Gene expression in the primate orbitofrontal cortex related to anxious temperament.

Anxiety disorders are among the most prevalent psychiatric disorders, causing significant suffering and disability. Relative to other psychiatric disorders, anxiety disorders tend to emerge early in life, supporting the importance of developmental mechanisms in their emergence and maintenance. Behavioral inhibition (BI) is a temperament that emerges early in life and, when stable and extreme, is linked to an increased risk for the later development of anxiety disorders and other stress-related psychopathology. Understanding the neural systems and molecular mechanisms underlying this dispositional risk could provide insight into treatment targets for anxiety disorders. Nonhuman primates (NHPs) have an anxiety-related temperament, called anxious temperament (AT), that is remarkably similar to BI in humans, facilitating the design of highly translational models for studying the early risk for stress-related psychopathology. Because of the recent evolutionary divergence between humans and NHPs, many of the anxiety-related brain regions that contribute to psychopathology are highly similar in terms of their structure and function, particularly with respect to the prefrontal cortex. The orbitofrontal cortex plays a critical role in the flexible encoding and regulation of threat responses, in part through connections with subcortical structures like the amygdala. Here, we explore individual differences in the transcriptional profile of cells within the region, using laser capture microdissection and single nuclear sequencing, providing insight into the molecules underlying individual differences in AT-related function of the pOFC, with a particular focus on previously implicated cellular systems, including neurotrophins and glucocorticoid signaling.

Effect of Total SMS Activity on LDL Catabolism in Mice.

BACKGROUND: Sphingomyelin (SM) and cholesterol are 2 key lipid partners on cell membranes and on lipoproteins. Many studies have indicated the influence of cholesterol on SM metabolism. This study examined the influence of SM biosynthesis on cholesterol metabolism. METHODS: Inducible global Sms1 KO (knockout)/global Sms2 KO mice were prepared to evaluate the effect of whole-body SM biosynthesis deficiency on lipoprotein metabolism. Tissue cholesterol, SM, ceramide, and glucosylceramide levels were measured. Triglyceride production rate and LDL (low-density lipoprotein) catabolism were measured. Lipid rafts were isolated and LDL receptor mass and function were evaluated. Also, the effects of exogenous sphingolipids on hepatocytes were investigated. RESULTS: We found that total SMS (SM synthase) depletion significantly reduced plasma SM levels. Also, the total deficiency significantly induced plasma cholesterol, apoB (apolipoprotein B), and apoE (apolipoprotein E) levels. Importantly, total SMS deficiency, but not SMS2 deficiency, dramatically decreased LDL receptors in the liver and attenuated LDL uptake through the receptor. Further, we found that total SMS deficiency greatly reduced LDL receptors in the lipid rafts, which contained significantly lower SM and significantly higher glucosylceramide, as well as cholesterol. Furthermore, we treated primary hepatocytes and Huh7 cells (a human hepatoma cell line) with SM, ceramide, or glucosylceramide, and we found that only SM could upregulate LDL receptor levels in a dose-dependent fashion. CONCLUSIONS: Whole-body SM biosynthesis plays an important role in LDL cholesterol catabolism. The total SMS deficiency, but not SMS2 deficiency, reduces LDL uptake and causes LDL cholesterol accumulation in the circulation. Given the fact that serum SM level is a risk factor for cardiovascular diseases, inhibiting SMS2 but not SMS1 should be the desirable approach.

Assessing characteristics of RNA amplification methods for single cell RNA sequencing.

BACKGROUND: Recently, measurement of RNA at single cell resolution has yielded surprising insights. Methods for single-cell RNA sequencing (scRNA-seq) have received considerable attention, but the broad reliability of single cell methods and the factors governing their performance are still poorly known. RESULTS: Here, we conducted a large-scale control experiment to assess the transfer function of three scRNA-seq methods and factors modulating the function. All three methods detected greater than 70% of the expected number of genes and had a 50% probability of detecting genes with abundance greater than 2 to 4 molecules. Despite the small number of molecules, sequencing depth significantly affected gene detection. While biases in detection and quantification were qualitatively similar across methods, the degree of bias differed, consistent with differences in molecular protocol. Measurement reliability increased with expression level for all methods and we conservatively estimate measurements to be quantitative at an expression level greater than ~5-10 molecules. CONCLUSIONS: Based on these extensive control studies, we propose that RNA-seq of single cells has come of age, yielding quantitative biological information.

FadE: whole genome methylation analysis for multiple sequencing platforms.

DNA methylation plays a central role in genomic regulation and disease. Sodium bisulfite treatment (SBT) causes unmethylated cytosines to be sequenced as thymine, which allows methylation levels to reflected in the number of 'C'-'C' alignments covering reference cytosines. Di-base color reads produced by lifetech's SOLiD sequencer provide unreliable results when translated to bases because single sequencing errors effect the downstream sequence. We describe FadE, an algorithm to accurately determine genome-wide methylation rates directly in color or nucleotide space. FadE uses SBT unmethylated and untreated data to determine background error rates and incorporate them into a model which uses Newton-Raphson optimization to estimate the methylation rate and provide a credible interval describing its distribution at every reference cytosine. We sequenced two slides of human fibroblast cell-line bisulfite-converted fragment library with the SOLiD sequencer to investigate genome-wide methylation levels. FadE reported widespread differences in methylation levels across CpG islands and a large number of differentially methylated regions adjacent to genes which compares favorably to the results of an investigation on the same cell-line using nucleotide-space reads at higher coverage levels, suggesting that FadE is an accurate method to estimate genome-wide methylation with color or nucleotide reads. http://code.google.com/p/fade/.

BridgePRS leverages shared genetic effects across ancestries to increase polygenic risk score portability.

Here we present BridgePRS, a novel Bayesian polygenic risk score (PRS) method that leverages shared genetic effects across ancestries to increase PRS portability. We evaluate BridgePRS via simulations and real UK Biobank data across 19 traits in individuals of African, South Asian and East Asian ancestry, using both UK Biobank and Biobank Japan genome-wide association study summary statistics; out-of-cohort validation is performed in the Mount Sinai (New York) BioMe biobank. BridgePRS is compared with the leading alternative, PRS-CSx, and two other PRS methods. Simulations suggest that the performance of BridgePRS relative to PRS-CSx increases as uncertainty increases: with lower trait heritability, higher polygenicity and greater between-population genetic diversity; and when causal variants are not present in the data. In real data, BridgePRS has a 61% larger average R2 than PRS-CSx in out-of-cohort prediction of African ancestry samples in BioMe (P = 6 × 10-5). BridgePRS is a computationally efficient, user-friendly and powerful approach for PRS analyses in non-European ancestries.

BridgePRS : A powerful trans-ancestry Polygenic Risk Score method.

Polygenic Risk Scores (PRS) have huge potential to contribute to biomedical research and to a future of precision medicine, but to date their calculation relies largely on Europeanancestry GWAS data. This global bias makes most PRS substantially less accurate in individuals of non-European ancestry. Here we present BridgePRS , a novel Bayesian PRS method that leverages shared genetic effects across ancestries to increase the accuracy of PRS in non-European populations. The performance of BridgePRS is evaluated in simulated data and real UK Biobank (UKB) data across 19 traits in African, South Asian and East Asian ancestry individuals, using both UKB and Biobank Japan GWAS summary statistics. BridgePRS is compared to the leading alternative, PRS-CSx , and two single-ancestry PRS methods adapted for trans-ancestry prediction. PRS trained in the UK Biobank are then validated out-of-cohort in the independent Mount Sinai (New York) Bio Me Biobank. Simulations reveal that BridgePRS performance, relative to PRS-CSx , increases as uncertainty increases: with lower heritability, higher polygenicity, greater between-population genetic diversity, and when causal variants are not present in the data. Our simulation results are consistent with real data analyses in which BridgePRS has better predictive accuracy in African ancestry samples, especially in out-of-cohort prediction (into Bio Me ), which shows a 60% boost in mean R 2 compared to PRS-CSx ( P = 2 × 10 -6 ). BridgePRS performs the full PRS analysis pipeline, is computationally efficient, and is a powerful method for deriving PRS in diverse and under-represented ancestry populations.

RseqFlow: workflows for RNA-Seq data analysis.

SUMMARY: We have developed an RNA-Seq analysis workflow for single-ended Illumina reads, termed RseqFlow. This workflow includes a set of analytic functions, such as quality control for sequencing data, signal tracks of mapped reads, calculation of expression levels, identification of differentially expressed genes and coding SNPs calling. This workflow is formalized and managed by the Pegasus Workflow Management System, which maps the analysis modules onto available computational resources, automatically executes the steps in the appropriate order and supervises the whole running process. RseqFlow is available as a Virtual Machine with all the necessary software, which eliminates any complex configuration and installation steps. AVAILABILITY AND IMPLEMENTATION: http://genomics.isi.edu/rnaseq CONTACT: wangying@xmu.edu.cn; knowles@med.usc.edu; deelman@isi.edu; tingchen@usc.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PerM: efficient mapping of short sequencing reads with periodic full sensitive spaced seeds.

MOTIVATION: The explosion of next-generation sequencing data has spawned the design of new algorithms and software tools to provide efficient mapping for different read lengths and sequencing technologies. In particular, ABI's sequencer (SOLiD system) poses a big computational challenge with its capacity to produce very large amounts of data, and its unique strategy of encoding sequence data into color signals. RESULTS: We present the mapping software, named PerM (Periodic Seed Mapping) that uses periodic spaced seeds to significantly improve mapping efficiency for large reference genomes when compared with state-of-the-art programs. The data structure in PerM requires only 4.5 bytes per base to index the human genome, allowing entire genomes to be loaded to memory, while multiple processors simultaneously map reads to the reference. Weight maximized periodic seeds offer full sensitivity for up to three mismatches and high sensitivity for four and five mismatches while minimizing the number random hits per query, significantly speeding up the running time. Such sensitivity makes PerM a valuable mapping tool for SOLiD and Solexa reads. AVAILABILITY: http://code.google.com/p/perm/

Robust RNA-Seq of aRNA-amplified single cell material collected by patch clamp.

Most single cell RNA sequencing protocols start with single cells dispersed from intact tissue. High-throughput processing of the separated cells is enabled using microfluidics platforms. However, dissociation of tissue results in loss of information about cell location and morphology and potentially alters the transcriptome. An alternative approach for collecting RNA from single cells is to re-purpose the electrophysiological technique of patch clamp recording. A hollow patch pipette is attached to individual cells, enabling the recording of electrical activity, after which the cytoplasm may be extracted for single cell RNA-Seq ("Patch-Seq"). Since the tissue is not disaggregated, the location of cells is readily determined, and the morphology of the cells is maintained, making possible the correlation of single cell transcriptomes with cell location, morphology and electrophysiology. Recent Patch-Seq studies utilizes PCR amplification to increase amount of nucleic acid material to the level required for current sequencing technologies. PCR is prone to create biased libraries - especially with the extremely high degrees of exponential amplification required for single cell amounts of RNA. We compared a PCR-based approach with linear amplifications and demonstrate that aRNA amplification (in vitro transcription, IVT) is more sensitive and robust for single cell RNA collected by a patch clamp pipette.

Transcriptional Profiling of Primate Central Nucleus of the Amygdala Neurons to Understand the Molecular Underpinnings of Early-Life Anxious Temperament.

BACKGROUND: Children exhibiting extreme anxious temperament (AT) are at an increased risk for developing anxiety and depression. Our previous mechanistic and neuroimaging work in young rhesus monkeys linked the central nucleus of the amygdala to AT and its underlying neural circuit. METHODS: Here, we used laser capture microscopy and RNA sequencing in 47 young rhesus monkeys to investigate AT's molecular underpinnings by focusing on neurons from the lateral division of the central nucleus of the amygdala (CeL). RNA sequencing identified numerous AT-related CeL transcripts, and we used immunofluorescence (n = 3) and tract-tracing (n = 2) methods in a different sample of monkeys to examine the expression, distribution, and projection pattern of neurons expressing one of these transcripts. RESULTS: We found 555 AT-related transcripts, 14 of which were confirmed with high statistical confidence (false discovery rate < .10), including protein kinase C delta (PKCδ), a CeL microcircuit cell marker implicated in rodent threat processing. We characterized PKCδ neurons in the rhesus CeL, compared its distribution with that of the mouse, and demonstrated that a subset of these neurons project to the laterodorsal bed nucleus of the stria terminalis. CONCLUSIONS: These findings demonstrate that CeL PKCδ is associated with primate anxiety, provides evidence of a CeL to laterodorsal bed nucleus of the stria terminalis circuit that may be relevant to understanding human anxiety, and points to specific molecules within this circuit that could serve as potential treatment targets for anxiety disorders.

Gene Expression in Patient-Derived Neural Progenitors Implicates WNT5A Signaling in the Etiology of Schizophrenia.

BACKGROUND: Genome-wide association studies of schizophrenia have demonstrated that variations in noncoding regions are responsible for most of the common variation heritability of the disease. It is hypothesized that these risk variants alter gene expression. Therefore, studying alterations in gene expression in schizophrenia may provide a direct approach to understanding the etiology of the disease. In this study we use cultured neural progenitor cells derived from olfactory neuroepithelium (CNON cells) as a genetically unaltered cellular model to elucidate the neurodevelopmental aspects of schizophrenia. METHODS: We performed a gene expression study using RNA sequencing of CNON cells from 111 control subjects and 144 individuals with schizophrenia. Differentially expressed genes were identified with DESeq2 software, using covariates to correct for sex, age, library batches, and 1 surrogate variable component. RESULTS: A total of 80 genes were differentially expressed (false discovery rate < 10%), showing enrichment in cell migration, cell adhesion, developmental process, synapse assembly, cell proliferation, and related Gene Ontology categories. Cadherin and Wnt signaling pathways were positive in overrepresentation test, and, in addition, many genes were specifically involved in WNT5A signaling. The differentially expressed genes were modestly, but significantly, enriched in the genes overlapping single nucleotide polymorphisms with genome-wide significant association from the Psychiatric Genomics Consortium genome-wide association study of schizophrenia. We also found substantial overlap with genes associated with other psychiatric disorders or brain development, enrichment in the same Gene Ontology categories as genes with mutations de novo in schizophrenia, and studies of induced pluripotent stem cell-derived neural progenitor cells. CONCLUSIONS: CNON cells are a good model of the neurodevelopmental aspects of schizophrenia and can be used to elucidate the etiology of the disorder.

Deconvolution of transcriptional networks identifies TCF4 as a master regulator in schizophrenia.

Applying tissue-specific deconvolution of transcriptional networks to identify their master regulators (MRs) in neuropsychiatric disorders has been largely unexplored. Here, using two schizophrenia (SCZ) case-control RNA-seq datasets, one on postmortem dorsolateral prefrontal cortex (DLPFC) and another on cultured olfactory neuroepithelium, we deconvolved the transcriptional networks and identified TCF4 as a top candidate MR that may be dysregulated in SCZ. We validated TCF4 as a MR through enrichment analysis of TCF4-binding sites in induced pluripotent stem cell (hiPSC)-derived neurons and in neuroblastoma cells. We further validated the predicted TCF4 targets by knocking down TCF4 in hiPSC-derived neural progenitor cells (NPCs) and glutamatergic neurons (Glut_Ns). The perturbed TCF4 gene network in NPCs was more enriched for pathways involved in neuronal activity and SCZ-associated risk genes, compared to Glut_Ns. Our results suggest that TCF4 may serve as a MR of a gene network dysregulated in SCZ at early stages of neurodevelopment.

Dorsal Amygdala Neurotrophin-3 Decreases Anxious Temperament in Primates.

BACKGROUND: An early-life anxious temperament (AT) is a risk factor for the development of anxiety, depression, and comorbid substance abuse. We validated a nonhuman primate model of early-life AT and identified the dorsal amygdala as a core component of AT's neural circuit. Here, we combine RNA sequencing, viral-vector gene manipulation, functional brain imaging, and behavioral phenotyping to uncover AT's molecular substrates. METHODS: In response to potential threat, AT and brain metabolism were assessed in 46 young rhesus monkeys. We identified AT-related transcripts using RNA-sequencing data from dorsal amygdala tissue (including central nucleus of the amygdala [Ce] and dorsal regions of the basal nucleus). Based on the results, we overexpressed the neurotrophin-3 gene, NTF3, in the dorsal amygdala using intraoperative magnetic resonance imaging-guided surgery (n = 5 per group). RESULTS: This discovery-based approach identified AT-related alterations in the expression of well-established and novel genes, including an inverse association between NTRK3 expression and AT. NTRK3 is an interesting target because it is a relatively unexplored neurotrophic factor that modulates intracellular neuroplasticity pathways. Overexpression of the transcript for NTRK3's endogenous ligand, NTF3, in the dorsal amygdala resulted in reduced AT and altered function in AT's neural circuit. CONCLUSIONS: Together, these data implicate neurotrophin-3/NTRK3 signaling in the dorsal amygdala in mediating primate anxiety. More generally, this approach provides an important step toward understanding the molecular underpinnings of early-life AT and will be useful in guiding the development of treatments to prevent the development of stress-related psychopathology.

Spatiotemporal profile of postsynaptic interactomes integrates components of complex brain disorders.

The postsynaptic density (PSD) contains a collection of scaffold proteins used for assembling synaptic signaling complexes. However, it is not known how the core-scaffold machinery associates in protein-interaction networks or how proteins encoded by genes involved in complex brain disorders are distributed through spatiotemporal protein complexes. Here using immunopurification, proteomics and bioinformatics, we isolated 2,876 proteins across 41 in vivo interactomes and determined their protein domain composition, correlation to gene expression levels and developmental integration to the PSD. We defined clusters for enrichment of schizophrenia, autism spectrum disorders, developmental delay and intellectual disability risk factors at embryonic day 14 and adult PSD in mice. Mutations in highly connected nodes alter protein-protein interactions modulating macromolecular complexes enriched in disease risk candidates. These results were integrated into a software platform, Synaptic Protein/Pathways Resource (SyPPRes), enabling the prioritization of disease risk factors and their placement within synaptic protein interaction networks.

Non-coding RNAs derived from an alternatively spliced REST transcript (REST-003) regulate breast cancer invasiveness.

RE1-Silencing Transcription factor (REST) has a well-established role in regulating transcription of genes important for neuronal development. Its role in cancer, though significant, is less well understood. We show that REST downregulation in weakly invasive MCF-7 breast cancer cells converts them to a more invasive phenotype, while REST overexpression in highly invasive MDA-MB-231 cells suppresses invasiveness. Surprisingly, the mechanism responsible for these phenotypic changes does not depend directly on the transcriptional function of REST protein. Instead, it is driven by previously unstudied mid-size (30-200 nt) non-coding RNAs (ncRNAs) derived from the first exon of an alternatively spliced REST transcript: REST-003. We show that processing of REST-003 into ncRNAs is controlled by an uncharacterized serine/arginine repeat-related protein, SRRM3. SRRM3 expression may be under REST-mediated transcriptional control, as it increases following REST downregulation. The SRRM3-dependent regulation of REST-003 processing into ncRNAs has many similarities to recently described promoter-associated small RNA-like processes. Targeting ncRNAs that control invasiveness could lead to new therapeutic approaches to limit breast cancer metastasis.

Effect of RNA integrity on uniquely mapped reads in RNA-Seq.

BACKGROUND: We examined the performance of three RNA-Sequencing library preparation protocols as a function of RNA integrity, comparing gene expressions between heat-degraded samples to their high-quality counterparts. This work is invaluable given the difficulty of obtaining high-quality RNA from tissues, particularly those from individuals with disease phenotypes. RESULTS: With the integrity of total RNA being a critical parameter for RNA-Sequencing analysis, degraded RNA can heavily influence the results of gene expression profiles. We discovered that gene expression read results are influenced by RNA quality when a common library construction protocol is used. These results are based on one technical experiment from a pool of 4 neural progenitor cell lines. CONCLUSIONS: The use of alternative protocols can allow samples with a wider range of RNA qualities to be used, facilitating the investigation of disease tissues.

ComB: SNP calling and mapping analysis for color and nucleotide space platforms.

The determination of single nucleotide polymorphisms (SNPs) has become faster and more cost effective since the advent of short read data from next generation sequencing platforms such as Roche's 454 Sequencer, Illumina's Solexa platform, and Applied Biosystems SOLiD sequencer. The SOLiD sequencing platform, which is capable of producing more than 6 GB of sequence data in a single run, uses a unique encoding scheme where color reads represent transitions between adjacent nucleotides. The determination of SNPs from color reads usually involves the translation of color alignments to likely nucleotide strings to facilitate the use of tools designed for nucleotide reads. This technique results in the loss of significant information in the color read, producing many incorrect SNP calls, especially if regions exist with dense or adjacent polymorphism. Additionally, color reads align ambiguously and incorrectly more often than nucleotide reads making integrated SNP calling a difficult challenge. We have developed ComB, a SNP calling tool which operates directly in color space, using a Bayesian model to incorporate unique and ambiguous reads to iteratively determine SNP identity. ComB is capable of accurately calling short consecutive nucleotide polymorphisms and densely clustered SNPs; both of which other SNP calling tools fail to identify. ComB, which is capable of using billions of short reads to accurately and efficiently perform whole human genome SNP calling in parallel, is also capable of using sequence data or even integrating sequence and color space data sets. We use real and simulated data to demonstrate that ComB's iterative strategy and recalibration of quality scores allow it to discover more true SNPs while calling fewer false positives than tools which use only color alignments as well as tools which translate color reads to nucleotide strings.