The hyperpolarization-activated cation current (termed I h , I q , or I f ) was recently shown to be encoded by a new family of genes, named HCN for hyperpolarization-activated cyclic nucleotidesensitive cation nonselective. When expressed in heterologous cells, each HCN isoform generates channels with distinct activation kinetics, mirroring the range of biophysical properties of native I h currents recorded in different classes of neurons. To determine whether the functional diversity of I h currents is attributable to different patterns of HCN gene expression, we determined the mRNA distribution across different regions of the mouse CNS of the three mouse HCN genes that are prominently expressed there (mHCN1, 2 and 4). We observe distinct patterns of distribution for each of the three genes. Whereas mHCN2 shows a widespread expression throughout the CNS, the expression of mHCN1 and mHCN4 is more limited, and generally complementary. mHCN1 is primarily expressed within neurons of the neocortex, hippocampus, and cerebellar cortex, but also in selected nuclei of the brainstem. mHCN4 is most highly expressed within neurons of the medial habenula, thalamus, and olfactory bulb, but also in distinct neuronal populations of the basal ganglia. Based on a comparison of mRNA expression with an electrophysiological characterization of native I h currents in hippocampal and thalamic neurons, our data support the idea that the functional heterogeneity of I h channels is attributable, in part, to differential isoform expression. Moreover, in some neurons, specific functional roles can be proposed for I h channels with defined subunit composition.

Individuals with 22q11.2 microdeletions show behavioral and cognitive deficits and are at high risk of developing schizophrenia. We analyzed an engineered mouse strain carrying a chromosomal deficiency spanning a segment syntenic to the human 22q11.2 locus. We uncovered a previously unknown alteration in the biogenesis of microRNAs (miRNAs) and identified a subset of brain miRNAs affected by the microdeletion. We provide evidence that the abnormal miRNA biogenesis emerges because of haploinsufficiency of the Dgcr8 gene, which encodes an RNA-binding moiety of the 'microprocessor' complex and contributes to the behavioral and neuronal deficits associated with the 22q11.2 microdeletion.

We present a large-scale analysis of mRNA coexpression based on 60 large human data sets containing a total of 3924 microarrays. We sought pairs of genes that were reliably coexpressed (based on the correlation of their expression profiles) in multiple data sets, establishing a high-confidence network of 8805 genes connected by 220,649 "coexpression links" that are observed in at least three data sets. Confirmed positive correlations between genes were much more common than confirmed negative correlations. We show that confirmation of coexpression in multiple data sets is correlated with functional relatedness, and show how cluster analysis of the network can reveal functionally coherent groups of genes. Our findings demonstrate how the large body of accumulated microarray data can be exploited to increase the reliability of inferences about gene function.[Supplemental material is available online at www.genome.org and http://microarray.cpmc.columbia.edu/tmm.]Gene expression microarray data is a form of high-throughput genomics data providing relative measurements of mRNA levels for thousands of genes in a biological sample. In the last few years, hundreds of laboratories have collected and analyzed microarray data, and the data are beginning to appear in public databases or on researchers' Web sites. These resources serve at least two purposes. One is as an archive of the data, which allows other researchers to confirm the results that have been published by the originator of the data. A second use is to permit novel analyses of the data, that go beyond what was envisioned or possible at the time of the original study. A novel analysis could involve just a single data set, or a meta-analysis of many data sets (where a "data set" is a group of microarrays that were collected together, and typically described as a group in a single publication). The combined analysis of multiple data sets forms the main topic of this paper.Most existing studies that have analyzed multiple independently collected microarray data sets have focused on differential expression, comparing two or more similar data sets to look for genes that distinguish different sets of samples (Breitling et al.

BackgroundA major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging.ResultsWe conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2.ConclusionsThe top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-016-1037-6) contains supplementary material, which is available to authorized users.

Genomic imprinting is an epigenetic mechanism of regulation that restrains the expression of a small subset of mammalian genes to one parental allele. The reason for the targeting of these approximately 80 genes by imprinting remains uncertain. We show that inactivation of the maternally repressed Zac1 transcription factor results in intrauterine growth restriction, altered bone formation, and neonatal lethality. A meta-analysis of microarray data reveals that Zac1 is a member of a network of coregulated genes comprising other imprinted genes involved in the control of embryonic growth. Zac1 alters the expression of several of these imprinted genes, including Igf2, H19, Cdkn1c, and Dlk1, and it directly regulates the Igf2/H19 locus through binding to a shared enhancer. Accordingly, these data identify a network of imprinted genes, including Zac1, which controls embryonic growth and which may be the basis for the implementation of a common mechanism of gene regulation during mammalian evolution.

Coronary artery disease (CAD) is one of the major cardiovascular diseases affecting the global human population. This disease has been proved to be the major cause of death in both the developed and developing countries. Lifestyle, environmental factors, and genetic factors pose as risk factors for the development of cardiovascular disease. The prevalence of risk factors among healthy individuals elucidates the probable occurrence of CAD in near future. Genome‐wide association studies have suggested the association of chromosome 9p21.3 in the premature onset of CAD. The risk factors of CAD include diabetes mellitus, hypertension, smoking, hyperlipidemia, obesity, homocystinuria, and psychosocial stress. The eradication and management of CAD has been established through extensive studies and trials. Antiplatelet agents, nitrates, β‐blockers, calcium antagonists, and ranolazine are some of the few therapeutic agents used for the relief of symptomatic angina associated with CAD.

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Schizophrenia is a serious psychiatric disorder with a broadly undiscovered genetic etiology. Recent studies of de novo mutations (DNM) in schizophrenia and autism have reinforced the hypothesis that rare genetic variation contributes to risk. We carried out exome sequencing on 57 trios with sporadic or familial schizophrenia. In sporadic trios, we observed a ~3.5-fold increase in the proportion of nonsense de novo mutations (DNMs) (0.101 vs. 0.031, empirical P=0.01, BH-corrected P=0.044). These mutations were significantly more likely to occur in genes with highly ranked probabilities of haploinsufficiency (P=0.0029, corrected P=0.006). DNMs of potential functional consequence were also found to occur in genes predicted to be less tolerant to rare variation (P=2.01×10−5, corrected P =2.1×10−3). Genes with DNMs overlapped with genes implicated in autism (e.g. AUTS2, CDH8, MECP2) and intellectual disability (ID) (e.g. HUWE1 and TRAPPC9), supporting a shared genetic etiology between these disorders. Functionally CHD8, MECP2 and HUWE1 converge on epigenetic regulation of transcription suggesting that this may be an important risk mechanism. Our results were consistent in an analysis of additional exome based sequencing studies of other neurodevelopmental disorders. These findings suggest that perturbations in genes which function in the epigenetic regulation of brain development and cognition could have a central role in the susceptibility to, pathogenesis, and treatment of mental disorders.