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Myers, R. M.

Publications and source records attributed to Myers, R. M..

At least 37 records · Page 2Linked to original sources

Genome-wide strand asymmetry in massively parallel reporter activity favors genic strands

Massively parallel reporter assays (MPRAs) are useful tools to discover and characterize regulatory elements in human genomes. Partly because enhancer function is assumed to be orientation independent with respect to each strand of the DNA helix, most reported MPRA results ignore stranded information. However, we find pervasive strand asymmetry of MPRA signals in datasets from multiple reporter configurations and in both published and newly reported data. These effects are reproducible across different cell types and in different treatments within a cell type, and are observed both within and outside of annotated regulatory elements. From elements in gene bodies, MPRA strand asymmetry favors the sense strand, suggesting that biological function related to endogenous transcription is driving the phenomenon. Similarly, within Alu mobile element insertions, we find that strand asymmetry favors the transcribed strand of the ancestral retrotransposon. The effect is consistent across the multiplicity of Alu elements in human genomes, and is more pronounced in younger, less diverged Alu elements. We find sequence features driving MPRA strand asymmetry and demonstrate its prediction from sequence alone. We see some evidence for both RNA stabilization and transcriptional activation mechanisms, and hypothesize that the effect is driven by natural selection favoring efficient transcription. Our results indicate that strand asymmetry, as a pervasive and reproducible feature, should be accounted for in analysis of MRPA data. More importantly, the fact that MPRA asymmetry favors naturally transcribed strands suggests that it stems from preserved biological functions that have a substantial, global impact on gene and genome evolution.

genomics↗

Aberrant regulation of a poison exon caused by a non-coding variant in Scn1a-associated epileptic encephalopathy

Dravet syndrome (DS) is a developmental and epileptic encephalopathy that results from mutations in the Nav1.1 sodium channel encoded by SCN1A. Most known DS-causing mutations are in coding regions of SCN1A, but we recently identified several disease-associated SCN1A mutations in intron 20 that are within or near to a cryptic and evolutionarily conserved "poison" exon, 20N, whose inclusion leads to transcript degradation. However, it is not clear how these intron 20 variants alter SCN1A transcript processing or DS pathophysiology in an organismal context, nor is it clear how exon 20N is regulated in a tissue-specific and developmental context. We address those questions here by generating an animal model of our index case, NM_006920.4(SCN1A):c.3969+2451G>C, using gene editing to create the orthologous mutation in laboratory mice. Scn1a heterozygous knock-in (+/KI) mice exhibited an ~50% reduction in brain Scn1a mRNA and Nav1.1 protein levels, together with characteristics observed in other DS mouse models, including premature mortality, seizures, and hyperactivity. In brain tissue from adult Scn1a +/+ animals, quantitative RT-PCR assays indicated that ~1% of Scn1a mRNA included exon 20N, while brain tissue from Scn1a +/KI mice exhibited an ~5-fold increase in the extent of exon 20N inclusion. We investigated the extent of exon 20N inclusion in brain during normal fetal development in RNA-seq data and discovered that levels of inclusion were ~70% at E14.5, declining progressively to ~10% postnatally. A similar pattern exists for the homologous sodium channel Nav1.6, encoded by Scn8a. For both genes, there is an inverse relationship between the level of functional transcript and the extent of poison exon inclusion. Taken together, our findings suggest that poison exon usage by Scn1a and Scn8a is a strategy to regulate channel expression during normal brain development, and that mutations recapitulating a fetal-like pattern of splicing cause reduced channel expression and epileptic encephalopathy. Author SummaryDravet syndrome (DS) is a neurological disorder affecting approximately 1:15,700 Americans[1]. While most patients have a mutation in the SCN1A gene encoding Nav1.1 sodium channels, about 20% do not have a mutation identified by exome sequencing. Recently, we identified variants in intron 20N, a noncoding region of SCN1A, in some DS patients [2]. We predicted that these variants alter SCN1A transcript processing, decrease Nav1.1 function, and lead to DS pathophysiology via inclusion of exon 20N, a "poison" exon that leads to a premature stop codon. In this study, we generated a knock-in mouse model, Scn1a+/KI, of one of these variants, NM_006920.4(SCN1A):c.3969+2451G>C, which resides in a genomic region that is extremely conserved across vertebrate species. We found that Scn1a+/KI mice have reduced levels of Scn1a transcript and Nav1.1 protein and develop DS-related phenotypes. Consistent with the poison exon hypothesis, transcripts from brains of Scn1a+/KI mice showed elevated rates of Scn1a exon 20N inclusion. Since Scn1a expression in the brain is regulated developmentally, we next explored the developmental relationship between exon 20N inclusion and Scn1a expression. During normal embryogenesis, when Scn1a expression was low, exon 20N inclusion was high; postnatally, as Scn1a expression increased, there was a corresponding decrease in exon 20N usage. Expression of another voltage-gated sodium channel transcript, Scn8a (Nav1.6), was similarly regulated, with inclusion of a poison exon termed as 18N early in development when Scn8a expression was low, followed by a postnatal decrease in exon 18N inclusion and corresponding increase in Scn8a expression. Together, these data demonstrate that poison exon inclusion is a conserved mechanism to control sodium channel expression in the brain, and that an intronic mutation that disrupts the normal developmental regulation of poison exon inclusion leads to reduced Nav1.1 and DS pathophysiology.

genetics↗

Dissecting the regulatory activity and key sequence elements of loci with exceptional numbers of transcription factor associations

DNA associated proteins (DAPs) classically regulate gene expression by binding to regulatory loci such as enhancers or promoters. As expanding catalogs of genome-wide DAP binding maps reveal thousands of loci that, unlike the majority of conventional enhancers and promoters, associate with dozens of different DAPs with apparently little regard for motif preference, an understanding of DAP association and coordination at such regulatory loci is essential to deciphering how these regions contribute to normal development and disease. In this study, we aggregated publicly available ChIP-seq data from 469 human DAPs assayed in three cell lines and integrated these data with an orthogonal dataset of 352 non-redundant, in vitro-derived motifs mapped to the genome within DNase hypersensitivity footprints in an effort to characterize regions of the genome that have exceptionally high numbers of DAP associations. We subsequently performed a massively parallel mutagenesis assay to search for sequence elements driving transcriptional activity at such loci and explored plausible biological mechanisms underlying their formation. We establish a generalizable definition for High Occupancy Target (HOT) loci and identify putative driver DAP motifs in HEPG2 cells, including HNF4A, SP1, SP5, and ETV4, that are highly prevalent and exhibit sequence conservation at HOT loci. The number of different DAPs associated with an element is positively associated with evidence of regulatory activity and, by systematically mutating 245 HOT loci, we localized regulatory activity to a central core region that depends on the motif sequences of our previously nominated driver DAPs. In sum, this work leverages the increasingly large number of DAP motif and ChIP-seq data publicly available to explore how DAP associations contribute to genome-wide transcriptional regulation.

genomics↗

Assembly of a young vertebrate Y chromosome reveals convergent signatures of sex chromosome evolution

Heteromorphic sex chromosomes have evolved repeatedly across diverse species. Suppression of recombination between X and Y chromosomes leads to rapid degeneration of the Y chromosome. However, these early stages of degeneration are not well understood, as complete Y chromosome sequence assemblies have only been generated across a handful of taxa with ancient sex chromosomes. Here we describe the assembly of the threespine stickleback (Gasterosteus aculeatus) Y chromosome, which is less than 26 million years old. Our previous work identified that the non-recombining region between the X and the Y spans [~]17.5 Mb on the X chromosome. Here, we combined long-read PacBio sequencing with a Hi-C-based proximity guided assembly to generate a 15.87 Mb assembly of the Y chromosome. Our assembly is concordant with cytogenetic maps and Sanger sequences of over 90 Y chromosome clones from a bacterial artificial chromosome (BAC) library. We found three evolutionary strata on the Y chromosome, consistent with the three inversions identified by our previous cytogenetic analyses. The young threespine stickleback Y shows convergence with older sex chromosomes in the retention of haploinsufficient genes and the accumulation of genes with testis-biased expression, many of which are recent duplicates. However, we found no evidence for large amplicons found in other sex chromosome systems. We also report an excellent candidate for the master sex-determination gene: a translocated copy of Amh (Amhy). Together, our work shows that the same evolutionary forces shaping older sex chromosomes can cause remarkably rapid changes in the overall genetic architecture on young Y chromosomes.

evolutionary biology↗

Non-Coding and Loss-of-Function Coding Variants in TET2 are Associated with Multiple Neurodegenerative Diseases

We conducted genome sequencing to search for rare variation contributing to early onset Alzheimers disease (EOAD) and frontotemporal dementia (FTD). Discovery analysis was conducted on 493 cases and 671 controls of European ancestry. Burden testing for rare variation associated with disease was conducted using filters based on variant rarity (less than 1 in 10,000 or private), computational prediction of deleteriousness (CADD 10 or 15 thresholds), and molecular function (protein loss-of-function only, coding alteration only, or coding plus non-coding variants in experimentally predicted regulatory regions).\n\nReplication analysis was conducted on 16,871 independent cases and 15,941 independent controls. Rare variants in TET2 were enriched in the discovery combined EOAD and FTD cohort (p=6.5x10-8, genome-wide corrected p=0.0037). Most of these variants were canonical loss-of-function or non-coding in predicted regulatory regions. This enrichment replicated across several cohorts of AD and FTD (replication only p=0.0071). The combined analysis odds ratio was 2.2 (95% CI 1.5-3.2) for AD and FTD. The odds ratio for qualifying non-coding variants considered independently from coding variants was 2.1 (95% CI 1.2-3.9). For loss-of-function variants, the combined odds ratio (for AD, FTD, and amyotrophic lateral sclerosis, which shares clinicopathological overlap with FTD) was 3.2 (95% CI 2.0-5.3). TET2 catalyzes DNA demethylation. Given well-defined changes in DNA methylation that occur during aging, rare variation in TET2 may confer risk for neurodegeneration by altering the homeostasis of key aging-related processes. Additionally, our study emphasizes the relevance of non-coding variation in genetic studies of complex disease.

neuroscience↗

Genome sequencing for early-onset dementia: high diagnostic yield and frequent observation of multiple contributory alleles

We assessed the utility of genome sequencing for early-onset dementia. Participants were selected from a memory disorders clinic. Genome sequencing was performed along with C9orf72 repeat expansion testing. All returned sequencing results were Sanger validated clinically. Prior clinical diagnoses included Alzheimers disease, frontotemporal dementia, and unspecified dementia. The mean age-of-onset was 54 (41-76). 50% of patients had a strong family history, 37.5% had some, and 12.5% had no known family history. Nine of 32 patients (28%) had a variant defined as pathogenic or likely pathogenic (P/LP) by American College of Medical Genetics standards, including variants in APP, C9orf72, CSF1R, and MAPT. Nine patients (including three with P/LP variants) harbored established risk alleles with moderate penetrance (odds ratios of about 2-5) in ABCA7, AKAP9, GBA, PLD3, SORL1, and TREM2. All six patients harboring these moderate penetrance variants but not P/LP variants also had one or two APOE {varepsilon}4 alleles. One patient had two APOE {varepsilon}4 alleles with no other established contributors. In total, 16 patients (50%) harbored one or more genetic variants likely to explain symptoms. We identified variants of uncertain significance (VUSs) in ABI3, ADAM10, ARSA, GRID2IP, MME, NOTCH3, PLCD1, PSEN1, TM2D3, TNK1, TTC3, and VPS13C, also often along with other variants. In summary, genome sequencing for early-onset dementia demonstrated high utility, with particular advantages where targeted testing may fail such as atypical variant-disease associations or presence of multiple moderate impact alleles. One or more established contributory alleles is often present in early-onset dementia, supporting an oligogenic model.

neuroscience↗

STAT3 and GR cooperate to drive basal-like triple negative breast cancer gene expression and proliferation.

Breast cancers can be divided into subtypes with different prognoses and treatment responses based on global gene expression differences. Luminal breast cancer gene expression and proliferation are driven by the transcription factors Estrogen Receptor (ER), FOXA1 and GATA3. Targeting ER is the most effective therapy for treating luminal breast cancer because ER is the master regulator of the luminal gene expression program. In contrast, it is unclear which transcription factors are responsible for driving the gene expression signature that defines basal-like triple negative breast cancer, and there are no targeted therapies approved to treat this aggressive subtype of the disease. This study utilized integrated analysis of DNA methylation, chromatin accessibility, transcription factor binding, and gene expression in large collections of breast cancer cell lines and patient tumors to identify transcription factors responsible for the basal-like gene expression program. The results of this study indicate that glucocorticoid receptor (GR) and signal transducer and activator of transcription 3 (STAT3) bind to the same genomic regulatory regions that are specifically open and unmethylated in basal-like breast cancer. These transcription factors cooperate to regulate expression of hundreds of genes in the basal-like gene expression signature and these downstream genes are associated with poor prognosis in patients. Furthermore, combination treatment with small molecule drugs that inhibit both transcription factors leads to synergistic decreases in cell proliferation in cell lines and patient-derived organoid models. This study demonstrates that GR and STAT3 cooperate to regulate the basal-like breast cancer gene expression program and provides the basis for improved therapy for basal-like triple negative breast cancer through rational combination of STAT3 and GR inhibitors.

cancer biology↗

High-throughput identification of genes involved in single and multi-drug resistance in pancreatic cancer with pooled CRISPR screening

Pancreatic ductal adenocarcinoma (PDAC) patients suffer poor outcomes in part due to therapeutic resistance. We conducted four genome-wide CRISPR activation (CRISPRact) and CRISPR knock out (CRISPRko) screens to identify novel resistance mechanisms to four cytotoxic chemotherapies (gemcitabine, 5-fluorouracil, irinotecan, and oxaliplatin). ABCG2, a well-described efflux pump was the strongest mediator of resistance. We showed that overexpressing HDAC1 altered promoter occupancy and expression of genes involved in the epithelial-to-mesenchymal transition. Using the results of our CRISPR screens, we predicted drug sensitivity for patients and cell lines based on gene expression profiles. These predictions could be clinically useful for treatment selection.

genomics↗

Dynamics of microRNA expression during mouse prenatal development

MicroRNAs (miRNAs) play a critical role as post-transcriptional regulators of gene expression. The ENCODE project profiled the expression of miRNAs in a comprehensive set of tissues during a time-course of mouse embryonic development and captured the expression dynamics of 785 miRNAs. We found distinct tissue and developmental stage specific miRNA expression clusters, with an overall pattern of increasing tissue specific expression as development proceeds. Comparative analysis of conserved miRNAs in mouse and human revealed stronger clustering of expression patterns by tissue types rather than by species. An analysis of messenger RNA gene expression clusters compared with miRNA expression clusters identifies the potential role of specific miRNA expression clusters in suppressing the expression of mRNAs specific to other developmental programs in the tissue where these microRNAs are expressed during embryonic development. Our results provide the most comprehensive timecourse of miRNA expression as an integrated part of the ENCODE reference dataset for mouse embryonic development.

genomics↗

Occupancy patterns of 208 DNA-associated proteins in a single human cell type

Genome-wide occupancy maps of transcriptional regulators are important for understanding gene regulation and its effects on diverse biological processes, but only a small fraction of the >1,600 transcription factors (TFs) encoded in the human genome has been assayed. Here we present data and analyses of ChIP-seq experiments for 208 DNA-associated proteins (DAPs) in the HepG2 hepatocellular carcinoma line, spanning nearly a quarter of its expressed TFs, transcriptional co-factors, and chromatin regulator proteins. The DAP binding profiles classify into major groups associated predominantly with promoters or enhancers, or with both. We confirm and expand the current catalog of DNA sequence motifs; 77 factors showed similar motifs to those previously described using in vivo and/or in vitro methods, and 17 yielded novel motifs. We also describe motifs corresponding to other TFs that co-enrich with the primary ChIP target. FOX family motifs are, for example, significantly enriched in ChIP-seq peaks of 37 other DAPs. We show that promoters and enhancers can be discriminated based on motif content and occupancy patterns. This large catalog reveals High Occupancy Target (HOT) regions at which many DAPs associate, although each contains motifs for only a minority of the numerous associated DAPs. These analyses provide a deeper and more complete overview of the gene regulatory networks that define this cell type.

genomics↗

De novo mutations in the GTP/GDP-binding region of RALA, a RAS-like small GTPase, cause intellectual disability and developmental delay

Mutations that alter signaling of RAS/MAPK-family proteins give rise to a group of Mendelian diseases known as RASopathies, but the matrix of genotype-phenotype relationships is still incomplete, in part because there are many RAS-related proteins, and in part because the phenotypic consequences may be variable and/or pleiotropic. Here, we describe a cohort of ten cases, drawn from six clinical sites and over 16,000 sequenced probands, with de novo protein-altering variation in RALA, a RAS-like small GTPase. All probands present with speech and motor delays, and most have intellectual disability, low weight, short stature, and facial dysmorphism. The observed rate of de novo RALA variants in affected probands is significantly higher (p=4.93 x 10-11) than expected from the estimated mutation rate. Further, all de novo variants described here affect conserved residues within the GTP/GDP-binding region of RALA; in fact, six alleles arose at only two codons, Val25 and Lys128. We directly assayed GTP hydrolysis and RALA effector-protein binding, and all but one tested variant significantly reduced both activities. The one exception, S157A, reduced GTP hydrolysis but significantly increased RALA-effector binding, an observation similar to that seen for oncogenic RAS variants. These results show the power of data sharing for the interpretation and analysis of rare variation, expand the spectrum of molecular causes of developmental disability to include RALA, and provide additional insight into the pathogenesis of human disease caused by mutations in small GTPases.\n\nAuthor SummaryWhile many causes of developmental disabilities have been identified, a large number of affected children cannot be diagnosed despite extensive medical testing. Previously unknown genetic factors are likely to be the culprits in many of these cases. Using DNA sequencing, and by sharing information among many doctors and researchers, we have identified a set of individuals with developmental problems who all have changes to the same gene, RALA. The affected individuals all have similar symptoms, including intellectual disability, speech delay (or no speech), and problems with motor skills like walking. In nearly all of these cases (10 of 11), the genetic change found in the child was not inherited from either parent. The locations and biological properties of these changes suggest that they are likely to disrupt the normal functions of RALA and cause significant health problems. We also performed experiments to show that the genetic changes found in these individuals alter two key functions of RALA. Together, we have provided evidence that genetic changes in RALA can cause DD/ID. These results will allow doctors and researchers to identify additional children with the same condition, providing a clinical diagnosis to these families and leading to new research opportunities.

genetics↗

Regional collapsing of rare variation implicates specific genic regions in ALS

Large-scale sequencing efforts in amyotrophic lateral sclerosis (ALS) have implicated novel genes using gene-based collapsing methods. However, pathogenic mutations may be concentrated in specific genic regions. To address this, we developed two collapsing strategies, one focuses rare variation collapsing on homology-based protein domains as the unit for collapsing and another gene-level approach that, unlike standard methods, leverages existing evidence of purifying selection against missense variation on said domains. The application of these two collapsing methods to 3,093 ALS cases and 8,186 controls of European ancestry, and also 3,239 cases and 11,808 controls of diversified populations, pinpoints risk regions of ALS genes including SOD1, NEK1, TARDBP and FUS. While not clearly implicating novel ALS genes, the new analyses not only pinpoint risk regions in known genes but also highlight candidate genes as well.

genetics↗

CRISPR/Cas9-targeted removal of unwanted sequences from small-RNA sequencing libraries

In small RNA (smRNAs) sequencing studies, highly abundant molecules such as adapter dimer products and tissue-specific microRNAs (miRNAs) inhibit accurate quantification of lowly expressed species. We previously developed a method to selectively deplete highly abundant miRNAs. However, this method does not deplete adapter dimer ligation products that, unless removed by gelseparation, comprise most of the library. Here, we have adapted and modified recently described methods for CRISPR/Cas9-based Depletion of Abundant Species by Hybridization (\"DASH\") to smRNA-seq, which we have termed miRNA and Adapter Dimer - DASH (MAD-DASH). In MAD-DASH, Cas9 is complexed with sgRNAs targeting adapter dimer ligation products, alongside highly expressed tissue-specific smRNAs, for cleavage in vitro. This process dramatically reduces (>90%) adapter dimer and targeted smRNA sequences, is multiplexable, shows minimal off-target effects, improves the quantification of lowly expressed miRNAs from human plasma and tissue derived RNA, and obviates the need for gel-separation, greatly increasing sample throughput. Additionally, the method is fully customizable to other smRNA-seq preparation methods. Like depletion of ribosomal RNA for mRNA-seq and mitochondrial DNA for ATAC-seq, our method allows for greater proportional read-depth of nontargeted sequences.

genomics↗

powerTCR: a model-based approach to comparative analysis of the clone size distribution of the T cell receptor repertoire

Sequencing of the T cell receptor repertoire is a powerful tool for deeper study of immune response, but the unique structure of this type of data makes its meaningful quantification challenging. We introduce a new method, the Gamma-GPD spliced threshold model, to address this difficulty. This biologically interpretable model captures the distribution of the TCR repertoire, demonstrates stability across varying sequencing depths, and permits comparative analysis across any number of sampled individuals. We apply our method to several datasets and obtain insights regarding the differentiating features in the T cell receptor repertoire among sampled individuals across conditions. We have implemented our method in the open-source R package powerTCR.\n\nAuthor summaryA more detailed understanding of the immune response can unlock critical information concerning diagnosis and treatment of disease. Here, in particular, we study T cells through T cell receptor sequencing, as T cells play a vital role in immune response. One important feature of T cell receptor sequencing data is the frequencies of each receptor in a given sample. These frequencies harbor global information about the landscape of the immune response. We introduce a flexible method that extracts this information by modeling the distribution of these frequencies, and show that it can be used to quantify differences in samples from individuals of different biological conditions.

immunology↗

Genomic sequencing identifies secondary findings in a cohort of parent study participants

PURPOSEClinically relevant secondary variants were identified in parents enrolled with a child with developmental delay and intellectual disability.\n\nMETHODSExome/genome sequencing and analysis of 789 unaffected parents was performed.\n\nRESULTSPathogenic/likely pathogenic variants were identified in 21 genes within 25 individuals (3.2%), with 11 (1.4%) participants harboring variation in a gene defined as clinically actionable by the ACMG. Of the 25 individuals, five carried a variant consistent with a previous clinical diagnosis, thirteen were not previously diagnosed but had symptoms or family history with probable association with the detected variant, and seven reported no symptoms or family history of disease. A limited carrier screen was performed yielding 15 variants in 48 (6.1%) parents. Parents were also analyzed as mate-pairs to identify cases in which both parents were carriers for the same recessive disease; this led to one finding in ATP7B. Four participants had two findings (one carrier and one non-carrier variant). In total, 71 of the 789 enrolled parents (9.0%) received secondary findings.\n\nCONCLUSIONWe provide an overview of the rates and types of clinically relevant secondary findings, which may be useful in the design, and implementation of research and clinical sequencing efforts to identify such findings.

genomics↗

A genome-wide interactome of DNA-associated proteins in the human liver

Large-scale efforts like the Encyclopedia of DNA Elements (ENCODE) Project have made tremendous progress in cataloging the genomic binding patterns of DNA-associated proteins (DAPs), such as transcription factors (TFs). However most chromatin immunoprecipitation-sequencing (ChIP-seq) analyses have focused on a few immortalized cell lines whose activities and physiology deviate in important ways from endogenous cells and tissues. Consequently, binding data from primary human tissue are essential to improving our understanding of in vivo gene regulation. Here we analyze ChIP-seq data for 20 DAPs assayed in two healthy human liver tissue samples, identifying more than 450,000 binding sites. We integrated binding data with transcriptome and phased whole genome data to investigate allelic DAP interactions and the impact of heterozygous sequence variation on the expression of neighboring genes. We find our tissue-based dataset demonstrates binding patterns more consistent with liver biology than cell lines, and describe uses of these data to better prioritize impactful non-coding variation. Collectively, our rich dataset offers novel insights into genome function in healthy liver tissue and provides a valuable research resource for assessing disease-related disruptions.

genomics↗

Extremely rare variants reveal patterns of germline mutation rate heterogeneity in humans

A detailed understanding of the genome-wide variability of single-nucleotide germline mutation rates is essential to studying human genome evolution. Here we use [~]36 million singleton variants from 3,560 whole-genome sequences to infer fine-scale patterns of mutation rate heterogeneity. Mutability is jointly affected by adjacent nucleotide context and diverse genomic features of the surrounding region, including histone modifications, replication timing, and recombination rate, sometimes suggesting specific mutagenic mechanisms. Remarkably, GC content, DNase hypersensitivity, CpG islands, and H3K36 trimethylation are associated with both increased and decreased mutation rates depending on nucleotide context. We validate these estimated effects in an independent dataset of [~]46,000 de novo mutations, and confirm our estimates are more accurate than previously published estimates based on ancestrally older variants without considering genomic features. Our results thus provide the most refined portrait to date of the factors contributing to genome-wide variability of the human germline mutation rate.

genomics↗

INFERENCE OF CELL TYPE COMPOSITION FROM HUMAN BRAIN TRANSCRIPTOMIC DATASETS ILLUMINATES THE EFFECTS OF AGE, MANNER OF DEATH, DISSECTION, AND PSYCHIATRIC DIAGNOSIS

Psychiatric illness is unlikely to arise from pathology occurring uniformly across all cell types in affected brain regions. Despite this, transcriptomic analyses of the human brain have typically been conducted using macro-dissected tissue due to the difficulty of performing single-cell type analyses with donated post-mortem brains. To address this issue statistically, we compiled a database of several thousand transcripts that were specifically-enriched in one of 10 primary cortical cell types in previous publications. Using this database, we predicted the relative cell type composition for 833 human cortical samples using microarray or RNA-Seq data from the Pritzker Consortium (GSE92538) or publicly-available databases (GSE53987, GSE21935, GSE21138, CommonMind Consortium). These predictions were generated by averaging normalized expression levels across transcripts specific to each cell type using our R-package BrainInABlender (validated and publicly-released: https://github.com/hagenaue/BrainInABlender). Using this method, we found that the principal components of variation in the datasets strongly correlated with the neuron to glia ratio of the samples.\n\nThis variability was not simply due to dissection - the relative balance of brain cell types appeared to be influenced by a variety of demographic, pre- and post-mortem variables. Prolonged hypoxia around the time of death predicted increased astrocytic and endothelial gene expression, illustrating vascular upregulation. Aging was associated with decreased neuronal gene expression. Red blood cell gene expression was reduced in individuals who died following systemic blood loss. Subjects with Major Depressive Disorder had decreased astrocytic gene expression, mirroring previous morphometric observations. Subjects with Schizophrenia had reduced red blood cell gene expression, resembling the hypofrontality detected in fMRI experiments. Finally, in datasets containing samples with especially variable cell content, we found that controlling for predicted sample cell content while evaluating differential expression improved the detection of previously-identified psychiatric effects. We conclude that accounting for cell type can greatly improve the interpretability of transcriptomic data.

bioinformatics↗