Challenges and best practices in omics benchmarking.

Technological advances enabling massively parallel measurement of biological features - such as microarrays, high-throughput sequencing and mass spectrometry - have ushered in the omics era, now in its third decade. The resulting complex landscape of analytical methods has naturally fostered the growth of an omics benchmarking industry. Benchmarking refers to the process of objectively comparing and evaluating the performance of different computational or analytical techniques when processing and analysing large-scale biological data sets, such as transcriptomics, proteomics and metabolomics. With thousands of omics benchmarking studies published over the past 25 years, the field has matured to the point where the foundations of benchmarking have been established and well described. However, generating meaningful benchmarking data and properly evaluating performance in this complex domain remains challenging. In this Review, we highlight some common oversights and pitfalls in omics benchmarking. We also establish a methodology to bring the issues that can be addressed into focus and to be transparent about those that cannot: this takes the form of a spreadsheet template of guidelines for comprehensive reporting, intended to accompany publications. In addition, a survey of recent developments in benchmarking is provided as well as specific guidance for commonly encountered difficulties.

BEERS2: RNA-Seq simulation through high fidelity in silico modeling.

Simulation of RNA-seq reads is critical in the assessment, comparison, benchmarking and development of bioinformatics tools. Yet the field of RNA-seq simulators has progressed little in the last decade. To address this need we have developed BEERS2, which combines a flexible and highly configurable design with detailed simulation of the entire library preparation and sequencing pipeline. BEERS2 takes input transcripts (typically fully length messenger RNA transcripts with polyA tails) from either customizable input or from CAMPAREE simulated RNA samples. It produces realistic reads of these transcripts as FASTQ, SAM or BAM formats with the SAM or BAM formats containing the true alignment to the reference genome. It also produces true transcript-level quantification values. BEERS2 combines a flexible and highly configurable design with detailed simulation of the entire library preparation and sequencing pipeline and is designed to include the effects of polyA selection and RiboZero for ribosomal depletion, hexamer priming sequence biases, GC-content biases in polymerase chain reaction (PCR) amplification, barcode read errors and errors during PCR amplification. These characteristics combine to make BEERS2 the most complete simulation of RNA-seq to date. Finally, we demonstrate the use of BEERS2 by measuring the effect of several settings on the popular Salmon pseudoalignment algorithm.

Differential Impact In Vivo of Pf4-ΔCre-Mediated and Gp1ba-ΔCre-Mediated Depletion of Cyclooxygenase-1 in Platelets in Mice.

BACKGROUND: Low-dose aspirin is widely used for the secondary prevention of cardiovascular disease. The beneficial effects of low-dose aspirin are attributable to its inhibition of platelet Cox (cyclooxygenase)-1-derived thromboxane A2. Until recently, the use of the Pf4 (platelet factor 4) Cre has been the only genetic approach to generating megakaryocyte/platelet ablation of Cox-1 in mice. However, Pf4-ΔCre displays ectopic expression outside the megakaryocyte/platelet lineage, especially during inflammation. The use of the Gp1ba (glycoprotein 1bα) Cre promises a more specific, targeted approach. METHODS: To evaluate the role of Cox-1 in platelets, we crossed Pf4-ΔCre or Gp1ba-ΔCre mice with Cox-1flox/flox mice to generate platelet Cox-1-/- mice on normolipidemic and hyperlipidemic (Ldlr-/-; low-density lipoprotein receptor) backgrounds. RESULTS: Ex vivo platelet aggregation induced by arachidonic acid or adenosine diphosphate in platelet-rich plasma was inhibited to a similar extent in Pf4-ΔCre Cox-1-/-/Ldlr-/- and Gp1ba-ΔCre Cox-1-/-/Ldlr-/- mice. In a mouse model of tail injury, Pf4-ΔCre-mediated and Gp1ba-ΔCre-mediated deletions of Cox-1 were similarly efficient in suppressing platelet prostanoid biosynthesis. Experimental thrombogenesis and attendant blood loss were similar in both models. However, the impact on atherogenesis was divergent, being accelerated in the Pf4-ΔCre mice while restrained in the Gp1ba-ΔCres. In the former, accelerated atherogenesis was associated with greater suppression of PGI2 biosynthesis, a reduction in the lipopolysaccharide-evoked capacity to produce PGE2 (prostaglandin E) and PGD2 (prostanglandin D), activation of the inflammasome, elevated plasma levels of IL-1ß (interleukin), reduced plasma levels of HDL-C (high-density lipoprotein receptor-cholesterol), and a reduction in the capacity for reverse cholesterol transport. By contrast, in the latter, plasma HDL-C and α-tocopherol were elevated, and MIP-1α (macrophage inflammatory protein-1α) and MCP-1 (monocyte chemoattractant protein 1) were reduced. CONCLUSIONS: Both approaches to Cox-1 deletion similarly restrain thrombogenesis, but a differential impact on Cox-1-dependent prostanoid formation by the vasculature may contribute to an inflammatory phenotype and accelerated atherogenesis in Pf4-ΔCre mice.

Modulation of the Immune Response to Severe Acute Respiratory Syndrome Coronavirus 2 Vaccination by Nonsteroidal Anti-Inflammatory Drugs.

Evidence is scarce to guide the use of nonsteroidal anti-inflammatory drugs (NSAIDs) to mitigate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine-related adverse effects, given the possibility of blunting the desired immune response. In this pilot study, we deeply phenotyped a small number of volunteers who did or did not take NSAIDs concomitant with SARS-CoV-2 immunizations to seek initial information on the immune response. A SARS-CoV-2 vaccine-specific receptor binding domain (RBD) IgG antibody response and efficacy in the evoked neutralization titers were evident irrespective of concomitant NSAID consumption. Given the sample size, only a large and consistent signal of immunomodulation would have been detectable, and this was not apparent. However, the information gathered may inform the design of a definitive clinical trial. Here we report a series of divergent omics signals that invites additional hypotheses testing. SIGNIFICANCE STATEMENT: The impact of nonsteroidal anti-inflammatory drugs (NSAIDs) on the immune response elicited by repeat severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunizations was profiled by immunophenotypic, proteomic, and metabolomic approaches in a clinical pilot study of small sample size. A SARS-CoV-2 vaccine-specific immune response was evident irrespective of concomitant NSAID consumption. The information gathered may inform the design of a definitive clinical trial.

Purcell Enhancement of Erbium Ions in TiO2 on Silicon Nanocavities.

Isolated solid-state atomic defects with telecom optical transitions are ideal quantum photon emitters and spin qubits for applications in long-distance quantum communication networks. Prototypical telecom defects, such as erbium, suffer from poor photon emission rates, requiring photonic enhancement using resonant optical cavities. Moreover, many of the traditional hosts for erbium ions are not amenable to direct incorporation with existing integrated photonics platforms, limiting scalable fabrication of qubit-based devices. Here, we present a scalable approach toward CMOS-compatible telecom qubits by using erbium-doped titanium dioxide thin films grown atop silicon-on-insulator substrates. From this heterostructure, we have fabricated one-dimensional photonic crystal cavities demonstrating quality factors in excess of 5 × 104 and corresponding Purcell-enhanced optical emission rates of the erbium ensembles in excess of 200. This easily fabricated materials platform represents an important step toward realizing telecom quantum memories in a scalable qubit architecture compatible with mature silicon technologies.

A Wireless Underground Sensor Network Field Pilot for Agriculture and Ecology: Soil Moisture Mapping Using Signal Attenuation.

Wireless Underground Sensor Networks (WUSNs) that collect geospatial in situ sensor data are a backbone of internet-of-things (IoT) applications for agriculture and terrestrial ecology. In this paper, we first show how WUSNs can operate reliably under field conditions year-round and at the same time be used for determining and mapping soil conditions from the buried sensor nodes. We demonstrate the design and deployment of a 23-node WUSN installed at an agricultural field site that covers an area with a 530 m radius. The WUSN has continuously operated since September 2019, enabling real-time monitoring of soil volumetric water content (VWC), soil temperature (ST), and soil electrical conductivity. Secondly, we present data collected over a nine-month period across three seasons. We evaluate the performance of a deep learning algorithm in predicting soil VWC using various combinations of the received signal strength (RSSI) from each buried wireless node, above-ground pathloss, the distance between wireless node and receive antenna (D), ST, air temperature (AT), relative humidity (RH), and precipitation as input parameters to the model. The AT, RH, and precipitation were obtained from a nearby weather station. We find that a model with RSSI, D, AT, ST, and RH as inputs was able to predict soil VWC with an R2 of 0.82 for test datasets, with a Root Mean Square Error of ±0.012 (m3/m3). Hence, a combination of deep learning and other easily available soil and climatic parameters can be a viable candidate for replacing expensive soil VWC sensors in WUSNs.

Comparative evaluation of full-length isoform quantification from RNA-Seq.

BACKGROUND: Full-length isoform quantification from RNA-Seq is a key goal in transcriptomics analyses and has been an area of active development since the beginning. The fundamental difficulty stems from the fact that RNA transcripts are long, while RNA-Seq reads are short. RESULTS: Here we use simulated benchmarking data that reflects many properties of real data, including polymorphisms, intron signal and non-uniform coverage, allowing for systematic comparative analyses of isoform quantification accuracy and its impact on differential expression analysis. Genome, transcriptome and pseudo alignment-based methods are included; and a simple approach is included as a baseline control. CONCLUSIONS: Salmon, kallisto, RSEM, and Cufflinks exhibit the highest accuracy on idealized data, while on more realistic data they do not perform dramatically better than the simple approach. We determine the structural parameters with the greatest impact on quantification accuracy to be length and sequence compression complexity and not so much the number of isoforms. The effect of incomplete annotation on performance is also investigated. Overall, the tested methods show sufficient divergence from the truth to suggest that full-length isoform quantification and isoform level DE should still be employed selectively.

CAMPAREE: a robust and configurable RNA expression simulator.

BACKGROUND: The accurate interpretation of RNA-Seq data presents a moving target as scientists continue to introduce new experimental techniques and analysis algorithms. Simulated datasets are an invaluable tool to accurately assess the performance of RNA-Seq analysis methods. However, existing RNA-Seq simulators focus on modeling the technical biases and artifacts of sequencing, rather than on simulating the original RNA samples. A first step in simulating RNA-Seq is to simulate RNA. RESULTS: To fill this need, we developed the Configurable And Modular Program Allowing RNA Expression Emulation (CAMPAREE), a simulator using empirical data to simulate diploid RNA samples at the level of individual molecules. We demonstrated CAMPAREE's use for generating idealized coverage plots from real data, and for adding the ability to generate allele-specific data to existing RNA-Seq simulators that do not natively support this feature. CONCLUSIONS: Separating input sample modeling from library preparation/sequencing offers added flexibility for both users and developers to mix-and-match different sample and sequencing simulators to suit their specific needs. Furthermore, the ability to maintain sample and sequencing simulators independently provides greater agility to incorporate new biological findings about transcriptomics and new developments in sequencing technologies. Additionally, by simulating at the level of individual molecules, CAMPAREE has the potential to model molecules transcribed from the same genes as a heterogeneous population of transcripts with different states of degradation and processing (splicing, editing, etc.). CAMPAREE was developed in Python, is open source, and freely available at https://github.com/itmat/CAMPAREE .

Correction: A specific sequence in the genome of respiratory syncytial virus regulates the generation of copy-back defective viral genomes.

[This corrects the article DOI: 10.1371/journal.ppat.1007707.].

A specific sequence in the genome of respiratory syncytial virus regulates the generation of copy-back defective viral genomes.

Defective viral genomes of the copy-back type (cbDVGs) are the primary initiators of the antiviral immune response during infection with respiratory syncytial virus (RSV) both in vitro and in vivo. However, the mechanism governing cbDVG generation remains unknown, thereby limiting our ability to manipulate cbDVG content in order to modulate the host response to infection. Here we report a specific genomic signal that mediates the generation of a subset of RSV cbDVG species. Using a customized bioinformatics tool, we identified regions in the RSV genome frequently used to generate cbDVGs during infection. We then created a minigenome system to validate the function of one of these sequences and to determine if specific nucleotides were essential for cbDVG generation at that position. Further, we created a recombinant virus unable to produce a subset of cbDVGs due to mutations introduced in this sequence. The identified sequence was also found as a site for cbDVG generation during natural RSV infections, and common cbDVGs originated at this sequence were found among samples from various infected patients. These data demonstrate that sequences encoded in the viral genome determine the location of cbDVG formation and, therefore, the generation of cbDVGs is not a stochastic process. These findings open the possibility of genetically manipulating cbDVG formation to modulate infection outcome.

Alleviating catastrophic forgetting using context-dependent gating and synaptic stabilization.

Humans and most animals can learn new tasks without forgetting old ones. However, training artificial neural networks (ANNs) on new tasks typically causes them to forget previously learned tasks. This phenomenon is the result of "catastrophic forgetting," in which training an ANN disrupts connection weights that were important for solving previous tasks, degrading task performance. Several recent studies have proposed methods to stabilize connection weights of ANNs that are deemed most important for solving a task, which helps alleviate catastrophic forgetting. Here, drawing inspiration from algorithms that are believed to be implemented in vivo, we propose a complementary method: adding a context-dependent gating signal, such that only sparse, mostly nonoverlapping patterns of units are active for any one task. This method is easy to implement, requires little computational overhead, and allows ANNs to maintain high performance across large numbers of sequentially presented tasks, particularly when combined with weight stabilization. We show that this method works for both feedforward and recurrent network architectures, trained using either supervised or reinforcement-based learning. This suggests that using multiple, complementary methods, akin to what is believed to occur in the brain, can be a highly effective strategy to support continual learning.

RNA-seq analysis of galaninergic neurons from ventrolateral preoptic nucleus identifies expression changes between sleep and wake.

BACKGROUND: Previous studies show that galanin neurons in ventrolateral preoptic nucleus (VLPO-Gal) are essential for sleep regulation. Here, we explored the transcriptional regulation of the VLPO-Gal neurons in sleep by comparing their transcriptional responses between sleeping mice and those kept awake, sacrificed at the same diurnal time. RESULTS: RNA-sequencing (RNA-seq) analysis was performed on eGFP(+) galanin neurons isolated using laser captured microdissection (LCM) from VLPO. Expression of Gal was assessed in our LCM eGFP(+) neurons via real time qPCR and showed marked enrichment when compared to LCM eGFP(-) cells and to bulk VLPO samples. Gene set enrichment analysis utilizing data from a recent single-cell RNA-seq study of the preoptic area demonstrated that our VLPO-Gal samples were highly enriched with galanin-expressing inhibitory neurons, but not galanin-expressing excitatory neurons. A total of 263 genes were differentially expressed between sleep and wake in VLPO-Gal neurons. When comparing differentially expressed genes in VLPO-Gal neurons to differentially expressed genes in a wake-active neuronal region (the medial prefrontal cortex), evidence indicates that both systemic and cell-specific mechanisms contribute to the transcriptional regulation in VLPO-Gal neurons. In both wake-active and sleep-active neurons, ER stress pathways are activated by wake and cold-inducible RNA-binding proteins are activated by sleep. In contrast, expression of DNA repair genes is increased in VLPO-Gal during wakefulness, but increased in wake-active cells during sleep. CONCLUSION: Our study identified transcriptomic responses of the galanin neurons in the ventrolateral preoptic nucleus during sleep and sleep deprivation. Data indicate that VLPO contains mainly sleep-active inhibitory galaninergic neurons. The VLPO galanin neurons show responses to sleep and wake similar to wake-active regions, indicating these responses, such as ER stress and cold-inducible RNA-binding proteins, are systemic affecting all neuronal populations. Region-specific differences in sleep/wake responses were also identified, in particular DNA repair. Our study expands knowledge about the transcriptional response of a distinct group of neurons essential for sleep.

Simulation-based comprehensive benchmarking of RNA-seq aligners.

Alignment is the first step in most RNA-seq analysis pipelines, and the accuracy of downstream analyses depends heavily on it. Unlike most steps in the pipeline, alignment is particularly amenable to benchmarking with simulated data. We performed a comprehensive benchmarking of 14 common splice-aware aligners for base, read, and exon junction-level accuracy and compared default with optimized parameters. We found that performance varied by genome complexity, and accuracy and popularity were poorly correlated. The most widely cited tool underperforms for most metrics, particularly when using default settings.

Outlier detection for improved differential splicing quantification from RNA-Seq experiments with replicates.

Motivation: A key component in many RNA-Seq-based studies is contrasting multiple replicates from different experimental conditions. In this setup, replicates play a key role as they allow to capture underlying biological variability inherent to the compared conditions, as well as experimental variability. However, what constitutes a 'bad' replicate is not necessarily well defined. Consequently, researchers might discard valuable data or downstream analysis may be hampered by failed experiments. Results: Here we develop a probability model to weigh a given RNA-Seq sample as a representative of an experimental condition when performing alternative splicing analysis. We demonstrate that this model detects outlier samples which are consistently and significantly different compared with other samples from the same condition. Moreover, we show that instead of discarding such samples the proposed weighting scheme can be used to downweight samples and specific splicing variations suspected as outliers, gaining statistical power. These weights can then be used for differential splicing (DS) analysis, where the resulting algorithm offers a generalization of the MAJIQ algorithm. Using both synthetic and real-life data, we perform an extensive evaluation of the improved MAJIQ algorithm in different scenarios involving perturbed samples, mislabeled samples, same condition groups, and different levels of coverage, showing it compares favorably to other tools. Overall, this work offers an outlier detection algorithm that can be combined with any splicing pipeline, a generalized and improved version of MAJIQ for DS detection, and evaluation metrics with matching code and data for DS algorithms. Availability and implementation: Software and data are accessible via majiq.biociphers.org/norton_et_al_2017/. Contact: yosephb@upenn.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

Determinants of substrate specificity in D-3-phosphoglycerate dehydrogenase. Conversion of the M. tuberculosis enzyme from one that does not use α-ketoglutarate as a substrate to one that does.

d-3-Phosphoglycerate dehydrogenase (PGDH) converts d-3-phosphoglycerate (PGA) to phosphohydroxypyruvate (PHP) in the first step of l-serine biosynthesis. This reaction is reversible, and some PGDHs are capable of using α-ketoglutarate (αKG) instead of PHP in the reverse direction to produce α-hydroxyglutarate. The enzymes so far shown to have this ability are Type II PGDHs, suggesting that this may be a common feature of the Type II enzymes. Type I PGDHs examined so far do not share this feature. Inspection of PGDH sequences shows that a GCFCI … WXKX motif is commonly found in Type II PGDHs while a GRAGT … WXRX motif is commonly associated with Type I PGDHs. The removal of the cationic side chain at the first position shown above in the Type I PGDH from Mycobacterium tuberculosis converts it to an enzyme capable of using αKG where the native enzyme is not. It also produces an enzyme that regenerates NAD+ in the forward reaction when coupled to phosphoserine aminotransferase, as was previously shown for E. coli PGDH. Substitution of an arginyl residue for a lysyl residue at the second position of ecPGDH, decreases the kcat/Km of the enzyme by approximately 50-fold when using αKG, but only approximately 3-fold when using PHP. This suggests that a PGDH dependent cycle that conserves NAD+ in E. coli may be operative in many other organisms expressing the GCFCI … WXKX motif.

Elucidation of a Self-Sustaining Cycle in Escherichia coli l-Serine Biosynthesis That Results in the Conservation of the Coenzyme, NAD.

The equilibrium of the reaction catalyzed by d-3-phosphoglycerate dehydrogenase (PGDH), the first enzyme in the l-serine biosynthetic pathway, is far in the direction away from serine synthesis. As such, the enzyme is usually assayed in this direction. To easily assay it in the direction of l-serine synthesis, it can be coupled to the next enzyme in the pathway, phosphoserine aminotransferase (PSAT), with the activity monitored by the conversion of NAD+ to NADH by PGDH. However, when PGDHs from several different species were coupled to PSAT, it was found that one of them, ecPGDH, conserves the coenzyme in the production of l-serine by utilizing an intrinsic cycle of NAD+/NADH interconversion coupled with the conversion of α-ketoglutarate (αKG) to α-hydroxyglutarate. Furthermore, the cycle can be maintained by production of αKG by the second enzyme in the pathway, PSAT, and does not require any additional enzymes. This is not the case for PGDH from another bacterial source, Mycobacterium tuberculosis, and a mammalian source, human liver, where net consumption of NAD+ occurs. Both NAD+ and NADH appear to remain tightly bound to ecPGDH during the cycle, effectively removing a requirement for the presence of an exogenous coenzyme pool to maintain the pathway and significantly reducing the energy requirement needed to maintain this major metabolic pathway.

Lipocalin-Like Prostaglandin D Synthase but Not Hemopoietic Prostaglandin D Synthase Deletion Causes Hypertension and Accelerates Thrombogenesis in Mice.

Prostaglandin (PG) D2 is formed by two distinct PGD synthases (PGDS): lipocalin-type PGDS (L-PGDS), which acts as a PGD2-producing enzyme and as extracellular lipophilic transporter, and hematopoietic PGDS (H-PGDS), a σ glutathione-S-transferase. PGD2 plays an important role in the maintenance of vascular function; however, the relative contribution of L-PGDS- and H-PGDS-dependent formation of PGD2 in this setting is unknown. To gain insight into the function played by these distinct PGDS, we assessed systemic blood pressure (BP) and thrombogenesis in L-Pgds and H-Pgds knockout (KO) mice. Deletion of L-Pgds depresses urinary PGD2 metabolite (PGDM) by ∼35%, whereas deletion of H-Pgds does so by ∼90%. Deletion of L-Pgds, but not H-Pgds, elevates BP and accelerates the thrombogenic occlusive response to a photochemical injury to the carotid artery. HQL-79, a H-PGDS inhibitor, further depresses PGDM in L-Pgds KO mice, but has no effect on BP or on the thrombogenic response. Gene expression profiling reveals that pathways relevant to vascular function are dysregulated in the aorta of L-Pgds KOs. These results indicate that the functional impact of L-Pgds deletion on vascular homeostasis may result from an autocrine effect of L-PGDS-dependent PGD2 on the vasculature and/or the L-PGDS function as lipophilic carrier protein.

Transcriptional and Cell Cycle Alterations Mark Aging of Primary Human Adipose-Derived Stem Cells.

Adult stem cells play a critical role in the maintenance of tissue homeostasis and prevention of aging. While the regenerative potential of stem cells with low cellular turnover, such as adipose-derived stem cells (ASCs), is increasingly recognized, the study of chronological aging in ASCs is technically difficult and remains poorly understood. Here, we use our model of chronological aging in primary human ASCs to examine genome-wide transcriptional networks. We demonstrate first that the transcriptome of aging ASCs is distinctly more stable than that of age-matched fibroblasts, and further, that age-dependent modifications in cell cycle progression and translation initiation specifically characterize aging ASCs in conjunction with increased nascent protein synthesis and a distinctly shortened G1 phase. Our results reveal novel chronological aging mechanisms in ASCs that are inherently different from differentiated cells and that may reflect an organismal attempt to meet the increased demands of tissue and organ homeostasis during aging. Stem Cells 2017;35:1392-1401.

The many faces of partial inhibition: Revealing imposters with graphical analysis.

Partial inhibition occurs when an enzyme-inhibitor complex is capable of producing a product, as opposed to complete inhibition where the enzyme-inhibitor complex is completely inactive and cannot produce a product. While not frequently encountered, partial inhibition is also not a rare phenomenon and can potentially have significant repercussions later on in a research project. It is therefore important to recognize partial inhibition when it occurs. However, it cannot be recognized from the standard velocity versus substrate concentration plots or even from other primary plots such as Lineweaver-Burk plots. Fortunately, partial inhibition is easily identified by using replots which can be generated from the data already gathered to produce the primary plots. Partial inhibition phenomena are also not usually addressed in introductory textbooks and are often given only brief mention in some articles or books dealing with enzyme kinetics. The same types of approaches can be used to study enzyme activation phenomena, which can be considered the flip-side of inhibition. This review presents a graphical approach to identifying partial inhibition in an attempt to provide a comprehensive treatment for those wishing for or needing additional information in carrying out steady-state kinetic inhibition analyses.

Histone posttranslational modifications predict specific alternative exon subtypes in mammalian brain.

A compelling body of literature, based on next generation chromatin immunoprecipitation and RNA sequencing of reward brain regions indicates that the regulation of the epigenetic landscape likely underlies chronic drug abuse and addiction. It is now critical to develop highly innovative computational strategies to reveal the relevant regulatory transcriptional mechanisms that may underlie neuropsychiatric disease. We have analyzed chromatin regulation of alternative splicing, which is implicated in cocaine exposure in mice. Recent literature has described chromatin-regulated alternative splicing, suggesting a novel function for drug-induced neuroepigenetic remodeling. However, the extent of the genome-wide association between particular histone modifications and alternative splicing remains unexplored. To address this, we have developed novel computational approaches to model the association between alternative splicing and histone posttranslational modifications in the nucleus accumbens (NAc), a brain reward region. Using classical statistical methods and machine learning to combine ChIP-Seq and RNA-Seq data, we found that specific histone modifications are strongly associated with various aspects of differential splicing. H3K36me3 and H3K4me1 have the strongest association with splicing indicating they play a significant role in alternative splicing in brain reward tissue.