Biology subjects

Marco, A.

Publications and source records attributed to Marco, A..

16 recordsLinked to original sources

bioRxiv2026

Individual natal assignment in highly migratory species: the genomic baseline and its application in loggerhead turtles

O_LIEffective conservation of highly migratory species requires understanding genetic structure across breeding populations and access high{square}resolution markers capable of assigning individuals from mixed aggregates (e.g. bycatch or new nesting sites) to their natal origins. Genomic approaches provide unprecedented resolution but add methodological challenges; thus, it is essential to first build a genomic baseline from known breeding areas and then evaluate strategies for assigning unknown individuals. C_LIO_LITo address this, we used 2b-RAD sequencing, a genomic reduction technique useful for degraded DNA, and loggerhead turtles as a case study. This species shows philopatric breeding, while juveniles and adults form mixed aggregations in foraging grounds. C_LIO_LIOur results highlight the importance of building baselines that include all potential source populations contributing to mixed aggregations. We detected hierarchical genetic differentiation and high resolution and successfully assigned the natal origin of 124 unknown individuals from four Mediterranean foraging grounds. These grounds showed distinct source contributions, and comparisons with previous studies suggest possible temporal shifts in stock composition. C_LIO_LIWe provide a comprehensive genomic baseline for individual assignment of Altanto-Mediterranean loggerhead turtles of unknown natal origin and a general framework for identifying population-specific threats in highly migratory species. C_LI

evolutionary biology↗

bioRxiv2026

A robust human airway organoid platform enables scalable expansion and trajectory mapping of pulmonary neuroendocrine cells

Pulmonary neuroendocrine cells (PNECs) are rare chemosensory epithelial cells, facultative stem cells, and a cell-of-origin for neuroendocrine lung cancers, yet the mechanisms governing their differentiation and heterogeneity are poorly understood. Here we establish NEr-fAOs, a human fetal airway organoid platform that robustly enriches PNECs, and identify a cooperative requirement for dual GSK3 and NOTCH inhibition to drive directed PNEC differentiation. This strategy yields stable cultures with up to 60-fold expansion of PNECs whose transcriptomes closely match fetal and adult PNECs. In addition to PNEC-enrichment, NEr-fAOs retain diverse airway epithelial cell types, preserving epithelial complexity. Time-resolved single-cell transcriptomics maps PNEC trajectories in NEr-fAOs, resolving precursor and mature states. Comparative analyses further reveal a distal airway bias in NEr-fAOs and enrichment for lower-airway progenitors. NEr-fAOs thus provide a scalable, tractable platform to dissect human PNEC biology and distal airway progenitor hierarchies relevant to lung development, cancer, and disease.

developmental biology↗

bioRxiv2025

An AGO2 adaptor expands the functional and evolutionary reach of microRNA targeting

Current models of microRNA (miRNA) silencing posit that RNA-sequence rules are sufficient for canonical targeting of mRNAs by Argonaute 2 (AGO2), the central protein of the miRNA-induced silencing complex (miRISC). Using chimeric eCLIP in CRISPR-edited LIMD1+/+, LIMD1+/-, and LIMD1-/- human small airway epithelial cells (hSAECs), we reveal a transcriptome-wide dependency on LIMD1, an AGO2 adaptor, for effective miRNA targeting and repression. In LIMD1-deficient cells, miRNA loading is uncoupled from productive targeting: despite increased AGO2-miRNA interactions, complexes engage fewer transcripts and sites, reducing occupancy and more than halving both the breadth and depth of targeting. We also observe altered AGO2 positional footprints across targets in LIMD1-deficient cells. LIMD1 dependence is most pronounced at defined RNA contexts: weak (GC-poor) seed pairings, interactions involving evolutionarily young miRNAs or sites that nonetheless form thermodynamically stable duplexes, with these losses particularly enriched in coding sequences of rapidly evolving C2H2-zinc-finger genes. Even within canonical seed repertoires of individual AGO2-miRNAs, LIMD1 is most critical at poorly conserved sites, indicating that LIMD1 broadens miRNA regulation beyond ancient, deeply conserved targets. In culture, LIMD1 deficiency de-represses oncogenic proteins that, in vivo, inversely correlate with LIMD1 levels in normal lung and adenocarcinoma, where LIMD1 is characteristically reduced, and whose dysregulation predicts poor survival. Thus, LIMD1 emerges as a key determinant of miRISC architecture, targeting, and potency, challenging RNA-centric models of miRNA function and exemplifying how adaptor proteins diversify post-transcriptional regulation. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=180 HEIGHT=200 SRC="FIGDIR/small/680889v2_ufig1.gif" ALT="Figure 1"> View larger version (58K): org.highwire.dtl.DTLVardef@e0f4f5org.highwire.dtl.DTLVardef@f23fd9org.highwire.dtl.DTLVardef@3de3f2org.highwire.dtl.DTLVardef@1404af2_HPS_FORMAT_FIGEXP M_FIG LIMD1 defines the scope of miRNA-mediated targeting and repression O_LIAGO2-chimeric eCLIP in CRISPR-edited human small airway epithelial cells (hSAECs) shows LIMD1 is required for productive AGO2-miRNA engagement transcriptome-wide. C_LIO_LILIMD1 deficiency reduces the AGO2-miRNA:targetome. Each AGO2-miRNA binds fewer targets, with lower occupancy per site and per transcript and fewer global silencing events. C_LIO_LILIMD1 dependence is strongest for GC-poor seed-sites, less conserved miRNAs and sites, and thermodynamically stronger duplexes. C_LIO_LIDosage-dependent effects of LIMD1 deficiency are broadly observed. C_LIO_LITarget-mRNA decay and translational repression are reduced in LIMD1-deficient hSAECs, increasing protein output. C_LIO_LIIn vivo, LIMD1 LOH-associated deficiency is prevalent and typically clonal in NSCLC. LIMD1 expression inversely correlates with oncogene levels in normal lung and adenocarcinoma, and target dysregulation predicts poor survival. C_LI C_FIG

molecular biology↗

bioRxiv2025

Epigenetic inheritance of complex learning abilities in the mammalian brain

For several decades, the question of whether cognitive and learning capacities can be inherited through non-genetic mechanisms has been the subject of ongoing debate. Here, we provide the first evidence of transgenerational inheritance of enhanced ability to learn complex tasks in the mammalian rodent brain. These inherited learning enhancements are not limited to specific stimuli, sensory modalities, or learning paradigms. Using behavioral, cellular biophysical, methylomics, genetics and molecular methods, we find that the inherited epigenetic modifications reflect an enhanced neuronal learning state, driven by increased intrinsic neuronal excitability in most pyramidal neurons in the relevant neuronal networks. This enhancement is mediated by persistent downregulation of the muscarinic M-current and is associated with widespread changes in DNA methylation, notably within coding genes associated with the M-current, the Kv7 pathway, in the hippocampi of trained F0 rats, as well as in non-coding RNAs in their sperm samples. Remarkably, a significant portion of these DNA methylation changes were also observed in the hippocampi of their untrained F1 offspring. These findings suggest that complex learning abilities can be inherited in the mammalian brain, as the offspring of trained rodents are born with the biophysical modifications that enable them to become super-learners, the exact change that occurs in their parents brains only after the rule learning.

neuroscience↗

bioRxiv2024

Somatic evolution of cancer genes in sex chromosomes

Cancer progression arises through the somatic evolution of oncogenes (OGs) and tumour-suppressor genes (TSGs). According to Knudsons two-hit hypothesis, both alleles of a TSG must typically be inactivated for tumorigenesis to proceed, whereas a single activating mutation can drive an OG. However, this diploid framework overlooks the distinct evolutionary dynamics of sex chromosomes. In males, the hemizygous (functionally haploid) state of the X chromosome implies that only a single mutational "hit" is needed to disable an X-linked TSG, potentially accelerating its contribution to cancer development. Here, we integrate somatic population genetics models with whole-genome mutation data to investigate how ploidy and dominance shape somatic evolution. We show that X-linked TSGs in male tumours evolve significantly faster than autosomal TSGs, particularly in highly proliferative tissues, whereas in low-proliferation tumours autosomal OGs accumulate mutations more rapidly than X-linked OGs. We further demonstrate that fixation times of advantageous mutations differ systematically between OGs and TSGs, converging only for male X-linked genes, as predicted from mathematical models. Our findings reveal that haploidy of sex chromosomes fundamentally alters the dynamics predicted by the two-hit hypothesis, providing the first systematic evidence that chromosomal context biases cancer gene evolution. Incorporating these principles into cancer biology offers a more accurate framework for understanding sex differences in tumorigenesis and highlights new avenues for therapeutic strategies targeting genomic regions with accelerated mutational dynamics.

genetics↗

bioRxiv2024

Analysis of coding gene expression from small RNA sequencing

The popularity of microRNA expression analyses is reflected by the existence of thousands of sRNA-seq studies where matched total RNA-seq data are often unavailable. The lack of paired sequencing experiments limits the analysis of microRNA-gene regulatory networks. We explore whether protein-coding gene expression can be quantified directly from transcript fragments present in sRNA-seq experiments. We analyze studies containing matched total RNA and small RNA from four human tissues and recover transcript fragments from the sRNA-seq datasets. We find that the expression levels of protein-coding gene transcripts derived from sRNA-seq datasets are comparable to those from total RNA-seq experiments (R2 ranging from 0.33 to 0.76). Analyses across multiple tissues and species show similar correlations, indicating that the approach is applicable across organisms. We confirm that transcript half-life and the expression of housekeeping or highly abundant genes do not bias the results. Analysis of the expression of both microRNAs and coding genes from the same sRNA-seq experiments demonstrate that known microRNA-target interactions are, as expected, inversely correlated with the expression profiles of these microRNA-mRNA pairs. For a dual mRNA/miRNA profile, we recommend sequencing the [≥]25 nucleotide fraction at [≥] 5 M reads. To confirm the utility of this approach, we apply our method to breast cancer sRNA-seq datasets lacking total RNA-seq data and achieve 75% recall and 64% accuracy comparing inferred coding gene expression with qPCR-validated targets. Our findings demonstrate that quantifying mRNA fragments from sRNA-seq experiments provides a reliable approach to investigate microRNA-mRNA interactions when total RNA-seq is unavailable.

genomics↗

bioRxiv2024

Forebrain neuronal SMC3 regulates body weight and metabolic health partially through regulation of hypothalamic Melanocortin 4 receptor

SMC3 is a major component of the cohesin complex that regulates higher-order chromatin organization and gene expression. Mutations in SMC3 gene are found in patients with Cornelia de Lange syndrome (CdLs). This syndrome is characterized by intellectual disabilities, behavioral patterns as self-injury, as well as metabolic dysregulation. Nonetheless, little is known about the role of neuronal SMC3 in gene expression and physiology in adulthood. This study determined the role of SMC3 in adulthood brain, by knocking out Smc3 specifically in adulthood forebrain excitatory neurons. Excitatory conditional neuron-specific SMC3 knockout (cKO) mice displayed a very strong metabolic phenotype in both male and female mice, including a robust overweight phenotype, loss of muscle mass, increased food consumption, lower respiratory exchange ratio, lower energy expenditure and hormonal changes. The hypothalamus displayed dysregulated neuronal morphology and associated transcriptional abnormalities in RNA-seq analysis across various cellular pathways, including decrease of Melanocortin 4 receptor (Mc4r) expression level, a pivotal regulator of appetite and metabolism. Correspondingly, ChIP-seq analysis revealed genome-wide alterations in the binding dynamics of SMC3 of the cKO animals, including Mc4r associated regions. Notably, a significant correlation emerged between multiple sites exhibiting a marked decrease in binding and downregulated genes. The administration of Setmelanotide, an MC4r agonist, to cKO group resulted in a notable reduction in both weight and food consumption in these mice. Therefore, we have identified specific and reversable metabolic parameters that are regulated by neuronal Smc3 in adulthood.

neuroscience↗

bioRxiv2024

The p90 Ribosomal S6 Kinases 2 and 4 promote Prostate Cancer cell proliferation in androgen-dependent and independent ways

Oncogenic activation of the phosphatidylinositol-3-kinase (PI3K) and mitogen-activated protein kinase (MAPK) pathways are frequent events in Prostate Cancer (PCa) that have been correlated to tumour formation, disease progression and therapeutic resistance. At the intersection of these two pathways lies the p90 ribosomal S6 kinase (RSKs) family, which regulates many proteins involved in cell survival, growth and proliferation. As such, deregulated RSKs activity has been associated with multiple cancer types, including PCa. However, the full extent of the RSKs involvement in prostate tumorigenesis remains to be determined. Here we have shown that RSKs levels are increased in PCa samples and cell lines. The RSKs were found to enhance Androgen Receptor (AR) activity, the key oncogenic driver in PCa. Indeed, all RSKs were found to interact in close proximity to the AR. However, RSK2/4, but not RSK1/3, showed changes in cell localisation following AR nuclear translocation. Consistently, silencing of RSK2/4, but not RSK1/3, inhibited PCa proliferation in an androgen-dependent and independent manner, respectively, and induced different signaling events downstream of the AR. The data suggests that RSK2 and RSK4 activity is required for PCa cell proliferation, but they are likely regulating growth via different mechanisms.

cancer biology↗

bioRxiv2021

The chromosomal distribution of sex-biased microRNAs in Drosophila is non-adaptive

Genes are often differentially expressed between males and females. In Drosophila melanogaster, the analysis of sex-biased microRNAs (short non-coding regulatory molecules) has revealed striking differences with protein-coding genes. Mainly, the X chromosome is enriched in male-biased microRNA genes, although it is depleted of male-biased protein-coding genes. The paucity of male-biased genes in the X chromosome is generally explained by an evolutionary process called demasculinization. I suggest that the excess of male-biased microRNAs in the X chromosome is due to high-rates of de novo emergence of microRNAs (mostly in other neighboring microRNAs), a tendency of novel microRNAs in the X chromosome to be expressed in testis, and to a lack of a demasculinization process. To test this hypothesis I analysed the expression profile of microRNAs in males, females and gonads in D. pseudoobscura, in which an autosome translocated into the X chromosome effectively becoming part of a sex chromosome (neo-X). I found that the pattern of sex-biased expression is generally conserved between D. melanogaster and D. pseudoobscura. Also, orthologous microRNAs in both species conserve their chromosomal location, indicating that there is no evidence of demasculinization or other inter-chromosomal movement of microRNAs. D. pseudoobscuraspecific microRNAs in the neo-X chromosome tend to be male-biased and particularly expressed in testis. In summary, the apparent paradox resulting from male-biased protein-coding genes depleted in the X chromosome and an enrichment in male-biased microRNAs is consistent with different evolutionary dynamics between coding genes and short RNAs.

evolutionary biology↗

bioRxiv2021

A diabetic milieu increases cellular susceptibility to SARS-CoV-2 infections in engineered human kidney organoids and diabetic patients

SARS-CoV-2 infections lead to a high risk of hospitalization and mortality in diabetic patients. Why diabetic individuals are more prone to develop severe COVID-19 remains unclear. Here, we established a novel human kidney organoid model that mimics early hallmarks of diabetic nephropathy. High oscillatory glucose exposure resulted in metabolic changes, expansion of extracellular membrane components, gene expression changes determined by scRNAseq, and marked upregulation of angiotensin-converting enzyme 2 (ACE2). Upon SARS-CoV-2 infection, hyperglycemic conditions lead to markedly higher viral loads in kidney organoids compared to normoglycemia. Genetic deletion of ACE2, but not of the candidate receptor BSG/CD147, in kidney organoids demonstrated the essential role of ACE2 in SARS-CoV-2 infections and completely prevented SARS-CoV-2 infection in the diabetogenic microenvironment. These data introduce a novel organoid model for diabetic kidney disease and show that diabetic-induced ACE2 licenses the diabetic kidney to enhanced SARS-CoV-2 replication.

cell biology↗

bioRxiv2019

Influence of fats, carotenoids and POPs on the reproduction of the leatherback turtle

This study provides baseline data on fatty acid profiles and carotenoids in eggs of the leatherback sea turtle, Dermochelys coriacea. Correlations among such compounds, persistent organic pollutants, and reproductive parameters are also investigated. A number of 18 clutches were evaluated during June and August of 2008 at Reserva Pacuare Beach, in the Caribbean side of Costa Rica. Viability and fertility were calculated for each nest. Concentration levels of saturated and unsaturated fatty acids (SFAs and PUFAs), carotenoids and different congeners of persistent organic pollutants (POPs) were determined from egg-yolk samples. Mean {+/-} SD values were calculated for each compound and for each clutch. Correlations were performed searching for interactions among different compounds and for potential effects on reproductive parameters, thus all the studied compounds were related to each other and to any of the reproductive parameters. Low carotenoid levels characterized all eggs of this species, and a positive relationship between carotenoid concentrations and the viability rate was found. POPs and PUFA were positive and strongly correlated, suggesting molecular interactions. PUFAs appeared to increase fertility rate and hatchling length. This study provides potential evidences of PUFA enhancing fertility and hatchling size, and of carotenoids limiting vitellogenesis. The positive correlation found between POPs and PUFAs may indicate that harmful effects of these contaminants on the reproduction of leatherback turtles could be masked.

physiology↗

bioRxiv2019

PopTargs: A database for studying population evolutionary genetics of human microRNA target sites

There is an increasing interest in the study of polymorphic variants at gene regulatory motifs, including microRNA target sites. Understanding the effects of selective forces at specific microRNA target sites, together with other factors like expression levels or evolutionary conservation, requires the joint study of multiple datasets. We have compiled information from multiple sources and compare it with predicted microRNA target sites to built a comprehensive database for the study of microRNA targets in human populations. PopTargs is a web-based tool that allows the easy extraction of multiple datasets and the joint analyses of them, including allele frequencies, ancestral status, population differentiation statistics and site conservation. The user can also compare the allele frequency spectrum between two groups of target sites, and conveniently produce plots. The database can be easily expanded as new data becomes available and the raw database as well as code for creating new custom made databases are available for downloading. We also describe a few illustrative examples.\n\nAvailability and implementationPoptargs is available at http://poptargs.essex.ac.uk\n\nContactamarco.bio@gmail.com

bioinformatics↗

bioRxiv2019

The impact of population variation in the analysis of microRNA target sites

The impact of population variation in the analysis of regulatory interactions is an underdeveloped area. MicroRNA target recognition occurs via pairwise complementarity. Consequently, a number of computational prediction tools have been developed to identify potential target sites, that can be further validated experimentally. However, as microRNA target predictions are done mostly considering a reference genome sequence, target sites showing variation among populations are neglected. Here we study variation at microRNA target sites in human populations and quantify their impact in microRNA target prediction. We found that African populations carry a significant number of potential microRNA target sites that are not detectable in the current human reference genome sequence. Some of these targets are conserved in primates and only lost in Out-of-Africa populations. Indeed, we identified experimentally validated microRNA/transcript interactions that are not detected in standard microRNA target prediction programs, yet they have segregating target alleles abundant in non-European populations. In conclusion, here we show that ignoring population diversity may leave out regulatory elements essential to understand disease and gene expression, particularly neglecting populations of African origin.

evolutionary biology↗

bioRxiv2018

Pervasive selection against microRNA target sites in human populations

MicroRNA target sites are often conserved during evolution and purifying selection to maintain such sites is expected. On the other hand, comparative analyses identified a paucity of microRNA target sites in co-expressed transcripts, and novel target sites can potentially be deleterious. We proposed that selection against novel target sites pervasive. The analysis of derived allele frequencies revealed that, when the derived allele is a target site, the proportion of non-target sites is higher than expected, particularly for highly expressed microRNAs. Thus, new alleles generating novel microRNA target sites can be deleterious and selected against. When we analysed ancestral target sites the derived (non-target) allele frequency does not show statistical support for microRNA target allele conservation. We investigated the joint effects of microRNA conservation and expression and found that selection against microRNA target sites depends mostly on the expression level of the microRNA. We identified microRNA target sites with relatively high levels of population differentiation. However, when we analyse separately target sites in which the target allele is ancestral to the population, the proportion of SNPs with high Fst significantly increases. These findings support population differentiation is more likely in target sites that are lost than in the gain of new target sites. Our results indicate that selection against novel microRNA target sites is prevalent and, although individual sites may have a weak selective pressure, the overall effect across untranslated regions is not negligible and should be accounted when studying the evolution of genomic sequences.

evolutionary biology↗

bioRxiv2018

No evidence of functional co-adaptation between clustered microRNAs

A significant fraction of microRNA loci are organized in genomic clusters. The origin and evolutionary dynamics of these clusters have been extensively studied, although different authors have come to different conclusions. In a recent paper, it has been suggested that microRNAs in the same clusters evolve to target overlapping sets of genes. The authors interpret this as functional co- adaptation between clustered microRNAs. Here I reanalyze their results and I show that the observed overlap is mostly due to two factors: similarity between two seed sequences of a pair of clustered microRNAs, and the expected high number of common targets between pairs of microRNAs that have a large number of targets each. After correcting for these factors, I observed that clustered microRNAs from different microRNA families do not share more targets than expected by chance. During an exchange of correspondence and manuscripts, the authors of the original report acknowledged that the permutation methods they performed was not the method they described in their original paper. Here I show that the new permutation test proposed is biased and leads to systematic errors of the first kind, which will explain why the p-values reported were extremely (and unrealistically) low. I also discuss how to investigate the evolutionary dynamics of clustered microRNAs and their targets. In conclusion, there is no evidence of widespread functional co-adaptation between clustered microRNAs.

evolutionary biology↗

bioRxiv2017

SeedVicious: analysis of microRNA target and near-target sites

Here I describe seedVicious, a versatile microRNA target site prediction software that can be easily fitted into annotation pipelines and run over custom datasets. SeedVicious finds microRNA canonical sites plus other, less efficient, target sites. The program also detects near-target sites, which have one nucleotide different from a canonical site. Near-target sites are important to study population variation in microRNA regulation. Here I show that near-target sites can also be functional sites. Among other features, seedVicious can also compute evolutionary gains/losses of target sites using maximum parsimony. SeedVicious does not aim to outperform but to complement existing microRNA prediction tools. For instance, the precision of TargetScan is doubled (from 11% to ~22%) when we filter predictions by the distance between target sites using our program. The software is written in Perl and runs on 64-bit Unix computers (Linux and MacOS X). Users can also try the program in a dedicated web-server by uploading custom data, or browsing pre-computed predictions. SeedVicious and its associated web-server and database (SeedBank) are distributed under the GPL/GNU license.

bioinformatics↗