Analysis of the wnt1 regulatory chromosomal landscape

Placental DNA methylation profile as predicting marker for autism spectrum disorder (ASD)

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that impairs normal brain development and socio-cognitive abilities. The pathogenesis of this condition points out the involvement of genetic and environmental factors during in-utero life. Placenta, as an interface tissue between mother and fetus, provides developing fetus requirements and exposes it to maternal environment as well. Therefore, the alteration of DNA methylation as epigenetic consequence of gene-environmental interaction in the placenta could shed light on ASD pathogenesis. In this study, we reviewed the current findings on placental methylation status and its association with ASD. Differentially methylated regions (DMRs) in ASD-developing placenta were found to be mainly enriched in ASD gene loci affecting synaptogenesis, microtubule dynamics, neurogenesis and neuritogenesis. In addition, non-genic DMRs in ASD-placenta proposes an alternative contributing mechanism for ASD development. Our study highlights the importance of placental DNA methylation signature as a biomarker for ASD prediction.

Building a three-dimensional model of early-stage zebrafish embryo brain

We introduce a computational approach to build three-dimensional (3D) surface mesh models of the early-stage zebrafish brain primordia from time-series microscopy images. The complexity of the early-stage brain primordia and lack of recognizable landmarks pose a distinct challenge for feature segmentation and 3D modeling. Additional difficulty arises because of noise and variations in pixel intensity. We overcome these by using a hierarchical approach in which simple geometric elements, such as "beads" and "bonds," are assigned to represent local features and their connectivity is used to smoothen the surface while retaining high-curvature regions. We apply our method to build models of two zebrafish embryo phenotypes at discrete time points between 19 and 28 h post-fertilization and collect measurements to quantify development. Our approach is fast and applicable to building models of other biological systems, as demonstrated by models from magnetic resonance images of the human fetal brain. The source code, input scripts, sample image files, and generated outputs are publicly available on GitHub.

Functional annotations of three domestic animal genomes provide vital resources for comparative and agricultural research

Gene regulatory elements are central drivers of phenotypic variation and thus of critical importance towards understanding the genetics of complex traits. The Functional Annotation of Animal Genomes consortium was formed to collaboratively annotate the functional elements in animal genomes, starting with domesticated animals. Here we present an expansive collection of datasets from eight diverse tissues in three important agricultural species: chicken (Gallus gallus), pig (Sus scrofa), and cattle (Bos taurus). Comparative analysis of these datasets and those from the human and mouse Encyclopedia of DNA Elements projects reveal that a core set of regulatory elements are functionally conserved independent of divergence between species, and that tissue-specific transcription factor occupancy at regulatory elements and their predicted target genes are also conserved. These datasets represent a unique opportunity for the emerging field of comparative epigenomics, as well as the agricultural research community, including species that are globally important food resources.