Biology subjects

Dave, B.

Publications and source records attributed to Dave, B..

3 recordsLinked to original sources

bioRxiv2025

Benchmarking of Human ReadRemoval Strategies for Viral andMicrobial Metagenomics

Human reads are a key contaminant in microbial metagenomics and enrichment-based studies, requiring removal for computational efficiency, biological analysis, and privacy protection. Various in silico methods exist, but their effectiveness depends on the parameters and reference genomes used. Here, we assess different methods, including the impact of the updated T2T-CHM13 human genome versus GRCh38. Using a synthetic dataset of viral and human reads, we evaluated performance metrics for multiple approaches. We found that the usage of high-sensitivity configuration of Bowtie2 with the T2T-CHM13 reference assembly significantly improves human read removal with minimal loss of specificity, albeit at higher computational cost compared to other methods investigated. Applying this approach to a publicly available microbiome dataset, we effectively removed sex-determining SNPs with little impact on microbial assembly. Our results suggest that our high-sensitivity Bowtie2 approach with the T2T-CHM13 is the best method tested to minimise identifiability risks from residual human reads.

genomics↗

bioRxiv2021

A Computational Approach in Identification of Putative Risk Genes in Parkinsons Disease

This study focussed on identification of risk genes involved in PD through analysis of microarray data. The two methods were applied viz; WGCNA and DEGs Analysis to identify important genes that are downregulated or upregulated in PD. Both methods show high agreement with each other and also with the available biomedical literature available on this neurodegenerative disease. On the basis of their p-value, 20 significantly upregulated and 19 significantly downregulated genes were found to be playing role in the manifestation of motor and non motor symptoms of the disease, as interpreted from the enrichment analysis. Gene expression dataset of Parkinsons Disease (PD) used in this study was obtained from the GeneExpression Omnibus namely GSE8397, GSE20164, and GSE20295 (Edgar, 2002). Among the important genes extracted, the top downregulated and upregulated genes were studied using enrichment analysis. Out of the 19 common downregulated genes, 10 were directly associated with neuron development and differentiation. Two of the genes, FGF13 and CDC42 were associated with multiple signalling pathways. The gene NSF was found to be enriched with GABAergic synapse, associated with the predominating inhibitory neurotransmitter in the mammalian CNS. The inhibitory synapses are thought to provide a brake to neural firing. The upregulated genes DDIT4, HSPB1, NUPR1, GPNMB and CH13L1 were enriched with apoptotic signalling pathway while MT1M, MT1E, MT1F, MT1X were associated with mineral absorption pathways. Genes like CDC42 have already been reported to be potential diagnostic markers of PD in clinic (Chi et al., 2018).

bioinformatics↗

bioRxiv2021

Exceptionally high sequence-level variation in the transcriptome of Plasmodium falciparum

Single-nucleotide variations in RNA (hereafter referred to simply as SNVs), arising from co- and post-transcriptional phenomena including transcription errors and RNA editing, are well studied in organisms ranging from bacteria to humans. In the malaria parasite Plasmodium falciparum, stage-specific and non-specific gene-expression variations are known to accompany the parasites array of developmental and morphological phenotypes over the course of its complex life cycle. However, the extent, rate and effect of sequence-level variation in the parasites transcriptome are unknown. Here, we report the presence of pervasive, non-specific SNVs in the transcriptome of the P. falciparum. We show that these SNVs cover most of the parasites transcriptome. SNV rates for the P. falciparum lines we assayed, as well as for publicly available P. vivax and P. falciparum clinical isolate datasets were of the order of 10-3 per base, about tenfold higher than rates we calculated for bacterial datasets. These SNVs may reflect an intrinsic transcriptional error rate in the parasite, and RNA editing may be responsible for a subset of them. This seemingly characteristic property of the parasite may have implications for clinical outcomes and the basic biology and evolution of P. falciparum and parasite biology more broadly, and we anticipate that our study will prompt further investigations into the exact sources, consequences and possible adaptive roles of these SNVs.

genomics↗