Pycallingcards: an integrated environment for visualizing, analyzing, and interpreting Calling Cards data.

MOTIVATION: Unraveling the transcriptional programs that control how cells divide, differentiate, and respond to their environments requires a precise understanding of transcription factors' (TFs) DNA-binding activities. Calling cards (CC) technology uses transposons to capture transient TF binding events at one instant in time and then read them out at a later time. This methodology can also be used to simultaneously measure TF binding and mRNA expression from single-cell CC and to record and integrate TF binding events across time in any cell type of interest without the need for purification. Despite these advantages, there has been a lack of dedicated bioinformatics tools for the detailed analysis of CC data. RESULTS: We introduce Pycallingcards, a comprehensive Python module specifically designed for the analysis of single-cell and bulk CC data across multiple species. Pycallingcards introduces two innovative peak callers, CCcaller and MACCs, enhancing the accuracy and speed of pinpointing TF binding sites from CC data. Pycallingcards offers a fully integrated environment for data visualization, motif finding, and comparative analysis with RNA-seq and ChIP-seq datasets. To illustrate its practical application, we have reanalyzed previously published mouse cortex and glioblastoma datasets. This analysis revealed novel cell-type-specific binding sites and potential sex-linked TF regulators, furthering our understanding of TF binding and gene expression relationships. Thus, Pycallingcards, with its user-friendly design and seamless interface with the Python data science ecosystem, stands as a critical tool for advancing the analysis of TF functions via CC data. AVAILABILITY AND IMPLEMENTATION: Pycallingcards can be accessed on the GitHub repository: https://github.com/The-Mitra-Lab/pycallingcards.

Calling Cards: A Customizable Platform to Longitudinally Record Protein-DNA Interactions Over Time in Cells and Tissues.

Calling Cards is a platform technology to record a cumulative history of transient protein-DNA interactions in the genome of genetically targeted cell types. The record of these interactions is recovered by next-generation sequencing. Compared with other genomic assays, readouts of which provide a snapshot at the time of harvest, Calling Cards enables correlation of historical molecular states to eventual outcomes or phenotypes. To achieve this, Calling Cards uses the piggyBac transposase to insert self-reporting transposon "Calling Cards" into the genome, leaving permanent marks at interaction sites. Calling Cards can be deployed in a variety of in vitro and in vivo biological systems to study gene regulatory networks involved in development, aging, and disease. Out of the box, it assesses enhancer usage but can be adapted to profile-specific transcription factor (TF) binding with custom TF-piggyBac fusion proteins. The Calling Cards workflow has five main stages: delivery of Calling Cards reagents, sample preparation, library preparation, sequencing, and data analysis. Here, we first present a comprehensive guide for experimental design, reagent selection, and optional customization of the platform to study additional TFs. Then, we provide an updated protocol for the five steps, using reagents that improve throughput and decrease costs, including an overview of a newly deployed computational pipeline. This protocol is designed for users with basic molecular biology experience to process samples into sequencing libraries in 2 days. Familiarity with bioinformatic analysis and command line tools is required to set up the pipeline in a high-performance computing environment and to conduct downstream analyses. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Preparation and delivery of Calling Cards reagents Support Protocol 1: Next-generation sequencing quantification of barcode distribution within self-reporting transposon plasmid pool and adeno-associated virus genome Basic Protocol 2: Sample collection and RNA purification Support Protocol 2: Library density quantitative PCR Basic Protocol 3: Sequencing library preparation Basic Protocol 4: Library pooling and sequencing Basic Protocol 5: Data analysis.

Epigenetic regulation of hybrid epithelial-mesenchymal cell states in cancer.

Epithelial-to-mesenchymal transition (EMT) is a process by which cells lose their epithelial characteristics and gain mesenchymal phenotypes. In cancer, EMT is thought to drive tumor invasion and metastasis. Recent efforts to understand EMT biology have uncovered that cells undergoing EMT attain a spectrum of intermediate "hybrid E/M" states, which exist along an epithelial-mesenchymal continuum. Here, we summarize recent studies characterizing the epigenetic drivers of hybrid E/M states. We focus on the histone-modification writers, erasers, and readers that assist or oppose the canonical hybrid E/M transcription factors that modulate hybrid E/M state transitions. We also examine the role of chromatin remodelers and DNA methylation in hybrid E/M states. Finally, we highlight the challenges of targeting hybrid E/M pharmacologically, and we propose future directions that might reveal the specific and targetable mechanisms by which hybrid E/M drives metastasis in patients.

Brd4-bound enhancers drive cell-intrinsic sex differences in glioblastoma.

Sex can be an important determinant of cancer phenotype, and exploring sex-biased tumor biology holds promise for identifying novel therapeutic targets and new approaches to cancer treatment. In an established isogenic murine model of glioblastoma (GBM), we discovered correlated transcriptome-wide sex differences in gene expression, H3K27ac marks, large Brd4-bound enhancer usage, and Brd4 localization to Myc and p53 genomic binding sites. These sex-biased gene expression patterns were also evident in human glioblastoma stem cells (GSCs). These observations led us to hypothesize that Brd4-bound enhancers might underlie sex differences in stem cell function and tumorigenicity in GBM. We found that male and female GBM cells exhibited sex-specific responses to pharmacological or genetic inhibition of Brd4. Brd4 knockdown or pharmacologic inhibition decreased male GBM cell clonogenicity and in vivo tumorigenesis while increasing both in female GBM cells. These results were validated in male and female patient-derived GBM cell lines. Furthermore, analysis of the Cancer Therapeutic Response Portal of human GBM samples segregated by sex revealed that male GBM cells are significantly more sensitive to BET (bromodomain and extraterminal) inhibitors than are female cells. Thus, Brd4 activity is revealed to drive sex differences in stem cell and tumorigenic phenotypes, which can be abrogated by sex-specific responses to BET inhibition. This has important implications for the clinical evaluation and use of BET inhibitors.

Human L1 Transposition Dynamics Unraveled with Functional Data Analysis.

Long INterspersed Elements-1 (L1s) constitute >17% of the human genome and still actively transpose in it. Characterizing L1 transposition across the genome is critical for understanding genome evolution and somatic mutations. However, to date, L1 insertion and fixation patterns have not been studied comprehensively. To fill this gap, we investigated three genome-wide data sets of L1s that integrated at different evolutionary times: 17,037 de novo L1s (from an L1 insertion cell-line experiment conducted in-house), and 1,212 polymorphic and 1,205 human-specific L1s (from public databases). We characterized 49 genomic features-proxying chromatin accessibility, transcriptional activity, replication, recombination, etc.-in the ±50 kb flanks of these elements. These features were contrasted between the three L1 data sets and L1-free regions using state-of-the-art Functional Data Analysis statistical methods, which treat high-resolution data as mathematical functions. Our results indicate that de novo, polymorphic, and human-specific L1s are surrounded by different genomic features acting at specific locations and scales. This led to an integrative model of L1 transposition, according to which L1s preferentially integrate into open-chromatin regions enriched in non-B DNA motifs, whereas they are fixed in regions largely free of purifying selection-depleted of genes and noncoding most conserved elements. Intriguingly, our results suggest that L1 insertions modify local genomic landscape by extending CpG methylation and increasing mononucleotide microsatellite density. Altogether, our findings substantially facilitate understanding of L1 integration and fixation preferences, pave the way for uncovering their role in aging and cancer, and inform their use as mutagenesis tools in genetic studies.

Self-Reporting Transposons Enable Simultaneous Readout of Gene Expression and Transcription Factor Binding in Single Cells.

Cellular heterogeneity confounds in situ assays of transcription factor (TF) binding. Single-cell RNA sequencing (scRNA-seq) deconvolves cell types from gene expression, but no technology links cell identity to TF binding sites (TFBS) in those cell types. We present self-reporting transposons (SRTs) and use them in single-cell calling cards (scCC), a novel assay for simultaneously measuring gene expression and mapping TFBS in single cells. The genomic locations of SRTs are recovered from mRNA, and SRTs deposited by exogenous, TF-transposase fusions can be used to map TFBS. We then present scCC, which map SRTs from scRNA-seq libraries, simultaneously identifying cell types and TFBS in those same cells. We benchmark multiple TFs with this technique. Next, we use scCC to discover BRD4-mediated cell-state transitions in K562 cells. Finally, we map BRD4 binding sites in the mouse cortex at single-cell resolution, establishing a new method for studying TF biology in situ.

A viral toolkit for recording transcription factor-DNA interactions in live mouse tissues.

Transcription factors (TFs) enact precise regulation of gene expression through site-specific, genome-wide binding. Common methods for TF-occupancy profiling, such as chromatin immunoprecipitation, are limited by requirement of TF-specific antibodies and provide only end-point snapshots of TF binding. Alternatively, TF-tagging techniques, in which a TF is fused to a DNA-modifying enzyme that marks TF-binding events across the genome as they occur, do not require TF-specific antibodies and offer the potential for unique applications, such as recording of TF occupancy over time and cell type specificity through conditional expression of the TF-enzyme fusion. Here, we create a viral toolkit for one such method, calling cards, and demonstrate that these reagents can be delivered to the live mouse brain and used to report TF occupancy. Further, we establish a Cre-dependent calling cards system and, in proof-of-principle experiments, show utility in defining cell type-specific TF profiles and recording and integrating TF-binding events across time. This versatile approach will enable unique studies of TF-mediated gene regulation in live animal models.

Transposase mapping identifies the genomic targets of BAP1 in uveal melanoma.

BACKGROUND: BAP1 is a histone deubiquitinase that acts as a tumor and metastasis suppressor associated with disease progression in human cancer. We have used the "Calling Card System" of transposase-directed transposon insertion mapping to identify the genomic targets of BAP1 in uveal melanoma (UM). This system was developed to identify the genomic loci visited by transcription factors that bind directly to DNA; our study is the first use of the system with a chromatin-remodeling factor that binds to histones but does not interact directly with DNA. METHODS: The transposase piggyBac (PBase) was fused to BAP1 and expressed in OCM-1A UM cells. The insertion of transposons near BAP1 binding sites in UM cells were identified by genomic sequencing. We also examined RNA expression in the same OCM-1A UM cells after BAP1 depletion to identify BAP1 binding sites associated with BAP1-responsive genes. Sets of significant genes were analyzed for common pathways, transcription factor binding sites, and ability to identify molecular tumor classes. RESULTS: We found a strong correlation between multiple calling-card transposon insertions targeted by BAP1-PBase and BAP1-responsive expression of adjacent genes. BAP1-bound genomic loci showed narrow distributions of insertions and were near transcription start sites, consistent with recruitment of BAP1 to these sites by specific DNA-binding proteins. Sequence consensus analysis of BAP1-bound sites showed enrichment of motifs specific for YY1, NRF1 and Ets transcription factors, which have been shown to interact with BAP1 in other cell types. Further, a subset of the BAP1 genomic target genes was able to discriminate aggressive tumors in published gene expression data from primary UM tumors. CONCLUSIONS: The calling card methodology works equally well for chromatin regulatory factors that do not interact directly with DNA as for transcription factors. This technique has generated a new and expanded list of BAP1 targets in UM that provides important insight into metastasis pathways and identifies novel potential therapeutic targets.

A role for genetic susceptibility in sporadic focal segmental glomerulosclerosis.

Focal segmental glomerulosclerosis (FSGS) is a syndrome that involves kidney podocyte dysfunction and causes chronic kidney disease. Multiple factors including chemical toxicity, inflammation, and infection underlie FSGS; however, highly penetrant disease genes have been identified in a small fraction of patients with a family history of FSGS. Variants of apolipoprotein L1 (APOL1) have been linked to FSGS in African Americans with HIV or hypertension, supporting the proposal that genetic factors enhance FSGS susceptibility. Here, we used sequencing to investigate whether genetics plays a role in the majority of FSGS cases that are identified as primary or sporadic FSGS and have no known cause. Given the limited number of biopsy-proven cases with ethnically matched controls, we devised an analytic strategy to identify and rank potential candidate genes and used an animal model for validation. Nine candidate FSGS susceptibility genes were identified in our patient cohort, and three were validated using a high-throughput mouse method that we developed. Specifically, we introduced a podocyte-specific, doxycycline-inducible transactivator into a murine embryonic stem cell line with an FSGS-susceptible genetic background that allows shRNA-mediated targeting of candidate genes in the adult kidney. Our analysis supports a broader role for genetic susceptibility of both sporadic and familial cases of FSGS and provides a tool to rapidly evaluate candidate FSGS-associated genes.

Novel markers of gonadectomy-induced adrenocortical neoplasia in the mouse and ferret.

Gonadectomy (GDX) induces sex steroid-producing adrenocortical tumors in certain mouse strains and in the domestic ferret. Transcriptome analysis and DNA methylation mapping were used to identify novel genetic and epigenetic markers of GDX-induced adrenocortical neoplasia in female DBA/2J mice. Markers were validated using a combination of laser capture microdissection, quantitative RT-PCR, in situ hybridization, and immunohistochemistry. Microarray expression profiling of whole adrenal mRNA from ovariectomized vs. intact mice demonstrated selective upregulation of gonadal-like genes including Spinlw1 and Insl3 in GDX-induced adrenocortical tumors of the mouse. A complementary candidate gene approach identified Foxl2 as another gonadal-like marker expressed in GDX-induced neoplasms of the mouse and ferret. That both "male-specific" (Spinlw1) and "female-specific" (Foxl2) markers were identified is noteworthy and implies that the neoplasms exhibit mixed characteristics of male and female gonadal somatic cells. Genome-wide methylation analysis showed that two genes with hypomethylated promoters, Igfbp6 and Foxs1, are upregulated in GDX-induced adrenocortical neoplasms. These new genetic and epigenetic markers may prove useful for studies of steroidogenic cell development and for diagnostic testing.

Toying with fate: Redirecting the differentiation of adrenocortical progenitor cells into gonadal-like tissue.

Cell fate decisions are integral to zonation and remodeling of the adrenal cortex. Animal models exhibiting ectopic differentiation of gonadal-like cells in the adrenal cortex can shed light on the molecular mechanisms regulating steroidogenic cell fate. In one such model, prepubertal gonadectomy (GDX) of mice triggers the formation of adrenocortical neoplasms that resemble luteinized ovarian stroma. Transcriptomic analysis and genome-wide DNA methylation mapping have identified genetic and epigenetic markers of GDX-induced adrenocortical neoplasia. Members of the GATA transcription factor family have emerged as key regulators of cell fate in this model. Expression of Gata4 is pivotal for the accumulation of gonadal-like cells in the adrenal glands of gonadectomized mice, whereas expression of Gata6 limits the spontaneous and GDX-induced differentiation of gonadal-like cells in the adrenal cortex. Additionally, Gata6 is essential for proper development of the adrenal X-zone, a layer analogous to the fetal zone of the human adrenal cortex. The relevance of these observations to developmental signaling pathways in the adrenal cortex, to other animal models of altered adrenocortical cell fate, and to human diseases is discussed.

PDE7B is a novel, prognostically significant mediator of glioblastoma growth whose expression is regulated by endothelial cells.

Cell-cell interactions between tumor cells and constituents of their microenvironment are critical determinants of tumor tissue biology and therapeutic responses. Interactions between glioblastoma (GBM) cells and endothelial cells (ECs) establish a purported cancer stem cell niche. We hypothesized that genes regulated by these interactions would be important, particularly as therapeutic targets. Using a computational approach, we deconvoluted expression data from a mixed physical co-culture of GBM cells and ECs and identified a previously undescribed upregulation of the cAMP specific phosphodiesterase PDE7B in GBM cells in response to direct contact with ECs. We further found that elevated PDE7B expression occurs in most GBM cases and has a negative effect on survival. PDE7B overexpression resulted in the expansion of a stem-like cell subpopulation in vitro and increased tumor growth and aggressiveness in an in vivo intracranial GBM model. Collectively these studies illustrate a novel approach for studying cell-cell interactions and identifying new therapeutic targets like PDE7B in GBM.

Mutation and expression analysis in medulloblastoma yields prognostic variants and a putative mechanism of disease for i17q tumors.

Current consensus identifies four molecular subtypes of medulloblastoma (MB): WNT, sonic hedgehog (SHH), and groups "3/C" and "4/D". Group 4 is not well characterized, but harbors the most frequently observed chromosomal abnormality in MB, i17q, whose presence may confer a worse outcome. Recent publications have identified mutations in chromatin remodeling genes that may be overrepresented in this group, suggesting a biological role for these genes in i17q. This work seeks to explore the pathology that underlies i17q in MB. Specifically, we examine the prognostic significance of the previously-identified gene mutations in an independent set of MBs as well as to examine biological relevance of these genes and related pathways by gene expression profiling. The previously-implicated p53 signaling pathway is also examined as a putative driver of i17q tumor oncogenesis. The data show gene mutations associated with i17q tumors in previous studies (KMD6A, ZMYM3, MLL3 and GPS2) were correlated with significantly worse outcomes despite not being specific to i17q in this set. Expression of these genes did not appear to underlie the biology of the molecular variants. TP53 expression was significantly reduced in i17q/group 4 tumors; this could not be accounted for by dosage effects alone. Expression of regulators and mediators of p53 signaling were significantly altered in i17q tumors. Our findings support that chromatin remodeling gene mutations are associated with significantly worse outcomes in MB but cannot explain outcomes or pathogenesis of i17q tumors. However, expression analyses of the p53 signaling pathway shows alterations in i17q tumors that cannot be explained by dosage effects and is strongly suggestive of an oncogenic role.

Synonymous ABCA3 variants do not increase risk for neonatal respiratory distress syndrome.

OBJECTIVE: To determine whether synonymous variants in the adenosine triphosphate-binding cassette A3 transporter (ABCA3) gene increase the risk for neonatal respiratory distress syndrome (RDS) in term and late preterm infants of European and African descent. STUDY DESIGN: Using next-generation pooled sequencing of race-stratified DNA samples from infants of European and African descent at ≥34 weeks gestation with and without RDS (n = 503), we scanned all exons of ABCA3, validated each synonymous variant with an independent genotyping platform, and evaluated race-stratified disease risk associated with common synonymous variants and collapsed frequencies of rare synonymous variants. RESULTS: The synonymous ABCA3 variant frequency spectrum differs between infants of European descent and those of African descent. Using in silico prediction programs and statistical strategies, we found no potentially disruptive synonymous ABCA3 variants or evidence of selection pressure. Individual common synonymous variants and collapsed frequencies of rare synonymous variants did not increase disease risk in term and late-preterm infants of European or African descent. CONCLUSION: In contrast to rare, nonsynonymous ABCA3 mutations, synonymous ABCA3 variants do not increase the risk for neonatal RDS among term and late-preterm infants of European or African descent.

Validation of a next-generation sequencing assay for clinical molecular oncology.

Currently, oncology testing includes molecular studies and cytogenetic analysis to detect genetic aberrations of clinical significance. Next-generation sequencing (NGS) allows rapid analysis of multiple genes for clinically actionable somatic variants. The WUCaMP assay uses targeted capture for NGS analysis of 25 cancer-associated genes to detect mutations at actionable loci. We present clinical validation of the assay and a detailed framework for design and validation of similar clinical assays. Deep sequencing of 78 tumor specimens (≥ 1000× average unique coverage across the capture region) achieved high sensitivity for detecting somatic variants at low allele fraction (AF). Validation revealed sensitivities and specificities of 100% for detection of single-nucleotide variants (SNVs) within coding regions, compared with SNP array sequence data (95% CI = 83.4-100.0 for sensitivity and 94.2-100.0 for specificity) or whole-genome sequencing (95% CI = 89.1-100.0 for sensitivity and 99.9-100.0 for specificity) of HapMap samples. Sensitivity for detecting variants at an observed 10% AF was 100% (95% CI = 93.2-100.0) in HapMap mixes. Analysis of 15 masked specimens harboring clinically reported variants yielded concordant calls for 13/13 variants at AF of ≥ 15%. The WUCaMP assay is a robust and sensitive method to detect somatic variants of clinical significance in molecular oncology laboratories, with reduced time and cost of genetic analysis allowing for strategic patient management.

Clinical genomicist workstation.

The use of NextGen Sequencing clinically necessitates the need for informatics tools that support the complete workflow from sample accessioning to data analysis and reporting. To address this need we have developed Clinical Genomicist Workstation (CGW). CGW is a secure, n-tiered application where web browser submits requests to application servers that persist the data in a relational database. CGW is used by Washington University Genomic and Pathology Services for clinical genomic testing of many cancers. CGW has been used to accession, analyze and sign out over 409 cases since November, 2011. There are 22 ordering oncologists and 7 clinical genomicists that use the CGW. In summary, CGW a 'soup-to-nuts' solution to track, analyze, interpret, and report clinical genomic diagnostic tests.

Laser capture microdissection-reduced representation bisulfite sequencing (LCM-RRBS) maps changes in DNA methylation associated with gonadectomy-induced adrenocortical neoplasia in the mouse.

DNA methylation is a mechanism for long-term transcriptional regulation and is required for normal cellular differentiation. Failure to properly establish or maintain DNA methylation patterns leads to cell dysfunction and diseases such as cancer. Identifying DNA methylation signatures in complex tissues can be challenging owing to inaccurate cell enrichment methods and low DNA yields. We have developed a technique called laser capture microdissection-reduced representation bisulfite sequencing (LCM-RRBS) for the multiplexed interrogation of the DNA methylation status of cytosine-guanine dinucleotide islands and promoters. LCM-RRBS accurately and reproducibly profiles genome-wide methylation of DNA extracted from microdissected fresh frozen or formalin-fixed paraffin-embedded tissue samples. To demonstrate the utility of LCM-RRBS, we characterized changes in DNA methylation associated with gonadectomy-induced adrenocortical neoplasia in the mouse. Compared with adjacent normal tissue, the adrenocortical tumors showed reproducible gains and losses of DNA methylation at genes involved in cell differentiation and organ development. LCM-RRBS is a rapid, cost-effective, and sensitive technique for analyzing DNA methylation in heterogeneous tissues and will facilitate the investigation of DNA methylation in cancer and organ development.

Single ABCA3 mutations increase risk for neonatal respiratory distress syndrome.

BACKGROUND AND OBJECTIVE: Neonatal respiratory distress syndrome (RDS) due to pulmonary surfactant deficiency is heritable, but common variants do not fully explain disease heritability. METHODS: Using next-generation, pooled sequencing of race-stratified DNA samples from infants ≥34 weeks' gestation with and without RDS (n = 513) and from a Missouri population-based cohort (n = 1066), we scanned all exons of 5 surfactant-associated genes and used in silico algorithms to identify functional mutations. We validated each mutation with an independent genotyping platform and compared race-stratified, collapsed frequencies of rare mutations by gene to investigate disease associations and estimate attributable risk. RESULTS: Single ABCA3 mutations were overrepresented among European-descent RDS infants (14.3% of RDS vs 3.7% of non-RDS; P = .002) but were not statistically overrepresented among African-descent RDS infants (4.5% of RDS vs 1.5% of non-RDS; P = .23). In the Missouri population-based cohort, 3.6% of European-descent and 1.5% of African-descent infants carried a single ABCA3 mutation. We found no mutations among the RDS infants and no evidence of contribution to population-based disease burden for SFTPC, CHPT1, LPCAT1, or PCYT1B. CONCLUSIONS: In contrast to lethal neonatal RDS resulting from homozygous or compound heterozygous ABCA3 mutations, single ABCA3 mutations are overrepresented among European-descent infants ≥34 weeks' gestation with RDS and account for ~10.9% of the attributable risk among term and late preterm infants. Although ABCA3 mutations are individually rare, they are collectively common among European- and African-descent individuals in the general population.

Detection of rare genomic variants from pooled sequencing using SPLINTER.

As DNA sequencing technology has markedly advanced in recent years(2), it has become increasingly evident that the amount of genetic variation between any two individuals is greater than previously thought(3). In contrast, array-based genotyping has failed to identify a significant contribution of common sequence variants to the phenotypic variability of common disease(4,5). Taken together, these observations have led to the evolution of the Common Disease / Rare Variant hypothesis suggesting that the majority of the "missing heritability" in common and complex phenotypes is instead due to an individual's personal profile of rare or private DNA variants(6-8). However, characterizing how rare variation impacts complex phenotypes requires the analysis of many affected individuals at many genomic loci, and is ideally compared to a similar survey in an unaffected cohort. Despite the sequencing power offered by today's platforms, a population-based survey of many genomic loci and the subsequent computational analysis required remains prohibitive for many investigators. To address this need, we have developed a pooled sequencing approach(1,9) and a novel software package(1) for highly accurate rare variant detection from the resulting data. The ability to pool genomes from entire populations of affected individuals and survey the degree of genetic variation at multiple targeted regions in a single sequencing library provides excellent cost and time savings to traditional single-sample sequencing methodology. With a mean sequencing coverage per allele of 25-fold, our custom algorithm, SPLINTER, uses an internal variant calling control strategy to call insertions, deletions and substitutions up to four base pairs in length with high sensitivity and specificity from pools of up to 1 mutant allele in 500 individuals. Here we describe the method for preparing the pooled sequencing library followed by step-by-step instructions on how to use the SPLINTER package for pooled sequencing analysis (http://www.ibridgenetwork.org/wustl/splinter). We show a comparison between pooled sequencing of 947 individuals, all of whom also underwent genome-wide array, at over 20kb of sequencing per person. Concordance between genotyping of tagged and novel variants called in the pooled sample were excellent. This method can be easily scaled up to any number of genomic loci and any number of individuals. By incorporating the internal positive and negative amplicon controls at ratios that mimic the population under study, the algorithm can be calibrated for optimal performance. This strategy can also be modified for use with hybridization capture or individual-specific barcodes and can be applied to the sequencing of naturally heterogeneous samples, such as tumor DNA.

Rare missense variants in CHRNB4 are associated with reduced risk of nicotine dependence.

Genome-wide association studies have identified common variation in the CHRNA5-CHRNA3-CHRNB4 and CHRNA6-CHRNB3 gene clusters that contribute to nicotine dependence. However, the role of rare variation in risk for nicotine dependence in these nicotinic receptor genes has not been studied. We undertook pooled sequencing of the coding regions and flanking sequence of the CHRNA5, CHRNA3, CHRNB4, CHRNA6 and CHRNB3 genes in African American and European American nicotine-dependent smokers and smokers without symptoms of dependence. Carrier status of individuals harboring rare missense variants at conserved sites in each of these genes was then compared in cases and controls to test for an association with nicotine dependence. Missense variants at conserved residues in CHRNB4 are associated with lower risk for nicotine dependence in African Americans and European Americans (AA P = 0.0025, odds-ratio (OR) = 0.31, 95% confidence-interval (CI) = 0.31-0.72; EA P = 0.023, OR = 0.69, 95% CI = 0.50-0.95). Furthermore, these individuals were found to smoke fewer cigarettes per day than non-carriers (AA P = 6.6 × 10(-5), EA P = 0.021). Given the possibility of stochastic differences in rare allele frequencies between groups replication of this association is necessary to confirm these findings. The functional effects of the two CHRNB4 variants contributing most to this association (T375I and T91I) and a missense variant in CHRNA3 (R37H) in strong linkage disequilibrium with T91I were examined in vitro. The minor allele of each polymorphism increased cellular response to nicotine (T375I P = 0.01, T91I P = 0.02, R37H P = 0.003), but the largest effect on in vitro receptor activity was seen in the presence of both CHRNB4 T91I and CHRNA3 R37H (P = 2 × 10(-6)).