Biology subjects

Myrthil, M.

Publications and source records attributed to Myrthil, M..

3 recordsLinked to original sources

bioRxiv2017

A Comparative Study Of Endoderm Differentiation In Humans And Chimpanzees

There is substantial interest in the evolutionary forces that shaped the regulatory framework that is established in early human development. Progress in this area has been slow because it is difficult to obtain relevant biological samples. Inducible pluripotent stem cells (iPSCs) provide the ability to establish in vitro models of early human and non-human primate developmental stages. Using matched iPSC panels from humans and chimpanzees, we comparatively characterized gene regulatory changes through a four-day timecourse differentiation of iPSCs (day 0) into primary streak (day 1), endoderm progenitors (day 2), and definitive endoderm (day 3). As might be expected, we found that differentiation stage is the major driver of variation in gene expression levels, followed by species. We identified thousands of differentially expressed genes between humans and chimpanzees in each differentiation stage. Yet, when we considered gene-specific dynamic regulatory trajectories throughout the timecourse, we found that 75.. of genes, including nearly all known endoderm developmental markers, have similar trajectories in the two species. Interestingly, we observed a marked reduction of both intra-and inter-species variation in gene expression levels in primitive streak samples compared to the iPSCs, with a recovery of regulatory variation in endoderm progenitors. The reduction of variation in gene expression levels at a specific developmental stage, paired with overall high degree of conservation of temporal gene regulation, is consistent with the dynamics of developmental canalization. Overall, we conclude that endoderm development in iPSC-based models are highly conserved and canalized between humans and our closest evolutionary relative.

genomics↗

bioRxiv2017

Predicting susceptibility to tuberculosis based on gene expression profiling in dendritic cells

Tuberculosis (TB) is a deadly infectious disease, which kills millions of people every year. The causative pathogen, Mycobac-terium tuberculosis (MTB), is estimated to have infected up to a third of the worlds population; however, only approximately 10% of infected healthy individuals progress to active TB. Despite evidence for heritability, it is not currently possible to predict who may develop TB. To explore approaches to classify susceptibility to TB, we infected with MTB dendritic cells (DCs) from putatively resistant individuals diagnosed with latent TB, and from susceptible individuals that had recovered from active TB. We measured gene expression levels in infected and non-infected cells and found hundreds of differentially expressed genes between susceptible and resistant individuals in the non-infected cells. We further found that genetic polymorphisms nearby the differentially expressed genes between susceptible and resistant individuals are more likely to be associated with TB susceptibility in published GWAS data. Lastly, we trained a classifier based on the gene expression levels in the non-infected cells, and demonstrated decent performance on our data and an independent data set. Overall, our promising results from this small study suggest that training a classifier on a larger cohort may enable us to accurately predict TB susceptibility.

genomics↗

bioRxiv2016

Impact of regulatory variation across human iPSCs and differentiated cells

Induced pluripotent stem cells (iPSCs) are an essential tool for studying cellular differentiation and cell types that are otherwise difficult to access. We investigated the use of iPSCs and iPSC-derived cells to study the impact of genetic variation across different cell types and as models for studies of complex disease. We established a panel of iPSCs from 58 well-studied Yoruba lymphoblastoid cell lines (LCLs); 14 of these lines were further differentiated into cardiomyocytes. We characterized regulatory variation across individuals and cell types by measuring gene expression, chromatin accessibility and DNA methylation. Regulatory variation between individuals is lower in iPSCs than in the differentiated cell types, consistent with the intuition that developmental processes are generally canalized. While most cell type-specific regulatory quantitative trait loci (QTLs) lie in chromatin that is open only in the affected cell types, we found that 20% of cell type-specific QTLs are in shared open chromatin. Finally, we developed a deep neural network to predict open chromatin regions from DNA sequence alone and were able to use the sequences of segregating haplotypes to predict the effects of common SNPs on cell type-specific chromatin accessibility.

genomics↗