Cooper, A. — Page 3 | Search bioRxiv

bioRxiv2018

Dimension Reduction and Visualization for Single-copy Alignments via Generalized PCA

Single-copy sequence alignments have been a valuable source of information for genetic studies; their lack of recombination makes phylogenetic analyses tractable [1]. Specifically, mitochondrial DNA will continue to play an important role in genetic studies due to its high mutation rate and high copy per cell count of the molecule [2]. In this paper we develop a new method for the analysis of single-copy sequence data that simultaneously considers the relationships between sequenced individuals and positions of interest in the genome. We then show that tests for relationships between genetic information and qualitative and quantitative characteristics can be calculated. We motivate the use of our method with examples from empirical data.

bioinformatics↗

bioRxiv2017

T cell activation and the HLA locus associate with latent infections of human African trypanosomiasis

Infections by many pathogens can result in a wide range of phenotypes, from severe to mild, or even asymptomatic. Understanding the genetic basis of these phenotypes can lead to better tools to treat patients or detect reservoirs. To identify human genetic factors that contribute to symptoms diversity, we examined the range of disease severities caused by the parasite T. b. gambiense, the primary cause of human African trypanosomiasis (HAT). We analyzed the transcriptomes of immune cells from both symptomatic HAT cases and individuals with latent infections. Our analysis identified several genes and pathways that associated with the latent phenotype, primarily suggesting increased T and B cell activation in HAT patients relative to latent infections. We also used these transcriptome data to conduct an exome-wide single nucleotide polymorphism (SNP) association study. This suggested that SNPs in the human major histocompatibility locus (HLA) associate with severity, supporting the transcription data and suggesting that T cell activation is a determining factor in outcome. Finally, to establish if T cell activation controls disease severity, we blocked co-stimulatory dependent T cell activation in an animal model for HAT. This showed that reducing T cell activation during trypanosome infection improves symptoms and reduces parasitemia. Our data has used a combination of transcriptome-wide analysis and an in vivo model to reveal that T cell activation and the HLA locus associate with the development of symptoms during HAT. This may open new avenues for the development of new therapeutics and prognostics.

genetics↗