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Mahecha, D.

Publications and source records attributed to Mahecha, D..

2 recordsLinked to original sources

Single Cell Transcriptomics of Refractory Epilepsy patients in Colombia

Maintaining electrical signaling homeostasis in the human neocortex relies on cell-type specific gene expression programs. However, when these programs are disrupted, the resulting imbalances can contribute to the pathogenesis of neurological disorders like epilepsy. Genetic factors are particularly implicated in a specific subtype of epilepsy known as refractory epilepsy or drug-resistant epilepsy (RE/DRE). This study shows the main results of the analysis of single cell transcriptomics for five pediatric RE patients in Colombia. A total of six samples obtained through surgical resection were analyzed by single-nuclei RNA sequencing (snRNA-seq). The genome of one patient was sequenced using high fidelity long-read sequencing. Functional enrichment of differentially expressed genes (DEGs) revealed glia-driven dysregulation of synaptic signaling, impaired glial-neuronal communication, and altered expression of genes related to neurotransmitter transport and calcium signaling. Activation of taste receptors in neurons was associated with neuroinflammatory processes. Structural variants were detected in genes associated with alterations of expression in specific cell types. This new data resource increases the diversity of information needed to develop new strategies for diagnosis of refractory epilepsy.

neuroscience↗

NGSEP 4: Efficient and Accurate Identification of Orthogroups and Whole Genome Alignment

Whole-genome alignment allows researchers to understand the genomic structure and variations among the genomes. Approaches based on direct pairwise comparisons of DNA sequences require large computational capacities. As a consequence, pipelines combining tools for orthologous gene identification and synteny have been developed. In this manuscript, we present the latest functionalities implemented in NGSEP 4, to identify orthogroups and perform whole genome alignments. NGSEP implements functionalities for identification of clusters of homologus genes, synteny analysis and whole genome alignment, and visualization. Our results showed that the NGSEP algorithm for ortholog identification has competitive accuracy and better efficiency in comparison to commonly used tools. The implementation also includes a visualization of the whole genome alignment based on synteny of the orthogroups that were identified, and a reconstruction of the pangenome based on frequencies of the orthogroups among the genomes. Finally, our software includes a new graphical user interface. We expect that these new developments will be very useful for several studies in evolutionary biology and population genomics.

bioinformatics↗