Genes, behavior and next-generation RNA sequencing

Aggregated gene co-expression networks predict transcription factor regulatory landscapes in grapevine

Gene co-expression networks (GCNs) have not been extensively studied in non-model plants. However, the rapid accumulation of transcriptome datasets in certain species represents an opportunity to explore underutilized network aggregation approaches. In fact, aggregated GCNs (aggGCNs) highlight robust co-expression interactions and improve functional connectivity. We applied and evaluated two different aggregation methods on public grapevine RNA-Seq datasets from three different tissues (leaf, berry, and 'all organs'). Our results show that co-occurrence-based aggregation generally yielded the best-performing networks. We applied aggGCNs to study several transcription factor gene families, showing their capacity for detecting both already-described and novel regulatory relationships between R2R3-MYBs, bHLH/MYC, and multiple specialized metabolic pathways. Specifically, transcription factor gene- and pathway-centered network analyses successfully ascertained the previously established role of VviMYBPA1 in controlling the accumulation of proanthocyanidins while providing insights into its novel role as a regulator of p-coumaroyl-CoA biosynthesis as well as the shikimate and aromatic amino acid pathways. This network was validated using DNA affinity purification sequencing data, demonstrating that co-expression networks of transcriptional activators can serve as a proxy of gene regulatory networks. This study presents an open repository to reproduce networks in other crops and a GCN application within the Vitviz platform, a user-friendly tool for exploring co-expression relationships.

Modeling Brain Gene Expression in Alcohol Use Disorder with Genetic Animal Models

Animal genetic models have and will continue to provide important new information about the behavioral and physiological adaptations associated with alcohol use disorder (AUD). This chapter focuses on two models, ethanol preference and drinking in the dark (DID), their usefulness in interrogating brain gene expression data and the relevance of the data obtained to interpret AUD-related GWAS and TWAS studies. Both the animal and human data point to the importance for AUD of changes in synaptic transmission (particularly glutamate and GABA transmission), of changes in the extracellular matrix (specifically including collagens, cadherins and protocadherins) and of changes in neuroimmune processes. The implementation of new technologies (e.g., cell type-specific gene expression) is expected to further enhance the value of genetic animal models in understanding AUD.

Relationship between hippocampal gene expression and cognitive performance differences in visual discrimination learning task of male rats

Learning to discriminate between environmental visual stimuli is essential to make right decisions and guide appropriate behaviors. Moreover, impairments in visual discrimination learning are observed in several neuropsychiatric disorders. Visual discrimination learning requires perception and memory processing, in which the hippocampus critically involved. To understand the molecular mechanisms underpinning hippocampus function in visual discrimination learning, we examined the hippocampal gene expression profiles of Sprague-Dawley rats with different cognitive performance (high cognition group vs. low cognition group) in the modified visual discrimination learning task, using high-throughput RNA sequencing technology. Compared with the low cognition group, bioinformatics analysis indicated that 319 genes were differentially expressed in the high cognition group with statistical significance, of which 253 genes were down-regulated and 66 genes were up-regulated. The functional enrichment analysis showed that protein translation and energy metabolism were up-regulated pathways, while transforming growth factor beta receptor signaling pathway, bone morphogenetic protein signaling pathway, apoptosis, inflammation response, transport, and glycosaminoglycan metabolism were down-regulated pathways, which were related to good cognitive performance in the visual discrimination learning task. Taken together, our finding reveals the differential gene expression and enrichment biological pathways related to cognitive performance differences in visual discrimination learning of rats, which provides us direct insight into the molecular mechanisms of hippocampus function in visual discrimination learning and may contribute to developing potential treatment strategies for neuropsychiatric disorders accompanied with cognitive impairments.

Particulate matter impairs immune system function by up-regulating inflammatory pathways and decreasing pathogen response gene expression

Airborne particulate matter produced by industrial sources and automobiles has been linked to increased susceptibility to infectious diseases and it is known to be recognized by cells of the immune system. The molecular mechanisms and changes in gene expression profiles induced in immune cells by PM have not been fully mapped out or systematically integrated. Here, we use RNA-seq to analyze mRNA profiles of human peripheral blood mononuclear cells after exposure to coarse particulate matter (PM10). Our analyses showed that PM10 was able to reprogram the expression of 1,196 genes in immune cells, including activation of a proinflammatory state with an increase in cytokines and chemokines. Activation of the IL-36 signaling pathway and upregulation of chemokines involved in neutrophil and monocyte recruitment suggest mechanisms for inflammation upon PM exposure, while NK cell-recruiting chemokines are repressed. PM exposure also increases transcription factors associated with inflammatory pathways (e.g., JUN, RELB, NFKB2, etc.) and reduces expression of RNases and pathogen response genes CAMP, DEFAs, AZU1, APOBEC3A and LYZ. Our analysis across gene regulatory and signaling pathways suggests that PM plays a role in the dysregulation of immune cell functions, relevant for antiviral responses and general host defense against pathogens.

Optimization of RNA extraction for bacterial whole transcriptome studies of low-biomass samples

We developed a procedure for extracting maximal amounts of high-quality RNA from low-biomass producing (autotrophic) bacteria for experiments where sample volume is limited. Large amounts of high-quality RNA for downstream analyses cannot be obtained using larger quantities of culture volume. The performance of standard commercial silica-column based kit protocols and these procedures amended by ultrasonication or enzymatic lysis were assessed. The ammonium-oxidizing Nitrosomonas europaea and nitrite-oxidizing Nitrobacter winogradskyi were used as model organisms for optimization of the RNA isolation protocol. Enzymatic lysis through lysozyme digestion generated high-quality, high-yield RNA samples. Subsequent RNA-seq analysis resulted in qualitative data for both strains. The RNA extraction procedure is suitable for experiments with volume and/or biomass limitations, e.g., as encountered during space flight experiments. Furthermore, it will also result in higher RNA yields for whole transcriptome experiments where sample volume and/or biomass was increased to compensate the low-biomass characteristic of autotrophs.

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Lysis through ultrasonication results in a high RNA yield but in a low RNA quality

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Enzymatic lysis using lysozyme provides high-yield, high-quality RNA samples

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RNA from low-biomass bacterial samples is suitable for downstream RNA-seq

Transcriptomic analysis reveals crucial regulatory roles of immediate-early response genes and related signaling pathways in coronavirus infectious bronchitis virus infection

Coronavirus infection of cells differentially regulates the expression of host genes and their related pathways. In this study, we present the transcriptomic profile of cells infected with gammacoronavirus infectious bronchitis virus (IBV). In IBV-infected human non-small cell lung carcinoma cells (H1299 cells), a total of 1162 differentially expressed genes (DEGs), including 984 upregulated and 178 downregulated genes, was identified. These DEGs were mainly enriched in MAPK and Wnt signaling pathways, and 5 out of the 10 top upregulated genes in all transcripts were immediate-early response genes (IEGs). In addition, the induction of 11 transcripts was validated in IBV-infected H1299 and Vero cells by RT-qPCR. The accuracy, reliability and genericity of the transcriptomic data were demonstrated by functional characterization of these IEGs in cells infected with different coronaviruses in our previous publications. This study provides a reliable transcriptomic profile of host genes and pathways regulated by coronavirus infection.

On the Use of Heterogeneous Stock Mice to Map Transcriptomes Associated With Excessive Ethanol Consumption

We and many others have noted the advantages of using heterogeneous (HS) animals to map genes and gene networks associated with both behavioral and non-behavioral phenotypes. Importantly, genetically complex Mus musculus crosses provide substantially increased resolution to examine old and new relationships between gene expression and behavior. Here we report on data obtained from two HS populations: the HS/NPT derived from eight inbred laboratory mouse strains and the HS-CC derived from the eight collaborative cross inbred mouse strains that includes three wild-derived strains. Our work has focused on the genes and gene networks associated with risk for excessive ethanol consumption, individual variation in ethanol consumption and the consequences, including escalation, of long-term ethanol consumption. Background data on the development of HS mice is provided, including advantages for the detection of expression quantitative trait loci. Examples are also provided of using HS animals to probe the genes associated with ethanol preference and binge ethanol consumption.

SeqNet: An R Package for Generating Gene-Gene Networks and Simulating RNA-Seq Data

Gene expression data provide an abundant resource for inferring connections in gene regulatory networks. While methodologies developed for this task have shown success, a challenge remains in comparing the performance among methods. Gold-standard datasets are scarce and limited in use. And while tools for simulating expression data are available, they are not designed to resemble the data obtained from RNA-seq experiments. SeqNet is an R package that provides tools for generating a rich variety of gene network structures and simulating RNA-seq data from them. This produces in silico RNA-seq data for benchmarking and assessing gene network inference methods. The package is available on CRAN and on GitHub at https://github.com/tgrimes/SeqNet.

Expression Profiles of Circular RNAs in Human Papillary Thyroid Carcinoma Based on RNA Deep Sequencing

Background

Papillary thyroid carcinoma (PTC) is the most prevalent type of thyroid cancer. Herein, we purposed to explore the expression patterns of circRNAs in PTC with the overarching goal of improving early diagnosis rates for individuals with PTC.

Methods

We used RNA deep sequencing to determine the expression patterns of circRNAs in PTC. Besides, RT-qPCR was employed to confirm circRNAs. The diagnostic potential of the circRNAs was explored by constructing ROC curves. GO along with KEGG pathway analyses were utilized to elucidate the potential biological roles of differentially expressed circRNAs. Moreover, we predicted cross talks among circRNAs, miRNAs, and mRNAs, followed by establishment of a ceRNA network.

Results

Deep sequencing of four PTC pairs and neighboring nontumor tissues identified 16569 circRNAs, of which, 301 were upregulated and 419 were downregulated. The RT-qPCR data demonstrated that the expression of chr5: 38481299-38530666-, chr2: 159932176-159945082-, chr10: 179994-249088+, chr3: 121378716-121381532+, and chr1: 237423092-237445522+ was downregulated, while the expression of chr4: 25665378-25667298+, chr5: 161330883-161336769-, chr1: 12578718-12579412-, chr7: 116695750-116700284+, and chr7: 116699071-116700284+ was upregulated. The stability test exhibited that circRNAs were more tolerant to temperature, RNase R, and time. On the other hand, ROC curves illustrated that chr4: 25665378-25667298+, chr1: 12578718-12579412-, chr7: 116699071-116700284+, chr7: 116695750-116700284+, chr5: 161330883-161336769-, and chr10: 179994-249088+ were effective as diagnostic indicators. However, a logistic regression model combining the six indicators achieved a better combined prediction index, with 97.7% sensitivity and 95.3% specificity. Moreover, GO along with KEGG pathway analyses illustrated that differentially expressed circRNAs were linked to tumorigenesis. Furthermore, bioinformatics analyses established a promising ceRNAs network among mRNAs, circRNAs, and miRNAs.

Conclusion

Herein, we demonstrated that several circRNAs are promising PTC diagnostic biomarkers. Further study on the functions and mechanisms of these circRNAs may contribute to the understanding of PTC.

Differential regulation of alcohol consumption and reward by the transcriptional cofactor LMO4

Repeated alcohol exposure leads to changes in gene expression that are thought to underlie the transition from moderate to excessive drinking. However, the mechanisms by which these changes are integrated into a maladaptive response that leads to alcohol dependence are not well understood. One mechanism could involve the recruitment of transcriptional co-regulators that bind and modulate the activity of transcription factors. Our results indicate that the transcriptional regulator LMO4 is one such candidate regulator. Lmo4-deficient mice (Lmo4gt/+) consumed significantly more and showed enhanced preference for alcohol in a 24 h intermittent access drinking procedure. shRNA-mediated knockdown of Lmo4 in the nucleus accumbens enhanced alcohol consumption, whereas knockdown in the basolateral amygdala (BLA) decreased alcohol consumption and reduced conditioned place preference for alcohol. To ascertain the molecular mechanisms that underlie these contrasting phenotypes, we carried out unbiased transcriptome profiling of these two brain regions in wild type and Lmo4gt/+ mice. Our results revealed that the transcriptional targets of LMO4 are vastly different between the two brain regions, which may explain the divergent phenotypes observed upon Lmo4 knockdown. Bioinformatic analyses revealed that Oprk1 and genes related to the extracellular matrix (ECM) are important transcriptional targets of LMO4 in the BLA. Chromatin immunoprecipitation revealed that LMO4 bound Oprk1 promoter elements. Consistent with these results, disruption of the ECM or infusion of norbinaltorphimine, a selective kappa opioid receptor antagonist, in the BLA reduced alcohol consumption. Hence our results indicate that an LMO4-regulated transcriptional network regulates alcohol consumption in the BLA.

Brain transcriptomics of nonhuman primates: A review

The brain is one of the most important and intricate organs in our bodies. Interpreting brain function and illustrating the changes and molecular mechanisms during physiological or pathological processes are essential but sometimes difficult to achieve. In addition to histology, ethology and pharmacology, the development of transcriptomics alleviates this condition by enabling high-throughput observation of the brain at various levels of anatomical specificity. Moreover, because human brain samples are scarce, the brains of nonhuman primates are important alternative models. Here in this review, we summarize the applications of transcriptomics in nonhuman primate brain studies, including investigations of brain development, aging, toxic effects and diseases. Overall, as a powerful tool with developmental potential, transcriptomics has been widely utilized in neuroscience.

Repeated morphine exposure activates synaptogenesis and other neuroplasticity-related gene networks in the dorsomedial prefrontal cortex of male and female rats

BACKGROUND

Opioid abuse is a chronic disorder likely involving stable neuroplastic modifications. While a number of molecules contributing to these changes have been identified, the broader spectrum of genes and gene networks that are affected by repeated opioid administration remain understudied.

METHODS

We employed Next-Generation RNA-sequencing (RNA-seq) followed by quantitative chromatin immunoprecipitation to investigate changes in gene expression and their regulation in adult male and female rats' dorsomedial prefrontal cortex (dmPFC) after a regimen of daily injection of morphine (5.0 mg/kg; 10 days). Ingenuity Pathway Analysis (IPA) was used to analyze affected molecular pathways, gene networks, and associated regulatory factors. A complementary behavioral study evaluated the effects of the same morphine injection regimen on locomotor activity, pain sensitivity, and somatic withdrawal signs.

RESULTS

Behaviorally, repeated morphine injection induced locomotor hyperactivity and hyperalgesia in both sexes. 90 % of differentially expressed genes (DEGs) in morphine-treated rats were upregulated in both males and females, with a 35 % overlap between sexes. A substantial number of DEGs play roles in synaptic signaling and neuroplasticity. Chromatin immunoprecipitation revealed enrichment of H3 acetylation, a transcriptionally activating chromatin mark. Although broadly similar, some differences were revealed in the gene ontology networks enriched in females and males.

CONCLUSIONS

Our results cohere with findings from previous studies based on a priori gene selection. Our results also reveal novel genes and molecular pathways that are upregulated by repeated morphine exposure, with some common to males and females and others that are sex-specific.

High heterogeneity undermines generalization of differential expression results in RNA-Seq analysis

BACKGROUND

RNA sequencing (RNA-Seq) has been widely applied in oncology for monitoring transcriptome changes. However, the emerging problem that high variation of gene expression levels caused by tumor heterogeneity may affect the reproducibility of differential expression (DE) results has rarely been studied. Here, we investigated the reproducibility of DE results for any given number of biological replicates between 3 and 24 and explored why a great many differentially expressed genes (DEGs) were not reproducible.

RESULTS

Our findings demonstrate that poor reproducibility of DE results exists not only for small sample sizes, but also for relatively large sample sizes. Quite a few of the DEGs detected are specific to the samples in use, rather than genuinely differentially expressed under different conditions. Poor reproducibility of DE results is mainly caused by high variation of gene expression levels for the same gene in different samples. Even though biological variation may account for much of the high variation of gene expression levels, the effect of outlier count data also needs to be treated seriously, as outlier data severely interfere with DE analysis.

CONCLUSIONS

High heterogeneity exists not only in tumor tissue samples of each cancer type studied, but also in normal samples. High heterogeneity leads to poor reproducibility of DEGs, undermining generalization of differential expression results. Therefore, it is necessary to use large sample sizes (at least 10 if possible) in RNA-Seq experimental designs to reduce the impact of biological variability and DE results should be interpreted cautiously unless soundly validated.

Experimental Strategies to Explore Drug Action and Resistance in Kinetoplastid Parasites

Kinetoplastids are the causative agents of leishmaniasis, human African trypanosomiasis, and American trypanosomiasis. They are responsible for high mortality and morbidity in (sub)tropical regions. Adequate treatment options are limited and have several drawbacks, such as toxicity, need for parenteral administration, and occurrence of treatment failure and drug resistance. Therefore, there is an urgency for the development of new drugs. Phenotypic screening already allowed the identification of promising new chemical entities with anti-kinetoplastid activity potential, but knowledge on their mode-of-action (MoA) is lacking due to the generally applied whole-cell based approach. However, identification of the drug target is essential to steer further drug discovery and development. Multiple complementary techniques have indeed been used for MoA elucidation. In this review, the different 'omics' approaches employed to define the MoA or mode-of-resistance of current reference drugs and some new anti-kinetoplastid compounds are discussed.

Non-coding RNAs in neuropathic pain

Neuro-immune alterations in the peripheral and central nervous system play a role in the pathophysiology of chronic pain in general, and members of the non-coding RNA (ncRNA) family, specifically the short, 22 nucleotide microRNAs (miRNAs) and the long non-coding RNAs (lncRNAs) act as master switches orchestrating both immune as well as neuronal processes. Several chronic disorders reveal unique ncRNA expression signatures, which recently generated big hopes for new perspectives for the development of diagnostic applications. lncRNAs may offer perspectives as candidates indicative of neuropathic pain in liquid biopsies. Numerous studies have provided novel mechanistic insight into the role of miRNAs in the molecular sequelae involved in the pathogenesis of neuropathic pain along the entire pain pathway. Specific processes within neurons, immune cells, and glia as the cellular components of the neuropathic pain triad and the communication paths between them are controlled by specific miRNAs. Therefore, nucleotide sequences mimicking or antagonizing miRNA actions can provide novel therapeutic strategies for pain treatment, provided their human homologues serve the same or similar functions. Increasing evidence also sheds light on the function of lncRNAs, which converge so far mainly on purinergic signalling pathways both in neurons and glia, and possibly even other ncRNA species that have not been explored so far.

RNA-Seq Analysis of Genetic and Transcriptome Network Effects of Dual-Trait Selection for Ethanol Preference and Withdrawal Using SOT and NOT Genetic Models

BACKGROUND

Genetic factors significantly affect alcohol consumption and vulnerability to withdrawal. Furthermore, some genetic models showing predisposition to severe withdrawal are also predisposed to low ethanol (EtOH) consumption and vice versa, even when tested independently in naïve animals.

METHODS

Beginning with a C57BL/6J × DBA/2J F2 intercross founder population, animals were simultaneously selectively bred for both high alcohol consumption and low acute withdrawal (SOT line), or vice versa (NOT line). Using randomly chosen fourth selected generation (S4) mice (N = 18-22/sex/line), RNA-Seq was employed to assess genome-wide gene expression in ventral striatum. The MegaMUGA array was used to detect genome-wide genotypic differences. Differential gene expression and the weighted gene co-expression network analysis were implemented as described elsewhere (Genes Brain Behav 16, 2017, 462).

RESULTS

The new selection of the SOT and NOT lines was similar to that reported previously (Alcohol Clin Exp Res 38, 2014, 2915). One thousand eight hundred and sixteen transcripts were detected as differentially expressed between the lines. For genes more highly expressed in the SOT line, there was enrichment in genes associated with cell adhesion, synapse organization, and postsynaptic membrane. The genes with a cell adhesion annotation included 23 protocadherins, Mpdz and Dlg2. Genes with a postsynaptic membrane annotation included Gabrb3, Gphn, Grid1, Grin2b, Grin2c, and Grm3. The genes more highly expressed in the NOT line were enriched in a network module (red) with annotations associated with mitochondrial function. Several of these genes were module hub nodes, and these included Nedd8, Guk1, Elof1, Ndufa8, and Atp6v1f.

CONCLUSIONS

Marked effects of selection on gene expression were detected. The NOT line was characterized by higher expression of hub nodes associated with mitochondrial function. Genes more highly expressed in the SOT aligned with previous findings, for example, Colville and colleagues (Genes Brain Behav 16, 2017, 462) that both high EtOH preference and consumption are associated with effects on cell adhesion and glutamate synaptic plasticity.

Transcriptomic Analysis of Testicular Gene Expression in Normal and Cryptorchid Horses

Simple Summary

Cryptorchidism is a common congenital malformation that results in impaired fertility in horses. The high abdominal temperature and the effects of this disease lead to differences in gene expression between retained testes and descended testes (DTs). Here, we focus on the genetic effects of cryptorchidism. All the differentially expressed genes (DEGs) between undescended testes (UDTs) and DTs were analyzed in this study. A total of 84 DEGs were associated with functions related to sperm development and male reproductive performance. Our study has provided fundamental transcriptomic data for future studies on equine testes and cryptorchidism.

Abstract

Testes produce sperm, and investigations into gene expression in the testes will enhance the understanding of the roles of testicular genes in male reproduction. Cryptorchidism, the failure of one or both testes to descend into the scrotal sac, is a common congenital malformation in horses. The major clinical consequence of this abnormality is impaired fertility. The aim of this study was to analyze the expression patterns of testicular genes and to identify the differentially expressed genes (DEGs) in testes between cryptorchid and normal horses. In this study, the gene expression patterns in equine testes and the DEGs between mature descended testes (DTs) and undescended testes (UDTs) were identified by RNA-seq and validated by real-time qPCR. Our results provide comprehensive transcriptomic data on equine testes. The transcriptomic analysis revealed 11 affected genes that were downregulated in UDTs, possibly as a result of the higher temperature in the abdomen than in the scrotal sac. These 11 genes have previously been associated with male reproduction, and their downregulation might explain the impaired fertility of cryptorchid horses. Two homozygous missense mutations detected in horses with cryptorchidism were absent in normal horses and were listed as potential pathogenic mutations; these mutations should be verified in the future.

Function of fibroblast growth factor 2 in gastric cancer occurrence and prognosis

The present study aimed to explore the role of fibroblast growth factor 2 (FGF2) in the development and prognosis of gastric cancer (GC). The relationship between FGF2 mRNA expression levels and the clinical characteristics of GC was investigated using microarray data from four GC cohorts involving 726 patients obtained from the Gene Expression Omnibus. The results of the present study indicated that FGF2 expression levels were an independent factor affecting the prognosis of GC. The primary functions of FGF2 were related to cell adhesion and angiogenesis, and patients with high levels of FGF2 expression had poorer TNM staging and prognosis; these differences were statistically significant. In terms of immune infiltration, a higher extent of M2 macrophage intrusion was observed in patients with higher levels of FGF2. However, the degree of infiltration by dendritic and CD4⁺ T cells was lower, and this difference was statistically significant. Multivariate Cox proportional hazards model analysis revealed that age, TNM staging and FGF2 expression levels were independent prognostic factors for GC. In summary, FGF2 expression was demonstrated to be an independent prognostic factor in GC, and higher levels of FGF2 may promote the progression of this malignancy.

RNA sampling from tissue sections using infrared laser ablation

RNA was obtained from discrete locations of frozen rat brain tissue sections through infrared (IR) laser ablation using a 3-μm wavelength in transmission geometry. The ablated plume was captured in a microcentrifuge tube containing RNAse-free buffer and processed using a commercial RNA purification kit. RNA transfer efficiency and integrity were evaluated based on automated electrophoresis in microfluidic chips. Reproducible IR-laser ablation of intact RNA was demonstrated with purified RNA at laser fluences of 3-5 kJ/m² (72 ± 12% transfer efficiency) and with tissue sections at a laser fluence of 13 kJ/m² (79 ± 14% transfer efficiency); laser energies were attenuated ∼20% by the soda-lime glass slides used to support the samples. RNA integrity from tissue ablation was >90% of its original RIN value (∼7) and the purified RNA was sufficiently intact for conversion to cDNA and subsequent qPCR assay.

Regional Analysis of the Brain Transcriptome in Mice Bred for High and Low Methamphetamine Consumption

Transcriptome profiling can broadly characterize drug effects and risk for addiction in the absence of drug exposure. Modern large-scale molecular methods, including RNA-sequencing (RNA-Seq), have been extensively applied to alcohol-related disease traits, but rarely to risk for methamphetamine (MA) addiction. We used RNA-Seq data from selectively bred mice with high or low risk for voluntary MA intake to construct coexpression and cosplicing networks for differential risk. Three brain reward circuitry regions were explored, the nucleus accumbens (NAc), prefrontal cortex (PFC), and ventral midbrain (VMB). With respect to differential gene expression and wiring, the VMB was more strongly affected than either the PFC or NAc. Coexpression network connectivity was higher in the low MA drinking line than in the high MA drinking line in the VMB, oppositely affected in the NAc, and little impacted in the PFC. Gene modules protected from the effects of selection may help to eliminate certain mechanisms from significant involvement in risk for MA intake. One such module was enriched in genes with dopamine-associated annotations. Overall, the data suggest that mitochondrial function and glutamate-mediated synaptic plasticity have key roles in the outcomes of selective breeding for high versus low levels of MA intake.

Expression profiles of circular RNAs in human colorectal cancer based on RNA deep sequencing

Background

Circular RNAs (circRNAs) are a novel group of RNAs and play essential roles in cancers. However, the expression profiles of circRNAs in human colorectal cancer (CRC) are largely unclear.

Methods

The differentially expressed circRNAs, mRNAs, and microRNAs (miRNAs) between CRC tissues and paired adjacent normal tissues were first screened. Then, gene ontology and pathway analyses were performed to predict the possible functions. In addition, we identified the differentially expressed circRNAs in CRC correlated with Krüppel‐like factor 4 (KLF4) and validated their expression levels in CRC tissues. Finally, the correlations between hsa_circ_0142527 expression levels and clinicopathological features of patients with CRC were also analyzed.

Results

After filtered 4735 circRNAs by RNA deep sequencing, 67 differentially expressed circRNAs (fold change >2.0, P < 0.05) were selected. The top two pathways were cell cycle and other glycan degradation. Hsa_circ_0142527 and KLF4 mRNA were significantly lower expressed in CRC tissues in both training and confirm groups and have high positive correlation (r = 0.754). We further found that the expression levels of hsa_circ_0142527 were significantly associated with age (P = 0.004), differentiation (P = 0.008), invasion (P = 0.029), distal metastasis (P = 0.004), TNM stage (P = 0.005), and carcinoembryonic antigen (CEA; P = 0.037).

Conclusions

The circRNA expression profile of CRC provided new clues for understanding the occurrence of CRC. Hsa_circ_0142527 may be served as a potential biomarker for the diagnosis of CRC.

Studying alcohol use disorder using Drosophila melanogaster in the era of 'Big Data'

Our understanding of the networks of genes and protein functions involved in Alcohol Use Disorder (AUD) remains incomplete, as do the mechanisms by which these networks lead to AUD phenotypes. The fruit fly (Drosophila melanogaster) is an efficient model for functional and mechanistic characterization of the genes involved in alcohol behavior. The fly offers many advantages as a model organism for investigating the molecular and cellular mechanisms of alcohol-related behaviors, and for understanding the underlying neural circuitry driving behaviors, such as locomotor stimulation, sedation, tolerance, and appetitive (reward) learning and memory. Fly researchers are able to use an extensive variety of tools for functional characterization of gene products. To understand how the fly can guide our understanding of AUD in the era of Big Data we will explore these tools, and review some of the gene networks identified in the fly through their use, including chromatin-remodeling, glial, cellular stress, and innate immunity genes. These networks hold great potential as translational drug targets, making it prudent to conduct further research into how these gene mechanisms are involved in alcohol behavior.

Cross-species molecular dissection across alcohol behavioral domains

This review summarizes the proceedings of a symposium presented at the "Alcoholism and Stress: A Framework for Future Treatment Strategies" conference held in Volterra, Italy on May 9-12, 2017. Psychiatric diseases, including alcohol-use disorders (AUDs), are influenced through complex interactions of genes, neurobiological pathways, and environmental influences. A better understanding of the common neurobiological mechanisms underlying an AUD necessitates an integrative approach, involving a systematic assessment of diverse species and phenotype measures. As part of the World Congress on Stress and Alcoholism, this symposium provided a detailed account of current strategies to identify mechanisms underlying the development and progression of AUDs. Dr. Sean Farris discussed the integration and organization of transcriptome and postmortem human brain data to identify brain regional- and cell type-specific differences related to excessive alcohol consumption that are conserved across species. Dr. Brien Riley presented the results of a genome-wide association study of DSM-IV alcohol dependence; although replication of genetic associations with alcohol phenotypes in humans remains challenging, model organism studies show that COL6A3, KLF12, and RYR3 affect behavioral responses to ethanol, and provide substantial evidence for their role in human alcohol-related traits. Dr. Rob Williams expanded upon the systematic characterization of extensive genetic-genomic resources for quantifying and clarifying phenotypes across species that are relevant to precision medicine in human disease. The symposium concluded with Dr. Robert Hitzemann's description of transcriptome studies in a mouse model selectively bred for high alcohol ("binge-like") consumption and a non-human primate model of long-term alcohol consumption. Together, the different components of this session provided an overview of systems-based approaches that are pioneering the experimental prioritization and validation of novel genes and gene networks linked with a range of behavioral phenotypes associated with stress and AUDs.

Early neurogenomic response associated with variation in guppy female mate preference

Understanding the evolution of mate choice requires dissecting the mechanisms of female preference, particularly how these differ among social contexts and preference phenotypes. Here we study the female neurogenomic response after only 10 minutes of mate exposure in both a sensory component (optic tectum) and a decision-making component (telencephalon) of the brain. By comparing the transcriptional response between females with and without preferences for colorful males, we identified unique neurogenomic elements associated with the female preference phenotype that are not present in females without preference. Network analysis revealed different properties for this response at the sensory-processing and the decision-making levels, and showed that this response is highly centralized in the telencephalon. Furthermore, we identified an additional set of genes that vary in expression across social contexts, beyond mate evaluation. We show that transcription factors among those loci are predicted to regulate the transcriptional response of the genes we found to be associated with female preference.

Neuroepigenetics and addictive behaviors: Where do we stand?

Substance use disorders involve long-term changes in the brain that lead to compulsive drug seeking, craving, and a high probability of relapse. Recent findings have highlighted the role of epigenetic regulations in controlling chromatin access and regulation of gene expression following exposure to drugs of abuse. In the present review, we focus on data investigating genome-wide epigenetic modifications in the brain of addicted patients or in rodent models exposed to drugs of abuse, with a particular focus on DNA methylation and histone modifications associated with transcriptional studies. We highlight critical factors for epigenomic studies in addiction. We discuss new findings related to psychostimulants, alcohol, opiate, nicotine and cannabinoids. We examine the possible transmission of these changes across generations. We highlight developing tools, specifically those that allow investigation of structural reorganization of the chromatin. These have the potential to increase our understanding of alteration of chromatin architecture at gene regulatory regions. Neuroepigenetic mechanisms involved in addictive behaviors could explain persistent phenotypic effects of drugs and, in particular, vulnerability to relapse.

Gender-Specific Effects of Selection for Drinking in the Dark on the Network Roles of Coding and Noncoding RNAs

BACKGROUND

Transcriptional differences between heterogeneous stock mice and high drinking-in-the-dark selected mouse lines have previously been described based on microarray technology coupled with network-based analysis. The network changes were reproducible in 2 independent selections and largely confined to 2 distinct network modules; in contrast, differential expression appeared more specific to each selected line. This study extends these results by utilizing RNA-Seq technology, allowing evaluation of the relationship between genetic risk and transcription of noncoding RNA (ncRNA); we additionally evaluate sex-specific transcriptional effects of selection.

METHODS

Naïve mice (N = 24/group and sex) were utilized for gene expression analysis in the ventral striatum; the transcriptome was sequenced with the Illumina HiSeq platform. Differential gene expression and the weighted gene co-expression network analysis were implemented largely as described elsewhere, resulting in the identification of genes that change expression level or (co)variance structure.

RESULTS

Across both sexes, we detect selection effects on the extracellular matrix and synaptic signaling, although the identity of individual genes varies. A majority of nc RNAs cluster in a single module of relatively low density in both the male and female network. The most strongly differentially expressed transcript in both sexes was Gm22513, a small nuclear RNA with unknown function. Associated with selection, we also found a number of network hubs that change edge strength and connectivity. At the individual gene level, there are many sex-specific effects; however, at the annotation level, results are more concordant.

CONCLUSIONS

In addition to demonstrating sex-specific effects of selection on the transcriptome, the data point to the involvement of extracellular matrix genes as being associated with the binge drinking phenotype.

Post-genomic behavioral genetics: From revolution to routine

What was once expensive and revolutionary-full-genome sequence-is now affordable and routine. Costs will continue to drop, opening up new frontiers in behavioral genetics. This shift in costs from the genome to the phenome is most notable in large clinical studies of behavior and associated diseases in cohorts that exceed hundreds of thousands of subjects. Examples include the Women's Health Initiative (www.whi.org), the Million Veterans Program (www.

RESEARCH

va.gov/MVP), the 100 000 Genomes Project (genomicsengland.co.uk) and commercial efforts such as those by deCode (www.decode.com) and 23andme (www.23andme.com). The same transition is happening in experimental neuro- and behavioral genetics, and sample sizes of many hundreds of cases are becoming routine (www.genenetwork.org, www.mousephenotyping.org). There are two major consequences of this new affordability of massive omics datasets: (1) it is now far more practical to explore genetic modulation of behavioral differences and the key role of gene-by-environment interactions. Researchers are already doing the hard part-the quantitative analysis of behavior. Adding the omics component can provide powerful links to molecules, cells, circuits and even better treatment. (2) There is an acute need to highlight and train behavioral scientists in how best to exploit new omics approaches. This review addresses this second issue and highlights several new trends and opportunities that will be of interest to experts in animal and human behaviors.

Differential gene expression is not required for facultative sex allocation: a transcriptome analysis of brain tissue in the parasitoid wasp Nasonia vitripennis

Whole-transcriptome technologies have been widely used in behavioural genetics to identify genes associated with the performance of a behaviour and provide clues to its mechanistic basis. Here, we consider the genetic basis of sex allocation behaviour in the parasitoid wasp Nasonia vitripennis. Female Nasonia facultatively vary their offspring sex ratio in line with Hamilton's theory of local mate competition (LMC). A single female or 'foundress' laying eggs on a patch will lay just enough sons to fertilize her daughters. As the number of 'foundresses' laying eggs on a patch increases (and LMC declines), females produce increasingly male-biased sex ratios. Phenotypic studies have revealed the cues females use to estimate the level of LMC their sons will experience, but our understanding of the genetics underlying sex allocation is limited. Here, we exposed females to three foundress number conditions, i.e. three LMC conditions, and allowed them to oviposit. mRNA was extracted from only the heads of these females to target the brain tissue. The subsequent RNA-seq experiment confirmed that differential gene expression is not associated with the response to sex allocation cues and that we must instead turn to the underlying neuroscience to reveal the underpinnings of this impressive behavioural plasticity.

Progress With Nonhuman Animal Models of Addiction

Nonhuman animals have been major contributors to the science of the genetics of addiction. Given the explosion of interest in genetics, it is fair to ask, are we making reasonable progress toward our goals with animal models? I will argue that our goals are changing and that overall progress has been steady and seems likely to continue apace. Genetics tools have developed almost incredibly rapidly, enabling both more reductionist and more synthetic or integrative approaches. I believe that these approaches to making progress have been unbalanced in biomedical science, favoring reductionism, particularly in animal genetics. I argue that substantial, novel progress is also likely to come in the other direction, toward synthesis and abstraction. Another area in which future progress with genetic animal models seems poised to contribute more is the reconciliation of human and animal phenotypes, or consilience. The inherent power of the genetic animal models could be more profitably exploited. In the end, animal research has continued to provide novel insights about how genes influence individual differences in addiction risk and consequences. The rules of the genetics game are changing so fast that it is hard to remember how comparatively little we knew even a generation ago. Rather than worry about whether we have been wasting time and resources asking the questions we have been, we should look to the future and see if we can come up with some new ones. The valuable findings from the past will endure, and the sidetracks will be forgotten.

RNA-seq in kinetoplastids: A powerful tool for the understanding of the biology and host-pathogen interactions

The kinetoplastids include a large number of parasites responsible for serious diseases in humans and animals (Leishmania and Trypanosoma brucei) considered endemic in several regions of the world. These parasites are characterized by digenetic life cycles that undergo morphological and genetic changes that allow them to adapt to different microenvironments on their vertebrates and invertebrates hosts. Recent advances in ´omics´ technology, specifically transcriptomics have allowed to reveal aspects associated with such molecular changes. So far, different techniques have been used to evaluate the gene expression profile during the various stages of the life cycle of these parasites and during the host-parasite interactions. However, some of them have serious drawbacks that limit the precise study and full understanding of their transcriptomes. Therefore, recently has been implemented the latest technology (RNA-seq), which overcomes the drawbacks of traditional methods. In this review, studies that so far have used RNA-seq are presented and allowed to expand our knowledge regarding the biology of these parasites and their interactions with their hosts.

A de novo transcriptome analysis shows that modulation of the JAK-STAT signaling pathway by salmonid alphavirus subtype 3 favors virus replication in macrophage/dendritic-like TO-cells

BACKGROUND

The Janus kinase (Jak) and signaling transducer activator of transcription (Stat) pathway mediates the signaling of genes required for cellular development and homeostasis. To elucidate the effect of type I IFN on the Jak/stat pathway in salmonid alphavirus subtype 3 (SAV3) infected macrophage/dendritic like TO-cells derived from Atlantic salmon (Salmo salar L) headkidney leukocytes, we used a differential transcriptome analysis by RNA-seq and the Kyoto encyclopedia of genes and genomes (KEGGs) pathway analysis to generate a repertoire of de novo assembled genes from type I IFN treated and non-treated TO-cells infected with SAV3.

RESULTS

Concurrent SAV3 infection with type I IFN treatment of TO-cells suppressed SAV3 structural protein (SP) expression by 2log10 at 2 days post infection compared to SAV3 infection without IFN treatment which paved way to evaluating the impact of type I IFN on expression of Jak/stat pathway genes in SAV3 infected TO-cells. In the absence of type I IFN treatment, SAV3 downregulated several Jak/stat pathway genes that included type I and II receptor genes, Jak2, tyrosine kinase 2 (Tyk2), Stat3 and Stat5 pointing to possible failure to activate the Jak/stat signaling pathway and inhibition of signal transducers caused by SAV3 infection. Although the suppressor of cytokine signaling (SOCS) genes 1 and 3 were upregulated in the IFN treated cells, only SOCS3 was downregulated in the SAV3 infected cells which points to inhibition of SOCS3 by SAV3 infection in TO-cells.

CONCLUSION

Data presented in this study shows that SAV3 infection downregulates several genes of the Jak/stat pathway, which could be an immune evasion strategy, used to block the transcription of antiviral genes that would interfere with SAV3 replication in TO-cells. Overall, we have shown that combining de novo assembly with pathway based transcriptome analyses provides a contextual approach to understanding the molecular networks of genes that form the Jak/stat pathway in TO-cells infected by SAV3.

Recursive Indirect-Paths Modularity (RIP-M) for Detecting Community Structure in RNA-Seq Co-expression Networks

Clusters of genes in co-expression networks are commonly used as functional units for gene set enrichment detection and increasingly as features (attribute construction) for statistical inference and sample classification. One of the practical challenges of clustering for these purposes is to identify an optimal partition of the network where the individual clusters are neither too large, prohibiting interpretation, nor too small, precluding general inference. Newman Modularity is a spectral clustering algorithm that automatically finds the number of clusters, but for many biological networks the cluster sizes are suboptimal. In this work, we generalize Newman Modularity to incorporate information from indirect paths in RNA-Seq co-expression networks. We implement a merge-and-split algorithm that allows the user to constrain the range of cluster sizes: large enough to capture genes in relevant pathways, yet small enough to resolve distinct functions. We investigate the properties of our recursive indirect-pathways modularity (RIP-M) and compare it with other clustering methods using simulated co-expression networks and RNA-seq data from an influenza vaccine response study. RIP-M had higher cluster assignment accuracy than Newman Modularity for finding clusters in simulated co-expression networks for all scenarios, and RIP-M had comparable accuracy to Weighted Gene Correlation Network Analysis (WGCNA). RIP-M was more accurate than WGCNA for modest hard thresholds and comparable for high, while WGCNA was slightly more accurate for soft thresholds. In the vaccine study data, RIP-M and WGCNA enriched for a comparable number of immunologically relevant pathways.

"RADIOTRANSCRIPTOMICS": A synergy of imaging and transcriptomics in clinical assessment

Recent advances in quantitative imaging and "omics" technology have generated a wealth of mineable biological "big data". With the push towards a P4 "predictive, preventive, personalized, and participatory" approach to medicine, researchers began integrating complementary tools to further tune existing diagnostic and therapeutic models. The field of radiogenomics has long pioneered such multidisciplinary investigations in neuroscience and oncology, correlating genotypic and phenotypic signatures to study structural and functional changes in relation to altered molecular behavior. Given the innate dynamic nature of complex disorders and the role of environmental and epigenetic factors in pathogenesis, the transcriptome can further elucidate serial modifications undetected at the genome level. We therefore propose "radiotranscriptomics" as a new member of the P4 medicine initiative, combining transcriptome information, including gene expression and isoform variation, and quantitative image annotations.

Pediatric asthma and autism-genomic perspectives

High-throughput technologies, ranging from microarrays to NexGen sequencing of RNA and genomic DNA, have opened new avenues for exploration of the pathobiology of human disease. Comparisons of the architecture of the genome, identification of mutated or modified sequences, and pre-and post- transcriptional regulation of gene expression as disease specific biomarkers are revolutionizing our understanding of the causes of disease and are guiding the development of new therapies. There is enormous heterogeneity in types of genomic variation that occur in human disease. Some are inherited, while others are the result of new somatic or germline mutations or errors in chromosomal replication. In this review, we provide examples of changes that occur in the human genome in two of the most common chronic pediatric disorders, autism and asthma. The incidence and economic burden of both of these disorders are increasing worldwide. Genomic variations have the potential to serve as biomarkers for personalization of therapy and prediction of outcomes.

Transcriptome organization for chronic alcohol abuse in human brain

Alcohol dependence is a heterogeneous psychiatric disorder characterized by high genetic heritability and neuroadaptations occurring from repeated drug exposure. Through an integrated systems approach we observed consistent differences in transcriptome organization within postmortem human brain tissue associated with the lifetime consumption of alcohol. Molecular networks, determined using high-throughput RNA sequencing, for drinking behavior were dominated by neurophysiological targets and signaling mechanisms of alcohol. The systematic structure of gene sets demonstrates a novel alliance of multiple ion channels, and related processes, underlying lifetime alcohol consumption. Coordinate expression of these transcripts was enriched for genome-wide association signals in alcohol dependence and a meta-analysis of alcohol self-administration in mice. Further dissection of genes within alcohol consumption networks revealed the potential interaction of alternatively spliced transcripts. For example, expression of a human-specific isoform of the voltage-gated sodium channel subunit SCN4B was significantly correlated to lifetime alcohol consumption. Overall, our work demonstrates novel convergent evidence for biological networks related to excessive alcohol consumption, which may prove fundamentally important in the development of pharmacotherapies for alcohol dependence.

Dual-trait selection for ethanol consumption and withdrawal: genetic and transcriptional network effects

BACKGROUND

Data from C57BL/6J (B6) × DBA/2J (D2) F2 intercrosses (B6xD2 F2 ), standard and recombinant inbred strains, and heterogeneous stock mice indicate that a reciprocal (or inverse) genetic relationship exists between alcohol consumption and withdrawal severity. Furthermore, some genetic studies have detected reciprocal quantitative trait loci (QTLs) for these traits. We used a novel mouse model developed by simultaneous selection for both high alcohol consumption/low withdrawal and low alcohol consumption/high withdrawal and analyzed the gene expression and genome-wide genotypic differences.

METHODS

Randomly chosen third selected generation (S3 ) mice (N = 24/sex/line), bred from a B6xD2 F2 , were genotyped using the Mouse Universal Genotyping Array, which provided 2,760 informative markers. QTL analysis used a marker-by-marker strategy with the threshold for a significant log of the odds (LOD) set at 10. Gene expression in the ventral striatum was measured using the Illumina Mouse 8.2 array. Differential gene expression and the weighted gene co-expression network analysis (WGCNA) were implemented.

RESULTS

Significant QTLs for consumption/withdrawal were detected on chromosomes (Chr) 2, 4, 9, and 12. A suggestive QTL mapped to Chr 6. Some of the QTLs overlapped with known QTLs mapped for 1 of the traits individually. One thousand seven hundred and forty-five transcripts were detected as being differentially expressed between the lines; there was some overlap with known withdrawal genes (e.g., Mpdz) located within QTL regions. WGCNA revealed several modules of co-expressed genes showing significant effects in both differential expression and intramodular connectivity; a module richly annotated with kinase-related annotations was most affected.

CONCLUSIONS

Marked effects of selection on expression and network structure were detected. QTLs overlapping with differentially expressed genes on Chr 2 (distal) and 4 suggest that these are cis-eQTLs (Chr 2: Kif3b, Kcnq2; Chr 4: Mpdz, Snapc3). Other QTLs identified were on Chr 2 (proximal), 9, and 12. Network results point to involvement of kinase-related mechanisms and outline the need for further efforts such as interrogation of noncoding RNAs.

Social Regulation of Gene Expression in Threespine Sticklebacks

Identifying genes that are differentially expressed in response to social interactions is informative for understanding the molecular basis of social behavior. To address this question, we described changes in gene expression as a result of differences in the extent of social interactions. We housed threespine stickleback (Gasterosteus aculeatus) females in either group conditions or individually for one week, then measured levels of gene expression in three brain regions using RNA-sequencing. We found that numerous genes in the hindbrain/cerebellum had altered expression in response to group or individual housing. However, relatively few genes were differentially expressed in either the diencephalon or telencephalon. The list of genes upregulated in fish from social groups included many genes related to neural development and cell adhesion as well as genes with functions in sensory signaling, stress, and social and reproductive behavior. The list of genes expressed at higher levels in individually-housed fish included several genes previously identified as regulated by social interactions in other animals. The identified genes are interesting targets for future research on the molecular mechanisms of normal social interactions.

RNA-sequencing elucidates the regulation of behavioural transitions associated with the mating process in honey bee queens

Background

Mating is a complex process, which is frequently associated with behavioural and physiological changes. However, understanding of the genetic underpinnings of these changes is limited. Honey bees are both a model system in behavioural genomics, and the dominant managed pollinator of human crops; consequently understanding the mating process has both pure and applied value. We used next-generation transcriptomics to probe changes in gene expression in the brains of honey bee queens, as they transition from virgin to mated reproductive status. In addition, we used CO₂-narcosis, which induces oviposition without mating, to isolate the process of reproductive maturation.

Results

The mating process produced significant changes in the expression of vision, chemo-reception, metabolic, and immune-related genes. Differential expression of these genes maps clearly onto known behavioural and physiological changes that occur during the transition from being a virgin queen to a newly-mated queen. A subset of these changes in gene expression were also detected in CO₂-treated queens, as predicted from previous physiological studies. In addition, we compared our results to previous studies that used microarray techniques across a range of experimental time-points. Changes in expression of immune- and vision-related genes were common to all studies, supporting an involvement of these groups of genes in the mating process.

Conclusions

Our study is an important step in understanding the molecular mechanisms regulating post-mating behavioural transitions in a natural system. The weak overlap in patterns of gene expression with previous studies demonstrates the high sensitivity of genome-wide approaches. Thus, while we build on previous microarray studies that explored post-mating changes in honey bees, the broader experimental design, use of RNA-sequencing, and focus on Australian honey bees, which remain free from the devastating parasite Varroa destructor, in the current study, provide unique insights into the biology of the mating process in honey bees.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1750-7) contains supplementary material, which is available to authorized users.

Use of RNA sequencing to evaluate rheumatic disease patients

Studying the factors that control gene expression is of substantial importance for rheumatic diseases with poorly understood etiopathogenesis. In the past, gene expression microarrays have been used to measure transcript abundance on a genome-wide scale in a particular cell, tissue or organ. Microarray analysis has led to gene signatures that differentiate rheumatic diseases, and stages of a disease, as well as response to treatments. Nowadays, however, with the advent of next-generation sequencing methods, massive parallel sequencing of RNA tends to be the technology of choice for gene expression profiling, due to several advantages over microarrays, as well as for the detection of non-coding transcripts and alternative splicing events. In this review, we describe how RNA sequencing enables unbiased interrogation of the abundance and complexity of the transcriptome, and present a typical experimental workflow and bioinformatics tools that are often used for RNA sequencing analysis. We also discuss different uses of this next-generation sequencing technology to evaluate rheumatic disease patients and investigate the pathogenesis of rheumatic diseases such as rheumatoid arthritis, systemic lupus erythematosus, juvenile idiopathic arthritis and Sjögren’s syndrome.

Do housekeeping genes exist?

The searching of human housekeeping (HK) genes has been a long quest since the emergence of transcriptomics, and is instrumental for us to understand the structure of genome and the fundamentals of biological processes. The resolved genes are frequently used in evolution studies and as normalization standards in quantitative gene-expression analysis. Within the past 20 years, more than a dozen HK-gene studies have been conducted, yet none of them sampled human tissues completely. We believe an integration of these results will help remove false positive genes owing to the inadequate sampling. Surprisingly, we only find one common gene across 15 examined HK-gene datasets comprising 187 different tissue and cell types. Our subsequent analyses suggest that it might not be appropriate to rigidly define HK genes as expressed in all tissue types that have diverse developmental, physiological, and pathological states. It might be beneficial to use more robustly identified HK functions for filtering criteria, in which the representing genes can be a subset of genome. These genes are not necessarily the same, and perhaps need not to be the same, everywhere in our body.

Cosplicing network analysis of mammalian brain RNA-Seq data utilizing WGCNA and Mantel correlations

Across species and tissues and especially in the mammalian brain, production of gene isoforms is widespread. While gene expression coordination has been previously described as a scale-free coexpression network, the properties of transcriptome-wide isoform production coordination have been less studied. Here we evaluate the system-level properties of cosplicing in mouse, macaque, and human brain gene expression data using a novel network inference procedure. Genes are represented as vectors/lists of exon counts and distance measures sensitive to exon inclusion rates quantifies differences across samples. For all gene pairs, distance matrices are correlated across samples, resulting in cosplicing or cotranscriptional network matrices. We show that networks including cosplicing information are scale-free and distinct from coexpression. In the networks capturing cosplicing we find a set of novel hubs with unique characteristics distinguishing them from coexpression hubs: heavy representation in neurobiological functional pathways, strong overlap with markers of neurons and neuroglia, long coding lengths, and high number of both exons and annotated transcripts. Further, the cosplicing hubs are enriched in genes associated with autism spectrum disorders. Cosplicing hub homologs across eukaryotes show dramatically increasing intronic lengths but stable coding region lengths. Shared transcription factor binding sites increase coexpression but not cosplicing; the reverse is true for splicing-factor binding sites. Genes with protein-protein interactions have strong coexpression and cosplicing. Additional factors affecting the networks include shared microRNA binding sites, spatial colocalization within the striatum, and sharing a chromosomal folding domain. Cosplicing network patterns remain relatively stable across species.

Guidance for RNA-seq co-expression network construction and analysis: safety in numbers

MOTIVATION

RNA-seq co-expression analysis is in its infancy and reasonable practices remain poorly defined. We assessed a variety of RNA-seq expression data to determine factors affecting functional connectivity and topology in co-expression networks.

RESULTS

We examine RNA-seq co-expression data generated from 1970 RNA-seq samples using a Guilt-By-Association framework, in which genes are assessed for the tendency of co-expression to reflect shared function. Minimal experimental criteria to obtain performance on par with microarrays were >20 samples with read depth >10 M per sample. While the aggregate network constructed shows good performance (area under the receiver operator characteristic curve ∼0.71), the dependency on number of experiments used is nearly identical to that present in microarrays, suggesting thousands of samples are required to obtain 'gold-standard' co-expression. We find a major topological difference between RNA-seq and microarray co-expression in the form of low overlaps between hub-like genes from each network due to changes in the correlation of expression noise within each technology.

CONTACT

jgillis@cshl.edu or sballouz@cshl.edu

SUPPLEMENTARY INFORMATION

Networks are available at: http://gillislab.labsites.cshl.edu/supplements/rna-seq-networks/ and supplementary data are available at Bioinformatics online.

Genes regulating lipid and protein metabolism are highly expressed in mammary gland of lactating dairy goats

Dairy goats serve as an important source of milk and also fulfill agricultural and economic roles in developing countries. Understanding the genetic background of goat mammary gland is important for research on the regulatory mechanisms controlling tissue function and the synthesis of milk components. We collected tissue at four different stages of goat mammary gland development and generated approximately 25 GB of data from Illumina de novo RNA sequencing. The combined reads were assembled into 51,361 unigenes, and approximately 60.07 % of the unigenes had homology to other proteins in the NCBI non-redundant protein database (NR). Functional classification through eukaryotic Ortholog Groups of Protein (KOG), gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed that the unigenes from goat mammary glands are involved in a wide range of biological processes and metabolic pathways, including lipid metabolism and lactose metabolism. The results of qPCR revealed that genes encoding FABP3, FASN, SCD, PLIN2, whey proteins (LALBA and BLG), and caseins (CSN1S1, CSN1S2, CSN2 and CSN3) at 100 and 310 days postpartum increased significantly compared with the non-lactating period. In addition to their role in lipid and protein synthesis, the higher expression at 310 days postpartum could contribute to mammary cell turnover during pregnancy. In conclusion, this is the first study to characterize the complete transcriptome of goat mammary glands and constitutes a comprehensive genomic resource available for further studies of ruminant lactation.

Systems-based analyses of brain regions functionally impacted in Parkinson's disease reveals underlying causal mechanisms

Detailed analysis of disease-affected tissue provides insight into molecular mechanisms contributing to pathogenesis. Substantia nigra, striatum, and cortex are functionally connected with increasing degrees of alpha-synuclein pathology in Parkinson's disease. We undertook functional and causal pathway analysis of gene expression and proteomic alterations in these three regions, and the data revealed pathways that correlated with disease progression. In addition, microarray and RNAseq experiments revealed previously unidentified causal changes related to oligodendrocyte function and synaptic vesicle release, and these and other changes were reflected across all brain regions. Importantly, subsets of these changes were replicated in Parkinson's disease blood; suggesting peripheral tissue may provide important avenues for understanding and measuring disease status and progression. Proteomic assessment revealed alterations in mitochondria and vesicular transport proteins that preceded gene expression changes indicating defects in translation and/or protein turnover. Our combined approach of proteomics, RNAseq and microarray analyses provides a comprehensive view of the molecular changes that accompany functional loss and alpha-synuclein pathology in Parkinson's disease, and may be instrumental to understand, diagnose and follow Parkinson's disease progression.

Circadian rhythms and addiction: mechanistic insights and future directions

Circadian rhythms are prominent in many physiological and behavioral functions. Circadian disruptions either by environmental or molecular perturbation can have profound health consequences, including the development and progression of addiction. Both animal and humans studies indicate extensive bidirectional relationships between the circadian system and drugs of abuse. Addicted individuals display disrupted rhythms, and chronic disruption or particular chronotypes may increase the risk for substance abuse and relapse. Moreover, polymorphisms in circadian genes and an evening chronotype have been linked to mood and addiction disorders, and recent efforts suggest an association with the function of reward neurocircuitry. Animal studies are beginning to determine how altered circadian gene function results in drug-induced neuroplasticity and behaviors. Many studies suggest a critical role for circadian rhythms in reward-related pathways in the brain and indicate that drugs of abuse directly affect the central circadian pacemaker. In this review, we highlight key findings demonstrating the importance of circadian rhythms in addiction and how future studies will reveal important mechanistic insights into the involvement of circadian rhythms in drug addiction.