DNA methylation alters transcriptional rates of differentially expressed genes and contributes to pathophysiology in mice fed a high fat diet.

OBJECTIVE: Overnutrition can alter gene expression patterns through epigenetic mechanisms that may persist through generations. However, it is less clear if overnutrition, for example a high fat diet, modifies epigenetic control of gene expression in adults, or by what molecular mechanisms, or if such mechanisms contribute to the pathology of the metabolic syndrome. Here we test the hypothesis that a high fat diet alters hepatic DNA methylation, transcription and gene expression patterns, and explore the contribution of such changes to the pathophysiology of obesity. METHODS: RNA-seq and targeted high-throughput bisulfite DNA sequencing were used to undertake a systematic analysis of the hepatic response to a high fat diet. RT-PCR, chromatin immunoprecipitation and in vivo knockdown of an identified driver gene, Phlda1, were used to validate the results. RESULTS: A high fat diet resulted in the hypermethylation and decreased transcription and expression of Phlda1 and several other genes. A subnetwork of genes associated with Phlda1 was identified from an existing Bayesian gene network that contained numerous hepatic regulatory genes involved in lipid and body weight homeostasis. Hepatic-specific depletion of Phlda1 in mice decreased expression of the genes in the subnetwork, and led to increased oil droplet size in standard chow-fed mice, an early indicator of steatosis, validating the contribution of this gene to the phenotype. CONCLUSIONS: We conclude that a high fat diet alters the epigenetics and transcriptional activity of key hepatic genes controlling lipid homeostasis, contributing to the pathophysiology of obesity.

Comparative evaluation of the Minimally-Invasive Karyotyping (MINK) algorithm for non-invasive prenatal testing.

Minimally Invasive Karyotyping (MINK) was communicated in 2009 as a novel method for the non-invasive detection of fetal copy number anomalies in maternal plasma DNA. The original manuscript illustrated the potential of MINK using a model system in which fragmented genomic DNA obtained from a trisomy 21 male individual was mixed with that of his karyotypically normal mother at dilutions representing fetal fractions found in maternal plasma. Although it has been previously shown that MINK is able to non-invasively detect fetal microdeletions, its utility for aneuploidy detection in maternal plasma has not previously been demonstrated. The current study illustrates the ability of MINK to detect common aneuploidy in early gestation, compares its performance to other published third party methods (and related software packages) for prenatal aneuploidy detection and evaluates the performance of these methods across a range of sequencing read inputs. Plasma samples were obtained from 416 pregnant women between gestational weeks 8.1 and 34.4. Shotgun DNA sequencing was performed and data analyzed using MINK RAPIDR and WISECONDOR. MINK performed with greater accuracy than RAPIDR and WISECONDOR, correctly identifying 60 out of 61 true trisomy cases, and reporting only one false positive in 355 normal pregnancies. Significantly, MINK achieved accurate detection of trisomy 21 using just 2 million aligned input reads, whereas WISECONDOR required 6 million reads and RAPIDR did not achieve complete accuracy at any read input tested. In conclusion, we demonstrate that MINK provides an analysis pipeline for the detection of fetal aneuploidy in samples of maternal plasma DNA.

Correction: High Levels of Sample-to-Sample Variation Confound Data Analysis for Non-Invasive Prenatal Screening of Fetal Microdeletions.

[This corrects the article DOI: 10.1371/journal.pone.0153182.].

High Levels of Sample-to-Sample Variation Confound Data Analysis for Non-Invasive Prenatal Screening of Fetal Microdeletions.

Our goal was to test the hypothesis that inter-individual genomic copy number variation in control samples is a confounding factor in the non-invasive prenatal detection of fetal microdeletions via the sequence-based analysis of maternal plasma DNA. The database of genomic variants (DGV) was used to determine the "Genomic Variants Frequency" (GVF) for each 50kb region in the human genome. Whole genome sequencing of fifteen karyotypically normal maternal plasma and six CVS DNA controls samples was performed. The coefficient of variation of relative read counts (cv.RTC) for these samples was determined for each 50kb region. Maternal plasma from two pregnancies affected with a chromosome 5p microdeletion was also sequenced, and analyzed using the GCREM algorithm. We found strong correlation between high variance in read counts and GVF amongst controls. Consequently we were unable to confirm the presence of the microdeletion via sequencing of maternal plasma samples obtained from two sequential affected pregnancies. Caution should be exercised when performing NIPT for microdeletions. It is vital to develop our understanding of the factors that impact the sensitivity and specificity of these approaches. In particular, benign copy number variation amongst controls is a major confounder, and their effects should be corrected bioinformatically.