Major Impacts of Widespread Structural Variation on Gene Expression and Crop Improvement in Tomato.

Structural variants (SVs) underlie important crop improvement and domestication traits. However, resolving the extent, diversity, and quantitative impact of SVs has been challenging. We used long-read nanopore sequencing to capture 238,490 SVs in 100 diverse tomato lines. This panSV genome, along with 14 new reference assemblies, revealed large-scale intermixing of diverse genotypes, as well as thousands of SVs intersecting genes and cis-regulatory regions. Hundreds of SV-gene pairs exhibit subtle and significant expression changes, which could broadly influence quantitative trait variation. By combining quantitative genetics with genome editing, we show how multiple SVs that changed gene dosage and expression levels modified fruit flavor, size, and production. In the last example, higher order epistasis among four SVs affecting three related transcription factors allowed introduction of an important harvesting trait in modern tomato. Our findings highlight the underexplored role of SVs in genotype-to-phenotype relationships and their widespread importance and utility in crop improvement.

Familial long-read sequencing increases yield of de novo mutations.

Studies of de novo mutation (DNM) have typically excluded some of the most repetitive and complex regions of the genome because these regions cannot be unambiguously mapped with short-read sequencing data. To better understand the genome-wide pattern of DNM, we generated long-read sequence data from an autism parent-child quad with an affected female where no pathogenic variant had been discovered in short-read Illumina sequence data. We deeply sequenced all four individuals by using three sequencing platforms (Illumina, Oxford Nanopore, and Pacific Biosciences) and three complementary technologies (Strand-seq, optical mapping, and 10X Genomics). Using long-read sequencing, we initially discovered and validated 171 DNMs across two children-a 20% increase in the number of de novo single-nucleotide variants (SNVs) and indels when compared to short-read callsets. The number of DNMs further increased by 5% when considering a more complete human reference (T2T-CHM13) because of the recovery of events in regions absent from GRCh38 (e.g., three DNMs in heterochromatic satellites). In total, we validated 195 de novo germline mutations and 23 potential post-zygotic mosaic mutations across both children; the overall true substitution rate based on this integrated callset is at least 1.41 × 10-8 substitutions per nucleotide per generation. We also identified six de novo insertions and deletions in tandem repeats, two of which represent structural variants. We demonstrate that long-read sequencing and assembly, especially when combined with a more complete reference genome, increases the number of DNMs by >25% compared to previous studies, providing a more complete catalog of DNM compared to short-read data alone.

Evaluating the quality of life impact of recurrent urinary tract infection: Validation and refinement of the Recurrent UTI Impact Questionnaire (RUTIIQ).

BACKGROUND AND AIMS: Recurrent urinary tract infection (rUTI) has significant negative consequences for a wide variety of quality of life (QoL) domains. Without adequate validation and assessment of the unique insights of people living with rUTI, clinical results cannot be fully understood. The Recurrent UTI Impact Questionnaire (RUTIIQ), a novel patient-reported outcome measure of rUTI psychosocial impact, has been robustly developed with extensive patient and clinician input to facilitate enhanced rUTI management and research. This study aimed to confirm the structural validity of the RUTIIQ, assessing its strength and bifactor model fit. METHODS: A sample of 389 adults experiencing rUTI (96.9% female, aged 18-87 years) completed an online cross-sectional survey comprising a demographic questionnaire and the RUTIIQ. A bifactor graded response model was fitted to the data, optimizing the questionnaire structure based on item fit, discrimination capability, local dependence, and differential item functioning. RESULTS: The final RUTIIQ demonstrated excellent bifactor model fit (RMSEA = 0.054, CFI = 0.99, SRMSR = 0.052), and mean-square fit indices indicated that all included items were productive for measurement (MNSQ = 0.52-1.41). The final questionnaire comprised an 18-item general "rUTI QoL impact" factor, and five subfactor domains measuring "personal wellbeing" (three items), "social wellbeing" (four items), "work and activity interference" (four items), "patient satisfaction" (four items), and "sexual wellbeing" (three items). Together, the general factor and five subfactors explained 81.6% of the common model variance. All factor loadings were greater than 0.30 and communalities greater than 0.60, indicating good model fit and structural validity. CONCLUSIONS: The 18-item RUTIIQ is a robust, patient-tested questionnaire with excellent psychometric properties, which capably assesses the patient experience of rUTI-related impact to QoL and healthcare satisfaction. Facilitating standardized patient monitoring and improved shared decision-making, the RUTIIQ delivers the unique opportunity to improve patient-centered care.

Comprehensive analysis of structural variants in breast cancer genomes using single-molecule sequencing.

Improved identification of structural variants (SVs) in cancer can lead to more targeted and effective treatment options as well as advance our basic understanding of the disease and its progression. We performed whole-genome sequencing of the SKBR3 breast cancer cell line and patient-derived tumor and normal organoids from two breast cancer patients using Illumina/10x Genomics, Pacific Biosciences (PacBio), and Oxford Nanopore Technologies (ONT) sequencing. We then inferred SVs and large-scale allele-specific copy number variants (CNVs) using an ensemble of methods. Our findings show that long-read sequencing allows for substantially more accurate and sensitive SV detection, with between 90% and 95% of variants supported by each long-read technology also supported by the other. We also report high accuracy for long reads even at relatively low coverage (25×-30×). Furthermore, we integrated SV and CNV data into a unifying karyotype-graph structure to present a more accurate representation of the mutated cancer genomes. We find hundreds of variants within known cancer-related genes detectable only through long-read sequencing. These findings highlight the need for long-read sequencing of cancer genomes for the precise analysis of their genetic instability.

Development and psychometric validation of a patient-reported outcome measure of recurrent urinary tract infection impact: the Recurrent UTI Impact Questionnaire.

PURPOSE: Recurrent urinary tract infection (rUTI) is a highly prevalent condition associated with significant poor quality of life outcomes. A patient-reported outcome measure (PROM) of rUTI-associated psychosocial impact is urgently required to supplement clinical evaluation and validate the challenges experienced by patients. This study therefore developed and validated the Recurrent UTI Impact Questionnaire (RUTIIQ). METHODS: A rigorous four-stage methodology was followed: (I) concept elicitation through a qualitative survey of the experiences of people with rUTI (N = 1983); (II) Delphi expert screening of the RUTIIQ with expert rUTI clinicians (N = 15); (III) one-to-one cognitive interviews with people experiencing rUTI (N = 28) to evaluate the comprehensiveness and comprehensibility of the RUTIIQ, and (IV) full pilot testing of the RUTIIQ with people experiencing rUTI (N = 240) to perform final item reduction and psychometric analysis. RESULTS: Exploratory factor analysis demonstrated a five-factor structure comprising: 'patient satisfaction', 'work and activity interference', 'social wellbeing', 'personal wellbeing', and 'sexual wellbeing', collectively accounting for 73.8% of the total variance in pilot scores. Results from expert clinicians and patients indicated strong item content validity (I-CVI > .75). The internal consistency and test-retest reliability of the RUTIIQ subscales were excellent (Cronbach's α = .81-.96, ICC = .66-.91), and construct validity was strong (Spearman's ρ > .69). CONCLUSION: The RUTIIQ is a 30-item questionnaire with excellent psychometric properties, assessing the patient-reported psychosocial impact of living with rUTI symptoms and pain. This new instrument delivers the unique opportunity to enhance patient-centred care through standardised observation and monitoring of rUTI patient outcomes. TRIAL REGISTRATION: This study was pre-registered with ClinicalTrials.gov (identifier: NCT05086900).

Complex rearrangements and oncogene amplifications revealed by long-read DNA and RNA sequencing of a breast cancer cell line.

The SK-BR-3 cell line is one of the most important models for HER2+ breast cancers, which affect one in five breast cancer patients. SK-BR-3 is known to be highly rearranged, although much of the variation is in complex and repetitive regions that may be underreported. Addressing this, we sequenced SK-BR-3 using long-read single molecule sequencing from Pacific Biosciences and develop one of the most detailed maps of structural variations (SVs) in a cancer genome available, with nearly 20,000 variants present, most of which were missed by short-read sequencing. Surrounding the important ERBB2 oncogene (also known as HER2), we discover a complex sequence of nested duplications and translocations, suggesting a punctuated progression. Full-length transcriptome sequencing further revealed several novel gene fusions within the nested genomic variants. Combining long-read genome and transcriptome sequencing enables an in-depth analysis of how SVs disrupt the genome and sheds new light on the complex mechanisms involved in cancer genome evolution.

Development of BET inhibitors as potential treatments for cancer: A search for structural diversity.

We describe our efforts to identify structurally diverse leads in the triazole-containing N1-carboline series of bromodomain and extra-terminal inhibitors. Replacement of the N5 "cap" phenyl moiety with various heteroaryls, coupled with additional modifications to the carboline core, provided analogs with similar potency, improved pharmacokinetic properties, and increased solubility compared to our backup lead, BMS-986225 (2). Rapid SAR exploration was enabled by a convergent, synthetic route. These efforts provided a potent BET inhibitor, 3-fluoropyridyl 12, that demonstrated robust efficacy in a multiple myeloma mouse tumor model at 1 mg/kg.

Development of BET inhibitors as potential treatments for cancer: A new carboline chemotype.

We describe our efforts to introduce structural diversity to a previously described triazole-containing N1-carboline series of bromodomain and extra-terminal (BET) inhibitors. N9 carbolines were designed to retain favorable binding interactions that the N1-carbolines possess. A convergent synthetic route enabled modifications to reduce clearance, enhance physicochemical properties, and improve the overall in vitro profile. This work led to the identification of a potent BET inhibitor, (S)-2-{8-fluoro-5-[(3-fluoropyridin-2-yl)(oxan-4-yl)methyl]-7-[4-(2H3)methyl-1-methyl-1H-1,2,3-triazol-5-yl]-5H-pyrido[3,2-b]indol-3-yl}propan-2-ol (10), a compound with enhanced oral exposure in mice. Subsequent evaluation in a mouse triple-negative breast cancer tumor model revealed efficacy at 4 mg/kg of N9-carboline 10.

Resensitizing daclatasvir-resistant hepatitis C variants by allosteric modulation of NS5A.

It is estimated that more than 170 million people are infected with hepatitis C virus (HCV) worldwide. Clinical trials have demonstrated that, for the first time in human history, the potential exists to eradicate a chronic viral disease using combination therapies that contain only direct-acting antiviral agents. HCV non-structural protein 5A (NS5A) is a multifunctional protein required for several stages of the virus replication cycle. NS5A replication complex inhibitors, exemplified by daclatasvir (DCV; also known as BMS-790052 and Daklinza), belong to the most potent class of direct-acting anti-HCV agents described so far, with in vitro activity in the picomolar (pM) to low nanomolar (nM) range. The potency observed in vitro has translated into clinical efficacy, with HCV RNA declining by ~3-4 log10 in infected patients after administration of single oral doses of DCV. Understanding the exceptional potency of DCV was a key objective of this study. Here we show that although DCV and an NS5A inhibitor analogue (Syn-395) are inactive against certain NS5A resistance variants, combinations of the pair enhance DCV potency by >1,000-fold, restoring activity to the pM range. This synergistic effect was validated in vivo using an HCV-infected chimaeric mouse model. The cooperative interaction of a pair of compounds suggests that NS5A protein molecules communicate with each other: one inhibitor binds to resistant NS5A, causing a conformational change that is transmitted to adjacent NS5As, resensitizing resistant NS5A so that the second inhibitor can act to restore inhibition. This unprecedented synergistic anti-HCV activity also enhances the resistance barrier of DCV, providing additional options for HCV combination therapy and new insight into the role of NS5A in the HCV replication cycle.

Mutations in the pancreatic secretory enzymes CPA1 and CPB1 are associated with pancreatic cancer.

To evaluate whether germline variants in genes encoding pancreatic secretory enzymes contribute to pancreatic cancer susceptibility, we sequenced the coding regions of CPB1 and other genes encoding pancreatic secretory enzymes and known pancreatitis susceptibility genes (PRSS1, CPA1, CTRC, and SPINK1) in a hospital series of pancreatic cancer cases and controls. Variants in CPB1, CPA1 (encoding carboxypeptidase B1 and A1), and CTRC were evaluated in a second set of cases with familial pancreatic cancer and controls. More deleterious CPB1 variants, defined as having impaired protein secretion and induction of endoplasmic reticulum (ER) stress in transfected HEK 293T cells, were found in the hospital series of pancreatic cancer cases (5/986, 0.5%) than in controls (0/1,045, P = 0.027). Among familial pancreatic cancer cases, ER stress-inducing CPB1 variants were found in 4 of 593 (0.67%) vs. 0 of 967 additional controls (P = 0.020), with a combined prevalence in pancreatic cancer cases of 9/1,579 vs. 0/2,012 controls (P < 0.01). More ER stress-inducing CPA1 variants were also found in the combined set of hospital and familial cases with pancreatic cancer than in controls [7/1,546 vs. 1/2,012; P = 0.025; odds ratio, 9.36 (95% CI, 1.15-76.02)]. Overall, 16 (1%) of 1,579 pancreatic cancer cases had an ER stress-inducing CPA1 or CPB1 variant, compared with 1 of 2,068 controls (P < 0.00001). No other candidate genes had statistically significant differences in variant prevalence between cases and controls. Our study indicates ER stress-inducing variants in CPB1 and CPA1 are associated with pancreatic cancer susceptibility and implicate ER stress in pancreatic acinar cells in pancreatic cancer development.

DNA sequence-level analyses reveal potential phenotypic modifiers in a large family with psychiatric disorders.

Psychiatric disorders are a group of genetically related diseases with highly polygenic architectures. Genome-wide association analyses have made substantial progress towards understanding the genetic architecture of these disorders. More recently, exome- and whole-genome sequencing of cases and families have identified rare, high penetrant variants that provide direct functional insight. There remains, however, a gap in the heritability explained by these complementary approaches. To understand how multiple genetic variants combine to modify both severity and penetrance of a highly penetrant variant, we sequenced 48 whole genomes from a family with a high loading of psychiatric disorder linked to a balanced chromosomal translocation. The (1;11)(q42;q14.3) translocation directly disrupts three genes: DISC1, DISC2, DISC1FP and has been linked to multiple brain imaging and neurocognitive outcomes in the family. Using DNA sequence-level linkage analysis, functional annotation and population-based association, we identified common and rare variants in GRM5 (minor allele frequency (MAF) > 0.05), PDE4D (MAF > 0.2) and CNTN5 (MAF < 0.01) that may help explain the individual differences in phenotypic expression in the family. We suggest that whole-genome sequencing in large families will improve the understanding of the combined effects of the rare and common sequence variation underlying psychiatric phenotypes.

Analysis of the bread wheat genome using whole-genome shotgun sequencing.

Bread wheat (Triticum aestivum) is a globally important crop, accounting for 20 per cent of the calories consumed by humans. Major efforts are underway worldwide to increase wheat production by extending genetic diversity and analysing key traits, and genomic resources can accelerate progress. But so far the very large size and polyploid complexity of the bread wheat genome have been substantial barriers to genome analysis. Here we report the sequencing of its large, 17-gigabase-pair, hexaploid genome using 454 pyrosequencing, and comparison of this with the sequences of diploid ancestral and progenitor genomes. We identified between 94,000 and 96,000 genes, and assigned two-thirds to the three component genomes (A, B and D) of hexaploid wheat. High-resolution synteny maps identified many small disruptions to conserved gene order. We show that the hexaploid genome is highly dynamic, with significant loss of gene family members on polyploidization and domestication, and an abundance of gene fragments. Several classes of genes involved in energy harvesting, metabolism and growth are among expanded gene families that could be associated with crop productivity. Our analyses, coupled with the identification of extensive genetic variation, provide a resource for accelerating gene discovery and improving this major crop.

The real-time fMRI neurofeedback based stratification of Default Network Regulation Neuroimaging data repository.

This data descriptor describes a repository of openly shared data from an experiment to assess inter-individual differences in default mode network (DMN) activity. This repository includes cross-sectional functional magnetic resonance imaging (fMRI) data from the Multi Source Interference Task, to assess DMN deactivation, the Moral Dilemma Task, to assess DMN activation, a resting state fMRI scan, and a DMN neurofeedback paradigm, to assess DMN modulation, along with accompanying behavioral and cognitive measures. We report technical validation from n=125 participants of the final targeted sample of 180 participants. Each session includes acquisition of one whole-brain anatomical scan and whole-brain echo-planar imaging (EPI) scans, acquired during the aforementioned tasks and resting state. The data includes several self-report measures related to perseverative thinking, emotion regulation, and imaginative processes, along with a behavioral measure of rapid visual information processing. Technical validation of the data confirms that the tasks deactivate and activate the DMN as expected. Group level analysis of the neurofeedback data indicates that the participants are able to modulate their DMN with considerable inter-subject variability. Preliminary analysis of behavioral responses and specifically self-reported sleep indicate that as many as 73 participants may need to be excluded from an analysis depending on the hypothesis being tested. The present data are linked to the enhanced Nathan Kline Institute, Rockland Sample and builds on the comprehensive neuroimaging and deep phenotyping available therein. As limited information is presently available about individual differences in the capacity to directly modulate the default mode network, these data provide a unique opportunity to examine DMN modulation ability in relation to numerous phenotypic characteristics.

Functionalized triazines as potent HCV entry inhibitors.

A series of potent and novel acylsulfonamide-bearing triazines were synthesized and the structure-activity relationships (SARs) as HCV entry inhibitors were evaluated. This acylsulfonamide series was derived from an early lead, 4-(4-(1-(4-chlorophenyl)cyclopropylamino)-6-(2,2,2-trifluoroethoxy)-1,3,5-triazin-2-ylamino)benzoic acid wherein the carboxylic acid was replaced with an acylsulfonamide moiety. This structural modification provided a class of compounds which projected an additional vector off the terminus of the acylsulfonamide functionality as a means to drive activity. This effort led to the discovery of potent analogues within this series that demonstrated sub-nanomolar EC50 values in the HCV pseudotype particle (HCVpp) assay.

Comprehensive evaluation of liver microsomal cytochrome P450 3A (CYP3A) inhibition: comparison of cynomolgus monkey and human.

1. Members of the cytochrome P450 3A (CYP3A) subfamily metabolize numerous compounds and serve as the loci of drug-drug interactions (DDIs). Because of high amino acid sequence identity with human CYP3A, the cynomolgus monkey has been proposed as a model species to support DDI risk assessment. 2. Therefore, the objective of this study was to evaluate 35 known inhibitors of human CYP3A using human (HLM) and cynomolgus monkey (CLM) liver microsomes. Midazolam was employed as substrate to generate IC50 values (concentration of inhibitor rendering 50% inhibition) in the absence and presence of a preincubation (30 mins) with NADPH. 3. In the absence of preincubation, the IC50 values generated with CLM were similar to those obtained with HLM (86% within 2-fold; 100% within 3-fold difference). However, significant differences (up to 48-fold) in preincubation IC50 were observed with 17% of the compounds (raloxifene, bergamottin, nicardipine, mibefradil, ritonavir, and diltiazem). 4. Our results indicate that in most cases the cynomolgus monkey can be a viable DDI model. However, significant species differences in time-dependent CYP3A inhibition can be observed for some compounds. In the case of raloxifene, such a difference can be ascribed to a specific CYP3A4 amino acid residue.

A hybrid likelihood model for sequence-based disease association studies.

In the past few years, case-control studies of common diseases have shifted their focus from single genes to whole exomes. New sequencing technologies now routinely detect hundreds of thousands of sequence variants in a single study, many of which are rare or even novel. The limitation of classical single-marker association analysis for rare variants has been a challenge in such studies. A new generation of statistical methods for case-control association studies has been developed to meet this challenge. A common approach to association analysis of rare variants is the burden-style collapsing methods to combine rare variant data within individuals across or within genes. Here, we propose a new hybrid likelihood model that combines a burden test with a test of the position distribution of variants. In extensive simulations and on empirical data from the Dallas Heart Study, the new model demonstrates consistently good power, in particular when applied to a gene set (e.g., multiple candidate genes with shared biological function or pathway), when rare variants cluster in key functional regions of a gene, and when protective variants are present. When applied to data from an ongoing sequencing study of bipolar disorder (191 cases, 107 controls), the model identifies seven gene sets with nominal p-values < 0.05, of which one MAPK signaling pathway (KEGG) reaches trend-level significance after correcting for multiple testing.

A 4-gigabase physical map unlocks the structure and evolution of the complex genome of Aegilops tauschii, the wheat D-genome progenitor.

The current limitations in genome sequencing technology require the construction of physical maps for high-quality draft sequences of large plant genomes, such as that of Aegilops tauschii, the wheat D-genome progenitor. To construct a physical map of the Ae. tauschii genome, we fingerprinted 461,706 bacterial artificial chromosome clones, assembled contigs, designed a 10K Ae. tauschii Infinium SNP array, constructed a 7,185-marker genetic map, and anchored on the map contigs totaling 4.03 Gb. Using whole genome shotgun reads, we extended the SNP marker sequences and found 17,093 genes and gene fragments. We showed that collinearity of the Ae. tauschii genes with Brachypodium distachyon, rice, and sorghum decreased with phylogenetic distance and that structural genome evolution rates have been high across all investigated lineages in subfamily Pooideae, including that of Brachypodieae. We obtained additional information about the evolution of the seven Triticeae chromosomes from 12 ancestral chromosomes and uncovered a pattern of centromere inactivation accompanying nested chromosome insertions in grasses. We showed that the density of noncollinear genes along the Ae. tauschii chromosomes positively correlates with recombination rates, suggested a cause, and showed that new genes, exemplified by disease resistance genes, are preferentially located in high-recombination chromosome regions.

The combination of rapamycin and resveratrol blocks autophagy and induces apoptosis in breast cancer cells.

Hyperactivation of the mechanistic target of rapamycin complex 1 (mTORC1) is a frequent event in breast cancer and current efforts are aimed at targeting the mTORC1 signaling pathway in combination with other targeted therapies. However, patients often develop drug resistance in part due to activation of the oncogenic Akt signaling and upregulation of autophagy, which protects cancer cells from apoptosis. In the present study we investigated the effects of combination therapy of rapamycin (an allosteric mTORC1 inhibitor) together with resveratrol (a phytoestrogen that inhibits autophagy). Our results show that combination of these drugs maintains inhibition of mTORC1 signaling, while preventing upregulation of Akt activation and autophagy, causing apoptosis. Additionally, this combination was effective in estrogen receptor positive and negative breast cancer cells, underscoring its versatility.

FamAnn: an automated variant annotation pipeline to facilitate target discovery for family-based sequencing studies.

FamAnn is an automated variant annotation pipeline designed for facilitating target discovery for family-based sequencing studies. It can apply a different inheritance pattern or a de novo mutations discovery model to each family and select single nucleotide variants and small insertions and deletions segregating in each family or shared by multiple families. It also provides a variety of variant annotations and retains and annotates all transcripts hit by a single variant. Excel-compatible outputs including all annotated variants segregating in each family or shared by multiple families will be provided for users to prioritize variants based on their customized thresholds. A list of genes that harbor the segregating variants will be provided as well for possible pathway/network analyses. FamAnn uses the de facto community standard Variant Call Format as the input format and can be applied to whole exome, genome or targeted resequencing data. AVAILABILITY: https://sites.google.com/site/famannotation/home CONTACT: jianchaoyao@gmail.com, kelvinzhang@mednet.ucla.edu, mccombie@cshl.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Validation and assessment of variant calling pipelines for next-generation sequencing.

BACKGROUND: The processing and analysis of the large scale data generated by next-generation sequencing (NGS) experiments is challenging and is a burgeoning area of new methods development. Several new bioinformatics tools have been developed for calling sequence variants from NGS data. Here, we validate the variant calling of these tools and compare their relative accuracy to determine which data processing pipeline is optimal. RESULTS: We developed a unified pipeline for processing NGS data that encompasses four modules: mapping, filtering, realignment and recalibration, and variant calling. We processed 130 subjects from an ongoing whole exome sequencing study through this pipeline. To evaluate the accuracy of each module, we conducted a series of comparisons between the single nucleotide variant (SNV) calls from the NGS data and either gold-standard Sanger sequencing on a total of 700 variants or array genotyping data on a total of 9,935 single-nucleotide polymorphisms. A head to head comparison showed that Genome Analysis Toolkit (GATK) provided more accurate calls than SAMtools (positive predictive value of 92.55% vs. 80.35%, respectively). Realignment of mapped reads and recalibration of base quality scores before SNV calling proved to be crucial to accurate variant calling. GATK HaplotypeCaller algorithm for variant calling outperformed the UnifiedGenotype algorithm. We also showed a relationship between mapping quality, read depth and allele balance, and SNV call accuracy. However, if best practices are used in data processing, then additional filtering based on these metrics provides little gains and accuracies of >99% are achievable. CONCLUSIONS: Our findings will help to determine the best approach for processing NGS data to confidently call variants for downstream analyses. To enable others to implement and replicate our results, all of our codes are freely available at http://metamoodics.org/wes.