Biology subjects

Ahmed, O.

Publications and source records attributed to Ahmed, O..

11 recordsLinked to original sources

bioRxiv2025

Quality control of single-cell ATAC-seq data without peak calling using Chromap

In this work, we extend Chromap, an ultrafast method for single-cell ATAC-seq data alignment, to directly report peak-based quality control (QC) metrics, such as the fraction of reads in peaks, without calling peaks. Recent single-cell ATAC-seq analysis methods like SnapATAC2 utilize the genome-interval-based feature for data analysis, which disables filtering low-quality cells using common peak-based QC metrics. We show that Chromaps QC metrics capture additional low-quality cells missed by SnapATAC2 and improve downstream analysis results without sacrificing computational efficiency.

bioinformatics↗

bioRxiv2024

A draft Arab pangenome reference

Pangenomes represent a significant shift from relying on a single reference sequence to a robust set of assemblies, Arab populations remain significantly underrepresented; hence, we present the first Arab Pangenome Reference (APR) utilizing 53 individuals of diverse Arab ethnicities. We assembled nuclear and mitochondrial pangenomes using 35.27X high-fidelity long reads, 54.22X ultralong reads and 65.46X Hi-C reads yielded contiguous haplotype-phased de novo assemblies of exceptional quality, with an average N50 of 124.28 Mb. We discovered 111.96 million base pairs of novel euchromatic sequences absent from existing human pangenomes, the T2T-CHM13, GRCh38 reference human genomes, and other public datasets. We identified 8.94 million population-specific small variants and 235,195 structural variants within the Arab pangenome. We detected 883 gene duplications including 15.06% associated with recessive diseases and 1,436 bp of novel mitochondrial pangenome sequence. Our study provides a valuable resource for future genomic medicine initiatives in Arab population and other global populations.

genomics↗

bioRxiv2024

O-GlcNAcylation of FOXK1 orchestrates the E2F pathway and promotes oncogenesis

Gene transcription is a highly regulated process, and deregulation of transcription factors activity underlies numerous pathologies including cancer. Albeit near four decades of studies have established that the E2F pathway is a core transcriptional network that govern cell division in multi-cellular organisms1,2, the molecular mechanisms that underlie the functions of E2F transcription factors remain incompletely understood. FOXK1 and FOXK2 transcription factors have recently emerged as important regulators of cell metabolism, autophagy and cell differentiation3-6. While both FOXK1 and FOXK2 interact with the histone H2AK119ub deubiquitinase BAP1 and possess many overlapping functions in normal biology, their specific functions as well as deregulation of their transcriptional activity in cancer is less clear and sometimes contradictory7-13. Here, we show that elevated expression of FOXK1, but not FOXK2, in primary normal cells promotes transcription of E2F target genes associated with increased proliferation and delayed entry into cellular senescence. FOXK1 expressing cells are highly prone to cellular transformation revealing important oncogenic properties of FOXK1 in tumor initiation. High expression of FOXK1 in patient tumors is also highly correlated with E2F gene expression. Mechanistically, we demonstrate that FOXK1, but not FOXK2, is specifically modified by O-GlcNAcylation. FOXK1 O-GlcNAcylation is modulated during the cell cycle with the highest levels occurring during the time of E2F pathway activation at G1/S. Moreover, loss of FOXK1 O-GlcNAcylation impairs FOXK1 ability to promote cell proliferation, cellular transformation and tumor growth. Mechanistically, expression of FOXK1 O-GlcNAcylation-defective mutants results in reduced recruitment of BAP1 to gene regulatory regions. This event is associated with a concomitant increase in the levels of histone H2AK119ub and a decrease in the levels of H3K4me1, resulting in a transcriptional repressive chromatin environment. Our results define an essential role of O-GlcNAcylation in modulating the functions of FOXK1 in controlling the cell cycle of normal and cancer cells through orchestration of the E2F pathway.

molecular biology↗

bioRxiv2023

DandD: efficient measurement of sequence growth and similarity

Genome assembly databases are growing rapidly. The sequence content in each new assembly can be largely redundant with previous ones, but this is neither conceptually nor algorithmically easy to measure. We propose new methods and a new tool called DandD that addresses the question of how much new sequence is gained when a sequence collection grows. DandD can describe how much human structural variation is being discovered in each new human genome assembly and when discoveries will level off in the future. DandD uses a measure called {delta} ("delta"), developed initially for data compression. Computing {delta} directly requires counting k-mers, but DandD can rapidly estimate it using genomic sketches. We also propose {delta} as an alternative to k-mer-specific cardinalities when computing the Jaccard coefficient, avoiding the pitfalls of a poor choice of k. We demonstrate the utility of DandDs functions for estimating {delta}, characterizing the rate of pangenome growth, and computing allpairs similarities using k-independent Jaccard. DandD is open source software available at: https://github.com/jessicabonnie/dandd.

bioinformatics↗

bioRxiv2022

Kupffer cells dictate hepatic responses to the atherogenic dyslipidemic insult

Apolipoprotein-B (APOB) containing lipoproteins are causative for atherosclerotic cardiovascular disease. Whether the vasculature is the initial responding site or if atherogenic-dyslipidemia effects other organs simultaneously is unknown. We set out to discover how the liver responds to a dyslipidemic insult through the creation of inducible mouse models based on human familial hypercholesterolemia mutations and in vivo tracing of APOB. An acute transition to atherogenic APOB-lipoprotein plasma levels resulted in rapid accumulation of triglycerides and cholesterol in the liver. Single cell RNA-seq and flow cytometry disclosed that multiple immune cells have the ability to engulf APOB-lipoproteins. However bulk RNA-seq of the liver revealed an inflammatory Kupffer cell-specific transcriptional program that could not be activated by a western diet alone. Depletion of Kupffer cells through clodronate liposomes or CD8 T cell targeting rapidly raised plasma lipoprotein levels, indicating that these liver macrophages help restrain and buffer atherogenic lipoproteins, whilst simultaneously secreting pro-atherosclerotic factors into plasma. Our results place Kupffer cells as a key gateway in organizing systemic responses at the initiation of atherosclerosis.

immunology↗

bioRxiv2022

SPUMONI 2: Improved pangenome classification using a compressed index of minimizer digests

Genomics analyses often use a large sequence collection as a reference, like a pangenome or taxonomic database. We previously described SPUMONI, which performs binary classification of nanopore reads using pangenomic matching statistics. Here we describe SPUMONI 2, an improved version that is faster, more memory efficient, works effectively for both short and long reads, and can solve multi-class classification problems with the aid of a novel sampled document array structure. By incorporating minimizers, SPUMONI 2 reduces index size by a factor of 2 compared to SPUMONI, yielding an index more than 65 times smaller than minimap2s for a mock community pangenome. SPUMONI 2 also achieves a speed improvement of 3-fold compared to SPUMONI and 15-fold compared to minimap2. We show SPUMONI 2 achieves an advantageous mix of accuracy and efficiency for short and long reads, including in an adaptive sampling scenario. We further demonstrate that SPUMONI 2 can detect contaminated contigs in genome assemblies, and can perform multi-class metagenomic read classification.

bioinformatics↗

bioRxiv2022

Seasonal eDNA-based monitoring of Batrachochytrium dendrobatidis and amphibian species in Norway

Freshwaters represent the most threatened environments with regard to biodiversity loss and therefore there is a need for national monitoring programs to effectively document species distribution and evaluate potential risks for vulnerable species. The monitoring of species for effective management practices is, however, challenged by insufficient data acquisition when using traditional methods. Here we present the application of environmental DNA (eDNA) metabarcoding of amphibians in combination with quantitative PCR assays for an invasive pathogenic chytrid species (Batrachochytrium dendrobatidis-Bd), a potential threat to endemic and endangered amphibian species. Statistical comparison of amphibian species detection using either traditional or eDNA-based approaches showed weak correspondence. By tracking the distribution of Bd over three years, we concluded that the risk for amphibian extinction is low since Bd was only detected at five sites where multiple amphibians were present over the sampled years. Our results show that eDNA-based detection can be used for simultaneous monitoring of amphibian diversity and the presence of amphibian pathogens at the national level in order to assess potential species extinction risks and establish effective management practices. As such our study represents suggestions for a national monitoring program based on eDNA.

ecology↗

bioRxiv2022

Detecting aquatic pathogens with field-compatible dried qPCR assays

Field-ready qPCR assays with a long shelf-life support monitoring programs for emerging aquatic pathogens and enable quick conservation and management decisions. Here, we develop, validate, and test the shelf-life of qPCR assays targeting Gyrodactylus salaris and Aphanomyces astaci with lyophilization and air-drying.

microbiology↗

bioRxiv2021

Pan-genomic Matching Statistics for Targeted Nanopore Sequencing

Nanopore sequencing is an increasingly powerful tool for genomics. Recently, computational advances have allowed nanopores to sequence in a targeted fashion; as the sequencer emits data, software can analyze the data in real time and signal the sequencer to eject "non-target" DNA molecules. We present a novel method called SPUMONI, which enables rapid and accurate targeted sequencing with the help of efficient pangenome indexes. SPUMONI uses a compressed index to rapidly generate exact or approximate matching statistics (half-maximal exact matches) in a streaming fashion. When used to target a specific strain in a mock community, SPUMONI has similar accuracy as minimap2 when both are run against an index containing many strains per species. However SPUMONI is 12 times faster than minimap2. SPUMONIs index and peak memory footprint are also 15 to 4 times smaller than minimap2, respectively. These improvements become even more pronounced with even larger reference databases; SPUMONIs index size scales sublinearly with the number of reference genomes included. This could enable accurate targeted sequencing even in the case where the targeted strains have not necessarily been sequenced or assembled previously. SPUMONI is open source software available from https://github.com/oma219/spumoni.

bioinformatics↗

bioRxiv2020

Megadepth: efficient coverage quantification for BigWigs and BAMs

MotivationA common way to summarize sequencing datasets is to quantify data lying within genes or other genomic intervals. This can be slow and can require different tools for different input file types. ResultsMegadepth is a fast tool for quantifying alignments and coverage for BigWig and BAM/CRAM input files, using substantially less memory than the next-fastest competitor. Megadepth can summarize coverage within all disjoint intervals of the Gencode V35 gene annotation for more than 19,000 GTExV8 BigWig files in approximately one hour using 32 threads. Megadepth is available both as a command-line tool and as an R/Bioconductor package providing much faster quantification compared to the rtracklayer package. Availabilityhttps://github.com/ChristopherWilks/megadepth, https://bioconductor.org/packages/megadepth. Contactchris.wilks@jhu.edu

bioinformatics↗

bioRxiv2020

A machine-vision approach for automated pain measurement at millisecond timescales

Objective and automatic measurement of pain in mice remains a barrier for discovery in both basic and translational neuroscience. Here we capture rapid paw kinematics during pain behavior in mice with high-speed videography and automated paw tracking with machine and deep learning approaches. Our statistical software platform, PAWS (Pain Assessment at Withdrawal Speeds), uses a univariate projection of paw position over time to automatically quantify fast paw dynamics at the onset of paw withdrawal and also lingering pain-related behaviors such as paw guarding and shaking. Applied to innocuous and noxious stimuli across six inbred mouse strains, a linear discriminant analysis reveals a two-dimensional subspace that separates painful from non-painful stimuli on one axis, and further distinguishes the severity of pain on the second axis. Automated paw tracking combined with PAWS reveals behaviorally-divergent mouse strains that display hypo- and hyper-sensitivity to mechanical stimuli. To demonstrate the efficacy of PAWS for detecting hypersensitivity to noxious stimuli, we chemogenetically activated pain-aversion neurons in the amygdala, which further separated the behavioral representation of pain-related behaviors along a low-dimensional path. Taken together, this automated pain quantification approach should increase the ease and objectivity of collecting rigorous behavioral data, and it is compatible with other neural circuit dissection tools for determining the mouse pain state.

neuroscience↗