Ancestry dependent balancing selection of placental dysferlin at high-altitude.

The placenta mediates fetal growth by regulating gas and nutrient exchange between the mother and the fetus. The cell type in the placenta where this nutrient exchange occurs is called the syncytiotrophoblast, which is the barrier between the fetal and maternal blood. Residence at high-altitude is strongly associated with reduced 3rd trimester fetal growth and increased rates of complications such as preeclampsia.

Prediction of adenocarcinoma development using game theory.

Recent research shows that gene expression changes appear to correlate well with the progression of many types of cancers. Using changes in gene expression as a basis, this paper proposes a data-driven 2-player game-theoretic model to predict the risk of adenocarcinoma based on Nash equilibrium. A key innovation in this work is the pay-off function which is a weighted composite of the expression of a cohort of tumor-suppressor genes (as one player) and an analogous cohort of oncogenes (as the other player).

A review of inter- and intraspecific variation in the eutherian placenta.

The placenta is one of the most morphologically variable mammalian organs. Four major characteristics are typically discussed when comparing the placentas of different eutherian species: placental shape, maternal-fetal interdigitation, intimacy of the maternal-fetal interface and the pattern of maternal-fetal blood flow. Here, we describe the evolution of three of these features as well as other key aspects of eutherian placentation.

Long noncoding RNAs are rarely translated in two human cell lines.

Data from the Encyclopedia of DNA Elements (ENCODE) project show over 9640 human genome loci classified as long noncoding RNAs (lncRNAs), yet only ~100 have been deeply characterized to determine their role in the cell. To measure the protein-coding output from these RNAs, we jointly analyzed two recent data sets produced in the ENCODE project: tandem mass spectrometry (MS/MS) data mapping expressed peptides to their encoding genomic loci, and RNA-seq data generated by ENCODE in long polyA+ and polyA- fractions in the cell lines K562 and GM12878. We used the machine-learning algorithm RuleFit3 to regress the peptide data against RNA expression data.