Biology subjects

Gohar, Y.

Publications and source records attributed to Gohar, Y..

4 recordsLinked to original sources

bioRxiv2026

KIR*BLOOM: Accurate KIR genotyping using a new copy number-aware integrated genotype likelihood framework

Killer-cell immunoglobulin-like receptor (KIR) genes, key modulators of natural killer (NK) cell activity, play critical roles in immune response and disease susceptibility. Accurate KIR genotyping from short-read sequencing data remains challenging because of high sequence similarity among genes, extensive copy number variation, and substantial allelic diversity. Here, we present KIR*BLOOM, a likelihood-based approach for KIR genotyping from short-read data that models read depth and sequencing error across alternative genotype configurations. KIR*BLOOM first identifies KIR-relevant read pairs, maps them to a KIR allele database, and reduces the candidate allele space by excluding alleles unlikely to be present. It then infers gene copy number and selects alleles under the inferred copy-number constraints. Finally, variant calling is used to refine CDS sequences and identify potential novel alleles. We evaluated performance on 45 whole-genome sequencing samples with haplotype-resolved assemblies from the HPRC or HGSVC, using Immuannot-derived annotations as ground truth. KIR*BLOOM achieved 99.85% precision, 99.92% recall, and a Jaccard index of 99.77% for copy-number inference. At five-digit allele resolution, it achieved 92.73% precision, 92.69% recall, and an 87.29% Jaccard index, outperforming T1K, GraphKIR, and Geny. Together, these results demonstrate that KIR*BLOOM enables highly accurate KIR genotyping from short-read sequencing data.

bioinformatics↗

bioRxiv2026

The Interaction with Nanotopographical Environment regulates nuclear mechanoresponse in mESCs via Histone Demethylase KDM3A

Cell identity is traditionally viewed as a product of biochemical signalling, yet cells are exposed to defined physical landscapes, whose role in fate control remains unclear. In particular, how pluripotent stem cells integrate nanoscale extracellular cues into gene regulatory programs remains poorly understood. Here, we show that biomimetic substrate nanotopography acts as a potent regulator of naive pluripotency in mouse embryonic stem cells (mESCs). Using supersonic cluster beam deposition, we generate substrates with defined nanotopography that recapitulate native features of extracellular matrix. We demonstrate that nanotopography induces a mechanically relaxed cell state characterised by reduced adhesion, cellular and nuclear softening, and altered nuclear architecture. These mechanical changes are coupled with chromatin remodelling, including reduced H3K27me3 and H3K9me2, redistribution of H3K9me3, and increased H3K4me3. Transcriptomic analyses reveal suppression of adhesion- and cytoskeleton-associated programs together with the activation of a naive pluripotency transcriptional signature, including upregulation of Nanog. Mechanistically, we identify the H3K9 demethylase KDM3A as a mechanosensitive epigenetic regulator required for nanotopography-induced Nanog expression. Together, our findings uncover a novel mechanotransductive pathway directly linking extracellular nanotopography to chromatin state and pluripotency control.

molecular biology↗

bioRxiv2025

Intra-Strain Genetic Heterogeneity in Toxoplasma gondii ME49: Oxford Nanopore Long-Read Sequencing Reveals Copy Number Variation in the ROP8-ROP2A Locus

BackgroundToxoplasma gondii is an important pathogen and model organism for studying mechanisms of immune evasion and defense. Within the same strain, model organisms are typically assumed to be isogenic; for T. gondii, within-strain genetic divergence has been detected based on phenotypic changes and older molecular techniques but not characterized at the genomic level. We therefore used Oxford Nanopore long-read sequencing to characterize three independently maintained T. gondii ME49 isolates: 2015T and 2020T (obtained from ATCC and propagated in cell culture), and 2000B (propagated in mice). ResultsWe de novo assembled a new T. gondii ME49 reference genome and, using state of-the-art variant calling combined with pangenomic genotyping, detected variants between the sequenced isolates. Our new reference genome exceeded existing reference genomes in continuity (NG50 = 6.68 Mb versus 1.2 Mb in RefSeq) and structural accuracy, resolving all chromosomes except for a single break in the ribosomal DNA region. For isolates 2000B and 2020T, we identified 106 and 128 variants, respectively, across a final call set of 79 SNVs, 93 INDELs, and five structural variants; 18 small non-synonymous variants included genes associated with T. gondii life cycle (AP2X-8) and virulence in vivo (6-phosphogluconate dehydrogenase). A 13 kb expansion in the ROP8-ROP2A virulence locus increased the copy number of ROP2A-ROP8 genes in isolates 2000B and 2020T from three to six. ConclusionsWe provide an improved T. gondii ME49 reference genome and demonstrate the potentially confounding effect of intra-strain genetic heterogeneity, highlighting the need for continuous genomic monitoring for long-term genetic identity.

genomics↗

bioRxiv2023

Transcriptional clusters follow a conserved condensation-dispersal sequence during stem cell differentiation

Spatiotemporal organization of transcription is essential for organism development. Most eukaryotic genes are transcribed by RNA polymerase II (Pol II). In stem cells, Pol II forms prominent clusters, which gradually disappear during differentiation, such that only smaller clusters remain. Here, we ask whether the formation and loss of large Pol II clusters is a stereotypical process explicable by changes in the Pol II transcriptional state during differentiation. We assess clusters by super-resolution microscopy in differentiating mouse embryonic stem cells, sperm precursor formation in fruit flies, and germ layer induction in zebrafish. In all cases, Pol II clusters first become larger and rounder, then unfold, and finally disperse into small clusters. These shape changes are accompanied by initial increase in recruited Pol II, subsequent transition into transcript elongation, and finally reduction of active enhancers. We reproduce these observations using a biophysical surface condensation model, where enhancers support Pol II cluster formation, and transcriptional activity unfolds clusters. Our work indicates that changes in enhancer marks and transcriptional activity during differentiation define a stereotyped trajectory through a generally applicable space of cluster shapes. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=189 HEIGHT=200 SRC="FIGDIR/small/547621v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@1fb769borg.highwire.dtl.DTLVardef@27f6a0org.highwire.dtl.DTLVardef@1b0ab7corg.highwire.dtl.DTLVardef@1ca932d_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗