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Biology subjects

Aninta, S. I.

Publications and source records attributed to Aninta, S. I..

2 recordsLinked to original sources

Position-dependent variant effects reveal importance of context in genomic regulation

Gene expression is governed by the DNA sequence, which is read out through complex interactions between transcription factors (TFs), co-activators, and chromatin. Massively Parallel Reporter Assays (MPRAs) provide a high-throughput framework for functionally characterizing how regulatory DNA sequences impact the expression of a model gene. MPRAs have also proven to be useful for measuring the effects of genetic variation, where each allele is typically tested in the center of [~]200 bp of genomic context cloned into the MPRA; but the impact of variant position and local context remains largely unexplored. In this study, we systematically investigate how shifting the position of a variant within an MPRA probe influences its regulatory activity using models that predict expression in MPRAs from DNA sequence. We find that while the direction of variant effects is usually preserved across positions, the magnitude of expression changes can vary substantially depending on where the variant is placed within the construct. This positional bias appears to be largely explained by the strong position-dependent activity of TFs whose binding the variants perturb. In a subset of cases, interactions consistent with cooperativity between TFs also contributes to position-specific effects. [~]1% of variants appear to disrupt RNA polymerase III (Pol III) promoters within Alu elements, resulting in position-specificity because both A and B boxes are required for function and exclusion of either motif due to window shifts disrupts the variants effects. However, we saw little evidence to support the hypothesis that the positional dependence of variant effects resulted from redundancy of motifs. Overall, our study demonstrates the complexity of cis-regulatory grammar and how it can confound the interpretation of regulatory variants.

genomics↗

Mining the UniProtKB/Swiss-Prot database forantimicrobial peptides

The ever-growing global health threat of antibiotic resistance is compelling researchers to explore alternatives to conventional antibiotics. Antimicrobial peptides (AMPs) are emerging as a promising solution to fill this need. Naturally occurring AMPs are produced by all forms of life as part of the innate immune system. High-throughput bioinformatics tools have enabled fast and large-scale discovery of AMPs from genomic, transcriptomic, and proteomic resources of selected organisms. Public protein sequence databases, comprising over 200 million records and growing, serve as comprehensive compendia of sequences from a broad range of source organisms. Yet, large-scale in silico probing of those databases for novel AMPs has never been reported. In the present study, we propose an AMP mining workflow to predict novel AMPs from the UniProtKB/Swiss-Prot database using the AMP prediction tool, AMPlify, as its discovery engine. Using this workflow, we identified 8,008 novel putative AMPs from all eukaryotic sequences in the database. Focusing on the practical use of AMPs as suitable antimicrobial agents with applications in the poultry industry, we prioritized 40 of those AMPs based on their similarities to known chicken AMPs in predicted structures. In our tests, 13 out of the 38 successfully synthesized peptides showed antimicrobial activity against Escherichia coli and/or Staphylococcus aureus.

bioinformatics↗