Biology subjects

Abugessaisa, I.

Publications and source records attributed to Abugessaisa, I..

12 recordsLinked to original sources

bioRxiv2025

Genome-wide mapping of the Galleria mellonella larvae transcription start sites during fungal infection and treatment

Using Low Quantity single strand CAGE (LQ-ssCAGE), we mapped the transcription start sites (TSS). We annotated the 5 end of the invertebrate Galleria mellonella, an upcoming and booming experimental model in infectious disease and immunology research. However, the current genome annotation of this model organism lacks annotation of the 5 end and TSS information. G. mellonella larva was infected with the fungal pathogen Madurella mycetomatis to map TSS under healthy and infection conditions. Larvae were first treated with itraconazole or ravuconazole, and then RNA-seq and LQ-ssCAGE libraries were prepared and sequenced 4, 30, and 52 hours following infection. The LQ-ssCAGE data was processed to identify CAGE transcription start site (CTSS), uni-, and bi-directional clusters. LQ-ssCAGE enabled us to precisely identify 39,410 TSS and 249 active enhancers; we assigned genomic features to the resulting TSSs and enhancers. The majority of the TSS peaks are annotated as promoter regions, while the enhancers were annotated as intergenic and genic. Furthermore, we confirmed the quality of TSS calling by promoter shapes and GC bias. Furthermore, we identified a set of super-enhancers and predicted de-novo motifs. The raw and processed data was deposited to NCBI GEO GSE282923. CTSS, TSS peaks, and enhancers coordinated are available through the ZENBU Genome browser. In this study, we reported the first atlas of TSS and active enhancers of G. mellonella.

genomics↗

bioRxiv2024

Impacts of Cell Ranger versions on Chromium gene expression data

In droplet-based single cell gene expression data, cell barcode processing by Cell Ranger (CR) is a standard pipeline. But no systematic evaluation of the impact of CR version on single cell gene expression data has been conducted. To comprehensively evaluate the impact of CR version, we considered six molecular quality criteria, quantified gene expression, and performed downstream analysis for 12 single-cell datasets. Each dataset was processed by 15 versions of CR. We demonstrated that different versions of CR yield different numbers of cell barcodes with significant variation in detected UMIs, features, molecular qualities and average gene expression of protein-coding and lncRNA for the same dataset. Our analysis finds distinction between two diverse categories of cell barcodes: common barcodes unmasked by all versions of CR, and specific barcodes only unmasked/masked by some versions. Surprisingly, we observed variation in molecular read-out between common cell barcodes when called by different versions of CR. The specific barcodes yield skewed gene body coverage and form distinct clusters. The choice of CR version affects scores for quality, average gene expression, clustering results, and top cluster marker genes of the dataset.

bioinformatics↗

bioRxiv2022

Iron regulatory pathways differentially expressed during Madurella mycetomatis grain development in Galleria mellonella

BackgroundMycetoma is a neglected, chronic granulomatous infection of the subcutaneous tissue, most often caused by the fungal pathogen Madurella mycetomatis. Characteristic of the infection is the formation of grains. However, knowledge of the function and formation of the grain is limited. To map the processes leading to M. mycetomatis grain formation, we used a Galleria mellonella larvae infection model and time-course transcriptomic profiling. MethodsGalleria mellonella larvae were infected with M. mycetomatis genome strain mm55. At 4h, 24h, 72h and 168h post-inoculation, RNA was extracted from larval content. Two types of sequencing libraries were prepared for time-course transcriptomic profiling and analysis. FindingsIn the infected G. mellonella, 88.0% of the RNA sequence reads mapped to G. mellonella, while only 0.01% mapped to M. mycetomatis. Differential Gene Expression analysis revealed that 3,498 G. mellonella and 136 M. mycetomatis genes were differentially expressed during infection. Most of the enriched GO terms of both host and pathogen are linked to energy pathways, nucleobase metabolic process as well as cation and iron transport. Genes related to iron transport were highly expressed by both G. mellonella (transferrin and ferritin) and M. mycetomatis (SidA, SidD and SidI). A protein-protein interaction network analysis of D. melanogaster homologous genes in M. mycetomatis revealed the expression of the entire siderophore biosynthesis pathway throughout infection. InterpretationThe identification of the importance of iron acquisition during grain formation can be exploited as a potential novel diagnostic and therapeutic strategy for mycetoma. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSMycetoma is a chronic, neglected tropical infectious disease, characterised by a large subcutaneous mass and the formation of black grains in the affected tissue. Treatment for mycetoma is disappointing as in 25-50% of the patients recurrences are noted and up to 15% of patients will have to undergo amputation. The main reason behind this poor treatment response is the formation of protective structures by the pathogen upon entering the human body. These structures are called grains and provide a strong barrier for antifungal agents. Although grains are the hallmark of mycetoma, it is currently not known how these grains are formed. To improve the current therapy, it is important to gain insights in grain formation. Added value of this studyWe unravel the processes leading to grain formation and development in an invertebrate model of Madurella mycetomatis grain. We were able to build a model of grain formation and demonstrated that iron sequestering plays an important role in this process. Our findings were an important milestone in understanding the pathogenesis of mycetoma which has been a mystery for decades. Implications of all the available evidenceThe findings, will provide leads for future drug development of mycetoma treatment and therefore, improve patients live and end the need for amputations.

microbiology↗

bioRxiv2022

The high-throughput perturbation of long non-coding RNA reveals functional features in stem cells and across cell-types

Within the scope of FANTOM6 consortium, we perform a large-scale knockdown of 200 long non-coding RNAs (lncRNAs) in human induced pluripotent stem (iPS) cells, and systematically characterize their roles in self-renewal and pluripotency. We find 36 lncRNAs (18%) exhibiting cell growth inhibition From the knockdown of 123 lncRNAs with transcriptome profiling, 36 lncRNAs (29.3%) show molecular phenotypes. Integrating the molecular phenotypes with chromatin-interaction assays further reveals cis- and trans-interacting partners as potential primary targets. Additionally, cell type enrichment analysis identifies lncRNAs associated with pluripotency while the knockdown of LINC02595, CATG00000090305.1 and RP11-148B6.2 modulates colony formation of iPS cells. We compare our results with previously published fibroblasts phenotyping data and find that 2.9% of the lncRNAs exhibit consistent cell growth phenotype, whereas we observe 58.3% agreement in molecular phenotypes. This highlights molecular phenotyping is more comprehensive in revealing affected pathways.

genomics↗

bioRxiv2021

Functional annotation of human long noncoding RNAs using chromatin conformation data

The human genome is pervasively transcribed and produces a wide variety of long non-coding RNAs (lncRNAs), constituting the majority of transcripts across human cell types. Studying lncRNAs is challenging due to their low expression level, cell type-specific occurrence, poor sequence conservation between orthologs, and lack of information about RNA domains. LncRNAs direct the regulatory factors in the locations that are in cis to their transcription sites. We designed a model to predict if an lncRNA acts in cis based on its features and trained it using RNA-chromatin interaction data. The trained model is cell type-independent and does not require RNA-chromatin data. Combining RNA-chromatin and Hi-C data, we showed that lncRNA-chromatin binding sites are determined by chromosome conformation. For each lncRNA, the spatially proximal genes were identified as their potential targets by combining Hi-C and Cap Analysis Gene Expression (CAGE) data in 18 human cell types. RNA-protein and RNA-chromatin interaction data suggested that lncRNAs act as scaffolds to recruit regulatory proteins to target promoters and enhancers. We provide the data through an interactive visualization web portal at https://fantom.gsc.riken.jp/zenbu/reports/#F6_3D_lncRNA.

genomics↗

bioRxiv2020

Single-cell transcriptomics, scRNA-Seq and C1 CAGE discovered distinct phases of pluripotency during naïve-to-primed conversion in mice

BackgroundTwo types of mammalian pluripotent stem cells (PSC), i.e. naive and primed possess distinct cellular characteristics. It is largely unknown how these differences are generated during naive-to-primed transition process. We have established a robust in vitro transition system using a Wnt inhibitor for the first time and analyzed dynamic changes in cellular status via single-cell RNA-sequencing and C1 CAGE analyses. ResultsAnalysis of known marker genes suggested that the cell transition process progresses as expected. However, cluster analyses revealed a sudden increase in expression profile diversities three and four days after induction of the transition. These expression diversities can be reconciled by the presence of two subpopulations with distinct transcription profiles emerging at these time points. One of the subpopulations appears transiently, and surprisingly these cells showed a global downregulation of gene expression. Moreover, initiation of random X chromosome inactivation (XCI) coincides with the appearance of these transient cells. The other subpopulation can be maintained as a stem cell line and possesses expression profiles more similar to those of primed epiblast stem cells (EpiSC) than embryonic stem cells (ESC). However, there are important differences in gene expression related to epithelial-mesenchymal transition (EMT), suggesting that this subpopulation may represent a novel pluripotent state that has an intermediate cellular phenotype between ESC and EpiSC. ConclusionsThese findings should contribute to our understanding of the establishment and maintenance of distinct differentiation statuses of mammalian PSCs and provide new insights into the pluripotency spectrum in general.

genomics↗

bioRxiv2020

Inducing Human Retinal Pigment Epithelium-like Cells from Somatic Tissue

Regenerative medicine relies on basic research to find safe and useful outcomes that are only practical when cost-effective. The human eyeball requires the retinal pigment epithelium (RPE) for support and maintenance that interfaces the neural retina and the choroid at large. Nearly 200 million people suffer from age-related macular degeneration (AMD), a blinding multifactor genetic disease among other retinal pathologies related to RPE degradation. Recently, autologous pluripotent stem cell-derived RPE cells were prohibitively expensive due to time, therefore we developed a new simplified cell reprogramming system. We stably induced RPE-like cells (iRPE) from human fibroblasts by conditional overexpression of broad plasticity and lineage-specific pioneering transcription factors. iRPE cells showed features of modern RPE benchmarks and significant in-vivo integration in transplanted chimeric hosts. Herein, we detail the iRPE system with comprehensive modern single-cell RNA (scRNA) sequencing profiling to interpret and characterize its best cells. We anticipate that our system may enable robust retinal cell induction for regenerative medicine research and affordable autologous human RPE tissue for cell therapy.

bioengineering↗

bioRxiv2019

Quality assessment of single-cell RNA sequencing data by coverage skewness analysis

Analysis and interpretation of single-cell RNA-sequencing (scRNA-seq) experiments are compromised by the presence of poor quality cells. For meaningful analyses, such poor quality cells should be excluded to avoid biases and large variation. However, no clear guidelines exist. We introduce SkewC, a novel quality-assessment method to identify poor quality single-cells in scRNA-seq experiments. The method is based on the assessment of gene coverage for each single cell and its skewness as a quality measure. To validate the method, we investigated the impact of poor quality cells on downstream analyses and compared biological differences between typical and poor quality cells. Moreover, we measured the ratio of intergenic expression, suggesting genomic contamination, and foreign organism contamination of single-cell samples. SkewC is tested in 37,993 single-cells generated by 15 scRNA-seq protocols. We envision SkewC as an indispensable QC method to be incorporated into scRNA-seq experiment to preclude the possibility of scRNA-seq data misinterpretation.

genomics↗

bioRxiv2019

Functional Annotation of Human Long Non-Coding RNAs via Molecular Phenotyping

Long non-coding RNAs (lncRNAs) constitute the majority of transcripts in the mammalian genomes and yet, their functions remain largely unknown. We systematically knockdown 285 lncRNAs expression in human dermal fibroblasts and quantified cellular growth, morphological changes, and transcriptomic responses using Capped Analysis of Gene Expression (CAGE). Antisense oligonucleotides targeting the same lncRNA exhibited global concordance, and the molecular phenotype, measured by CAGE, recapitulated the observed cellular phenotypes while providing additional insights on the affected genes and pathways. Here, we disseminate the largest to-date lncRNA knockdown dataset with molecular phenotyping (over 1,000 CAGE deep-sequencing libraries) for further exploration and highlight functional roles for ZNF213-AS1 and lnc-KHDC3L-2.

genomics↗

bioRxiv2018

C1 CAGE detects transcription start sites and enhancer activity at single-cell resolution

Single-cell transcriptomic profiling is a powerful tool to explore cellular heterogeneity. However, most of these methods focus on the 3-end of polyadenylated transcripts and provide only a partial view of the transcriptome. We introduce C1 CAGE, a method for the detection of transcript 5-ends with an original sample multiplexing strategy in the C1 microfluidic system. We first quantified the performance of C1 CAGE and found it as accurate and sensitive as other methods in C1 system. We then used it to profile promoter and enhancer activities in the cellular response to TGF-{beta} of lung cancer cells and discovered subpopulations of cells differing in their response. We also describe enhancer RNA dynamics revealing transcriptional bursts in subsets of cells with transcripts arising from either strand within a single-cell in a mutually exclusive manner, which was validated using single molecule fluorescence in-situ hybridization.

genomics↗

bioRxiv2017

Linking FANTOM5 CAGE Peaks To Annotations With CAGEscan

The FANTOM5 expression atlas is a quantitative measurement of the activity of nearly 200,000 promoter regions across nearly 2,000 different human primary cells, tissue types and cell lines. Generation of this atlas was made possible by the use of CAGE, an experimental approach to localise transcription start sites at single-nucleotide resolution by sequencing the 5' ends of capped RNAs after their conversion to cDNAs. While 50% of CAGE-defined promoter regions could be confidently associated to adjacent transcriptional units, nearly 100,000 promoter regions remained gene-orphan. To address this, we used the CAGEscan method, in which random-primed 5'-cDNAs are paired-end sequenced. Pairs starting in the same region are assembled in transcript models called CAGEscan clusters. Here, we present the production and quality control of CAGEscan libraries from 56 FANTOM5 RNA sources, which enhances the FANTOM5 expression atlas by providing experimental evidence associating core promoter regions with their cognate transcripts.

genomics↗

bioRxiv2016

Single-cell transcriptomes of fluorescent, ubiquitination-based cell cycle indicator cells

We used a transgenic HeLa cell line that reports cell cycle phases through fluorescent, ubiquitination-based cell cycle indicators (Fucci), to produce a reference dataset of more than 270 curated single cells. Microscopic images were taken from each cell followed by RNA-sequencing, so that single-cell expression data is associated to the fluorescence intensity of the Fucci probes in the same cell. We developed an open data management and quality control workflow that enables users to replicate the processing of the sequence and microscopic image data that we deposited in public repositories. The workflow outputs a table with metadata, that is the starting point for further studies on these data. Beyond its use for cell cycle studies, We also expect that our workflow can be adapted to other single-cell projects using a similar combination of sequencing data and fluorescence measurements.

genomics↗