Biology subjects

Parameswaran, S.

Publications and source records attributed to Parameswaran, S..

22 records · Page 2Linked to original sources

bioRxiv2020

Genome-wide discovery of lupus genetic risk variant allelic regulatory activity

Genome-wide association studies of Systemic Lupus Erythematosus (SLE) nominate 3,073 genetic variants at 91 risk loci. To systematically screen these variants for allelic transcriptional enhancer activity, we constructed a massively parallel reporter assay (MPRA) library comprising 12,396 DNA oligonucleotides containing the genomic context around every allele of each SLE variant. Transfection into the Epstein-Barr virus-transformed B cell line GM12878 revealed 482 variants with enhancer activity, with 51 variants showing genotype-dependent (allelic) enhancer activity at 27 risk loci. Comparison of MPRA results in GM12878 and Jurkat T cell lines highlights shared and unique allelic transcriptional regulatory mechanisms at SLE risk loci. In-depth analysis of allelic transcription factor (TF) binding at and around allelic variants identifies one class of TFs whose DNA-binding motif tends to be directly altered by the risk variant and a second, larger class of TFs that bind allelically without direct alteration of their motif by the variant. Collectively, our approach provides a blueprint for the discovery of allelic gene regulation at risk loci for any disease and offers insight into the transcriptional regulatory mechanisms underlying SLE.

genomics↗

bioRxiv2019

GPU Accelerated Adaptive Banded Event Alignment for Rapid Comparative Nanopore Signal Analysis

Nanopore sequencing has the potential to revolutionise genomics by realising portable, real-time sequencing applications, including point-of-care diagnostics and in-the-field genotyping. Achieving these applications requires efficient bioinformatic algorithms for the analysis of raw nanopore signal data. For instance, comparing raw nanopore signals to a biological reference sequence is a computationally complex task despite leveraging a dynamic programming algorithm for Adaptive Banded Event Alignment (ABEA)--a commonly used approach to polish sequencing data and identify non-standard nucleotides, such as measuring DNA methylation. Here, we parallelise and optimise an implementation of the ABEA algorithm (termed f5c) to efficiently run on heterogeneous CPU-GPU architectures. By optimising memory, compute and load balancing between CPU and GPU, we demonstrate how f5c can perform ~3-5x faster than the original implementation of ABEA in the Nanopolish software package. We also show that f5c enables DNA methylation detection on-the-fly using an embedded System on Chip (SoC) equipped with GPUs. Our work not only demonstrates that complex genomics analyses can be performed on lightweight computing systems, but also benefits High-Performance Computing (HPC). The associated source code for f5c along with GPU optimised ABEA is available at https://github.com/hasindu2008/f5c.

bioinformatics↗

bioRxiv2018

Featherweight long read alignment using partitioned reference indexes

The advent of nanopore sequencing has realised portable genomic research and applications. However, state of the art long read aligners and large reference genomes are not compatible with most mobile computing devices due to their high memory requirements. We show how memory requirements can be reduced through parameter optimization and reference genome partitioning, but highlight the associated limitations and caveats of these approaches. We then demonstrate how these issues can be overcome through an appropriate merging technique. We extend the Minimap2 aligner and demonstrate that long read alignment to the human genome can be performed on a system with 2GB RAM with negligible impact on accuracy.

bioinformatics↗

bioRxiv2018

Expression-based analyses indicate a central role for hypoxia in driving tumor plasticity through microenvironment remodeling and chromosomal instability

Can transcriptomic alterations drive the evolution of tumors? We rationalize that expressional changes found in all patients arise earlier in tumor development compared to alterations that occur only in limited subsets of patients. Our analyses of non-mutated genes from the non-amplified regions of the genome of 158 triple negative breast cancer (TNBC) cases identified 219 exclusively expression-altered (EEA) genes that may play important role in TNBC. Phylogenetic analyses of these genes predict a \"punctuated burst\" of multiple gene up-regulation events occurring at early stages of tumor development, followed by minimal subsequent changes later in tumor progression. Remarkably, this punctuated burst of expressional changes is instigated by hypoxia-related molecular events, predominantly in two groups of genes that control chromosomal instability (CIN) and remodel tumor microenvironment (TME). We conclude that alterations in the transcriptome are not stochastic and that early stage hypoxia induces CIN and TME remodeling to permit further tumor evolution.

cancer biology↗