Project description:Genome-wide premortem DNA methylation patterns can be computationally reconstructed from high-coverage DNA sequences of ancient samples. As DNA methylation is more conserved across species than across tissues, and as ancient DNA is typically extracted from bones and teeth, previous works utilizing ancient DNA methylation maps focused on studying evolutionary changes in the skeletal system. Here, we suggest that DNA methylation patterns in one tissue may, under certain conditions, be informative on DNA methylation patterns in other tissues of the same individual. Using the fact that tissue- specific DNA methylation builds up during embryonic development, we identified the conditions that allow for such cross-tissue inference and devised an algorithm that carries it out. We trained the algorithm on methylation data from extant species and reached high precisions of up to 0.92 for validation data sets. We then used the algorithm on archaic humans, and identified more than 1,850 positions for which we were able to observe differential DNA methylation in prefrontal cortex neurons. These positions are linked to hundreds of genes, many of which are involved in neural functions such as structural and developmental processes. Six positions are located in the NBPF gene family, which likely played a role in human brain evolution. The algorithm we present here allows for the examination of epigenetic changes in tissues and cell types that are absent from the paleontological record, and therefore provides new ways to study the evolutionary impacts of epigenetic changes.
Project description:This SuperSeries is composed of the following subset Series: GSE37200: Gene expression profiling of Barrett’s esophageal tissues and esophageal adenocarcinoma specimens GSE37201: Gene expression profiling of esophageal adenocarcinoma Refer to individual Series
Project description:We have used SmartSeq2 to sequence single phenotypic human skeletal stem cell (SSCs) and downstream lineage populations purified via FACS from fetal skeletal tissues and patient specimens. SSC populations were isolated based on their previously reported surface marker profiles. A human SSC (CD45-CD235a-CD31-TIE2-CD146-PDPN+CD73+CD164+), a human bone-cartilage-stroma-progenitor (BCSP; CD45-CD235a-CD31-TIE2-CD146+PDPN+) and an osteoprogenitor (OP; CD45-CD235a-CD31-TIE2-CD146+PDPN-) were investigated.
Project description:Skeletal muscles are a diverse family of highly specialized tissues that perform a wide array of physiological activities and maintain whole-body glucose metabolism and energy homeostasis. Functional diversity is a distinctive feature of muscle tissues, which demonstrate remarkable variability in their speed of contraction, metabolic profile, resistance to fatigue, and regenerative capacity. Unsurprisingly, many disorders of skeletal muscle afflict a remarkably specific subset of tissues, including muscular dystrophies, cancer cachexia, aging sarcopenia, and amyotrophic lateral sclerosis. Taken as a whole, these observations indicate that specific genetic programs establish and maintain physiological specialization of muscle tissues. Elucidating these genetic programs is essential to understanding muscle specialization and propensity for disease. Nevertheless, most global profiling studies performed to-date have not directly addressed intrinsic variability between different muscle tissues. This gap in the literature is particularly glaring for more sophisticated mechanisms of gene expression regulation such as circadian control, post-transcriptional regulation and non-coding RNA expression, despite their well-established roles in many disease mechanisms. In an effort to understand the variability present within specific skeletal muscles with respect to gene expression, our lab has performed RNA-Seq on a variety of skeletal muscle tissues.
Project description:Expression profiles of mouse skeletal muscle tissues, mouse skeletal muscle from Aged animals with high fat diet and chemical treatment