Biology subjects

Patikas, N.

Publications and source records attributed to Patikas, N..

3 recordsLinked to original sources

bioRxiv2026

Integration of large, complex single-cell datasets with Harmony2

Integrating single cell RNA-seq profiles is posing new challenges as datasets are rapidly expanding, now with over 100 million cells in the public domain. We present the latest version of the Harmony integration software, which efficiently scales to >100M cells and >1K datasets without specialized hardware. Moreover, optimizations to the underlying algorithm help prevent overintegration in biologically heterogeneous datasets. Harmony2 enables efficient, accurate integration of large, complex single-cell atlases.

bioinformatics↗

bioRxiv2022

HNRNPH1 regulates the neuroprotective cold-shock protein RBM3 expression through poison exon exclusion

Enhanced expression of the cold-shock protein RNA binding motif 3 (RBM3) is highly neuroprotective both in vitro and in vivo. Whilst upstream signalling pathways leading to RBM3 expression have been described, the precise molecular mechanism of RBM3 induction during cooling remains elusive. To identify temperature-dependent modulators of RBM3, we performed a genome-wide CRISPR-Cas9 knockout screen using RBM3-reporter human iPSC-derived neurons. We found that RBM3 mRNA and protein levels are robustly regulated by several splicing factors, with heterogeneous nuclear ribonucleoprotein H1 (HNRNPH1) being the strongest positive regulator. Splicing analysis revealed that moderate hypothermia significantly represses the inclusion of a poison exon, which, when retained, targets the mRNA for nonsense-mediated decay. Importantly, we show that HNRNPH1 mediates this cold-dependent exon skipping via its interaction with a G-rich motif within the poison exon. Our study provides novel mechanistic insights into the regulation of RBM3 and provides further targets for neuroprotective therapeutic strategies. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/514062v1_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@ef0a5org.highwire.dtl.DTLVardef@d907a5org.highwire.dtl.DTLVardef@85176aorg.highwire.dtl.DTLVardef@1c4306a_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2019

Fast searches of large collections of single cell data using scfind

Single cell technologies have made it possible to profile millions of cells, but for these resources to be useful they must be easy to query and access. To facilitate interactive and intuitive access to single cell data we have developed scfind, a search engine for cell atlases. Using transcriptome data from mouse cell atlases we show how scfind can be used to evaluate marker genes, to perform in silico gating, and to identify both cell-type specific and housekeeping genes. Moreover, we have developed a subquery optimization routine to ensure that long and complex queries return meaningful results. To make scfind more user friendly and accessible, we use indices of PubMed abstracts and techniques from natural language processing to allow for arbitrary queries. Finally, we show how scfind can be used for multi-omics analyses by combining single-cell ATAC-seq data with transcriptome data.

bioinformatics↗