Amin, M. | Search bioRxiv

bioRxiv2018

MALARIA and BURKITT′S LYMPHOMA: An IN SILICO ANALYSIS of GENE EXPRESSION LINKS BETWEEN MALARIA and BURKITT’S LYMPHOMA and POTENTIAL ANTICANCER ACTIVITY of ARTEMISININ DERIVATIVES

BackgroundBurkitts lymphoma (BL) is an aggressive form of B-cell non-Hodgkin lymphoma. Endemic subtype of the disease showed a remarkable statistical and epidemiological association with malaria infection. Despite the numerous studies performed to explain this association; molecular mechanisms underlie such coincidence still remain unclear. Dissecting molecular mechanisms which link Malaria infection and Burkitts lymphoma can provide insights about reported anticancer action of certain antimalarial drugs, namely artemisinin derivatives.\n\nMethodsHere we applied an integrative approach to investigate for potential links between malaria infection and endemic Burkitts lymphoma regarding their gene expression, and further explore common molecular mechanisms through which artemisinin compounds might act in endemic Burkitts lymphoma. Using gene expression data of malaria (Plasmodium falciparum infected erythroblasts) and endemic Burkitts lymphoma from Gene Expression Omnibus database, expression patterns in the two conditions were examined through clustering analysis using Self Organizing Maps, and then by significance testing of differentially expressed genes in each condition followed by Functional annotation using Gene Ontology clustering and Pathways analysis.\n\nResultsClustering analysis identified a significant overlap between the expression patterns in endemic Burkitts lymphoma and Plasmodium falciparum infected cells. Four out of the 12 identified clusters contained genes with similar expression patterns in both conditions. Differential expression analysis identified 1689 genes as significantly differentially expressed in endemic Burkitts lymphoma and 405 in malaria. Those genes were found to be related to important Gene Ontology terms and pathways. Interestingly 65% of the identified pathways in Malaria were overlapped with those identified in endemic Burkitts lymphoma. Several of these pathways reported to be related to actions of artemisinin derivatives.\n\nConclusionOur In-silico analysis showed a significant molecular convergence between endemic Burkitts lymphoma and malaria. A number of 43pathways which demonstrated enrichment in tumour were shared with Plasmodium falciparum infected erythrocytes. Such pathways represent potential targets for antimalarial drugs to exert therapeutic effects in such malignancy.

bioinformatics↗

bioRxiv2018

Dynamics and spatial genomics of the nascent transcriptome in single mESCs by intron seqFISH

Recent single cell experiments have revealed significant heterogeneities at the levels of transcription, DNA methylation and chromosome organization in individual cells. However, existing method of profiling mRNAs effectively averages transcriptional dynamics over many hours due to hours-long life time of most mRNAs. To capture the instantaneous activity of the transcriptome that reflects the rapid regulatory changes in cells, we imaged up to 10,421 nascent transcription active sites (TAS) in single mouse embryonic stem cells using seqFISH followed by multiple rounds of single molecule FISH and immunofluorescence. We observed that nascent transcription active sites appear to be distributed on the surface of individual chromosome territories and are dispersed throughout the nucleus. In addition, there are significant variability in the number of active transcription sites in single cells, representing globally more active to quiescent states. These states interconverted on the time scale of 2 hours as determined by a single cell pulse-chase experiment. Thus, transcriptome level seqFISH experiments provide an unprecedented spatial and dynamic view of chromosome organization and global nascent transcription activity in single cells.

systems biology↗

bioRxiv2016

A bioinformatic panel to interrogate thousands of ExAC variants with minor reference allele that are missed by conventional variant calling

In variation sites with minor reference alleles, overlooking the detection of homozygous reference genotypes results in inadequate identification of potential disease variants. Current variant calling practices miss these clinically relevant alleles warranting new approaches. More than 26,000 Eome Aggregation Consortium (ExAC) variants have a minor reference allele including 44 variants with known ClinVar disease alleles. We demonstrated how the current variant calling standards miss homozygous reference disease variants in these sites. We developed a bioinformatic panel that can be used to screen these variants using commonly available variant callers. We provide here a simple strategy to screen potential disease-causing variants when present in homozygous reference state.

genomics↗