Large-scale Deep Proteomic Analysis in Alzheimer's Disease Brain Regions Across Race and Ethnicity

Introduction

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease, yet our comprehension predominantly relies on studies within the non-Hispanic White (NHW) population. Here we aimed to provide comprehensive insights into the proteomic landscape of AD across diverse racial and ethnic groups.

Methods

Dorsolateral prefrontal cortex (DLPFC) and superior temporal gyrus (STG) brain tissues were donated from multiple centers (Mayo Clinic, Emory University, Rush University, Mt. Sinai School of Medicine) and were harmonized through neuropathological evaluation, specifically adhering to the Braak staging and CERAD criteria. Among 1105 DLPFC tissue samples (998 unique individuals), 333 were from African American donors, 223 from Latino Americans, 529 from NHW donors, and the rest were from a mixed or unknown racial background. Among 280 STG tissue samples (244 unique individuals), 86 were African American, 76 Latino American, 116 NHW and the rest were mixed or unknown ethnicity. All tissues were uniformly homogenized and analyzed by tandem mass tag mass spectrometry (TMT-MS).

Results

As a Quality control (QC) measure, proteins with more than 50% missing values were removed and iterative principal component analysis was conducted to remove outliers within brain regions. After QC, 9,180 and 9,734 proteins remained in the DLPC and STG proteome, respectively, of which approximately 9,000 proteins were shared between regions. Protein levels of microtubule-associated protein tau (MAPT) and amyloid-precursor protein (APP) demonstrated AD-related elevations in DLPFC tissues with a strong association with CERAD and Braak across racial groups. APOE4 protein levels in brain were highly concordant with APOE genotype of the individuals.

Discussion

This comprehensive region resolved large-scale proteomic dataset provides a resource for the understanding of ethnoracial-specific protein differences in AD brain.

Hypomethylation and Overexpression of Th17-Associated Genes is a Hallmark of Intestinal CD4+ Lymphocytes in Crohn's Disease

BACKGROUND

The development of Crohn's disease [CD] involves immune cell signalling pathways regulated by epigenetic modifications. Aberrant DNA methylation has been identified in peripheral blood and bulk intestinal tissue from CD patients. However, the DNA methylome of disease-associated intestinal CD4+ lymphocytes has not been evaluated.

MATERIALS AND METHODS

Genome-wide DNA methylation sequencing was performed from terminal ileum CD4+ cells from 21 CD patients and 12 age- and sex-matched controls. Data were analysed for differentially methylated CpGs [DMCs] and methylated regions [DMRs]. Integration was performed with RNA-sequencing data to evaluate the functional impact of DNA methylation changes on gene expression. DMRs were overlapped with regions of differentially open chromatin [by ATAC-seq] and CCCTC-binding factor [CTCF] binding sites [by ChIP-seq] between peripherally derived Th17 and Treg cells.

RESULTS

CD4+ cells in CD patients had significantly increased DNA methylation compared to those from the controls. A total of 119 051 DMCs and 8113 DMRs were detected. While hypermethylated genes were mostly related to cell metabolism and homeostasis, hypomethylated genes were significantly enriched within the Th17 signalling pathway. The differentially enriched ATAC regions in Th17 cells [compared to Tregs] were hypomethylated in CD patients, suggesting heightened Th17 activity. There was significant overlap between hypomethylated DNA regions and CTCF-associated binding sites.

CONCLUSIONS

The methylome of CD patients shows an overall dominant hypermethylation yet hypomethylation is more concentrated in proinflammatory pathways, including Th17 differentiation. Hypomethylation of Th17-related genes associated with areas of open chromatin and CTCF binding sites constitutes a hallmark of CD-associated intestinal CD4+ cells.

Genome-wide Epigenetic Study of Chronic Rhinosinusitis Tissues Reveals Dysregulated Inflammatory, Immunologic and Remodeling Pathways

BACKGROUND

Epigenetics studies mechanisms such as DNA methylation, histone modifications, non-coding RNAs, and alternative polyadenylation that can modify gene activity without changing the underlying DNA nucleotide base-pair structure. Because these changes are reversible, they have potential in developing novel therapeutics. Currently, seven pharmaceutical agents targeting epigenetic changes are FDA approved and commercially available for treatment of certain cancers. However, studies investigating epigenetics in chronic rhinosinusitis (CRS) have not been undertaken previously in the United States.

OBJECTIVES

The goal of this study was to investigate sinonasal DNA methylation patterns in CRS versus controls, to discern environmentally-induced epigenetic changes impacting CRS subjects.

METHODS AND RESULTS

Ethmoidal samples from CRS and inferior turbinate mucosal tissue samples from controls without CRS were studied. DNA methylation was studied by Reduced Representation Bisulfite Sequencing. RADMeth® biostatistical package was used to identify differentially methylated regions (DMRs) between CRS and controls. Ingenuity Pathway analysis of DMRs was performed to identify top upstream regulators and canonical pathways. Ninety-three samples from 64 CRS subjects (36 CRSwNP; 28 CRSsNP) and 29 controls were studied. CRS and control samples differed in 13 662 CpGs sites and 1381 DMRs. Top upstream regulators identified included: 1. CRS versus controls: TGFB1, TNF, TP53, DGCR8, and beta-estradiol. 2. CRSwNP versus controls: TGFB1, CTNNB1, lipopolysaccharide, ID2, and TCF7L2. 3. CRSsNP versus controls: MYOD1, acetone, ID2, ST8SIA4, and LEPR.

CONCLUSIONS

Differential patterns of methylation were identified between controls and CRS, CRSwNP, and CRSsNP. Epigenetic, environmentally-induced changes related to novel, inflammatory, immunologic, and remodeling pathways appear to affect epithelial integrity, cell proliferation, homeostasis, vascular permeability, and other yet uncharacterized pathways and genes.

Fine-mapping of the non-coding variation driving the Caucasian LRRK2 GWAS signal in Parkinson's disease

INTRODUCTION

Genome-wide association studies (GWAS) have confirmed the leucine-rich repeat kinase 2 (LRRK2) gene as a susceptibility locus for idiopathic Parkinson's disease (PD) in Caucasians. Though the rs1491942 and rs76904798 variants have shown the strongest associations, the causal variant(s) remains unresolved. Therefore, the aim of this study was to identify variants that may be driving the LRRK2 GWAS signal by sequencing the entire LRRK2 gene in Caucasian PD patients and controls.

METHODS

A discovery series (287 PD patients, 294 controls) and replication series (362 PD patients, 168 controls) were included. The entire LRRK2 gene as well as 10 Kb upstream/downstream was sequenced. Candidate potential causal variants were considered to be those that (a) were in at least weak linkage disequilibrium with the two GWAS-nominated variants (rs1491942 and rs76904798), and (b) displayed an association odds ratio (OR) that is stronger than the two GWAS variants.

RESULTS

Thirty-four candidate variants (all intronic/intergenic) that may drive the LRRK2 PD GWAS signal were identified in the discovery series. However, examination of the replication series for these variants did not reveal any with a consistently stronger OR than both PD GWAS variants. Evaluation of public databases to determine which candidate variants are most likely to have a direct functional effect on LRRK2 expression was inconclusive.

CONCLUSION

Though our findings provide novel insights into the LRRK2 GWAS association, a clear causal variant was not identified. The identified candidate variants can form the basis for future experiments and functional studies that can more definitively assess causal LRRK2 variants.

Genome-wide detection of tandem DNA repeats that are expanded in autism

Tandem DNA repeats vary in the size and sequence of each unit (motif). When expanded, these tandem DNA repeats have been associated with more than 40 monogenic disorders1. Their involvement in disorders with complex genetics is largely unknown, as is the extent of their heterogeneity. Here we investigated the genome-wide characteristics of tandem repeats that had motifs with a length of 2-20 base pairs in 17,231 genomes of families containing individuals with autism spectrum disorder (ASD)2,3 and population control individuals4. We found extensive polymorphism in the size and sequence of motifs. Many of the tandem repeat loci that we detected correlated with cytogenetic fragile sites. At 2,588 loci, gene-associated expansions of tandem repeats that were rare among population control individuals were significantly more prevalent among individuals with ASD than their siblings without ASD, particularly in exons and near splice junctions, and in genes related to the development of the nervous system and cardiovascular system or muscle. Rare tandem repeat expansions had a prevalence of 23.3% in children with ASD compared with 20.7% in children without ASD, which suggests that tandem repeat expansions make a collective contribution to the risk of ASD of 2.6%. These rare tandem repeat expansions included previously undescribed ASD-linked expansions in DMPK and FXN, which are associated with neuromuscular conditions, and in previously unknown loci such as FGF14 and CACNB1. Rare tandem repeat expansions were associated with lower IQ and adaptive ability. Our results show that tandem DNA repeat expansions contribute strongly to the genetic aetiology and phenotypic complexity of ASD.

Next-Generation Sequencing of CYP2C19 in Stent Thrombosis: Implications for Clopidogrel Pharmacogenomics

PURPOSE

Describe CYP2C19 sequencing results in the largest series of clopidogrel-treated cases with stent thrombosis (ST), the closest clinical phenotype to clopidogrel resistance. Evaluate the impact of CYP2C19 genetic variation detected by next-generation sequencing (NGS) with comprehensive annotation and functional studies.

METHODS

Seventy ST cases on clopidogrel identified from the PLATO trial (n = 58) and Mayo Clinic biorepository (n = 12) were matched 1:1 with controls for age, race, sex, diabetes mellitus, presentation, and stent type. NGS was performed to cover the entire CYP2C19 gene. Assessment of exonic variants involved measuring in vitro protein expression levels. Intronic variants were evaluated for potential splicing motif variations.

RESULTS

Poor metabolizers (n = 4) and rare CYP2C19*8, CYP2C19*15, and CYP2C19*11 alleles were identified only in ST cases. CYP2C19*17 heterozygote carriers were observed more frequently in cases (n = 29) than controls (n = 18). Functional studies of CYP2C19 exonic variants (n = 11) revealed 3 cases and only 1 control carrying a deleterious variant as determined by in vitro protein expression studies. Greater intronic variation unique to ST cases (n = 169) compared with controls (n = 84) was observed with predictions revealing 13 allele candidates that may lead to a potential disruption of splicing and a loss-of-function effect of CYP2C19 in ST cases.

CONCLUSION

NGS detected CYP2C19 poor metabolizers and paradoxically greater number of so-called rapid metabolizers in ST cases. Rare deleterious exonic variation occurs in 4%, and potentially disruptive intronic alleles occur in 16% of ST cases. Additional studies are required to evaluate the role of these variants in platelet aggregation and clopidogrel metabolism.

Recommendations for performance optimizations when using GATK3.8 and GATK4

BACKGROUND

Use of the Genome Analysis Toolkit (GATK) continues to be the standard practice in genomic variant calling in both research and the clinic. Recently the toolkit has been rapidly evolving. Significant computational performance improvements have been introduced in GATK3.8 through collaboration with Intel in 2017. The first release of GATK4 in early 2018 revealed rewrites in the code base, as the stepping stone toward a Spark implementation. As the software continues to be a moving target for optimal deployment in highly productive environments, we present a detailed analysis of these improvements, to help the community stay abreast with changes in performance.

RESULTS

We re-evaluated multiple options, such as threading, parallel garbage collection, I/O options and data-level parallelization. Additionally, we considered the trade-offs of using GATK3.8 and GATK4. We found optimized parameter values that reduce the time of executing the best practices variant calling procedure by 29.3% for GATK3.8 and 16.9% for GATK4. Further speedups can be accomplished by splitting data for parallel analysis, resulting in run time of only a few hours on whole human genome sequenced to the depth of 20X, for both versions of GATK. Nonetheless, GATK4 is already much more cost-effective than GATK3.8. Thanks to significant rewrites of the algorithms, the same analysis can be run largely in a single-threaded fashion, allowing users to process multiple samples on the same CPU.

CONCLUSIONS

In time-sensitive situations, when a patient has a critical or rapidly developing condition, it is useful to minimize the time to process a single sample. In such cases we recommend using GATK3.8 by splitting the sample into chunks and computing across multiple nodes. The resultant walltime will be nnn.4 hours at the cost of $41.60 on 4 c5.18xlarge instances of Amazon Cloud. For cost-effectiveness of routine analyses or for large population studies, it is useful to maximize the number of samples processed per unit time. Thus we recommend GATK4, running multiple samples on one node. The total walltime will be ∼34.1 hours on 40 samples, with 1.18 samples processed per hour at the cost of $2.60 per sample on c5.18xlarge instance of Amazon Cloud.

Detection and characterization of mosaicism in autosomal dominant polycystic kidney disease

Autosomal dominant polycystic kidney disease (ADPKD) is an inherited, progressive nephropathy accounting for 4-10% of end stage renal disease worldwide. PKD1 and PKD2 are the most common disease loci, but even accounting for other genetic causes, about 7% of families remain unresolved. Typically, these unsolved cases have relatively mild kidney disease and often have a negative family history. Mosaicism, due to de novo mutation in the early embryo, has rarely been identified by conventional genetic analysis of ADPKD families. Here we screened for mosaicism by employing two next generation sequencing screens, specific analysis of PKD1 and PKD2 employing long-range polymerase chain reaction, or targeted capture of cystogenes. We characterized mosaicism in 20 ADPKD families; the pathogenic variant was transmitted to the next generation in five families and sporadic in 15. The mosaic pathogenic variant was newly discovered by next generation sequencing in 13 families, and these methods precisely quantified the level of mosaicism in all. All of the mosaic cases had PKD1 mutations, 14 were deletions or insertions, and 16 occurred in females. Analysis of kidney size and function showed the mosaic cases had milder disease than a control PKD1 population, but only a few had clearly asymmetric disease. Thus, in a typical ADPKD population, readily detectable mosaicism by next generation sequencing accounts for about 1% of cases, and about 10% of genetically unresolved cases with an uncertain family history. Hence, identification of mosaicism is important to fully characterize ADPKD populations and provides informed prognostic information.

DNA methylation patterns in human iPSC-derived sensory neuronal differentiation

Sensory neurons of the peripheral nervous system are critical in health and disease. Sensory neurons derived from induced pluripotent stem (iPS) cells are now being used increasingly for in vitro models of neuropathy, pain, and neurotoxicity. DNA methylation is critical for neurodevelopment and has been implicated in many neuronal diseases, but has not been examined in iPS-derived sensory neurons. In order to better characterize the iPS-derived sensory neuron model, we have undertaken a genome-wide DNA methylation study on the cells from human iPS to iPS-derived sensory neurons during differentiation through reduced representation and bisulfite sequencing. We report decreasing DNA methylation with iPS-derived sensory neuronal differentiation that is reflected in increasing numbers and proportions of hypomethylated individual CpGs and regions, as well as lowered DNMT3b expression. Furthermore, genes with changes in DNA methylation near their TSS suggest key pathways that may be involved in iPS-derived sensory neuronal differentiation. These findings provide insights into sensory neuronal differentiation and can be used for further in vitro modelling of disease states.

Sentieon DNASeq Variant Calling Workflow Demonstrates Strong Computational Performance and Accuracy

As reliable, efficient genome sequencing becomes ubiquitous, the need for similarly reliable and efficient variant calling becomes increasingly important. The Genome Analysis Toolkit (GATK), maintained by the Broad Institute, is currently the widely accepted standard for variant calling software. However, alternative solutions may provide faster variant calling without sacrificing accuracy. One such alternative is Sentieon DNASeq, a toolkit analogous to GATK but built on a highly optimized backend. We conducted an independent evaluation of the DNASeq single-sample variant calling pipeline in comparison to that of GATK. Our results support the near-identical accuracy of the two software packages, showcase optimal scalability and great speed from Sentieon, and describe computational performance considerations for the deployment of DNASeq.

An expanded variant list and assembly annotation identifies multiple novel coding and noncoding genes for prostate cancer risk using a normal prostate tissue eQTL data set

Prostate cancer (PrCa) is highly heritable; 284 variants have been identified to date that are associated with increased prostate cancer risk, yet few genes contributing to its development are known. Expression quantitative trait loci (eQTL) studies link variants with affected genes, helping to determine how these variants might regulate gene expression and may influence prostate cancer risk. In the current study, we performed eQTL analysis on 471 normal prostate epithelium samples and 249 PrCa-risk variants in 196 risk loci, utilizing RNA sequencing transcriptome data based on ENSEMBL gene definition and genome-wide variant data. We identified a total of 213 genes associated with known PrCa-risk variants, including 141 protein-coding genes, 16 lncRNAs, and 56 other non-coding RNA species with differential expression. Compared to our previous analysis, where RefSeq was used for gene annotation, we identified an additional 130 expressed genes associated with known PrCa-risk variants. We detected an eQTL signal for more than half (n = 102, 52%) of the 196 loci tested; 52 (51%) of which were a Group 1 signal, indicating high linkage disequilibrium (LD) between the peak eQTL variant and the PrCa-risk variant (r2>0.5) and may help explain how risk variants influence the development of prostate cancer.

Statistical method evaluation for differentially methylated CpGs in base resolution next-generation DNA sequencing data

High-throughput bisulfite methylation sequencing such as reduced representation bisulfite sequencing (RRBS), Agilent SureSelect Human Methyl-Seq (Methyl-seq) or whole-genome bisulfite sequencing is commonly used for base resolution methylome research. These data are represented either by the ratio of methylated cytosine versus total coverage at a CpG site or numbers of methylated and unmethylated cytosines. Multiple statistical methods can be used to detect differentially methylated CpGs (DMCs) between conditions, and these methods are often the base for the next step of differentially methylated region identification. The ratio data have a flexibility of fitting to many linear models, but the raw count data take consideration of coverage information. There is an array of options in each datatype for DMC detection; however, it is not clear which is an optimal statistical method. In this study, we systematically evaluated four statistic methods on methylation ratio data and four methods on count-based data and compared their performances with regard to type I error control, sensitivity and specificity of DMC detection and computational resource demands using real RRBS data along with simulation. Our results show that the ratio-based tests are generally more conservative (less sensitive) than the count-based tests. However, some count-based methods have high false-positive rates and should be avoided. The beta-binomial model gives a good balance between sensitivity and specificity and is preferred method. Selection of methods in different settings, signal versus noise and sample size estimation are also discussed.

Perinatal Nutritional Reprogramming of the Epigenome Promotes Subsequent Development of Nonalcoholic Steatohepatitis

With the epidemic of obesity, nonalcoholic fatty liver disease (NAFLD) has become the most common pediatric liver disease. The influence of a perinatal obesity‐inducing diet (OID) on the development and progression of NAFLD in offspring is important but incompletely studied. Hence, we fed breeding pairs of C57BL/6J mice during gestation and lactation (perinatally) either chow or an OID rich in fat, fructose, and cholesterol (FFC). The offspring were weaned to either chow or an FFC diet, generating four groups: perinatal (p)Chow‐Chow, pChow‐FFC, pFFC‐Chow, and pFFC‐FFC. Mice were sacrificed at 10 weeks of age. We examined the whole‐liver transcriptome by RNA sequencing (RNA‐seq) and whole‐liver genome methylation by reduced representation bisulfite sequencing (RRBS). Our results indicated that the pFFC‐FFC mice had a significant increase in hepatic steatosis, injury, inflammation, and fibrosis, as assessed histologically and biochemically. We identified 189 genes that were differentially expressed and methylated in the pFFC‐FFC mice versus the pChow‐FFC mice. Gene set enrichment analysis identified hepatic fibrosis/hepatic stellate cell activation as the top canonical pathway, suggesting that the differential DNA methylation events in the mice exposed to the FFC diet perinatally were associated with a profibrogenic transcriptome. To verify that this finding was consistent with perinatal nutritional reprogramming of the methylome, we exposed pFFC‐Chow mice to an FFC diet in adulthood. These mice developed significant hepatic steatosis, injury, inflammation, and more importantly fibrosis when compared to the appropriate controls. Conclusion: Perinatal exposure to an OID primes the immature liver for an accentuated fibrosing nonalcoholic steatohepatitis (NASH) phenotype, likely through nutritional reprogramming of the offspring methylome. These data have potential clinical implications for monitoring children of obese mothers and risk stratification of children with NAFLD.

HGT-ID: an efficient and sensitive workflow to detect human-viral insertion sites using next-generation sequencing data

Background

Transfer of genetic material from microbes or viruses into the host genome is known as horizontal gene transfer (HGT). The integration of viruses into the human genome is associated with multiple cancers, and these can now be detected using next-generation sequencing methods such as whole genome sequencing and RNA-sequencing.

Results

We designed a novel computational workflow, HGT-ID, to identify the integration of viruses into the human genome using the sequencing data. The HGT-ID workflow primarily follows a four-step procedure: i) pre-processing of unaligned reads, ii) virus detection using subtraction approach, iii) identification of virus integration site using discordant and soft-clipped reads and iv) HGT candidates prioritization through a scoring function. Annotation and visualization of the events, as well as primer design for experimental validation, are also provided in the final report. We evaluated the tool performance with the well-understood cervical cancer samples. The HGT-ID workflow accurately detected known human papillomavirus (HPV) integration sites with high sensitivity and specificity compared to previous HGT methods. We applied HGT-ID to The Cancer Genome Atlas (TCGA) whole-genome sequencing data (WGS) from liver tumor-normal pairs. Multiple hepatitis B virus (HBV) integration sites were identified in TCGA liver samples and confirmed by HGT-ID using the RNA-Seq data from the matched liver pairs. This shows the applicability of the method in both the data types and cross-validation of the HGT events in liver samples. We also processed 220 breast tumor WGS data through the workflow; however, there were no HGT events detected in those samples.

Conclusions

HGT-ID is a novel computational workflow to detect the integration of viruses in the human genome using the sequencing data. It is fast and accurate with functions such as prioritization, annotation, visualization and primer design for future validation of HGTs. The HGT-ID workflow is released under the MIT License and available at http://kalarikrlab.org/Software/HGT-ID.html.

Monoallelic Mutations to DNAJB11 Cause Atypical Autosomal-Dominant Polycystic Kidney Disease

Autosomal-dominant polycystic kidney disease (ADPKD) is characterized by the progressive development of kidney cysts, often resulting in end-stage renal disease (ESRD). This disorder is genetically heterogeneous with ∼7% of families genetically unresolved. We performed whole-exome sequencing (WES) in two multiplex ADPKD-like pedigrees, and we analyzed a further 591 genetically unresolved, phenotypically similar families by targeted next-generation sequencing of 65 candidate genes. WES identified a DNAJB11 missense variant (p.Pro54Arg) in two family members presenting with non-enlarged polycystic kidneys and a frameshifting change (c.166_167insTT) in a second family with small renal and liver cysts. DNAJB11 is a co-factor of BiP, a key chaperone in the endoplasmic reticulum controlling folding, trafficking, and degradation of secreted and membrane proteins. Five additional multigenerational families carrying DNAJB11 mutations were identified by the targeted analysis. The clinical phenotype was consistent in the 23 affected members, with non-enlarged cystic kidneys that often evolved to kidney atrophy; 7 subjects reached ESRD from 59 to 89 years. The lack of kidney enlargement, histologically evident interstitial fibrosis in non-cystic parenchyma, and recurring episodes of gout (one family) suggested partial phenotypic overlap with autosomal-dominant tubulointerstitial diseases (ADTKD). Characterization of DNAJB11-null cells and kidney samples from affected individuals revealed a pathogenesis associated with maturation and trafficking defects involving the ADPKD protein, PC1, and ADTKD proteins, such as UMOD. DNAJB11-associated disease is a phenotypic hybrid of ADPKD and ADTKD, characterized by normal-sized cystic kidneys and progressive interstitial fibrosis resulting in late-onset ESRD.

Molecular characterization of colorectal adenomas with and without malignancy reveals distinguishing genome, transcriptome and methylome alterations

The majority of colorectal cancer (CRC) arises from precursor lesions known as polyps. The molecular determinants that distinguish benign from malignant polyps remain unclear. To molecularly characterize polyps, we utilized Cancer Adjacent Polyp (CAP) and Cancer Free Polyp (CFP) patients. CAPs had tissues from the residual polyp of origin and contiguous cancer; CFPs had polyp tissues matched to CAPs based on polyp size, histology and dysplasia. To determine whether molecular features distinguish CAPs and CFPs, we conducted Whole Genome Sequencing, RNA-seq, and RRBS on over 90 tissues from 31 patients. CAPs had significantly more mutations, altered expression and hypermethylation compared to CFPs. APC was significantly mutated in both polyp groups, but mutations in TP53, FBXW7, PIK3CA, KIAA1804 and SMAD2 were exclusive to CAPs. We found significant expression changes between CAPs and CFPs in GREM1, IGF2, CTGF, and PLAU, and both expression and methylation alterations in FES and HES1. Integrative analyses revealed 124 genes with alterations in at least two platforms, and ERBB3 and E2F8 showed aberrations specific to CAPs across all platforms. These findings provide a resource of molecular distinctions between polyps with and without cancer, which have the potential to enhance the diagnosis, risk assessment and management of polyps.

Network-directed cis-mediator analysis of normal prostate tissue expression profiles reveals downstream regulatory associations of prostate cancer susceptibility loci

Large-scale genome-wide association studies have identified multiple single-nucleotide polymorphisms associated with risk of prostate cancer. Many of these genetic variants are presumed to be regulatory in nature; however, follow-up expression quantitative trait loci (eQTL) association studies have to-date been restricted largely to cis-acting associations due to study limitations. While trans-eQTL scans suffer from high testing dimensionality, recent evidence indicates most trans-eQTL associations are mediated by cis-regulated genes, such as transcription factors. Leveraging a data-driven gene co-expression network, we conducted a comprehensive cis-mediator analysis using RNA-Seq data from 471 normal prostate tissue samples to identify downstream regulatory associations of previously identified prostate cancer risk variants. We discovered multiple trans-eQTL associations that were significantly mediated by cis-regulated transcripts, four of which involved risk locus 17q12, proximal transcription factor HNF1B, and target trans-genes with known HNF response elements (MIA2, SRC, SEMA6A, KIF12). We additionally identified evidence of cis-acting down-regulation of MSMB via rs10993994 corresponding to reduced co-expression of NDRG1. The majority of these cis-mediator relationships demonstrated trans-eQTL replicability in 87 prostate tissue samples from the Gene-Tissue Expression Project. These findings provide further biological context to known risk loci and outline new hypotheses for investigation into the etiology of prostate cancer.

Adipose tissue DNA methylome changes in development of new-onset diabetes after kidney transplantation

AIM

New-onset diabetes after kidney transplant (NODAT) adversely impacts kidney allograft and patient survival. Epigenetic alterations in adipose tissue like DNA methylation may play a contributory role.

METHODS

Adipose tissue DNA of the patients with NODAT and their age, sex and BMI matched controls (nine each) were sequenced by reduced representation bisulfite sequencing. Differentially methylated CpGs (DMCs) and differentially methylated regions (DMRs) were studied.

RESULTS

Adipose tissue from the patients had reduced DNA methylation in intergenic and intronic regions. DMCs were found to be more hypomethylated in repeat regions and hypermethylated in CGIs and promoter region. About 900 DMRs were found and their associated genes were significantly enriched in 32 pathways, the top ones of which were associated with insulin resistance and inflammation. Some DMR or DMC genes have known T2DM associations.

CONCLUSION

Changes in DNA methylation in adipose tissue may be suggestive of future NODAT.

Germline miRNA DNA variants and the risk of colorectal cancer by subtype

MicroRNAs (miRNAs) regulate up to one-third of all protein-coding genes including genes relevant to cancer. Variants within miRNAs have been reported to be associated with prognosis, survival, response to chemotherapy across cancer types, in vitro parameters of cell growth, and altered risks for development of cancer. Five miRNA variants have been reported to be associated with risk for development of colorectal cancer (CRC). In this study, we evaluated germline genetic variation in 1,123 miRNAs in 899 individuals with CRCs categorized by clinical subtypes and in 204 controls. The role of common miRNA variation in CRC was investigated using single variant and miRNA-level association tests. Twenty-nine miRNAs and 30 variants exhibited some marginal association with CRC in at least one subtype of CRC. Previously reported associations were not confirmed (n = 4) or could not be evaluated (n = 1). The variants noted for the CRCs with deficient mismatch repair showed little overlap with the variants noted for CRCs with proficient mismatch repair, consistent with our evolving understanding of the distinct biology underlying these two groups. © 2016 The Authors Genes, Chromosomes & Cancer Published by Wiley Periodicals, Inc.

The Role of the Histone Methyltransferase Enhancer of Zeste Homolog 2 (EZH2) in the Pathobiological Mechanisms Underlying Inflammatory Bowel Disease (IBD)

Regulatory T (Treg) cells expressing the transcription factor FOXP3 play a pivotal role in maintaining immunologic self-tolerance. We and others have shown previously that EZH2 is recruited to the FOXP3 promoter and its targets in Treg cells. To further address the role for EZH2 in Treg cellular function, we have now generated mice that lack EZH2 specifically in Treg cells (EZH2^Δ/ΔFOXP3⁺). We find that EZH2 deficiency in FOXP3⁺ T cells results in lethal multiorgan autoimmunity. We further demonstrate that EZH2^Δ/ΔFOXP3⁺ T cells lack a regulatory phenotype in vitro and secrete proinflammatory cytokines. Of special interest, EZH2^Δ/ΔFOXP3⁺ mice develop spontaneous inflammatory bowel disease. Guided by these results, we assessed the FOXP3 and EZH2 gene networks by RNA sequencing in isolated intestinal CD4⁺ T cells from patients with Crohn's disease. Gene network analysis demonstrates that these CD4⁺ T cells display a Th1/Th17-like phenotype with an enrichment of gene targets shared by FOXP3 and EZH2. Combined, these results suggest that the inflammatory milieu found in Crohn's disease could lead to or result from deregulation of FOXP3/EZH2-enforced T cell gene networks contributing to the underlying intestinal inflammation.

REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants

The vast majority of coding variants are rare, and assessment of the contribution of rare variants to complex traits is hampered by low statistical power and limited functional data. Improved methods for predicting the pathogenicity of rare coding variants are needed to facilitate the discovery of disease variants from exome sequencing studies. We developed REVEL (rare exome variant ensemble learner), an ensemble method for predicting the pathogenicity of missense variants on the basis of individual tools: MutPred, FATHMM, VEST, PolyPhen, SIFT, PROVEAN, MutationAssessor, MutationTaster, LRT, GERP, SiPhy, phyloP, and phastCons. REVEL was trained with recently discovered pathogenic and rare neutral missense variants, excluding those previously used to train its constituent tools. When applied to two independent test sets, REVEL had the best overall performance (p < 10^-12) as compared to any individual tool and seven ensemble methods: MetaSVM, MetaLR, KGGSeq, Condel, CADD, DANN, and Eigen. Importantly, REVEL also had the best performance for distinguishing pathogenic from rare neutral variants with allele frequencies <0.5%. The area under the receiver operating characteristic curve (AUC) for REVEL was 0.046-0.182 higher in an independent test set of 935 recent SwissVar disease variants and 123,935 putatively neutral exome sequencing variants and 0.027-0.143 higher in an independent test set of 1,953 pathogenic and 2,406 benign variants recently reported in ClinVar than the AUCs for other ensemble methods. We provide pre-computed REVEL scores for all possible human missense variants to facilitate the identification of pathogenic variants in the sea of rare variants discovered as sequencing studies expand in scale.

Gene expression, methylation and neuropathology correlations at progressive supranuclear palsy risk loci

To determine the effects of single nucleotide polymorphisms (SNPs) identified in a genome-wide association study of progressive supranuclear palsy (PSP), we tested their association with brain gene expression, CpG methylation and neuropathology. In 175 autopsied PSP subjects, we performed associations between seven PSP risk variants and temporal cortex levels of 20 genes in-cis, within ±100 kb. Methylation measures were collected using reduced representation bisulfite sequencing in 43 PSP brains. To determine whether SNP/expression associations are due to epigenetic modifications, CpG methylation levels of associated genes were tested against relevant variants. Quantitative neuropathology endophenotypes were tested for SNP associations in 422 PSP subjects. Brain levels of LRRC37A4 and ARL17B were associated with rs8070723; MOBP with rs1768208 and both ARL17A and ARL17B with rs242557. Expression associations for LRRC37A4 and MOBP were available in an additional 100 PSP subjects. Meta-analysis revealed highly significant associations for PSP risk alleles of rs8070723 and rs1768208 with higher LRRC37A4 and MOBP brain levels, respectively. Methylation levels of one CpG in the 3' region of ARL17B associated with rs242557 and rs8070723. Additionally, methylation levels of an intronic ARL17A CpG associated with rs242557 and that of an intronic MOBP CpG with rs1768208. MAPT and MOBP region risk alleles also associated with higher levels of neuropathology. Strongest associations were observed for rs242557/coiled bodies and tufted astrocytes; and for rs1768208/coiled bodies and tau threads. These findings suggest that PSP variants at MAPT and MOBP loci may confer PSP risk via influencing gene expression and tau neuropathology. MOBP, LRRC37A4, ARL17A and ARL17B warrant further assessment as candidate PSP risk genes. Our findings have implications for the mechanism of action of variants at some of the top PSP risk loci.

Mutations in GANAB, Encoding the Glucosidase IIα Subunit, Cause Autosomal-Dominant Polycystic Kidney and Liver Disease

Autosomal-dominant polycystic kidney disease (ADPKD) is a common, progressive, adult-onset disease that is an important cause of end-stage renal disease (ESRD), which requires transplantation or dialysis. Mutations in PKD1 or PKD2 (∼85% and ∼15% of resolved cases, respectively) are the known causes of ADPKD. Extrarenal manifestations include an increased level of intracranial aneurysms and polycystic liver disease (PLD), which can be severe and associated with significant morbidity. Autosomal-dominant PLD (ADPLD) with no or very few renal cysts is a separate disorder caused by PRKCSH, SEC63, or LRP5 mutations. After screening, 7%-10% of ADPKD-affected and ∼50% of ADPLD-affected families were genetically unresolved (GUR), suggesting further genetic heterogeneity of both disorders. Whole-exome sequencing of six GUR ADPKD-affected families identified one with a missense mutation in GANAB, encoding glucosidase II subunit α (GIIα). Because PRKCSH encodes GIIβ, GANAB is a strong ADPKD and ADPLD candidate gene. Sanger screening of 321 additional GUR families identified eight further likely mutations (six truncating), and a total of 20 affected individuals were identified in seven ADPKD- and two ADPLD-affected families. The phenotype was mild PKD and variable, including severe, PLD. Analysis of GANAB-null cells showed an absolute requirement of GIIα for maturation and surface and ciliary localization of the ADPKD proteins (PC1 and PC2), and reduced mature PC1 was seen in GANAB(+/-) cells. PC1 surface localization in GANAB(-/-) cells was rescued by wild-type, but not mutant, GIIα. Overall, we show that GANAB mutations cause ADPKD and ADPLD and that the cystogenesis is most likely driven by defects in PC1 maturation.

Target-enrichment sequencing and copy number evaluation in inherited polyneuropathy

OBJECTIVE

To assess the efficiency of target-enrichment next-generation sequencing (NGS) with copy number assessment in inherited neuropathy diagnosis.

METHODS

A 197 polyneuropathy gene panel was designed to assess for mutations in 93 patients with inherited or idiopathic neuropathy without known genetic cause. We applied our novel copy number variation algorithm on NGS data, and validated the identified copy number mutations using CytoScan (Affymetrix). Cost and efficacy of this targeted NGS approach was compared to earlier evaluations.

RESULTS

Average coverage depth was ∼760× (median = 600, 99.4% > 100×). Among 93 patients, 18 mutations were identified in 17 cases (18%), including 3 copy number mutations: 2 PMP22 duplications and 1 MPZ duplication. The 2 patients with PMP22 duplication presented with bulbar and respiratory involvement and had absent extremity nerve conductions, leading to axonal diagnosis. Average onset age of these 17 patients was 25 years (2-61 years), vs 45 years for those without genetic discovery. Among those with onset age less than 40 years, the diagnostic yield of targeted NGS approach is high (27%) and cost savings is significant (∼20%). However, the cost savings for patients with late onset age and without family history is not demonstrated.

CONCLUSIONS

Incorporating copy number analysis in target-enrichment NGS approach improved the efficiency of mutation discovery for chronic, inherited, progressive length-dependent polyneuropathy diagnosis. The new technology is facilitating a simplified genetic diagnostic algorithm utilizing targeted NGS, clinical phenotypes, age at onset, and family history to improve diagnosis efficiency. Our findings prompt a need for updating the current practice parameters and payer guidelines.

Targeted alignment and end repair elimination increase alignment and methylation measure accuracy for reduced representation bisulfite sequencing data

Background

DNA methylation is an important epigenetic modification involved in many biological processes. Reduced representation bisulfite sequencing (RRBS) is a cost-effective method for studying DNA methylation at single base resolution. Although several tools are available for RRBS data processing and analysis, it is not clear which strategy performs the best and there has not been much attention to the contamination issue from artificial cytosines incorporated during the end repair step of library preparation. To address these issues, we describe a new method, Targeted Alignment and Artificial Cytosine Elimination for RRBS (TRACE-RRBS), which aligns bisulfite sequence reads to MSP1 digitally digested reference and specifically removes the end repair cytosines. We compared this approach on a simulated and a real dataset with 7 other RRBS analysis tools and Illumina 450 K microarray platform.

Results

TRACE-RRBS aligns sequence reads to a small fraction of the genome where RRBS protocol targets on and was demonstrated as the fastest, most sensitive and specific tool for the simulated dataset. For the real dataset, TRACE-RRBS took about the same time as RRBSMAP, a third to a sixth of time needed for BISMARK and NOVOALIGN. TRACE-RRBS aligned more reads uniquely than other tools and achieved the highest correlation with 450 k microarray data. The end repair artificial cytosine removal increased correlation between nearby CpGs and accuracy of methylation quantification.

Conclusions

TRACE-RRBS is fast and more accurate tool for RRBS data analysis. It is freely available for academic use at http://bioinformaticstools.mayo.edu/.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2494-8) contains supplementary material, which is available to authorized users.

Identification of candidate genes for prostate cancer-risk SNPs utilizing a normal prostate tissue eQTL data set

Multiple studies have identified loci associated with the risk of developing prostate cancer but the associated genes are not well studied. Here we create a normal prostate tissue-specific eQTL data set and apply this data set to previously identified prostate cancer (PrCa)-risk SNPs in an effort to identify candidate target genes. The eQTL data set is constructed by the genotyping and RNA sequencing of 471 samples. We focus on 146 PrCa-risk SNPs, including all SNPs in linkage disequilibrium with each risk SNP, resulting in 100 unique risk intervals. We analyse cis-acting associations where the transcript is located within 2 Mb (±1 Mb) of the risk SNP interval. Of all SNP–gene combinations tested, 41.7% of SNPs demonstrate a significant eQTL signal after adjustment for sample histology and 14 expression principal component covariates. Of the 100 PrCa-risk intervals, 51 have a significant eQTL signal and these are associated with 88 genes. This study provides a rich resource to study biological mechanisms underlying genetic risk to PrCa.

Single nucleotide polymorphisms—SNPs—have been identified for prostate cancer but whether these SNPs alter the expression of genes is largely unknown. In this study, the authors search for genes located within 2 Mb of the SNPs and identify SNPs that influence gene expression, so called expression quantitative trait loci.

Identification of differentially methylated regions in new genes associated with knee osteoarthritis

Epigenetic changes in articular chondrocytes are associated with osteoarthritis (OA) disease progression. Numerous studies have identified differentially methylated cytosines in OA tissues; however, the consequences of altered CpG methylation at single nucleotides on gene expression and phenotypes are difficult to predict. With the objective of detecting novel genes relevant to OA, we conducted a genome-wide assessment of differentially methylated sites (DMSs) and differentially methylated regions (DMRs). DNA was extracted from visually damaged and normal appearing, non-damaged human knee articular cartilage from the same joint and then subjected to reduced representation bisulfite sequencing. DMRs were identified using a genome-wide systematic bioinformatics approach. A sliding-window of 500 bp was used for screening the genome for regions with clusters of DMSs. Gene expression levels were assessed and cell culture demethylation experiments were performed to further examine top candidate genes associated with damaged articular cartilage. More than 1000 DMRs were detected in damaged osteoarthritic cartilage. Nineteen of these contained five or more DMSs and were located in gene promoters or first introns and exons. Gene expression assessment revealed that hypermethylated DMRs in damaged samples were more consistently associated with gene repression than hypomethylated DMRs were with gene activation. Accordingly, a demethylation agent induced expression of most hypermethylated genes in chondrocytes. Our study revealed the utility of a systematic DMR search as an alternative to focusing on single nucleotide data. In particular, this approach uncovered promising candidates for functional studies such as the hypermethylated protein-coding genes FOXP4 and SHROOM1, which appear to be linked to OA pathology in humans and warrant further investigation.

New DNA Methylation Markers for Pancreatic Cancer: Discovery, Tissue Validation, and Pilot Testing in Pancreatic Juice

PURPOSE

Discriminant markers for pancreatic cancer detection are needed. We sought to identify and validate methylated DNA markers for pancreatic cancer using next-generation sequencing unbiased by known targets.

EXPERIMENTAL DESIGN

At a referral center, we conducted four sequential case-control studies: discovery, technical validation, biologic validation, and clinical piloting. Candidate markers were identified using variance-inflated logistic regression on reduced-representation bisulfite DNA sequencing results from matched pancreatic cancers, benign pancreas, and normal colon tissues. Markers were validated technically on replicate discovery study DNA and biologically on independent, matched, blinded tissues by methylation-specific PCR. Clinical testing of six methylation candidates and mutant KRAS was performed on secretin-stimulated pancreatic juice samples from 61 patients with pancreatic cancer, 22 with chronic pancreatitis, and 19 with normal pancreas on endoscopic ultrasound. Areas under receiver-operating characteristics curves (AUC) for markers were calculated.

RESULTS

Sequencing identified >500 differentially hyper-methylated regions. On independent tissues, AUC on 19 selected markers ranged between 0.73 and 0.97. Pancreatic juice AUC values for CD1D, KCNK12, CLEC11A, NDRG4, IKZF1, PKRCB, and KRAS were 0.92*, 0.88, 0.85, 0.85, 0.84, 0.83, and 0.75, respectively, for pancreatic cancer compared with normal pancreas and 0.92*, 0.73, 0.76, 0.85*, 0.73, 0.77, and 0.62 for pancreatic cancer compared with chronic pancreatitis (*, P = 0.001 vs. KRAS).

CONCLUSIONS

We identified and validated novel DNA methylation markers strongly associated with pancreatic cancer. On pilot testing in pancreatic juice, best markers (especially CD1D) highly discriminated pancreatic cases from controls.

TP53 mutations, tetraploidy and homologous recombination repair defects in early stage high-grade serous ovarian cancer

To determine early somatic changes in high-grade serous ovarian cancer (HGSOC), we performed whole genome sequencing on a rare collection of 16 low stage HGSOCs. The majority showed extensive structural alterations (one had an ultramutated profile), exhibited high levels of p53 immunoreactivity, and harboured a TP53 mutation, deletion or inactivation. BRCA1 and BRCA2 mutations were observed in two tumors, with nine showing evidence of a homologous recombination (HR) defect. Combined Analysis with The Cancer Genome Atlas (TCGA) indicated that low and late stage HGSOCs have similar mutation and copy number profiles. We also found evidence that deleterious TP53 mutations are the earliest events, followed by deletions or loss of heterozygosity (LOH) of chromosomes carrying TP53, BRCA1 or BRCA2. Inactivation of HR appears to be an early event, as 62.5% of tumours showed a LOH pattern suggestive of HR defects. Three tumours with the highest ploidy had little genome-wide LOH, yet one of these had a homozygous somatic frame-shift BRCA2 mutation, suggesting that some carcinomas begin as tetraploid then descend into diploidy accompanied by genome-wide LOH. Lastly, we found evidence that structural variants (SV) cluster in HGSOC, but are absent in one ultramutated tumor, providing insights into the pathogenesis of low stage HGSOC.

DNA methylation profiling: comparison of genome-wide sequencing methods and the Infinium Human Methylation 450 Bead Chip

AIMS

To compare the performance of four sequence-based and one microarray methods for DNA methylation profiling.

METHODS

DNA from two cell lines were profiled by reduced representation bisulfite sequencing, methyl capture sequencing (SS-Meth Seq), NimbleGen SeqCapEpi CpGiant(Nimblegen MethSeq), methylated DNA immunoprecipitation (MeDIP) and the Human Methylation 450 Bead Chip (Meth450K).

RESULTS & CONCLUSION

Despite differences in genome-wide coverage, high correlation and concordance were observed between different methods. Significant overlap of differentially methylated regions was identified between sequenced-based platforms. MeDIP provided the best coverage for the whole genome and gene body regions, while RRBS and Nimblegen MethSeq were superior for CpGs in CpG islands and promoters. Methylation analyses can be achieved by any of the five methods but understanding their differences may better address the research question being posed.

Comprehensively evaluating cis-regulatory variation in the human prostate transcriptome by using gene-level allele-specific expression

The identification of cis-acting regulatory variation in primary tissues has the potential to elucidate the genetic basis of complex traits and further our understanding of transcriptomic diversity across cell types. Expression quantitative trait locus (eQTL) association analysis using RNA sequencing (RNA-seq) data can improve upon the detection of cis-acting regulatory variation by leveraging allele-specific expression (ASE) patterns in association analysis. Here, we present a comprehensive evaluation of cis-acting eQTLs by analyzing RNA-seq gene-expression data and genome-wide high-density genotypes from 471 samples of normal primary prostate tissue. Using statistical models that integrate ASE information, we identified extensive cis-eQTLs across the prostate transcriptome and found that approximately 70% of expressed genes corresponded to a significant eQTL at a gene-level false-discovery rate of 0.05. Overall, cis-eQTLs were heavily concentrated near the transcription start and stop sites of affected genes, and effects were negatively correlated with distance. We identified multiple instances of cis-acting co-regulation by using phased genotype data and discovered 233 SNPs as the most strongly associated eQTLs for more than one gene. We also noted significant enrichment (25/50, p = 2E-5) of previously reported prostate cancer risk SNPs in prostate eQTLs. Our results illustrate the benefit of assessing ASE data in cis-eQTL analyses by showing better reproducibility of prior eQTL findings than of eQTL mapping based on total expression alone. Altogether, our analysis provides extensive functional context of thousands of SNPs in prostate tissue, and these results will be of critical value in guiding studies examining disease of the human prostate.

The eSNV-detect: a computational system to identify expressed single nucleotide variants from transcriptome sequencing data

Rapid development of next generation sequencing technology has enabled the identification of genomic alterations from short sequencing reads. There are a number of software pipelines available for calling single nucleotide variants from genomic DNA but, no comprehensive pipelines to identify, annotate and prioritize expressed SNVs (eSNVs) from non-directional paired-end RNA-Seq data. We have developed the eSNV-Detect, a novel computational system, which utilizes data from multiple aligners to call, even at low read depths, and rank variants from RNA-Seq. Multi-platform comparisons with the eSNV-Detect variant candidates were performed. The method was first applied to RNA-Seq from a lymphoblastoid cell-line, achieving 99.7% precision and 91.0% sensitivity in the expressed SNPs for the matching HumanOmni2.5 BeadChip data. Comparison of RNA-Seq eSNV candidates from 25 ER+ breast tumors from The Cancer Genome Atlas (TCGA) project with whole exome coding data showed 90.6-96.8% precision and 91.6-95.7% sensitivity. Contrasting single-cell mRNA-Seq variants with matching traditional multicellular RNA-Seq data for the MD-MB231 breast cancer cell-line delineated variant heterogeneity among the single-cells. Further, Sanger sequencing validation was performed for an ER+ breast tumor with paired normal adjacent tissue validating 29 out of 31 candidate eSNVs. The source code and user manuals of the eSNV-Detect pipeline for Sun Grid Engine and virtual machine are available at http://bioinformaticstools.mayo.edu/research/esnv-detect/.

Comprehensive assessment of genetic variants within TCF4 in Fuchs' endothelial corneal dystrophy

PURPOSE

The single nucleotide variant (SNV), rs613872, in the transcription factor 4 (TCF4) gene was previously found to be strongly associated (P = 6 × 10(-26)) with Fuchs' endothelial corneal dystrophy (FECD). Subsequently, an intronic expansion of the repeating trinucleotides, TGC, was found to be even more predictive of disease. We performed comprehensive sequencing of the TCF4 gene region in order to identify the best marker for FECD within TCF4 and to identify other novel variants that may be associated with FECD.

METHODS

Leukocyte DNA was isolated from 68 subjects with FECD and 16 unaffected individuals. A custom capture panel was used to isolate the region surrounding the two previously validated markers of FECD. Sequencing of the TCF4 coding region, introns and flanking sequence, spanning 465 kb was performed at >1000× average coverage using the Illumina HiSequation 2000.

RESULTS

TGC expansion (>50 repeats) was present in 46 (68%) FECD-affected subjects and one (6%) normal subject. A total of 1866 variants, including 1540 SNVs, were identified. Only two previously reported SNVs resided in the TCF4 coding region, neither of which segregated with disease. No variant, including TGC expansion, correlated perfectly with disease status. Trinucleotide repeat expansion was a better predictor of disease than any other variant.

CONCLUSIONS

Complete sequencing of the TCF4 genomic region revealed no single causative variant for FECD. The intronic trinucleotide repeat expansion within TCF4 continues to be more strongly associated with FECD than any other genetic variant.

RVboost: RNA-seq variants prioritization using a boosting method

Motivation: RNA-seq has become the method of choice to quantify genes and exons, discover novel transcripts and detect fusion genes. However, reliable variant identification from RNA-seq data remains challenging because of the complexities of the transcriptome, the challenges of accurately mapping exon boundary spanning reads and the bias introduced during the sequencing library preparation.

Method: We developed RVboost, a novel method specific for RNA variant prioritization. RVboost uses several attributes unique in the process of RNA library preparation, sequencing and RNA-seq data analyses. It uses a boosting method to train a model of ‘good quality’ variants using common variants from HapMap, and prioritizes and calls the RNA variants based on the trained model. We packaged RVboost in a comprehensive workflow, which integrates tools of variant calling, annotation and filtering.

Results: RVboost consistently outperforms the variant quality score recalibration from the Genome Analysis Tool Kit and the RNA-seq variant-calling pipeline SNPiR in 12 RNA-seq samples using ground-truth variants from paired exome sequencing data. Several RNA-seq–specific attributes were identified as critical to differentiate true and false variants, including the distance of the variant positions to exon boundaries, and the percent of the reads supporting the variant in the first six base pairs. The latter identifies false variants introduced by the random hexamer priming during the library construction.

Availability and implementation: The RVboost package is implemented to readily run in Mac or Linux environments. The software and user manual are available at http://bioinformaticstools.mayo.edu/research/rvboost/.

Supplementary information:Supplementary data are available at Bioinformatics online.

Aberrant signature methylome by DNMT1 hot spot mutation in hereditary sensory and autonomic neuropathy 1E

DNA methyltransferase 1 (DNMT1) is essential for DNA methylation, gene regulation and chromatin stability. We previously discovered DNMT1 mutations cause hereditary sensory and autonomic neuropathy type 1 with dementia and hearing loss (HSAN1E; OMIM 614116). HSAN1E is the first adult-onset neurodegenerative disorder caused by a defect in a methyltransferase gene. HSAN1E patients appear clinically normal until young adulthood, then begin developing the characteristic symptoms involving central and peripheral nervous systems. Some HSAN1E patients also develop narcolepsy and it has recently been suggested that HSAN1E is allelic to autosomal dominant cerebellar ataxia, deafness, with narcolepsy (ADCA-DN; OMIM 604121), which is also caused by mutations in DNMT1. A hotspot mutation Y495C within the targeting sequence domain of DNMT1 has been identified among HSAN1E patients. The mutant DNMT1 protein shows premature degradation and reduced DNA methyltransferase activity. Herein, we investigate genome-wide DNA methylation at single-base resolution through whole-genome bisulfite sequencing of germline DNA in 3 pairs of HSAN1E patients and their gender- and age-matched siblings. Over 1 billion 75-bp single-end reads were generated for each sample. In the 3 affected siblings, overall methylation loss was consistently found in all chromosomes with X and 18 being most affected. Paired sample analysis identified 564,218 differentially methylated CpG sites (DMCs; P<0.05), of which 300 134 were intergenic and 264 084 genic CpGs. Hypomethylation was predominant in both genic and intergenic regions, including promoters, exons, most CpG islands, L1, L2, Alu, and satellite repeats and simple repeat sequences. In some CpG islands, hypermethylated CpGs outnumbered hypomethylated CpGs. In 201 imprinted genes, there were more DMCs than in non-imprinted genes and most were hypomethylated. Differentially methylated region (DMR) analysis identified 5649 hypomethylated and 1872 hypermethylated regions. Importantly, pathway analysis revealed 1693 genes associated with the identified DMRs were highly associated in diverse neurological disorders and NAD+/NADH metabolism pathways is implicated in the pathogenesis. Our results provide novel insights into the epigenetic mechanism of neurodegeneration arising from a hotspot DNMT1 mutation and reveal pathways potentially important in a broad category of neurological and psychological disorders.

MAP-RSeq: Mayo Analysis Pipeline for RNA sequencing

Background

Although the costs of next generation sequencing technology have decreased over the past years, there is still a lack of simple-to-use applications, for a comprehensive analysis of RNA sequencing data. There is no one-stop shop for transcriptomic genomics. We have developed MAP-RSeq, a comprehensive computational workflow that can be used for obtaining genomic features from transcriptomic sequencing data, for any genome.

Results

For optimization of tools and parameters, MAP-RSeq was validated using both simulated and real datasets. MAP-RSeq workflow consists of six major modules such as alignment of reads, quality assessment of reads, gene expression assessment and exon read counting, identification of expressed single nucleotide variants (SNVs), detection of fusion transcripts, summarization of transcriptomics data and final report. This workflow is available for Human transcriptome analysis and can be easily adapted and used for other genomes. Several clinical and research projects at the Mayo Clinic have applied the MAP-RSeq workflow for RNA-Seq studies. The results from MAP-RSeq have thus far enabled clinicians and researchers to understand the transcriptomic landscape of diseases for better diagnosis and treatment of patients.

Conclusions

Our software provides gene counts, exon counts, fusion candidates, expressed single nucleotide variants, mapping statistics, visualizations, and a detailed research data report for RNA-Seq. The workflow can be executed on a standalone virtual machine or on a parallel Sun Grid Engine cluster. The software can be downloaded from http://bioinformaticstools.mayo.edu/research/maprseq/.

From days to hours: reporting clinically actionable variants from whole genome sequencing

As the cost of whole genome sequencing (WGS) decreases, clinical laboratories will be looking at broadly adopting this technology to screen for variants of clinical significance. To fully leverage this technology in a clinical setting, results need to be reported quickly, as the turnaround rate could potentially impact patient care. The latest sequencers can sequence a whole human genome in about 24 hours. However, depending on the computing infrastructure available, the processing of data can take several days, with the majority of computing time devoted to aligning reads to genomics regions that are to date not clinically interpretable. In an attempt to accelerate the reporting of clinically actionable variants, we have investigated the utility of a multi-step alignment algorithm focused on aligning reads and calling variants in genomic regions of clinical relevance prior to processing the remaining reads on the whole genome. This iterative workflow significantly accelerates the reporting of clinically actionable variants with no loss of accuracy when compared to genotypes obtained with the OMNI SNP platform or to variants detected with a standard workflow that combines Novoalign and GATK.

Reservoir complete denture in a patient with xerostomia secondary to radiotherapy for oral carcinoma: A case report and review of literature

Xerostomia refers to a subjective sensation of dry mouth. A variety of factors can cause xerostomia including radiotherapy (RT) given for the treatment of oral carcinoma. Depending on the cause, treatment is provided to a patient suffering from xerostomia. In severe xerostomia salivary substitutes can be used and if the xerostomic patient is edentulous, then reservoir space for artificial salivary substitute can be created in partial as well as complete upper or lower dentures. The methods advocated so far for incorporating reservoir space in mandibular complete denture are costly, time consuming and require extra-laboratory steps. Therefore, the purpose of this article is to report a simpler method for fabrication of mandibular reservoir denture in a 67-year-old edentulous male patient suffering from xerostomia due to RT for oral carcinoma.

SoftSearch: integration of multiple sequence features to identify breakpoints of structural variations

Background

Structural variation (SV) represents a significant, yet poorly understood contribution to an individual’s genetic makeup. Advanced next-generation sequencing technologies are widely used to discover such variations, but there is no single detection tool that is considered a community standard. In an attempt to fulfil this need, we developed an algorithm, SoftSearch, for discovering structural variant breakpoints in Illumina paired-end next-generation sequencing data. SoftSearch combines multiple strategies for detecting SV including split-read, discordant read-pair, and unmated pairs. Co-localized split-reads and discordant read pairs are used to refine the breakpoints.

Results

We developed and validated SoftSearch using real and synthetic datasets. SoftSearch’s key features are 1) not requiring secondary (or exhaustive primary) alignment, 2) portability into established sequencing workflows, and 3) is applicable to any DNA-sequencing experiment (e.g. whole genome, exome, custom capture, etc.). SoftSearch identifies breakpoints from a small number of soft-clipped bases from split reads and a few discordant read-pairs which on their own would not be sufficient to make an SV call.

Conclusions

We show that SoftSearch can identify more true SVs by combining multiple sequence features. SoftSearch was able to call clinically relevant SVs in the BRCA2 gene not reported by other tools while offering significantly improved overall performance.

Abstract 3185: The eSNV-Detect: a computational system to identify expressed single nucleotide variants from tumor transcriptomes

MOTIVATION: Transcriptome sequencing (RNA-seq) is the most economical and information-rich next generation sequencing technology to study genomic medicine. Genomic features such as gene expression, transcript expression, fusion transcripts, long non-coding RNAs and expressed single nucleotide variants (eSNVs) can be obtained from RNA-seq data. There are several computational workflows to obtain gene counts, transcript counts and fusion gene candidates, but not a comprehensive system to identify expressed SNVs from RNA-sequencing data.

METHODS: We have developed a novel computational system (The eSNV-Detect) with parallel alignment strategies to identify expressed SNVs accurately from tumor transcriptome sequencing data. Sequence-based features like reads supporting reference allele, alternate allele, ratio of alternate reads to total read depth, base qualities, mapping qualities, forward strand and reverse strand supporting reads etc. along with a variety of databases such as dbSNP, 1000 genome, 5400 exome, refGene, avsift, ljb_phylop from UCSC were used to call SNVs from RNA-sequencing data. For the expressed SNVs detected in tumors, we can also identify the amino acid change and classify the protein domains using our method.

RESULTS: We have applied the eSNV-Detect method to call novel expressed SNVs in two tumors (one HER2 positive and one ER positive breast tumor). BWA and Bowtie were used to align the two breast tumors. Several filtering criteria's were applied to the tumors to remove any known (germ line) or low confidence SNVs. We randomly selected 83 and 31 eSNVs for the HER2 and ER positive tumors respectively and performed Sanger sequencing validation in tumor and matched normal tissues of the tumor. We were able to validate 81 out of 83 eSNVs in the HER2 tumor sample, and 29 out of 31 eSNVs in the ER positive tumor sample. Of the eSNVs that we validated 39/81 and 10/31 were localized to functional protein domains in HER2 and ER positive tumors respectively. We are also in the process of validating eSNVs detected from RNA-seq with the tumor and blood exome sequencing data we have for the same patients.

Citation Format: Xiaojia Tang, Saurabh Baheti, Khader Shameer, Kevin J. Thompson, Jean-Pierre Kocher, Edith A. Perez, Aubrey E. Thompson, Krishna R. Kalari. The eSNV-Detect: a computational system to identify expressed single nucleotide variants from tumor transcriptomes. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3185. doi:10.1158/1538-7445.AM2013-3185

SAAP-RRBS: streamlined analysis and annotation pipeline for reduced representation bisulfite sequencing

Reduced representation bisulfite sequencing (RRBS) is a cost-effective approach for genome-wide methylation pattern profiling. Analyzing RRBS sequencing data is challenging and specialized alignment/mapping programs are needed. Although such programs have been developed, a comprehensive solution that provides researchers with good quality and analyzable data is still lacking. To address this need, we have developed a Streamlined Analysis and Annotation Pipeline for RRBS data (SAAP-RRBS) that integrates read quality assessment/clean-up, alignment, methylation data extraction, annotation, reporting and visualization. This package facilitates a rapid transition from sequencing reads to a fully annotated CpG methylation report to biological interpretation.

AVAILABILITY AND IMPLEMENTATION

SAAP-RRBS is freely available to non-commercial users at the web site http://ndc.mayo.edu/mayo/research/biostat/stand-alone-packages.cfm.

Abstract 4926: Modeling the transcriptome landscape of HER2+ breast cancer

Motivation: Overexpression of HER2 (the product of the ERBB2 gene) occurs in about 15% of all breast tumors. We have undertaken to use next generation transcriptome sequencing technology to identify genomic features that are unique to HER2+ tumors. Interactome mapping was then used to integrate the genes associated with these features into a transcriptome landscape model, with a view towards identifying nodes of interaction that might be targeted in HER2+ tumors. Methods: We performed 50nt paired-end RNA-sequencing for 24 breast tumors: 8 each HER2+, ER+, triple negatives (TN). In addition to breast adenocarcinomas, we also sequenced 8 early passage non-transformed HMEC cell lines as normal controls. Reads from RNA sequencing were aligned to the genome and exon junctions using TopHat software. Gene counts were summarized and annotations were performed using our in-house programs. Tukey's test was used to obtain genes or transcripts that are specific to HER2 tumor group compared to other tumors/normal. A combination of bioinformatics softwares and algorithms were used to identify SNVs. Results: Only 13527 genes with median gene count greater than 16 reads in at least one of the 4 groups were considered for differential gene expression and splicing analysis. Some 696 genes were differentially expressed in HER2+ tumors compared to ER+, TN tumors and HMECs. We identified 272 alternately spliced transcripts for which the HER2+ tumors exhibited a mean transcript expression ratio significantly different from the means of other tumor groups. We also identified 4735 expressed single nucleotide variants that are uniquely associated with HER2+ tumors compared to other tumors/normal groups. Among these 3579/4735 sequence polymorphisms were not present in the 1000 genome germline sequence database or in the dbSNP132 database of naturally occurring germline polymorphisms. Integration of all the genes obtained from genomic feature analyses (differential expression, alternative splicing, single nucleotide variance) has been carried out to indentify biological processes that are specific to the HER2+ tumor subtype. Key nodes and pathways that are specific to HER2+ tumors will be evaluated for association with clinical outcome in a large series of patients who have received HER2-targeted therapy.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4926. doi:1538-7445.AM2012-4926

Deep Sequence Analysis of Non-Small Cell Lung Cancer: Integrated Analysis of Gene Expression, Alternative Splicing, and Single Nucleotide Variations in Lung Adenocarcinomas with and without Oncogenic KRAS Mutations

KRAS mutations are highly prevalent in non-small cell lung cancer (NSCLC), and tumors harboring these mutations tend to be aggressive and resistant to chemotherapy. We used next-generation sequencing technology to identify pathways that are specifically altered in lung tumors harboring a KRAS mutation. Paired-end RNA-sequencing of 15 primary lung adenocarcinoma tumors (8 harboring mutant KRAS and 7 with wild-type KRAS) were performed. Sequences were mapped to the human genome, and genomic features, including differentially expressed genes, alternate splicing isoforms and single nucleotide variants, were determined for tumors with and without KRAS mutation using a variety of computational methods. Network analysis was carried out on genes showing differential expression (374 genes), alternate splicing (259 genes), and SNV-related changes (65 genes) in NSCLC tumors harboring a KRAS mutation. Genes exhibiting two or more connections from the lung adenocarcinoma network were used to carry out integrated pathway analysis. The most significant signaling pathways identified through this analysis were the NFκB, ERK1/2, and AKT pathways. A 27 gene mutant KRAS-specific sub network was extracted based on gene-gene connections from the integrated network, and interrogated for druggable targets. Our results confirm previous evidence that mutant KRAS tumors exhibit activated NFκB, ERK1/2, and AKT pathways and may be preferentially sensitive to target therapeutics toward these pathways. In addition, our analysis indicates novel, previously unappreciated links between mutant KRAS and the TNFR and PPARγ signaling pathways, suggesting that targeted PPARγ antagonists and TNFR inhibitors may be useful therapeutic strategies for treatment of mutant KRAS lung tumors. Our study is the first to integrate genomic features from RNA-Seq data from NSCLC and to define a first draft genomic landscape model that is unique to tumors with oncogenic KRAS mutations.

TREAT: a bioinformatics tool for variant annotations and visualizations in targeted and exome sequencing data

TREAT (Targeted RE-sequencing Annotation Tool) is a tool for facile navigation and mining of the variants from both targeted resequencing and whole exome sequencing. It provides a rich integration of publicly available as well as in-house developed annotations and visualizations for variants, variant-hosting genes and host-gene pathways.

AVAILABILITY AND IMPLEMENTATION

TREAT is freely available to non-commercial users as either a stand-alone annotation and visualization tool, or as a comprehensive workflow integrating sequencing alignment and variant calling. The executables, instructions and the Amazon Cloud Images of TREAT can be downloaded at the website: http://ndc.mayo.edu/mayo/research/biostat/stand-alone-packages.cfm.