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Richards, A. L.

Publications and source records attributed to Richards, A. L..

18 recordsLinked to original sources

APOE4 disrupts the central dogma by arresting neuronal proteome dynamics

Apolipoprotein E4 (APOE4) is the strongest genetic risk factor for late-onset Alzheimers disease and promotes neuronal dysfunction through incompletely understood mechanisms. Here, we integrated transcriptomic, translatomic, and proteomic profiling of isogenic APOE3 and APOE4 human iPSC-derived neurons and found that APOE4 fundamentally impairs neuronal proteome renewal. Although transcriptional changes were modest, APOE4 disrupted ribosome occupancy, altered translational dynamics, and uncoupled protein abundance from transcript levels. Proteome-wide turnover measurements revealed a global extension of protein half-lives and widespread accumulation of long-lived proteins. Functional proteomic analyses demonstrated concurrent lysosomal and proteasomal impairments associated with reduced proteasome activity and increased association of APOE with neuronal proteasomes. Longitudinal proteomics further showed that protein accumulation emerges during neuronal maturation and precedes a senescence-like cellular stress state. Together, these findings identify impaired proteome renewal as a central mechanism underlying neuronal vulnerability to APOE4 and establish defective proteostasis as an early pathogenic event in Alzheimers disease.

neuroscience↗

Functional diversification of the cephalopod proteome by RNA-editing

Coleoid cephalopods exhibit the highest levels of ADAR-mediated RNA editing of any known animal, yet the functional consequences of most recoding events remain largely unknown. We integrate proteomics with biochemical and cellular assays to characterize thousands of recoding events across the Doryteuthis pealeii proteome. Using quantitative and functional mass spectrometry, we show that RNA edit-driven recoding reshapes the cellular proteome to alter protein stability, subcellular localization, post-translational modifications, and enzymatic activity. --Recoding can regulate post-translational modifications through their creation or ablation, and this has direct effects on protein function and protein-protein interactions. Recoding of the E3 ligase MARCHF5 drives widespread changes in substrate ubiquitylation and perturbs mitochondrial homeostasis, illustrating how RNA editing can influence organelle function. These data provide the first proteome-scale view of how extensive RNA recoding diversifies protein function in coleoid cephalopods and offers a new framework for understanding how RNA-level plasticity shapes protein function and cellular physiology.

molecular biology↗

Complete genomes of Rickettsia typhi reveal a clonal population

Murine typhus, caused by infection with Rickettsia typhi, is a neglected disease contributing to infectious disease burden in south- and southeast Asia. Despite its importance, we have minimal knowledge of the genomics of R. typhi, with only four complete genomes being sequenced prior to this work. We sequenced a further 25 genomes including historical strains collected before 1976 from both human and rat hosts, and recent genomes isolated from patients at a single hospital in Laos. Whole genome SNP analysis reveals extremely low levels of genetic diversity across the 29 genomes, with overall nucleotide diversity ({pi}) of 1.27e-05 and evidence of purifying selection, and a minimal pan-genome. Phylogenetic analysis shows clustering of the genome by historic or modern origin, with the exception of one modern strain which is most closely related to historic strains from Thailand, and no clustering by host origin. The highly conserved genome of R. typhi suggests strong constraints on genome evolution in this obligate intracellular parasite, and has implications for the design of future murine typhus diagnostic tools and vaccines. Impact StatementRickettsia typhi is the causative agent of murine typhus, an infectious disease that causes morbidity and mortality in humans. This study has expanded the genomic dataset from a small number of genomes to a comprehensive collection of 29 complete genomes. The genome comparison includes historic and modern strains and reveals a clonal population structure with minimal genetic diversity across time. This shows the evolutionary stability of R. typhi, which is most likely due to strong purifying selection and an intracellular lifestyle. This extremely low genomic variation has significant impacts for the development of murine typhus vaccines and robust diagnostic assays.

microbiology↗

Selective RNA sequestration in biomolecular condensates directs cell fate transitions

Recent studies have emphasized the significance of biomolecular condensates in modulating gene expression through RNA processing and translational control. However, the functional roles of RNA condensates in cell fate specification remains poorly understood. Here, we profiled the coding and non-coding transcriptome within intact biomolecular condensates, specifically P-bodies, in diverse developmental contexts, spanning multiple vertebrate species. Our analyses revealed the conserved, cell type-specific sequestration of untranslated RNAs encoding key cell fate regulators. Notably, P-body contents did not directly reflect active gene expression profiles for a given cell type, but rather were enriched for translationally repressed transcripts characteristic of the preceding developmental stage. Mechanistically, microRNAs (miRNAs) direct the selective sequestration of RNAs into P-bodies in a context-dependent manner, and perturbing AGO2 or alternative polyadenylation profoundly reshapes P-body RNA content. Building on these mechanistic insights, we demonstrate that modulating P-body assembly or miRNA activity dramatically enhances both activation of a totipotency transcriptional program in naive pluripotent stem cells as well as the programming of primed human embryonic cells towards the germ cell lineage. Collectively, our findings establish a direct link between biomolecular condensates and cell fate decisions across vertebrate species and provide a novel framework for harnessing condensate biology to expand clinically relevant cell populations.

cell biology↗

The Mac1 ADP-ribosylhydrolase is a Therapeutic Target for SARS-CoV-2

SARS-CoV-2 continues to pose a threat to public health. Current therapeutics remain limited to direct acting antivirals that lack distinct mechanisms of action and are already showing signs of viral resistance. The virus encodes an ADP-ribosylhydrolase macrodomain (Mac1) that plays an important role in the coronaviral lifecycle by suppressing host innate immune responses. Genetic inactivation of Mac1 abrogates viral replication in vivo by potentiating host innate immune responses. However, it is unknown whether this can be achieved by pharmacologic inhibition and can therefore be exploited therapeutically. Here we report a potent and selective lead small molecule, AVI-4206, that is effective in an in vivo model of SARS-CoV-2 infection. Standard cellular models indicate that AVI-4206 has high target engagement and can weakly inhibit viral replication in a gamma interferon- and Mac1 catalytic activity-dependent manner. However, a stronger antiviral effect for AVI-4206 is observed in human airway organoids and peripheral blood monocyte-derived macrophages. In an animal model of severe SARS-CoV-2 infection, AVI-4206 reduces viral replication, potentiates innate immune responses, and leads to a survival benefit. Our results provide pharmacological proof of concept that Mac1 is a valid therapeutic target via a novel immune-restoring mechanism that could potentially synergize with existing therapies targeting distinct, essential aspects of the coronaviral life cycle. This approach could be more widely used to target other viral macrodomains to develop antiviral therapeutics beyond COVID-19.

immunology↗

Deep learning from harmonized peptide libraries enables retention time prediction of diverse post translational modifications

In proteomics experiments, peptide retention time (RT) is an orthogonal property to fragmentation when assessing detection confidence. Advances in deep learning enable accurate RT prediction for any peptide from sequence alone, including those yet to be experimentally observed. Here we present Chronologer, an open-source software tool for rapid and accurate peptide RT prediction. Using new approaches to harmonize and false-discovery correct across independently collected datasets, Chronologer is built on a massive database with >2.2 million peptides including 10 common post-translational modification (PTM) types. By linking knowledge learned across diverse peptide chemistries, Chronologer predicts RTs with less than two-thirds the error of other deep learning tools. We show how RT for rare PTMs, such as OGlcNAc, can be learned with high accuracy using as few as 10-100 example peptides in newly harmonized datasets. This iteratively updatable workflow enables Chronologer to comprehensively predict RTs for PTM-marked peptides across entire proteomes.

bioinformatics↗

Global landscape of the host response to SARS-CoV-2 variants reveals viral evolutionary trajectories

A series of SARS-CoV-2 variants of concern (VOCs) have evolved in humans during the COVID-19 pandemic--Alpha, Beta, Gamma, Delta, and Omicron. Here, we used global proteomic and genomic analyses during infection to understand the molecular responses driving VOC evolution. We discovered VOC-specific differences in viral RNA and protein expression levels, including for N, Orf6, and Orf9b, and pinpointed several viral mutations responsible. An analysis of the host response to VOC infection and comprehensive interrogation of altered virus-host protein-protein interactions revealed conserved and divergent regulation of biological pathways. For example, regulation of host translation was highly conserved, consistent with suppression of VOC replication in mice using the translation inhibitor plitidepsin. Conversely, modulation of the host inflammatory response was most divergent, where we found Alpha and Beta, but not Omicron BA.1, antagonized interferon stimulated genes (ISGs), a phenotype that correlated with differing levels of Orf6. Additionally, Delta more strongly upregulated proinflammatory genes compared to other VOCs. Systematic comparison of Omicron subvariants revealed BA.5 to have evolved enhanced ISG and proinflammatory gene suppression that similarly correlated with Orf6 expression, effects not seen in BA.4 due to a mutation that disrupts the Orf6-nuclear pore interaction. Our findings describe how VOCs have evolved to fine-tune viral protein expression and protein-protein interactions to evade both innate and adaptive immune responses, offering a likely explanation for increased transmission in humans. One sentence summarySystematic proteomic and genomic analyses of SARS-CoV-2 variants of concern reveal how variant-specific mutations alter viral gene expression, virus-host protein complexes, and the host response to infection with applications to therapy and future pandemic preparedness.

systems biology↗

Data-independent acquisition protease-multiplexing enables increased proteome sequence coverage across multiple fragmentation modes

The use of multiple proteases has been shown to increase protein sequence coverage in proteomics experiments, however due to the additional analysis time required, it has not been widely adapted in routine data-dependent acquisition (DDA) proteomic workflows. Alternatively, data-independent acquisition (DIA) has the potential to analyze multiplexed samples from different protease digests, but has been primarily optimized for fragmenting tryptic peptides. Here we evaluate a DIA multiplexing approach that combines three proteolytic digests (Trypsin, AspN, and GluC) into a single sample. We first optimize data acquisition conditions for each protease individually with both the canonical DIA fragmentation mode (beam type CID), as well as resonance excitation CID, to determine optimal consensus conditions across proteases. Next, we demonstrate that application of these conditions to a protease-multiplexed sample of human peptides results in similar protein identifications and quantitative performance as compared to trypsin alone, but enables up to a 63% increase in peptide detections, and a 27% increase non-redundant amino acid detections. Importantly, this resulted in 100% sequence coverage for numerous proteins, suggesting the utility of this approach in applications where sequence coverage is critical, such as proteoform analysis.

systems biology↗

Evolution of enhanced innate immune evasion by the SARS-CoV-2 B.1.1.7 UK variant

Emergence of SARS-CoV-2 variants, including the globally successful B.1.1.7 lineage, suggests viral adaptations to host selective pressures resulting in more efficient transmission. Although much effort has focused on Spike adaptation for viral entry and adaptive immune escape, B.1.1.7 mutations outside Spike likely contribute to enhance transmission. Here we used unbiased abundance proteomics, phosphoproteomics, mRNA sequencing and viral replication assays to show that B.1.1.7 isolates more effectively suppress host innate immune responses in airway epithelial cells. We found that B.1.1.7 isolates have dramatically increased subgenomic RNA and protein levels of Orf9b and Orf6, both known innate immune antagonists. Expression of Orf9b alone suppressed the innate immune response through interaction with TOM70, a mitochondrial protein required for RNA sensing adaptor MAVS activation, and Orf9b binding and activity was regulated via phosphorylation. We conclude that B.1.1.7 has evolved beyond the Spike coding region to more effectively antagonise host innate immune responses through upregulation of specific subgenomic RNA synthesis and increased protein expression of key innate immune antagonists. We propose that more effective innate immune antagonism increases the likelihood of successful B.1.1.7 transmission, and may increase in vivo replication and duration of infection.

microbiology↗

Towards comprehensive plasma proteomics by orthogonal protease digestion

Rapid and consistent protein identification across large clinical cohorts is an important goal for clinical proteomics. With the development of data-independent technologies (DIA/SWATH-MS), it is now possible to analyze hundreds of samples with great reproducibility and quantitative accuracy. However, this technology benefits from empirically derived spectral libraries that define the detectable set of peptides and proteins. Here we apply a simple and accessible tip-based workflow for the generation of spectral libraries to provide a comprehensive overview on the plasma proteome in individuals with and without active tuberculosis (TB). To boost protein coverage, we utilized non-conventional proteases such as GluC and AspN together with the gold standard trypsin, identifying more than 30,000 peptides mapping to 3,309 proteins. Application of this library to quantify plasma proteome differences in TB infection recovered more than 400 proteins in 50 minutes of MS-acquisition, including diagnostic Mycobacterium tuberculosis (Mtb) proteins that have previously been detectable primarily by antibody-based assays and intracellular proteins not previously described to be in plasma.

systems biology↗

Functional dynamic genetic effects on gene regulation are specific to particular cell types and environmental conditions

Genetic effects on gene expression and splicing can be modulated by cellular and environmental factors; yet interactions between genotypes, cell type and treatment have not been comprehensively studied together. We used an induced pluripotent stem cell system to study multiple cell types derived from the same individuals and exposed them to a large panel of treatments. Cellular responses involved different genes and pathways for gene expression and splicing processes, and were also highly variable across cell types and treatments. For thousands of genes, we identified variable allelic expression across contexts, and characterized different types of gene-environment interactions. Many of these GxE genes are associated with complex traits. We characterized promoter functional and evolutionary features that distinguish genes with elevated allelic imbalance mean and variance. More than 47% of the genes with dynamic regulatory interactions were missed by GTEx, but we identified them using a suitable allelic imbalance study design. This indicates the importance of exploring multiple treatments to reveal previously unrecognized regulatory loci that may be important for disease.

genomics↗

Interspecies variation in hominid gut microbiota controls host gene regulation

The gut microbiome exhibits extreme compositional variation between hominid hosts. However, it is unclear how this variation impacts host physiology, and whether this effect can be mediated through microbial regulation of host gene expression in interacting epithelial cells. Here, we characterized the transcriptional response of colonic epithelial cells in vitro to live microbial communities extracted from humans, chimpanzees, gorillas, and orangutans. We found most host genes exhibit a conserved response, whereby they respond similarly to the four hominid microbiomes, while some genes respond only to microbiomes from specific host species. Genes that exhibit such a divergent response are associated with relevant intestinal diseases in humans, such as inflammatory bowel disease and Crohns disease. Lastly, we found that inflammation-associated microbial species regulate the expression of host genes previously associated with inflammatory bowel disease, suggesting health-related consequences for species-specific host-microbiome interactions across hominids.

genomics↗

A SARS-CoV-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Repurposing

An outbreak of the novel coronavirus SARS-CoV-2, the causative agent of COVID-19 respiratory disease, has infected over 290,000 people since the end of 2019, killed over 12,000, and caused worldwide social and economic disruption1,2. There are currently no antiviral drugs with proven efficacy nor are there vaccines for its prevention. Unfortunately, the scientific community has little knowledge of the molecular details of SARS-CoV-2 infection. To illuminate this, we cloned, tagged and expressed 26 of the 29 viral proteins in human cells and identified the human proteins physically associated with each using affinity-purification mass spectrometry (AP-MS), which identified 332 high confidence SARS-CoV-2-human protein-protein interactions (PPIs). Among these, we identify 66 druggable human proteins or host factors targeted by 69 existing FDA-approved drugs, drugs in clinical trials and/or preclinical compounds, that we are currently evaluating for efficacy in live SARS-CoV-2 infection assays. The identification of host dependency factors mediating virus infection may provide key insights into effective molecular targets for developing broadly acting antiviral therapeutics against SARS-CoV-2 and other deadly coronavirus strains.

systems biology↗

The independent and combined influence of schizophrenia polygenic risk score and heavy cannabis use on risk for psychotic disorder: A case-control analysis from the EUGEI study.

Background: Some recent studies have challenged the direction of causality for the association between cannabis use and psychotic disorder, suggesting that cannabis use initiation is explained by common genetic variants associated with risk of schizophrenia. We used data from the European Union Gene-Environment Interaction consortium (EUGEI) case-control study to test for the independent and combined effect of heavy cannabis use, and of Schizophrenia Polygenic risk score (SZ PRS), on risk for psychotic disorder. Methods: Genome-wide data were obtained from 492 first episode psychosis patients (FEPp) and from 787 controls of European Ancestry, and used to generate SZ PRS from the summary results of an independent meta-analysis. Information on pattern of cannabis use was used to build a 7-level frequency-type composite cannabis use measure that we previously found was a strong predictor of psychotic disorder. Results: SZ PRS did not predict cannabis initiation (b=0.027; p=0.51) or how frequently controls (b=0.027; p=0.06) or FEPp (b=0.006; p=0.91) used it, or the type of cannabis they used (Controls: b = 0.032; p=0.31); FEPp: b= 0.005; p=0.89). The frequency-type composite cannabis use measure (OR=1.32; 95% CI 1.22-1.44) and SZ PRS (OR=2.29; 95%CI 1.71-3.05) showed independent effects from each other on the OR for psychotic disorder. Conclusion: SZ PRS does not predict an individual s propensity to try cannabis, frequency of use, or the potency of the cannabis used. Our findings provide the first evidence that SZ PRS and heavy cannabis use exert effects independent from each other on the risk for psychotic disorder.

genetics↗

Analyses of rare and common alleles in parent-proband trios implicate rare missense variants in SLC6A1 in schizophrenia and confirm the involvement of loss of function intolerant and neurodevelopmental disorder genes.

Schizophrenia is a highly polygenic disorder with important contributions coming from both common and rare risk alleles, the latter including CNVs and rare coding variants (RCVs), sometimes occurring as de novo variants (DNVs). We performed DNV analysis in whole exome-sequencing data obtained from a new sample of 613 schizophrenia trios, and combined this with published data for a total of 3,444 trios. Loss-of-function (LoF) DNVs were significantly enriched among 3,488 LoF intolerant genes in our new trio data (rate ratio (RR) (95% CI) = 2.23 (1.31, 3.79); p = 2.2 x 10-3), supporting previous findings. In the full dataset, genes associated with neurodevelopmental disorders (NDD; n=160) were significantly enriched for LoF DNVs (RR (95% CI) = 3.32 (2.0, 5.21); p = 7.4 x 10-6). Within this set of NDD genes, SLC6A1, encoding a gamma-aminobutyric acid transporter, was associated with missense-damaging DNVs (p = 5.2 x 10-5). Using data from a subset of 1,122 trios for which we had genome-wide common variant data, schizophrenia polygenic risk was significantly over-transmitted to probands (p = 2.6 x 10-60), as was bipolar disorder common variant polygenic risk (p = 5.7 x 10-17). We defined carriers of candidate schizophrenia-related DNVs as those with LoF or deletion DNVs in LoF intolerant or NDD genes. These individuals had significantly less over-transmission of common risk alleles than non-carriers (p = 3.5 x 10-4), providing robust support for the hypothesis that this set of DNVs is enriched for those related to schizophrenia.

genetics↗

Interpreting coronary artery disease risk through gene-environment interactions in gene regulation

GWAS and eQTL studies identified thousands of genetic variants associated with complex traits and gene expression. Despite the important role of environmental exposures in complex traits, only a limited number of environmental factors are measured in these studies. Measuring molecular phenotypes in tightly controlled cellular environments provides a more tractable setting to study gene-environment interactions in the absence of other confounding variables.\n\nWe performed RNA-seq and ATAC-seq in endothelial cells exposed to retinoic acid, dexamethasone, caffeine, and selenium to model genetic and environmental effects on gene regulation in the vascular endothelium, a common site of pathology in cardiovascular disease. We found that genes near regions of differentially accessible chromatin were more likely to be differentially expressed (OR = [3.41, 6.52], p < 10-16). Furthermore, we confirmed that environment-specific changes in transcription factor binding are a key mechanism for cellular response to environmental stimuli. SNPs in these transcription response factor footprints for dexamethasone, caffeine, and retinoic acid were enriched in GTEx eQTLs from artery tissues indicating that these environmental conditions are latently present in GTEx samples. Additionally, SNPs in footprints for response factors in caffeine are enriched in colocalized eQTLs for coronary artery disease (CAD), suggesting a role for caffeine in CAD risk. Interestingly, each treatment may amplify or buffer genetic risk for CAD, depending on the particular SNP considered.

genomics↗

Association between schizophrenia and both loss of function and missense mutations in paralog conserved sites of voltage-gated sodium channels

Sequencing studies have highlighted candidate sets of genes involved in schizophrenia, including activity-regulated cytoskeleton-associated protein (ARC) and N-methyl-d-aspartate receptor (NMDAR) complexes. Two genes, SETD1A and RBM12, have also been associated with robust statistical evidence. Larger samples and novel methods for identifying disease-associated missense variants are needed to reveal novel genes and biological mechanisms associated with schizophrenia. We sequenced 187 genes, selected for prior evidence of association with schizophrenia, in a new dataset of 5,207 cases and 4,991 controls. Included were members of ARC and NMDAR post-synaptic protein complexes, as well as voltage-gated sodium and calcium channels. We observed a significant case excess of rare (<0.1% in frequency) loss-of-function (LoF) mutations across all 187 genes (OR = 1.36; Pcorrected = 0.0072) but no individual gene was associated with schizophrenia after correcting for multiple testing. We found novel evidence that LoF and missense variants at paralog conserved sites were enriched in sodium channels (OR = 1.26; P = 0.0035). Meta-analysis of our new data with published sequencing data (11,319 cases, 15,854 controls and 1,136 trios) supported and refined this association to sodium channel alpha subunits (P = 0.0029). Meta-analysis also confirmed association between schizophrenia and rare variants in ARC (P = 4.0 x 10-4) and NMDAR (P = 1.7 x 10-5) synaptic genes. No association was found between rare variants in calcium channels and schizophrenia.\n\nIn one of the largest sequencing studies of schizophrenia to date, we provide novel evidence that multiple voltage-gated sodium channels are involved in schizophrenia pathogenesis, and increase the evidence for association between rare variants in ARC and NMDAR post-synaptic complexes and schizophrenia. Larger samples are required to identify specific genes and variants driving these associations.\n\nAuthor SummaryCommon and rare genetic variations are known to play a substantial role in the development of schizophrenia. Recently, sequencing studies have started to highlight specific sets of genes that are enriched for rare variation in schizophrenia, such as the synaptic gene sets ARC and NMDAR, as well as voltage-gated sodium and calcium channels. To confirm the role of these gene sets in schizophrenia, and identify specific risk genes, we sequenced 187 genes in a new sample of 5,207 schizophrenia cases and 4,991 controls. We find an excess of protein truncating mutations with a frequency <0.1% in all 187 targeted genes, and provide novel evidence that mutations altering amino acids conserved across sodium channel proteins are risk factors for schizophrenia. Through meta-analysing our new data with previously published sequencing data sets, for a total of 11,319 cases, 15,854 controls and 1,136 trios, we increase the evidence for association between rare coding variants and schizophrenia in voltage-gated sodium channels, as well as in synaptic gene sets ARC and NMDAR. Although no individual gene was associated with schizophrenia, these findings suggest larger studies will identify the specific genes driving these associations.

genetics↗

Environmental Perturbations Lead To Extensive Directional Shifts In RNA Processing

Environmental perturbations have large effects on both organismal and cellular traits, including gene expression, but the extent to which the environment affects RNA processing remains largely uncharacterized. Recent studies have identified a large number of genetic variants associated with variation in RNA processing that also have an important role in complex traits; yet we do not know in which contexts the different underlying isoforms are used. Here, we comprehensively characterized changes in RNA processing events across 89 environments in five human cell types and identified 15,300 event shifts (FDR = 15%) comprised of eight event types in over 4,000 genes. Many of these changes occur consistently in the same direction across conditions, indicative of global regulation by trans factors. Accordingly, we demonstrate that environmental modulation of splicing factor binding predicts shifts in intron retention, and that binding of transcription factors predicts shifts in AFE usage in response to specific treatments. We validated the mechanism hypothesized for AFE in two independent datasets. Using ATAC-seq, we found altered binding of 64 factors in response to selenium at sites of AFE shift, including ELF2 and other factors in the ETS family. We also performed AFE QTL mapping in 373 individuals and found an enrichment for SNPs predicted to disrupt binding of the ELF2 factor. Together, these results demonstrate that RNA processing is dramatically changed in response to environmental perturbations through specific mechanisms regulated by trans factors.\n\nAuthor SummaryChanges in a cells environment and genetic variation have been shown to impact gene expression. Here, we demonstrate that environmental perturbations also lead to extensive changes in alternative RNA processing across a large number of cellular environments that we investigated. These changes often occur in a non-random manner. For example, many treatments lead to increased intron retention and usage of the downstream first exon. We also show that the changes to first exon usage are likely dependent on changes in transcription factor binding. We provide support for this hypothesis by considering how first exon usage is affected by disruption of binding due to treatment with selenium. We further validate the role of a specific factor by considering the effect of genetic variation in its binding sites on first exon usage. These results help to shed light on the vast number of changes that occur in response to environmental stimuli and will likely aid in understanding the impact of compounds to which we are daily exposed.

genomics↗