Project description:Transcriptome profiling of pyrethroid resistant field populations of Anopheles funestus across Uganda and neighboring Kenya from Uganda and Kenya compared to a susceptible lab strain FANG
Project description:The goal of this study was to characterize the non-hematopoietic compartment (Ter119NegCD45Neg) of the mouse embryonic liver. For that, we sorted the 3 major populations at embryonic day 14.5 and CD54 expressing cells at embryonic day 18.5 for whole genome analysis.
Project description:Comparisons of DNA from archaic and modern humans show that these groups interbred, and in some cases received an evolutionary advantage from doing so. This process-adaptive introgression-may lead to a faster rate of adaptation than is predicted from models with mutation and selection alone. Within the last couple of years, a series of studies have identified regions of the genome that are likely examples of adaptive introgression. In many cases, once a region was ascertained as being introgressed, commonly used statistics based on both haplotype as well as allele frequency information were employed to test for positive selection. Introgression by itself, however, changes both the haplotype structure and the distribution of allele frequencies, thus confounding traditional tests for detecting positive selection. Therefore, patterns generated by introgression alone may lead to false inferences of positive selection. Here we explore models involving both introgression and positive selection to investigate the behavior of various statistics under adaptive introgression. In particular, we find that the number and allelic frequencies of sites that are uniquely shared between archaic humans and specific present-day populations are particularly useful for detecting adaptive introgression. We then examine the 1000 Genomes dataset to characterize the landscape of uniquely shared archaic alleles in human populations. Finally, we identify regions that were likely subject to adaptive introgression and discuss some of the most promising candidate genes located in these regions.
Project description:The study aimed to define transcriptional signatures for detection of active TB (TB) compared to latent TB infection (LTBI) as well as to other diseases (OD) with similar clinical phenotypes in patients with and without HIV in a paediatric cohort from Kenya Transcriptional signatures were identified that distinguished active TB from LTBI, active TB from other diseases, and active TB from both LTBI and other diseases in HIV+/- patients. Children were recruited from 2 hospitals in Coast Province, Kenya (n=157) who were either HIV+ or HIV - with either active TB (culture confirmed), active TB (culture negative), LTBI or OD. Blood was collected into PAX gene tubes (PreAnalytiX). Total RNA integrity was assessed using an Agilent 2100 Bioanalyzer (Agilent, Palo Alto, CA). Labeled cRNA was hybridized to Illumina Human HT-12 Beadchips. Data were analysed in R.