Biology subjects

Salazar, D.

Publications and source records attributed to Salazar, D..

5 recordsLinked to original sources

bioRxiv2026

Body size, dental pathology and maternal genetic diversity of ancient horses in the eastern Baltic Sea region and western Russia

The early evolutionary history of modern domestic horses (Equus caballus/E. ferus caballus), known as the DOM2 lineage, is well documented due to numerous archaeological and ancient DNA (aDNA) studies. Although many uncertainties remain in the domestication timeline, current evidence suggests that the domestication of modern horses began in the Pontic-Caspian steppe at least [~]2700 BCE (before common era), or even earlier. However, it is not known how long remnant wild horse populations survived or when domestic horses were introduced into Northern Europe. In this study, we review the current knowledge of horse domestication, focusing on Northern Europe. We analysed prehistoric horses from western Russia to assess the body sizes of wild horses from the Ivanovskaya site (5900-3800 BCE) in the Pontic-Caspian steppe, and the body weight of one Lithuanian wild horse (4000-3800 BCE). Additionally, we analysed body sizes of Late Bronze Age-Early Roman Age horses (1100 BCE-300 CE; common era) and re-analysed body sizes and estimated rider weights of historic domestic horses from Lithuania (100-1400 CE). We searched for pathological changes and signs of bit wear indicative of bridling. Furthermore, we investigated maternal genetic diversity by sequencing ancient mitochondrial DNA. We found that wild horses from Ivanovskaya were intermediate in body size between earlier and more recent horses of the Eurasian Steppe, and that the Lithuanian wild horse weighed only [~]270 kg and Late Bronze Age-Early Roman Age horses 200-300 kg. Lithuanian domestic horses were pony-sized (< 130 cm on average). Bit wear was confirmed on one tooth, the oldest domestic horse in Lithuania (799-570 cal BCE). Another tooth showed signs of the Equine Odontoclastic Tooth Resorption and Hypercementosis (EOTRH) condition. Mitochondrial DNA was successfully amplified from one Ivanovskaya wild horse along with 25 other ancient samples, including Lithuanias oldest domestic horse. mtDNA diversity was high, revealing several maternal lineages.

genetics↗

bioRxiv2024

Diverse Database and Machine Learning Model to narrow the generalization gap in RNA structure prediction

Understanding macromolecular structures of proteins and nucleic acids is critical for discerning their functions and biological roles. Advanced techniques--crystallography, NMR, and CryoEM--have facilitated the determination of over 180,000 protein structures, all cataloged in the Protein Data Bank (PDB). This comprehensive repository has been pivotal in developing deep learning algorithms for predicting protein structures directly from sequences. In contrast, RNA structure prediction has lagged, and suffers from a scarcity of structural data. Here, we present the secondary structure models of 1098 pri-miRNAs and 1456 human mRNA regions determined through chemical probing. We develop a novel deep learning architecture, inspired from the Evoformer model of Alphafold and traditional architectures for secondary structure prediction. This new model, eFold, was trained on our newly generated database and over 300,000 secondary structures across multiple sources. We benchmark eFold on two new test sets of long and diverse RNA structures and show that our dataset and new architecture contribute to increasing the prediction performance, compared to similar state-of-the-art methods. All together, our results reveal that merely expanding the database size is insufficient for generalization across families, whereas incorporating a greater diversity and complexity of RNAs structures allows for enhanced model performance.

biochemistry↗

bioRxiv2024

Quantifying the advantage of multimodal data fusion for survival prediction in cancer patients

The last decade has seen an unprecedented advance in technologies at the level of high-throughput molecular assays and image capturing and analysis, as well as clinical phenotyping and digitization of patient data. For decades, genotyping (identification of genomic alterations), the casual anchor in biological processes, has been an essential component in interrogating disease progression and a guiding step in clinical decision making. Indeed, survival rates in patients tested with next-generation sequencing have been found to be significantly higher in those who received a genome-guided therapy than in those who did not. Nevertheless, DNA is only a small part of the complex pathophysiology of cancer development and progression. To assess a more complete picture, researchers have been using data taken from multiple modalities, such as transcripts, proteins, metabolites, and epigenetic factors, that are routinely captured for many patients. Multimodal machine learning offers the potential to leverage information across different bioinformatics modalities to improve predictions of patient outcome. Identifying a multiomics data fusion strategy that clearly demonstrates an improved performance over unimodal approaches is challenging, primarily due to increased dimensionality and other factors, such as small sample sizes and the sparsity and heterogeneity of data. Here we present a flexible pipeline for systematically exploring and comparing multiple multimodal fusion strategies. Using multiple independent data sets from The Cancer Genome Atlas, we developed a late fusion strategy that consistently outperformed unimodal models, clearly demonstrating the advantage of a multimodal fusion model.

bioinformatics↗

bioRxiv2023

A complete morphological characterization of all life stages of the phorid fly M. scalaris

Megaselia scalaris, commonly known as the scuttle fly, is a cosmopolitan species in the family Phoridae. It is an easily cultured fly species that is an emerging model organism in the fields of genetics and developmental biology. Its affinity for carrion and its predictable life cycle makes it useful in the field of forensic science for estimating the post-mortem interval (PMI) of human remains. Cases of human myasis caused by M. scalaris have also been reported in the medical literature. Despite its ubiquitous prevalence and its relevance across multiple fields, its morphology has not been adequately characterized. Here, we report the complete morphological characterization of all lifestages of M. scalaris, ranging from egg to adult. Scanning electron microscopy has enabled us to uncover morphological features and developmental processes that have previously not been reported in the literature. Our data lays the groundwork for future genetic studies: a morphological characterization of the wild type must be performed before mutants displaying different phenotypes can be identified. In this vein, we also report the observation of a acephalic, or headless, adult phenotype whose study could yield insights into the process of cephalogenesis.

zoology↗

bioRxiv2021

Comparative metabolomics of fruits and leaves in a hyperdiverse lineage suggests fruits are a key incubator of phytochemical diversification

Interactions between plants and leaf herbivores have long been implicated as the major driver of plant secondary metabolite diversity. However, other plant-animal interactions, such as those between fruits and frugivores, may also be involved in phytochemical diversification. Using 12 species of Piper, we conducted untargeted metabolomics and molecular networking with extracts of fruits and leaves. We evaluated organ-specific secondary metabolite composition and compared multiple dimensions of phytochemical diversity across organs, including richness, structural complexity, and variability across samples at multiple scales within and across species. Plant organ identity significantly influenced secondary metabolite composition, both independent of and in interaction with species identity. Leaves and fruit shared a majority of compounds, but fruits contained more unique compounds and had higher total estimated chemical richness. While organ-level chemical richness and structural complexity varied substantially across species, fruit diversity exceeded leaf diversity in more species than the reverse. Furthermore, the variance in chemical composition across samples was higher for fruits than leaves. By documenting a broad pattern of high phytochemical diversity in fruits relative to leaves, this study lays groundwork for incorporating fruit into a comprehensive and integrative understanding of the ecological and evolutionary factors shaping secondary metabolite composition at the whole-plant level.

plant biology↗