Biology subjects

Rahmat, J.

Publications and source records attributed to Rahmat, J..

4 recordsLinked to original sources

bioRxiv2026

kmerRRR: A k-mer based tool for functional genomics in Repeat Rich Regions

Highly repetitive sequences pose problems for genome assembly and analysis. While advances in long-read sequencing technologies have helped reveal the organization of repetitive genomic sequences at unprecedented resolution, their functional characterization remains difficult because molecular assays that probe protein-DNA interactions and characterize expression often rely on short read sequencing. The repetitive nature of these regions poses major challenges for methods relying on sequence mapping, which is exacerbated for short reads. Repetitive genome regions often have low mappability, leading to substantial information loss during downstream filtering. To address this challenge, we developed a bioinformatic tool--kmerRRR--that leverages k-mer frequency analyses to enhance the mappability of repetitive regions. KmerRRR compares k-mer frequencies within user-defined loci to their frequencies across the genome to identify repetitive sequences that are overrepresented locally relative to the global background. This approach quantifies locus uniqueness, allowing users to distinguish sequences that are globally repetitive from those that are repetitive, but restricted to specific genomic loci. We demonstrated the utility of this method by reanalyzing chromatin profiling data from human, Drosophila, and Arabidopsis centromeres and small RNA sequencing data. Our results show that incorporating local k-mer ratio information enhances read retention and signal interpretation within repetitive regions, thereby recovering biologically meaningful information that is typically lost in conventional analyses. The tool is freely available under MIT license in github: (https://github.com/LarracuenteLab/kmerRRR).

genomics↗

bioRxiv2026

Targeted editing of pericentromeric satellite DNA alters sensitivity to meiotic drive

Eukaryotic genomes are abundant in satellite DNA (satDNA): large blocks of tandemly-repeated sequences that accumulate in heterochromatic genome regions. SatDNAs are dynamic in their genomic location and abundance across species. Some satDNAs overlap essential genome regions such as centromeres and telomeres, but even pericentromeric satDNA can have effects on phenotypes, raising questions about their functional significance. However, it remains unclear whether these effects depend on satDNA sequence, copy number, higher-order structural organization, or genomic context. The highly repetitive nature of satDNA arrays has long hindered detailed genomic and genetic analyses. Recent advances in long-read sequencing now facilitate both the detailed characterization of satDNA structure and the development of more targeted approaches to genetic analysis. Here we present a sequential CRISPR/Cas9-based strategy to make mutations in satDNA arrays and demonstrate its utility using an autosomal pericentromeric satDNA in Drosophila melanogaster called Responder (Rsp). Rsp is the target of a sperm-killing male meiotic driver, Segregation Distorter (SD), where sensitivity to sperm killing positively correlates with Rsp copy number. Using our CRISPR/Cas9 approach, we generated an allelic series of Rsp deletion and expansion variants in two genetic backgrounds and examined their effects on spermatogenesis. Our approach produced precise satDNA variants efficiently, with minimal detectable off-target effects. The resulting mutations affect sensitivity to SD that scale with Rsp copy number. This work establishes a new framework for experimentally dissecting satDNA function and provides insights into the evolutionary and functional roles of satDNA in genome organization.

genetics↗

bioRxiv2024

Regulatory genome annotation of 33 insect species

Annotation of newly-sequenced genomes frequently includes genes, but rarely covers important non-coding genomic features such as the cis-regulatory modules--e.g., enhancers and silencers--that regulate gene expression. Here, we begin to remedy this situation by developing a workflow for rapid initial annotation of insect regulatory sequences, and provide a searchable database resource with enhancer predictions for 33 genomes. Using our previously-developed SCRMshaw computational enhancer prediction method, we predict over 2.8 million regulatory sequences along with the tissues where they are expected to be active, in a set of insect species ranging over 360 million years of evolution. Extensive analysis and validation of the data provides several lines of evidence suggesting that we achieve a high true-positive rate for enhancer prediction. One, we show that our predictions target specific loci, rather than random genomic locations. Two, we predict enhancers in orthologous loci across a diverged set of species to a significantly higher degree than random expectation would allow. Three, we demonstrate that our predictions are highly enriched for regions of accessible chromatin. Four, we achieve a validation rate in excess of 70% using in vivo reporter gene assays. As we continue to annotate both new tissues and new species, our regulatory annotation resource will provide a rich source of data for the research community and will have utility for both small-scale (single gene, single species) and large-scale (many genes, many species) studies of gene regulation. In particular, the ability to search for functionally-related regulatory elements in orthologous loci should greatly facilitate studies of enhancer evolution even among distantly related species.

genomics↗

bioRxiv2020

Transcriptomic dysregulations associated with SARS-CoV-2 infection in human nasopharyngeal and peripheral blood mononuclear cells

IntroductionOver 24 million people have been infected globally with the novel coronavirus, SARS-CoV-2, with more than 820,000 succumbing to the resulting COVID-19 disease as of the end of August 2020. The molecular mechanisms underlying the pathogenesis of the disease are not completely elucidated. Thus, we aim to understand host response to SARS-CoV-2 infection by comparing samples collected from two distinct compartments (infection site and blood), obtained from COVID-19 subjects and healthy controls. MethodsWe used two publicly available gene expression datasets generated via RNA sequencing in two different samples; nasopharyngeal swabs and peripheral blood mononuclear cells (PBMCs). We performed a differential gene expression analysis between COVID-19 subjects and healthy controls in the two datasets and then functionally profiled their differentially expressed genes (DEGs). The genes involved in innate immunity were also determined. ResultsWe found a clear difference in the host response to SARS-CoV-2 infection between the two sample groups. In COVID-19 subjects, the nasopharyngeal sample group indicated upregulation of genes involved in cytokine activity and interferon signalling pathway, as well as downregulation of genes involved in oxidative phosphorylation and viral transcription. Host response in COVID-19 subjects for the PBMC group, involved upregulation of genes involved in the complement system and immunoglobulin mediated immune response. CXCL13, GABRE, IFITM3 were upregulated and HSPA1B was downregulated in COVID-19 subjects in both sample groups. ConclusionOur results indicate the host response to SARS-CoV-2 is compartmentalized and suggests potential biomarkers of response to SARS-CoV-2 infection. HighlightsO_LITranscriptomic profiling from publicly available RNA-seq count data revealed a site-specific immune response in COVID-19. C_LIO_LIHost response was found cellular-mediated in nasopharyngeal samples and humoral-mediated in PBMCs samples. C_LIO_LICXCL13, GABRE and IFITM3 commonly upregulated and HSPA1B downregulated in both sample groups highlights the potential of these molecules as markers of response to SARS-CoV-2 infection. C_LI

immunology↗