bioRxiv2024

Unraveling the phylogenetic signal of gene expression from single-cell RNA-seq data

Single-cell RNA sequencing (scRNA-seq) has transformed our understanding of phenotypic heterogeneity. Although the predominant focus of scRNA-seq analyses has been assessing gene expression changes, several approaches have been proposed in recent years to identify changes at the DNA level from scRNA-seq data. In this study, we evaluated the relative performance of six strategies for calling single-nucleotide variants from scRNA-seq data using 381 single-cell transcriptomes from five cancer patients. Specifically, we focused on the quality of the inferred genotypes and the resulting single-cell phylogenies. We found that scAllele, Monopogen, and Monovar consistently returned phylogenetically informative genotype calls, providing more precise signals of discrimination between tumor and normal cells within heterogeneous samples and among distinct subclonal lineages in longitudinal samples. In addition, we evaluated the evolution of gene expression along the cell phylogenies. While most transcriptomic variation was very plastic and did not correlate with the cell phylogeny, a group of genes associated with cell cycle processes showed a strong phylogenetic signal in one of the patients, underscoring a potential link between gene expression patterns and lineage-specific traits in the context of cancer progression. In summary, our study highlights the potential of scRNA-seq data for inferring cell phylogenies to decipher the evolutionary dynamics of cell populations.

genomics↗
bioRxiv2021

FGF21 Response Varies by Sugar Type and is Associated with Body Weight, Dietary Added Sugar, and Neural Signaling in Humans

Fibroblast growth factor 21 (FGF21) is a liver-derived hormone that regulates energy homeostasis. In humans, few studies have investigated whether FGF21 may act to suppress sugar intake and influence eating behavior, and the effects of adiposity on post-ingestive FGF21 regulation of appetite are unknown. Here, we demonstrate among two cohorts of healthy, young adults that acute oral fructose and sucrose compared to glucose lead to greater circulating FGF21. Moreover, high compared to low dietary added sugar intake is associated with greater sucrose-stimulated FGF21 among participants with healthy weight but attenuated in people with overweight and obesity. In addition, our study is the first to demonstrate associations between circulating FGF21 and neural signaling following an acute sucrose load among humans with healthy weight. Collectively, our results suggest that these potential compensatory relationships between sucrose-stimulated circulating FGF21, habitual sugar intake, and post-ingestive brain responses may be altered among adults with overweight and obesity. Significance StatementAnimal models have established FGF21 as an autoregulator of sweet consumption, but few studies have examined post-ingestive FGF21 effects in humans. In this report, we demonstrate a compensatory relationship between sucrose-stimulated FGF21 and high dietary added sugar intake through a potential liver-to-brain negative-feedback cycle among healthy, young adults. Notably, our findings also suggest that humans with overweight and obesity may have altered FGF21 neuroendocrine signaling.

physiology↗
bioRxiv2020

CellPhy: accurate and fast probabilistic inference of single-cell phylogenies from scDNA-seq data

We introduce a maximum likelihood framework called CellPhy for inferring phylogenetic trees from single-cell DNA sequencing (scDNA-seq) data. CellPhy leverages a finite-site Markov genotype substitution model with 16 diploid states, akin to those typically used in statistical phylogenetics. It includes a dedicated error function for single cells that incorporates amplification/sequencing error and allelic dropout (ADO). Moreover, it can explicitly consider the uncertainty of the variant calling process by using genotype likelihoods as input. We implemented CellPhy in a widely used open-source phylogenetic inference package (RAxML-NG) that provides statistical confidence measurements on the estimated tree and scales particularly well on large scDNA-seq datasets with hundreds or thousands of cells. To benchmark CellPhy, we carried out 19,400 coalescent simulations of cell samples from exponentially-growing tumors for which the true phylogeny was known. We evolved single-cell diploid DNA genotypes along the simulated genealogies under different scenarios, including infinite- and finite-sites nucleotide mutation models, trinucleotide mutational signatures, sequencing, and amplification errors, allele dropouts, and cell doublets. Our simulations suggest that CellPhy is robust to amplification/sequencing errors and ADO and outperforms state-of-the-art methods under realistic scDNA-seq scenarios both in terms of accuracy and speed. Also, we sequenced 24 single-cell whole-genomes from a colorectal tumor. Together with three published scDNA-seq data sets, we analyzed these empirical data to illustrate how CellPhy can provide more reliable biological insights than most competing methods. CellPhy is freely available at https://github.com/amkozlov/cellphy.

bioinformatics↗
bioRxiv2019

Rapid evolution and biogeographic spread in a colorectal cancer

How and when tumoral clones start spreading to surrounding and distant tissues is currently unclear. Here, we leveraged a model-based evolutionary framework to investigate the demographic and biogeographic history of a colorectal cancer. Our analyses strongly support an early monoclonal metastatic colonization, followed by a rapid population expansion at both primary and secondary sites. Moreover, we infer a hematogenous metastatic spread seemingly under positive selection, plus the return of some tumoral cells from the liver back to the colon lymph nodes. This study illustrates how sophisticated techniques typical of organismal evolution can provide a detailed picture of the complex tumoral dynamics over time and space.

cancer biology↗
bioRxiv2017

Host shifts result in parallel genetic changes when viruses adapt to closely related species

Host shifts, where a pathogen invades and establishes in a new host species, are a major source of emerging infectious diseases. They frequently occur between related host species and often rely on the pathogen evolving adaptations that increase their fitness in the novel host species. To investigate genetic changes in novel hosts, we experimentally evolved replicate lineages of an RNA virus (Drosophila C Virus) in 19 different species of Drosophilidae and deep sequenced the viral genomes. We found a strong pattern of parallel evolution, where viral lineages from the same host were genetically more similar to each other than to lineages from other host species. When we compared viruses that had evolved in different host species, we found that parallel genetic changes were more likely to occur if the two host species were closely related. This suggests that when a virus adapts to one host it might also become better adapted to closely related host species. This may explain in part why host shifts tend to occur between related species, and may mean that when a new pathogen appears in a given species, closely related species may become vulnerable to the new disease.

evolutionary biology↗
bioRxiv2017

Sensitivity to sequencing depth in single-cell cancer genomics

BackgroundQuerying cancer genomes at single-cell resolution is expected to provide a powerful framework to understand in detail the dynamics of cancer evolution. However, given the high costs currently associated with single-cell sequencing, together with the inevitable technical noise arising from single-cell genome amplification, cost-effective strategies that maximize the quality of single-cell data are critically needed. Taking advantage of five published single-cell whole-genome and whole-exome cancer datasets, we studied the impact of sequencing depth and sampling effort towards single-cell variant detection, including structural and driver mutations, genotyping accuracy, clonal inference and phylogenetic reconstruction, using recent tools specifically designed for single-cell data.\n\nResultsAltogether, our results suggest that, for relatively large sample sizes (25 or more cells), sequencing single tumor cells at depths >5x does not drastically improve somatic variant discovery, the characterization of clonal genotypes or the estimation of phylogenies from single tumor cells.\n\nConclusionsWe demonstrate that sequencing many individual tumor cells at a modest depth represents an effective alternative to explore the mutational landscape and clonal evolutionary patterns of cancer genomes, without the excessively high costs associated with high-coverage genome sequencing.

genomics↗
bioRxiv2016

Biased evolutionary inferences from bulk tumor samples

It is generally agreed that tumors are composed of multiple cell clones defined by different somatic mutations. Characterizing the evolutionary mechanisms driving this intratumor genetic heterogeneity (ITH) is crucial to improve both cancer diagnosis and therapeutic strategies. For that purpose, recent ITH studies have focused on qualitative comparisons of mutational profiles derived from bulk sequencing of multiple tumor samples extracted from the same patient. Here, we show some examples where the naive use of bulk data in multiregional studies may lead to erroneous inferences of the evolutionary trajectories that underlie tumor progression, including biased timing of somatic mutations, spurious parallel mutation events, and/or incorrect chronological ordering of metastatic events. In addition, we analyze three real datasets to highlight how the use of bulk mutational profiles instead of inferred clones can lead to different conclusions about mutational recurrence and population structure.

evolutionary biology↗