bioRxiv Science⌕ Search

Biology subjects

Jastrzebski, J. P.

Publications and source records attributed to Jastrzebski, J. P..

2 recordsLinked to original sources

PMScanR: an R package for the large-scale identification, analysis, and visualization of protein motifs

Proteins play a crucial role in biological processes, with their functions closely related to structure. Protein functions are often associated with the presence of specific motifs, which are short amino acid sequences with a specific amino acid pattern. Most bioinformatics tools focus on identifying known motifs and they lack the ability to analyze the impact of single substitutions on entire domains or motifs. To address this, we developed PMScanR, an R-based library that automates the prediction and evaluation of the impact of single amino acid substitutions on the occurrence of protein motifs in large datasets. In addition, existing tools do not support comparative analysis of multiple motifs across multiple sequences - a key feature that PMScanR was designed to provide. The package integrates various methods to facilitate motif identification, characterization, and visualization. It includes functions for running PS-Scan, a PROSITE database tool. Additionally, PMScanR supports format conversion to GFF, enhancing downstream analyses such as graphical representation and database integration. The library offers multiple visualization tools, including heatmaps, sequence logos, and pie charts, enabling a deeper understanding of motif distribution and conservation. Through its integration with PROSITE, PMScanR provides access to up-to-date motif data, making it a valuable tool for biological and biomedical research, particularly in protein function annotation and therapeutic target identification. The PMScanR library is freely available (GPL license) on Bioconductor. The source code, precompiled library, installation instructions, tutorial files, and complete documentation can be found on GitHub: github.com/prodakt/PMScanR.

bioinformatics↗

A journey to understanding larval quality in fish by integrating transcriptomics and zootechnics

Transcriptomic analysis of freshly hatched fish larvae offers insights into phenotype development, yet it remains uncertain whether it reflects parental influence or predicts individual growth. This research scrutinizes the transcriptome of 16 Eurasian perch (Perca fluviatilis) larval groups alongside pre- and post-hatching traits. Despite consistent fertilization rates, significant variations in embryonic development and larval performance highlight diverse phenotypes studied. It enabled to bring our attention to the fact that larval transcriptome can serve as a window into both the parental contributions and the future performance of the larvae. Our further analysis shed light on ribosome biogenesis, neurogenesis, and the cell cycle, as important processes shaping early larval performance. Additionally, we propose a set of predictive, validated gene markers associated with further larval performance and key aquaculture traits, such as selenoo (associated with cannibalism), trim16 (fultons condition factor), slc15a1 (specific growth factor), and cipc (final weight). This study delves into the descriptive and predictive nature of the transcriptomic portrait of newly hatched larvae, paving the way to comprehend the intricate developmental pathways from fertilization towards juvenile stage.

developmental biology↗