W. Evan Johnson

Low concordance of multiple variant-calling pipelines: practical implications for exome and genome sequencing

BackgroundTo facilitate the clinical implementation of genomic medicine by next-generation sequencing, it will be critically important to obtain accurate and consistent variant calls on personal genomes. Multiple software tools for variant calling are available, but it is unclear how comparable these tools are or what their relative merits in real-world scenarios might be.MethodsWe sequenced 15 exomes from four families using commercial kits (Illumina HiSeq 2000 platform and Agilent SureSelect version 2 capture kit), with approximately 120X mean coverage. We analyzed the raw data using near-default parameters with five different alignment and variant-calling pipelines (SOAP, BWA-GATK, BWA-SNVer, GNUMAP, and BWA-SAMtools). We additionally sequenced a single whole genome using the sequencing and analysis pipeline from Complete Genomics (CG), with 95% of the exome region being covered by 20 or more reads per base. Finally, we validated 919 single-nucleotide variations (SNVs) and 841 insertions and deletions (indels), including similar fractions of GATK-only, SOAP-only, and shared calls, on the MiSeq platform by amplicon sequencing with approximately 5000X mean coverage.ResultsSNV concordance between five Illumina pipelines across all 15 exomes was 57.4%, while 0.5 to 5.1% of variants were called as unique to each pipeline. Indel concordance was only 26.8% between three indel-calling pipelines, even after left-normalizing and intervalizing genomic coordinates by 20 base pairs. There were 11% of CG variants falling within targeted regions in exome sequencing that were not called by any of the Illumina-based exome analysis pipelines. Based on targeted amplicon sequencing on the MiSeq platform, 97.1%, 60.2%, and 99.1% of the GATK-only, SOAP-only and shared SNVs could be validated, but only 54.0%, 44.6%, and 78.1% of the GATK-only, SOAP-only and shared indels could be validated. Additionally, our analysis of two families (one with four individuals and the other with seven), demonstrated additional accuracy gained in variant discovery by having access to genetic data from a multi-generational family.ConclusionsOur results suggest that more caution should be exercised in genomic medicine settings when analyzing individual genomes, including interpreting positive and negative findings with scrutiny, especially for indels. We advocate for renewed collection and sequencing of multi-generational families to increase the overall accuracy of whole genomes.

Nascent peptides that block protein synthesis in bacteria

Significance Ribosomes synthesize all proteins in living cells. There are limits, however, to which sequences they can make. We identified short motifs within translating proteins that inhibit their own synthesis. We developed in vitro methods to determine the molecular mechanism of ribosome stalling by these motifs. Some act by blocking the formation of peptide bonds; in a few of these cases, a translation factor, elongation factor P, alleviates stalling. Other motifs block release of the protein at stop codons. Stalling motifs occur less often than expected in bacterial proteins, suggesting that proteins have evolved to be synthesized efficiently. Although the ribosome is a very general catalyst, it cannot synthesize all protein sequences equally well. For example, ribosomes stall on the secretion monitor (SecM) leader peptide to regulate expression of a downstream gene. Using a genetic selection in Escherichia coli, we identified additional nascent peptide motifs that stall ribosomes. Kinetic studies show that some nascent peptides dramatically inhibit rates of peptide release by release factors. We find that residues upstream of the minimal stalling motif can either enhance or suppress this effect. In other stalling motifs, peptidyl transfer to certain aminoacyl-tRNAs is inhibited. In particular, three consecutive Pro codons pose a challenge for elongating ribosomes. The translation factor elongation factor P, which alleviates pausing at polyproline sequences, has little or no effect on other stalling peptides. The motifs that we identified are underrepresented in bacterial proteomes and show evidence of stalling on endogenous E. coli proteins.

Effects of ADARs on small RNA processing pathways in C. elegans

Adenosine deaminases that act on RNA (ADARs) are RNA editing enzymes that convert adenosine to inosine in double-stranded RNA (dsRNA). To evaluate effects of ADARs on small RNAs that derive from dsRNA precursors, we performed deep-sequencing, comparing small RNAs from wild-type and ADAR mutant Caenorhabditis elegans. While editing in small RNAs was rare, at least 40% of microRNAs had altered levels in at least one ADAR mutant strain, and miRNAs with significantly altered levels had mRNA targets with correspondingly affected levels. About 40% of siRNAs derived from endogenous genes (endo-siRNAs) also had altered levels in at least one mutant strain, including 63% of Dicer-dependent endo-siRNAs. The 26G class of endo-siRNAs was significantly affected by ADARs, and many altered 26G loci had intronic reads and histone modifications associated with transcriptional silencing. Our data indicate that ADARs, through both direct and indirect mechanisms, are important for maintaining wild-type levels of many small RNAs in C. elegans.

Metataxonomic and Metagenomic Approaches vs. Culture-Based Techniques for Clinical Pathology.

Diagnoses that are both timely and accurate are critically important for patients with life-threatening or drug resistant infections. Technological improvements in High-Throughput Sequencing (HTS) have led to its use in pathogen detection and its application in clinical diagnoses of infectious diseases. The present study compares two HTS methods, 16S rRNA marker gene sequencing (metataxonomics) and whole metagenomic shotgun sequencing (metagenomics), in their respective abilities to match the same diagnosis as traditional culture methods (culture inference) for patients with ventilator associated pneumonia (VAP). The metagenomic analysis was able to produce the same diagnosis as culture methods at the species-level for five of the six samples, while the metataxonomic analysis was only able to produce results with the same species-level identification as culture for two of the six samples. These results indicate that metagenomic analyses have the accuracy needed for a clinical diagnostic tool, but full integration in diagnostic protocols is contingent on technological improvements to decrease turnaround time and lower costs.

Xenosurveillance: a novel mosquito-based approach for examining the human-pathogen landscape.

Background Globally, regions at the highest risk for emerging infectious diseases are often the ones with the fewest resources. As a result, implementing sustainable infectious disease surveillance systems in these regions is challenging. The cost of these programs and difficulties associated with collecting, storing and transporting relevant samples have hindered them in the regions where they are most needed. Therefore, we tested the sensitivity and feasibility of a novel surveillance technique called xenosurveillance. This approach utilizes the host feeding preferences and behaviors of Anopheles gambiae, which are highly anthropophilic and rest indoors after feeding, to sample viruses in human beings. We hypothesized that mosquito bloodmeals could be used to detect vertebrate viral pathogens within realistic field collection timeframes and clinically relevant concentrations. Methodology/Principal Findings To validate this approach, we examined variables influencing virus detection such as the duration between mosquito blood feeding and mosquito processing, the pathogen nucleic acid stability in the mosquito gut and the pathogen load present in the host’s blood at the time of bloodmeal ingestion using our laboratory model. Our findings revealed that viral nucleic acids, at clinically relevant concentrations, could be detected from engorged mosquitoes for up to 24 hours post feeding by qRT-PCR. Subsequently, we tested this approach in the field by examining blood from engorged mosquitoes from two field sites in Liberia. Using next-generation sequencing and PCR we were able to detect the genetic signatures of multiple viral pathogens including Epstein-Barr virus and canine distemper virus. Conclusions/Significance Together, these data demonstrate the feasibility of xenosurveillance and in doing so validated a simple and non-invasive surveillance tool that could be used to complement current biosurveillance efforts.

Genomic pathway analysis reveals that EZH2 and HDAC4 represent mutually exclusive epigenetic pathways across human cancers

BackgroundAlterations in epigenetic marks, including methylation or acetylation, are common in human cancers. For many epigenetic pathways, however, direct measures of activity are unknown, making their role in various cancers difficult to assess. Gene expression signatures facilitate the examination of patterns of epigenetic pathway activation across and within human cancer types allowing better understanding of the relationships between these pathways.MethodsWe used Bayesian regression to generate gene expression signatures from normal epithelial cells before and after epigenetic pathway activation. Signatures were applied to datasets from TCGA, GEO, CaArray, ArrayExpress, and the cancer cell line encyclopedia. For TCGA data, signature results were correlated with copy number variation and DNA methylation changes. GSEA was used to identify biologic pathways related to the signatures.ResultsWe developed and validated signatures reflecting downstream effects of enhancer of zeste homolog 2(EZH2), histone deacetylase(HDAC) 1, HDAC4, sirtuin 1(SIRT1), and DNA methyltransferase 2(DNMT2). By applying these signatures to data from cancer cell lines and tumors in large public repositories, we identify those cancers that have the highest and lowest activation of each of these pathways. Highest EZH2 activation is seen in neuroblastoma, hepatocellular carcinoma, small cell lung cancer, and melanoma, while highest HDAC activity is seen in pharyngeal cancer, kidney cancer, and pancreatic cancer. Across all datasets studied, activation of both EZH2 and HDAC4 is significantly underrepresented. Using breast cancer and glioblastoma as examples to examine intrinsic subtypes of particular cancers, EZH2 activation was highest in luminal breast cancers and proneural glioblastomas, while HDAC4 activation was highest in basal breast cancer and mesenchymal glioblastoma. EZH2 and HDAC4 activation are associated with particular chromosome abnormalities: EZH2 activation with aberrations in genes from the TGF and phosphatidylinositol pathways and HDAC4 activation with aberrations in inflammatory and chemokine related genes.ConclusionGene expression patterns can reveal the activation level of epigenetic pathways. Epigenetic pathways define biologically relevant subsets of human cancers. EZH2 activation and HDAC4 activation correlate with growth factor signaling and inflammation, respectively, and represent two distinct states for cancer cells. This understanding may allow us to identify targetable drivers in these cancer subsets.

Shared Gene Expression Alterations in Nasal and Bronchial Epithelium for Lung Cancer Detection

Background: We previously derived and validated a bronchial epithelial gene expression biomarker to detect lung cancer in current and former smokers. Given that bronchial and nasal epithelial gene expression are similarly altered by cigarette smoke exposure, we sought to determine if cancer-associated gene expression might also be detectable in the more readily accessible nasal epithelium. Methods: Nasal epithelial brushings were prospectively collected from current and former smokers undergoing diagnostic evaluation for pulmonary lesions suspicious for lung cancer in the AEGIS-1 (n = 375) and AEGIS-2 (n = 130) clinical trials and gene expression profiled using microarrays. All statistical tests were two-sided. Results: We identified 535 genes that were differentially expressed in the nasal epithelium of AEGIS-1 patients diagnosed with lung cancer vs those with benign disease after one year of follow-up (P < .001). Using bronchial gene expression data from the AEGIS-1 patients, we found statistically significant concordant cancer-associated gene expression alterations between the two airway sites (P < .001). Differentially expressed genes in the nose were enriched for genes associated with the regulation of apoptosis and immune system signaling. A nasal lung cancer classifier derived in the AEGIS-1 cohort that combined clinical factors (age, smoking status, time since quit, mass size) and nasal gene expression (30 genes) had statistically significantly higher area under the curve (0.81; 95% confidence interval [CI] = 0.74 to 0.89, P = .01) and sensitivity (0.91; 95% CI = 0.81 to 0.97, P = .03) than a clinical-factor only model in independent samples from the AEGIS-2 cohort. Conclusions: These results support that the airway epithelial field of lung cancer–associated injury in ever smokers extends to the nose and demonstrates the potential of using nasal gene expression as a noninvasive biomarker for lung cancer detection.

Hnrnph1 Is A Quantitative Trait Gene for Methamphetamine Sensitivity

Psychostimulant addiction is a heritable substance use disorder; however its genetic basis is almost entirely unknown. Quantitative trait locus (QTL) mapping in mice offers a complementary approach to human genome-wide association studies and can facilitate environment control, statistical power, novel gene discovery, and neurobiological mechanisms. We used interval-specific congenic mouse lines carrying various segments of chromosome 11 from the DBA/2J strain on an isogenic C57BL/6J background to positionally clone a 206 kb QTL (50,185,512–50,391,845 bp) that was causally associated with a reduction in the locomotor stimulant response to methamphetamine (2 mg/kg, i.p.; DBA/2J < C57BL/6J)—a non-contingent, drug-induced behavior that is associated with stimulation of the dopaminergic reward circuitry. This chromosomal region contained only two protein coding genes—heterogeneous nuclear ribonucleoprotein, H1 (Hnrnph1) and RUN and FYVE domain-containing 1 (Rufy1). Transcriptome analysis via mRNA sequencing in the striatum implicated a neurobiological mechanism involving a reduction in mesolimbic innervation and striatal neurotransmission. For instance, Nr4a2 (nuclear receptor subfamily 4, group A, member 2), a transcription factor crucial for midbrain dopaminergic neuron development, exhibited a 2.1-fold decrease in expression (DBA/2J < C57BL/6J; p 4.2 x 10−15). Transcription activator-like effector nucleases (TALENs)-mediated introduction of frameshift deletions in the first coding exon of Hnrnph1, but not Rufy1, recapitulated the reduced methamphetamine behavioral response, thus identifying Hnrnph1 as a quantitative trait gene for methamphetamine sensitivity. These results define a novel contribution of Hnrnph1 to neurobehavioral dysfunction associated with dopaminergic neurotransmission. These findings could have implications for understanding the genetic basis of methamphetamine addiction in humans and the development of novel therapeutics for prevention and treatment of substance abuse and possibly other psychiatric disorders.

Cytoplasmic FMR1-Interacting Protein 2 Is a Major Genetic Factor Underlying Binge Eating

BACKGROUND Eating disorders are lethal and heritable; however, the underlying genetic factors are unknown. Binge eating is a highly heritable trait associated with eating disorders that is comorbid with mood and substance use disorders. Therefore, understanding its genetic basis will inform therapeutic development that could improve several comorbid neuropsychiatric conditions. METHODS We assessed binge eating in closely related C57BL/6 mouse substrains and in an F2 cross to identify quantitative trait loci associated with binge eating. We used gene targeting to validate candidate genetic factors. Finally, we used transcriptome analysis of the striatum via messenger RNA sequencing to identify the premorbid transcriptome and the binge-induced transcriptome to inform molecular mechanisms mediating binge eating susceptibility and establishment. RESULTS C57BL/6NJ but not C57BL/6J mice showed rapid and robust escalation in palatable food consumption. We mapped a single genome-wide significant quantitative trait locus on chromosome 11 (logarithm of the odds = 7.4) to a missense mutation in cytoplasmic FMR1-interacting protein 2 (Cyfip2). We validated Cyfip2 as a major genetic factor underlying binge eating in heterozygous knockout mice on a C57BL/6N background that showed reduced binge eating toward a wild-type C57BL/6J-like level. Transcriptome analysis of premorbid genetic risk identified the enrichment terms morphine addiction and retrograde endocannabinoid signaling, whereas binge eating resulted in the downregulation of a gene set enriched for decreased myelination, oligodendrocyte differentiation, and expression. CONCLUSIONS We identified Cyfip2 as a major significant genetic factor underlying binge eating and provide a behavioral paradigm for future genome-wide association studies in populations with increased genetic complexity.

Assessment of microRNA differential expression and detection in multiplexed small RNA sequencing data

Small RNA sequencing can be used to gain an unprecedented amount of detail into the microRNA transcriptome. The relatively high cost and low throughput of sequencing bases technologies can potentially be offset by the use of multiplexing. However, multiplexing involves a trade-off between increased number of sequenced samples and reduced number of reads per sample (i.e., lower depth of coverage). To assess the effect of different sequencing depths owing to multiplexing on microRNA differential expression and detection, we sequenced the small RNA of lung tissue samples collected in a clinical setting by multiplexing one, three, six, nine, or 12 samples per lane using the Illumina HiSeq 2000. As expected, the numbers of reads obtained per sample decreased as the number of samples in a multiplex increased. Furthermore, after normalization, replicate samples included in distinct multiplexes were highly correlated (R > 0.97). When detecting differential microRNA expression between groups of samples, microRNAs with average expression >1 reads per million (RPM) had reproducible fold change estimates (signal to noise) independent of the degree of multiplexing. The number of microRNAs detected was strongly correlated with the log2 number of reads aligning to microRNA loci (R = 0.96). However, most additional microRNAs detected in samples with greater sequencing depth were in the range of expression which had lower fold change reproducibility. These findings elucidate the trade-off between increasing the number of samples in a multiplex with decreasing sequencing depth and will aid in the design of large-scale clinical studies exploring microRNA expression and its role in disease.