Biology subjects

Cioffi, M. d. B.

Publications and source records attributed to Cioffi, M. d. B..

4 recordsLinked to original sources

bioRxiv2026

Repetitive DNA shapes genome architecture and chromosomal diversification in birds of prey

The evolution of genome architecture occurs through dynamic interactions between repetitive DNAs and chromosomal organization; nevertheless, the processes underlying these mechanisms are not well understood. This study presents a comprehensive genomic and cytogenetic analysis of repetitive DNA evolution across Accipitridae birds, a raptor family notable for its significant chromosomal variation. We aimed to investigate how repetitive DNAs have evolved across Accipitriform lineages and test whether shifts in repeat composition are associated with patterns of species diversification. Comparative investigations of eight genomes reveal lineage-specific spikes of transposable elements and satellite DNAs that substantially modify genome composition while preserving a common structural framework. Temporal insertion profiles indicate that repeat turnover is ongoing and frequently coincides with lineages exhibiting extensive chromosomal reorganization. By integrating comparative repeatome analyses with in silico and cytogenetic mapping, we elucidate the spatial architecture governing repeat dynamics, connecting molecular turnover to their chromosomal structure. These findings underscore the effectiveness of merging genomic and chromosomal data to elucidate the impact of repeat landscapes on chromosomal and genomic evolution.

genetics↗

bioRxiv2025

Rapid turnover of sex chromosomes likely drives speciation in Neotropical armored catfish Harttia (Siluriformes, Loricariidae)

Withdrawal StatementThe authors have withdrawn their manuscript because they have decided to incorporate new genomic datasets currently in production to strengthen the analysis of sex-linked markers presented in the current version of the manuscript. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

evolutionary biology↗

bioRxiv2025

Cytological and preliminary genomic analysis of two Leptodactylus frog species (Anura, Leptodactylidae) with recently evolved large meiotic rings of multiple X and Y sex chromosomes

A few species have evolved multiple sex chromosome systems with more than two Xs or Ys. These involve sex chromosome-autosome translocations (sometimes called fusions as very small heterochromatic arms may be deleted), creating neo-sex chromosome systems. Among vertebrates, frogs (Anura) have the highest known number of such translocation systems. This study within the genus Leptodactylus, investigated the two species L. pentadactylus (LPE) and L. paraensis (LPA), in which large ring multivalents are seen in male meiosis, indicating translocations involving the sex chromosomes. Four other species studied do not have such rings, but they share characteristics making rearrangements less likely to be eliminated. To start understanding the formation of multivalents, we used genomic and cytogenetic methods to investigate repetitive DNA sequences, including satellite DNAs, rDNAs, and telomeric sequences, and conducted comparative genomic hybridization (CGH). The LPE genome includes a large number of satDNA families, and in situ mapping of several satDNAs individually identified eight of the ten chromosomes in its multivalent. In LPA, morphological similarities indicate that several chromosomes are shared by the multivalents of both species, and a candidate ancestral sex chromosome pair could be identified. In situ mapping in LPE suggests recent satDNA accumulation in the subtelomeric regions, which differ from those in the outgroup species, contrary to the expectation that the translocations create sex-linkage in the pericentromeric regions.

evolutionary biology↗

bioRxiv2025

Integrative taxonomy using traits and genomic data for Species Delimitation with Deep learning

Recognizing species boundaries in complex speciation scenarios, including those involving gene flow and demographic fluctuations, remains a challenge, particularly given the diversity of existing species concepts. Promising recent approaches adopt an integrative taxonomy that combines multiple sources of evidence (e.g., genetic, morphology, geographic distributions), reflecting different properties associated with the dynamics of the speciation continuum. The use of statistical inference methods for model comparison, such as approximate Bayesian computation, approximate likelihood approaches, and machine learning, has improved the better assessment of species boundaries in such contexts. However, most existing approaches involve analyzing genetic and phenotypic/geographical information separately, followed by visual/qualitative comparison. Methods that integrate genetic information with other sources of evidence remain limited to simple evolutionary models and are typically unable to analyze more than a few hundred loci across a maximum of a few tens of samples. Here, we present a deep learning approach (DeepID) that combines two convolutional neural networks to integrate genomic data (thousands of loci or single nucleotide polymorphisms, SNPs) and trait information into a unified framework. Using both simulated and empirical data sets, we evaluate the power and accuracy of this approach for discriminating among competing divergence speciation scenarios (with minimal ongoing gene flow) across a varying number of SNPs and traits, as well as different levels of missing data. Analyses based on genomic or trait data alone yielded a slight lower accuracy, whereas integrating genomic and trait data resulted in improved performance. When we violated the speciation model by including extensive migration, approaches incorporating trait data were less affected than those relying solely on genomic information. Together, these results suggest that combining genomic and trait data may capture complementary signals associated with different stages of the speciation process. Moreover, our approach successfully recovered the expected delimitation scenarios in empirical data sets from a plant (Euphorbia balsamifera) and a fish (Lepomis megalotis) species complex. We argue that our method is a flexible and promising approach, allowing for complex scenario comparison and the use of multiple types of data. Combining genomic and trait data likely captures complementary signals associated with different stages of the speciation process, reflecting the fact that speciation is a continuum in which genetic and phenotypic divergence may proceed at different rates.

evolutionary biology↗