Corticosterone pattern-dependent glucocorticoid receptor binding and transcriptional regulation within the liver.

Ultradian glucocorticoid rhythms are highly conserved across mammalian species, however, their functional significance is not yet fully understood. Here we demonstrate that pulsatile corticosterone replacement in adrenalectomised rats induces a dynamic pattern of glucocorticoid receptor (GR) binding at ~3,000 genomic sites in liver at the pulse peak, subsequently not found during the pulse nadir. In contrast, constant corticosterone replacement induced prolonged binding at the majority of these sites.

Prediction of driver variants in the cancer genome via machine learning methodologies.

Sequencing technologies have led to the identification of many variants in the human genome which could act as disease-drivers. As a consequence, a variety of bioinformatics tools have been proposed for predicting which variants may drive disease, and which may be causatively neutral. After briefly reviewing generic tools, we focus on a subset of these methods specifically geared toward predicting which variants in the human cancer genome may act as enablers of unregulated cell proliferation.

Rapid, robust plasmid verification by de novo assembly of short sequencing reads.

Plasmids are a foundational tool for basic and applied research across all subfields of biology. Increasingly, researchers in synthetic biology are relying on and developing massive libraries of plasmids as vectors for directed evolution, combinatorial gene circuit tests, and for CRISPR multiplexing. Verification of plasmid sequences following synthesis is a crucial quality control step that creates a bottleneck in plasmid fabrication workflows.

Genetic interactions derived from high-throughput phenotyping of 6589 yeast cell cycle mutants.

Over the last 30 years, computational biologists have developed increasingly realistic mathematical models of the regulatory networks controlling the division of eukaryotic cells. These models capture data resulting from two complementary experimental approaches: low-throughput experiments aimed at extensively characterizing the functions of small numbers of genes, and large-scale genetic interaction screens that provide a systems-level perspective on the cell division process. The former is insufficient to capture the interconnectivity of the genetic control network, while the latter is fraught with irreproducibility issues.

CScape-somatic: distinguishing driver and passenger point mutations in the cancer genome.

Motivation: Next-generation sequencing technologies have accelerated the discovery of single nucleotide variants in the human genome, stimulating the development of predictors for classifying which of these variants are likely functional in disease, and which neutral. Recently, we proposed CScape, a method for discriminating between cancer driver mutations and presumed benign variants. For the neutral class, this method relied on benign germline variants found in the 1000 Genomes Project database.

Estimating the Frequency of Single Point Driver Mutations across Common Solid Tumours.

For cancers, such as common solid tumours, variants in the genome give a selective growth advantage to certain cells. It has recently been argued that the mean count of coding single nucleotide variants acting as disease-drivers in common solid tumours is frequently small in size, but significantly variable by cancer type (hypermutation is excluded from this study). In this paper we investigate this proposal through the use of integrative machine-learning-based classifiers we have proposed recently for predicting the disease-driver status of single nucleotide variants (SNVs) in the human cancer genome.

Glucocorticoid Receptor-Tethered Mineralocorticoid Receptors Increase Glucocorticoid-Induced Transcriptional Responses.

Mineralocorticoid and glucocorticoid receptors (MRs and GRs) constitute a functionally important dual receptor system detecting and transmitting circulating corticosteroid signals. High expression of MRs and GRs occurs in the same cells in the limbic system, the primary site of glucocorticoid action on cognition, behavior, and mood; however, modes of interaction between the receptors are poorly characterized. We used chromatin immunoprecipitation with nucleotide resolution using exonuclease digestion, unique barcode, and single ligation (ChIP-nexus) for high-resolution genome-wide characterization of MR and GR DNA binding profiles in neuroblastoma cells and demonstrate recruitment to highly similar DNA binding sites.

Improving Illumina assemblies with Hi-C and long reads: An example with the North African dromedary.

Researchers have assembled thousands of eukaryotic genomes using Illumina reads, but traditional mate-pair libraries cannot span all repetitive elements, resulting in highly fragmented assemblies. However, both chromosome conformation capture techniques, such as Hi-C and Dovetail Genomics Chicago libraries and long-read sequencing, such as Pacific Biosciences and Oxford Nanopore, help span and resolve repetitive regions and therefore improve genome assemblies. One important livestock species of arid regions that does not have a high-quality contiguous reference genome is the dromedary (Camelus dromedarius).

Preeclamptic placentae release factors that damage neurons: implications for foetal programming of disease.

Prenatal development is a critical period for programming of neurological disease. Preeclampsia, a pregnancy complication involving oxidative stress in the placenta, has been associated with long-term health implications for the child, including an increased risk of developing schizophrenia and autism spectrum disorders in later life. To investigate if molecules released by the placenta may be important mediators in foetal programming of the brain, we analysed if placental tissue delivered from patients with preeclampsia secreted molecules that could affect cortical cells in culture.

Differential aging-related changes in neurophysiology and gene expression in IB4-positive and IB4-negative nociceptive neurons.

Despite pain prevalence altering with age, the effects of aging on the properties of nociceptors are not well understood. Nociceptors, whose somas are located in dorsal root ganglia, are frequently divided into two groups based on their ability to bind isolectin B4 (IB4). Here, using cultured neurons from 1-, 3-, 5-, 8-, 12-, and 18-month-old mice, we investigate age-dependent changes in IB4-positive and IB4-negative neurons.

An integrative approach to predicting the functional effects of small indels in non-coding regions of the human genome.

Background: Small insertions and deletions (indels) have a significant influence in human disease and, in terms of frequency, they are second only to single nucleotide variants as pathogenic mutations. As the majority of mutations associated with complex traits are located outside the exome, it is crucial to investigate the potential pathogenic impact of indels in non-coding regions of the human genome.

Results: We present FATHMM-indel, an integrative approach to predict the functional effect, pathogenic or neutral, of indels in non-coding regions of the human genome.

FATHMM-XF: accurate prediction of pathogenic point mutations via extended features.

Summary: We present FATHMM-XF, a method for predicting pathogenic point mutations in the human genome. Drawing on an extensive feature set, FATHMM-XF outperforms competitors on benchmark tests, particularly in non-coding regions where the majority of pathogenic mutations are likely to be found.

Availability And Implementation: The FATHMM-XF web server is available at http://fathmm.

CScape: a tool for predicting oncogenic single-point mutations in the cancer genome.

For somatic point mutations in coding and non-coding regions of the genome, we propose CScape, an integrative classifier for predicting the likelihood that mutations are cancer drivers. Tested on somatic mutations, CScape tends to outperform alternative methods, reaching 91% balanced accuracy in coding regions and 70% in non-coding regions, while even higher accuracy may be achieved using thresholds to isolate high-confidence predictions. Positive predictions tend to cluster in genomic regions, so we apply a statistical approach to isolate coding and non-coding regions of the cancer genome that appear enriched for high-confidence predicted disease-drivers.

Treating the placenta to prevent adverse effects of gestational hypoxia on fetal brain development.

Some neuropsychiatric disease, including schizophrenia, may originate during prenatal development, following periods of gestational hypoxia and placental oxidative stress. Here we investigated if gestational hypoxia promotes damaging secretions from the placenta that affect fetal development and whether a mitochondria-targeted antioxidant MitoQ might prevent this. Gestational hypoxia caused low birth-weight and changes in young adult offspring brain, mimicking those in human neuropsychiatric disease.

Sex-specific differences in cardiovascular and metabolic hormones with integrated signalling in the paraventricular nucleus of the hypothalamus.

What is the topic of this review? We describe roles of crucial signalling molecules in the paraventricular nucleus of the hypothalamus and highlight recent data suggesting sex-specific changes in the expression of crucial signalling molecules and their receptors, which may underlie sex differences in both cardiovascular and metabolic function. What advances does it highlight? This review highlights the integrative capacity of the paraventricular nucleus in mediating cardiovascular and metabolic effects by integrating information from multiple signalling molecules. It also proposes that these signalling molecules have sex-specific differential gene expression, indicating the importance of considering these differences in our ongoing search to understand the female-male differences in the regulation of crucial autonomic systems.

Predicting the Pathogenic Impact of Sequence Variation in the Human Genome.

Sequencing data will become widely available in clinical practice within the near future. Uptake of sequence data is currently being stimulated within the UK through the government-funded 100,000 genomes project (Genomics England), with many similar initiatives being planned and supported internationally. The analysis of the large volumes of data derived from sequencing programmes poses a major challenge for data analysis.

Recognition memory-induced gene expression in the perirhinal cortex: A transcriptomic analysis.

We have used transcriptome analysis to identify genes and pathways that are activated during recognition memory formation in the perirhinal cortex. Rats were exposed to objects either repeatedly, so that the objects become familiar, or to novel objects in a bow-tie maze over six consecutive days. On the final day, one hour after the last exposure to the series of objects, RNA from the perirhinal cortex was sequenced to compare the transcriptome of naïve control rats and rats exposed to either novel or familiar stimuli.

HIPred: an integrative approach to predicting haploinsufficient genes.

Motivation: A major cause of autosomal dominant disease is haploinsufficiency, whereby a single copy of a gene is not sufficient to maintain the normal function of the gene. A large proportion of existing methods for predicting haploinsufficiency incorporate biological networks, e.g.

GTB - an online genome tolerance browser.

Background: Accurate methods capable of predicting the impact of single nucleotide variants (SNVs) are assuming ever increasing importance. There exists a plethora of in silico algorithms designed to help identify and prioritize SNVs across the human genome for further investigation. However, no tool exists to visualize the predicted tolerance of the genome to mutation, or the similarities between these methods.

Probabilistic inference of biological networks via data integration.

There is significant interest in inferring the structure of subcellular networks of interaction. Here we consider supervised interactive network inference in which a reference set of known network links and nonlinks is used to train a classifier for predicting new links. Many types of data are relevant to inferring functional links between genes, motivating the use of data integration.

An integrative approach to predicting the functional effects of non-coding and coding sequence variation.

Motivation: Technological advances have enabled the identification of an increasingly large spectrum of single nucleotide variants within the human genome, many of which may be associated with monogenic disease or complex traits. Here, we propose an integrative approach, named FATHMM-MKL, to predict the functional consequences of both coding and non-coding sequence variants. Our method utilizes various genomic annotations, which have recently become available, and learns to weight the significance of each component annotation source.

Deciphering the plant splicing code: experimental and computational approaches for predicting alternative splicing and splicing regulatory elements.

Extensive alternative splicing (AS) of precursor mRNAs (pre-mRNAs) in multicellular eukaryotes increases the protein-coding capacity of a genome and allows novel ways to regulate gene expression. In flowering plants, up to 48% of intron-containing genes exhibit AS. However, the full extent of AS in plants is not yet known, as only a few high-throughput RNA-Seq studies have been performed.

SpliceGrapher: detecting patterns of alternative splicing from RNA-Seq data in the context of gene models and EST data.

We propose a method for predicting splice graphs that enhances curated gene models using evidence from RNA-Seq and EST alignments. Results obtained using RNA-Seq experiments in Arabidopsis thaliana show that predictions made by our SpliceGrapher method are more consistent with current gene models than predictions made by TAU and Cufflinks. Furthermore, analysis of plant and human data indicates that the machine learning approach used by SpliceGrapher is useful for discriminating between real and spurious splice sites, and can improve the reliability of detection of alternative splicing.