Interchange reconnection as the source of the fast solar wind within coronal holes

The fast solar wind that fills the heliosphere originates from deep within regions of open magnetic field on the Sun called 'coronal holes'. The energy source responsible for accelerating the plasma is widely debated; however, there is evidence that it is ultimately magnetic in nature, with candidate mechanisms including wave heating^1,2 and interchange reconnection^3-5. The coronal magnetic field near the solar surface is structured on scales associated with 'supergranulation' convection cells, whereby descending flows create intense fields. The energy density in these 'network' magnetic field bundles is a candidate energy source for the wind. Here we report measurements of fast solar wind streams from the Parker Solar Probe (PSP) spacecraft⁶ that provide strong evidence for the interchange reconnection mechanism. We show that the supergranulation structure at the coronal base remains imprinted in the near-Sun solar wind, resulting in asymmetric patches of magnetic 'switchbacks'^7,8 and bursty wind streams with power-law-like energetic ion spectra to beyond 100 keV. Computer simulations of interchange reconnection support key features of the observations, including the ion spectra. Important characteristics of interchange reconnection in the low corona are inferred from the data, including that the reconnection is collisionless and that the energy release rate is sufficient to power the fast wind. In this scenario, magnetic reconnection is continuous and the wind is driven by both the resulting plasma pressure and the radial Alfvénic flow bursts.

Bam-readcount - rapid generation of basepair-resolution sequence metrics

Bam-readcount is a utility for generating low-level information about sequencing data at specific nucleotide positions. Originally designed to help filter genomic mutation calls, the metrics it outputs are useful as input for variant detection tools and for resolving ambiguity between variant callers1,2. In addition, it has found broad applicability in diverse fields including tumor evolution, single-cell genomics, climate change ecology, and tracking community spread of SARS-CoV-2.3-6.

Association of structural variation with cardiometabolic traits in Finns

The contribution of genome structural variation (SV) to quantitative traits associated with cardiometabolic diseases remains largely unknown. Here, we present the results of a study examining genetic association between SVs and cardiometabolic traits in the Finnish population. We used sensitive methods to identify and genotype 129,166 high-confidence SVs from deep whole-genome sequencing (WGS) data of 4,848 individuals. We tested the 64,572 common and low-frequency SVs for association with 116 quantitative traits and tested candidate associations using exome sequencing and array genotype data from an additional 15,205 individuals. We discovered 31 genome-wide significant associations at 15 loci, including 2 loci at which SVs have strong phenotypic effects: (1) a deletion of the ALB promoter that is greatly enriched in the Finnish population and causes decreased serum albumin level in carriers (p = 1.47 × 10-54) and is also associated with increased levels of total cholesterol (p = 1.22 × 10-28) and 14 additional cholesterol-related traits, and (2) a multi-allelic copy number variant (CNV) at PDPR that is strongly associated with pyruvate (p = 4.81 × 10-21) and alanine (p = 6.14 × 10-12) levels and resides within a structurally complex genomic region that has accumulated many rearrangements over evolutionary time. We also confirmed six previously reported associations, including five led by stronger signals in single nucleotide variants (SNVs) and one linking recurrent HP gene deletion and cholesterol levels (p = 6.24 × 10-10), which was also found to be strongly associated with increased glycoprotein level (p = 3.53 × 10-35). Our study confirms that integrating SVs in trait-mapping studies will expand our knowledge of genetic factors underlying disease risk.

Mapping and characterization of structural variation in 17,795 human genomes

A key goal of whole-genome sequencing for studies of human genetics is to interrogate all forms of variation, including single-nucleotide variants, small insertion or deletion (indel) variants and structural variants. However, tools and resources for the study of structural variants have lagged behind those for smaller variants. Here we used a scalable pipeline1 to map and characterize structural variants in 17,795 deeply sequenced human genomes. We publicly release site-frequency data to create the largest, to our knowledge, whole-genome-sequencing-based structural variant resource so far. On average, individuals carry 2.9 rare structural variants that alter coding regions; these variants affect the dosage or structure of 4.2 genes and account for 4.0-11.2% of rare high-impact coding alleles. Using a computational model, we estimate that structural variants account for 17.2% of rare alleles genome-wide, with predicted deleterious effects that are equivalent to loss-of-function coding alleles; approximately 90% of such structural variants are noncoding deletions (mean 19.1 per genome). We report 158,991 ultra-rare structural variants and show that 2% of individuals carry ultra-rare megabase-scale structural variants, nearly half of which are balanced or complex rearrangements. Finally, we infer the dosage sensitivity of genes and noncoding elements, and reveal trends that relate to element class and conservation. This work will help to guide the analysis and interpretation of structural variants in the era of whole-genome sequencing.

The clonal evolution of metastatic colorectal cancer

Tumor heterogeneity and evolution drive treatment resistance in metastatic colorectal cancer (mCRC). Patient-derived xenografts (PDXs) can model mCRC biology; however, their ability to accurately mimic human tumor heterogeneity is unclear. Current genomic studies in mCRC have limited scope and lack matched PDXs. Therefore, the landscape of tumor heterogeneity and its impact on the evolution of metastasis and PDXs remain undefined. We performed whole-genome, deep exome, and targeted validation sequencing of multiple primary regions, matched distant metastases, and PDXs from 11 patients with mCRC. We observed intricate clonal heterogeneity and evolution affecting metastasis dissemination and PDX clonal selection. Metastasis formation followed both monoclonal and polyclonal seeding models. In four cases, metastasis-seeding clones were not identified in any primary region, consistent with a metastasis-seeding-metastasis model. PDXs underrepresented the subclonal heterogeneity of parental tumors. These suggest that single sample tumor sequencing and current PDX models may be insufficient to guide precision medicine.

Alfvénic velocity spikes and rotational flows in the near-Sun solar wind

The prediction of a supersonic solar wind¹ was first confirmed by spacecraft near Earth^2,3 and later by spacecraft at heliocentric distances as small as 62 solar radii⁴. These missions showed that plasma accelerates as it emerges from the corona, aided by unidentified processes that transport energy outwards from the Sun before depositing it in the wind. Alfvénic fluctuations are a promising candidate for such a process because they are seen in the corona and solar wind and contain considerable energy^5-7. Magnetic tension forces the corona to co-rotate with the Sun, but any residual rotation far from the Sun reported until now has been much smaller than the amplitude of waves and deflections from interacting wind streams⁸. Here we report observations of solar-wind plasma at heliocentric distances of about 35 solar radii^9-11, well within the distance at which stream interactions become important. We find that Alfvén waves organize into structured velocity spikes with duration of up to minutes, which are associated with propagating S-like bends in the magnetic-field lines. We detect an increasing rotational component to the flow velocity of the solar wind around the Sun, peaking at 35 to 50 kilometres per second-considerably above the amplitude of the waves. These flows exceed classical velocity predictions of a few kilometres per second, challenging models of circulation in the corona and calling into question our understanding of how stars lose angular momentum and spin down as they age^12-14.

Author Correction: Exome sequencing of Finnish isolates enhances rare-variant association power

An Amendment to this paper has been published and can be accessed via a link at the top of the paper.

svtools: population-scale analysis of structural variation

SUMMARY

Large-scale human genetics studies are now employing whole genome sequencing with the goal of conducting comprehensive trait mapping analyses of all forms of genome variation. However, methods for structural variation (SV) analysis have lagged far behind those for smaller scale variants, and there is an urgent need to develop more efficient tools that scale to the size of human populations. Here, we present a fast and highly scalable software toolkit (svtools) and cloud-based pipeline for assembling high quality SV maps-including deletions, duplications, mobile element insertions, inversions and other rearrangements-in many thousands of human genomes. We show that this pipeline achieves similar variant detection performance to established per-sample methods (e.g. LUMPY), while providing fast and affordable joint analysis at the scale of ≥100 000 genomes. These tools will help enable the next generation of human genetics studies.

AVAILABILITY AND IMPLEMENTATION

svtools is implemented in Python and freely available (MIT) from https://github.com/hall-lab/svtools.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Exome sequencing of Finnish isolates enhances rare-variant association power

Exome-sequencing studies have generally been underpowered to identify deleterious alleles with a large effect on complex traits as such alleles are mostly rare. Because the population of northern and eastern Finland has expanded considerably and in isolation following a series of bottlenecks, individuals of these populations have numerous deleterious alleles at a relatively high frequency. Here, using exome sequencing of nearly 20,000 individuals from these regions, we investigate the role of rare coding variants in clinically relevant quantitative cardiometabolic traits. Exome-wide association studies for 64 quantitative traits identified 26 newly associated deleterious alleles. Of these 26 alleles, 19 are either unique to or more than 20 times more frequent in Finnish individuals than in other Europeans and show geographical clustering comparable to Mendelian disease mutations that are characteristic of the Finnish population. We estimate that sequencing studies of populations without this unique history would require hundreds of thousands to millions of participants to achieve comparable association power.

Functional equivalence of genome sequencing analysis pipelines enables harmonized variant calling across human genetics projects

Hundreds of thousands of human whole genome sequencing (WGS) datasets will be generated over the next few years. These data are more valuable in aggregate: joint analysis of genomes from many sources increases sample size and statistical power. A central challenge for joint analysis is that different WGS data processing pipelines cause substantial differences in variant calling in combined datasets, necessitating computationally expensive reprocessing. This approach is no longer tenable given the scale of current studies and data volumes. Here, we define WGS data processing standards that allow different groups to produce functionally equivalent (FE) results, yet still innovate on data processing pipelines. We present initial FE pipelines developed at five genome centers and show that they yield similar variant calling results and produce significantly less variability than sequencing replicates. This work alleviates a key technical bottleneck for genome aggregation and helps lay the foundation for community-wide human genetics studies.

Sharing of whole genome sequencing (WGS) data improves study scale and power, but data from different groups are often incompatible. Here, US genome centers and NIH programs define WGS data processing standards and a flexible validation method, facilitating collaboration in human genetics research.

Truncating Prolactin Receptor Mutations Promote Tumor Growth in Murine Estrogen Receptor-Alpha Mammary Carcinomas

Estrogen receptor alpha-positive (ERα+) luminal tumors are the most frequent subtype of breast cancer. Stat1(-/-) mice develop mammary tumors that closely recapitulate the biological characteristics of this cancer subtype. To identify transforming events that contribute to tumorigenesis, we performed whole genome sequencing of Stat1(-/-) primary mammary tumors and matched normal tissues. This investigation identified somatic truncating mutations affecting the prolactin receptor (PRLR) in all tumor and no normal samples. Targeted sequencing confirmed the presence of these mutations in precancerous lesions, indicating that this is an early event in tumorigenesis. Functional evaluation of these heterozygous mutations in Stat1(-/-) mouse embryonic fibroblasts showed that co-expression of truncated and wild-type PRLR led to aberrant STAT3 and STAT5 activation downstream of the receptor, cellular transformation in vitro, and tumor formation in vivo. In conclusion, truncating mutations of PRLR promote tumor growth in a model of human ERα+ breast cancer and warrant further investigation.

Comprehensive discovery of noncoding RNAs in acute myeloid leukemia cell transcriptomes

To detect diverse and novel RNA species comprehensively, we compared deep small RNA and RNA sequencing (RNA-seq) methods applied to a primary acute myeloid leukemia (AML) sample. We were able to discover previously unannotated small RNAs using deep sequencing of a library method using broader insert size selection. We analyzed the long noncoding RNA (lncRNA) landscape in AML by comparing deep sequencing from multiple RNA-seq library construction methods for the sample that we studied and then integrating RNA-seq data from 179 AML cases. This identified lncRNAs that are completely novel, differentially expressed, and associated with specific AML subtypes. Our study revealed the complexity of the noncoding RNA transcriptome through a combined strategy of strand-specific small RNA and total RNA-seq. This dataset will serve as an invaluable resource for future RNA-based analyses.

Brief Report: The Role of Rare Protein-Coding Variants in Anti-Tumor Necrosis Factor Treatment Response in Rheumatoid Arthritis

OBJECTIVE

In many rheumatoid arthritis (RA) patients, disease is controlled with anti-tumor necrosis factor (anti-TNF) biologic therapies. However, in a significant number of patients, the disease fails to respond to anti-TNF therapy. We undertook the present study to examine the hypothesis that rare and low-frequency genetic variants might influence response to anti-TNF treatment.

METHODS

We sequenced the coding region of 750 genes in 1,094 RA patients of European ancestry who were treated with anti-TNF. After quality control, 690 genes were included in the analysis. We applied single-variant association and gene-based association tests to identify variants associated with anti-TNF treatment response. In addition, given the key mechanistic role of TNF, we performed gene set analyses of 27 TNF pathway genes.

RESULTS

We identified 14,420 functional variants, of which 6,934 were predicted as nonsynonymous 2,136 of which were further predicted to be "damaging." Despite the fact that the study was well powered, no single variant or gene showed study-wide significant association with change in the outcome measures disease activity or European League Against Rheumatism response. Intriguingly, we observed 3 genes, of 27 with nominal signals of association (P < 0.05), that were involved in the TNF signaling pathway. However, when we performed a rigorous gene set enrichment analysis based on association P value ranking, we observed no evidence of enrichment of association at genes involved in the TNF pathway (P_enrichment  = 0.15, based on phenotype permutations).

CONCLUSION

Our findings suggest that rare and low-frequency protein-coding variants in TNF signaling pathway genes or other genes do not contribute substantially to anti-TNF treatment response in patients with RA.

Rare Variation in TET2 Is Associated with Clinically Relevant Prostate Carcinoma in African Americans

BACKGROUND

Common variants have been associated with prostate cancer risk. Unfortunately, few are reproducibly linked to aggressive disease, the phenotype of greatest clinical relevance. One possible explanation is that rare genetic variants underlie a significant proportion of the risk for aggressive disease.

METHOD

To identify such variants, we performed a two-stage approach using whole-exome sequencing followed by targeted sequencing of 800 genes in 652 aggressive prostate cancer patients and 752 disease-free controls in both African and European Americans. In each population, we tested rare variants for association using two gene-based aggregation tests. We established a study-wide significance threshold of 3.125 × 10^-5 to correct for multiple testing.

RESULTS

TET2 in African Americans was associated with aggressive disease, with 24.4% of cases harboring a rare deleterious variant compared with 9.6% of controls (FET P = 1.84 × 10^-5, OR = 3.0; SKAT-O P = 2.74 × 10^-5). We report 8 additional genes with suggestive evidence of association, including the DNA repair genes PARP2 and MSH6 Finally, we observed an excess of rare truncation variants in 5 genes, including the DNA repair genes MSH6, BRCA1, and BRCA2 This adds to the growing body of evidence that DNA repair pathway defects may influence susceptibility to aggressive prostate cancer.

CONCLUSIONS

Our findings suggest that rare variants influence risk of clinically relevant prostate cancer and, if validated, could serve to identify men for screening, prophylaxis, and treatment.

IMPACT

This study provides evidence that rare variants in TET2 may help identify African American men at increased risk for clinically relevant prostate cancer. Cancer Epidemiol Biomarkers Prev; 25(11); 1456-63. ©2016 AACR.

Using VarScan 2 for Germline Variant Calling and Somatic Mutation Detection

The identification of small sequence variants remains a challenging but critical step in the analysis of next-generation sequencing data. Our variant calling tool, VarScan 2, employs heuristic and statistic thresholds based on user-defined criteria to call variants using SAMtools mpileup data as input. Here, we provide guidelines for generating that input, and describe protocols for using VarScan 2 to (1) identify germline variants in individual samples; (2) call somatic mutations, copy number alterations, and LOH events in tumor-normal pairs; and (3) identify germline variants, de novo mutations, and Mendelian inheritance errors in family trios. Further, we describe a strategy for variant filtering that removes likely false positives associated with common sequencing- and alignment-related artifacts.

Using SomaticSniper to Detect Somatic Single Nucleotide Variants

Detecting somatic single nucleotide variants (SNVs) is an essential component of cancer research with next generation sequencing data. This protocol describes how to run the SomaticSniper somatic SNV detector and then filter the output to eliminate most false positives. It also includes support protocols detailing the compilation of the software.

Comprehensive genomic analysis reveals FLT3 activation and a therapeutic strategy for a patient with relapsed adult B-lymphoblastic leukemia

The genomic events responsible for the pathogenesis of relapsed adult B-lymphoblastic leukemia (B-ALL) are not yet clear. We performed integrative analysis of whole-genome, whole-exome, custom capture, whole-transcriptome (RNA-seq), and locus-specific genomic assays across nine time points from a patient with primary de novo B-ALL. Comprehensive genome and transcriptome characterization revealed a dramatic tumor evolution during progression, yielding a tumor with complex clonal architecture at second relapse. We observed and validated point mutations in EP300 and NF1, a highly expressed EP300-ZNF384 gene fusion, a microdeletion in IKZF1, a focal deletion affecting SETD2, and large deletions affecting RB1, PAX5, NF1, and ETV6. Although the genome analysis revealed events of potential biological relevance, no clinically actionable treatment options were evident at the time of the second relapse. However, transcriptome analysis identified aberrant overexpression of the targetable protein kinase encoded by the FLT3 gene. Although the patient had refractory disease after salvage therapy for the second relapse, treatment with the FLT3 inhibitor sunitinib rapidly induced a near complete molecular response, permitting the patient to proceed to a matched-unrelated donor stem cell transplantation. The patient remains in complete remission more than 4 years later. Analysis of this patient's relapse genome revealed an unexpected, actionable therapeutic target that led to a specific therapy associated with a rapid clinical response. For some patients with relapsed or refractory cancers, this approach may indicate a novel therapeutic intervention that could alter outcome.

A genomic case study of mixed fibrolamellar hepatocellular carcinoma

We report the first comprehensive genomic analysis of a case of mixed conventional and fibrolamellar HCC (mFL-HCC). This study confirms the expression of DNAJB1:PRKACA, a fusion previously associated with pure FL-HCC but not conventional HCC, in mFL-HCC. These results indicate the DNAJB1:PRKACA fusion has diagnostic utility for both pure and mixed FL-HCC.

Background

Mixed fibrolamellar hepatocellular carcinoma (mFL-HCC) is a rare liver tumor defined by the presence of both pure FL-HCC and conventional HCC components, represents up to 25% of cases of FL-HCC, and has been associated with worse prognosis. Recent genomic characterization of pure FL-HCC identified a highly recurrent transcript fusion (DNAJB1:PRKACA) not found in conventional HCC.

Patients and Methods

We performed exome and transcriptome sequencing of a case of mFL-HCC. A novel BAC-capture approach was developed to identify a 400 kb deletion as the underlying genomic mechanism for a DNAJB1:PRKACA fusion in this case. A sensitive Nanostring Elements assay was used to screen for this transcript fusion in a second case of mFL-HCC, 112 additional HCC samples and 44 adjacent non-tumor liver samples.

Results

We report the first comprehensive genomic analysis of a case of mFL-HCC. No common HCC-associated mutations were identified. The very low mutation rate of this case, large number of mostly single-copy, long-range copy number variants, and high expression of ERBB2 were more consistent with previous reports of pure FL-HCC than conventional HCC. In particular, the DNAJB1:PRKACA fusion transcript specifically associated with pure FL-HCC was detected at very high expression levels. Subsequent analysis revealed the presence of this fusion in all primary and metastatic samples, including those with mixed or conventional HCC pathology. A second case of mFL-HCC confirmed our finding that the fusion was detectable in conventional components. An expanded screen identified a third case of fusion-positive HCC, which upon review, also had both conventional and fibrolamellar features. This screen confirmed the absence of the fusion in all conventional HCC and adjacent non-tumor liver samples.

Conclusion

These results indicate that mFL-HCC is similar to pure FL-HCC at the genomic level and the DNAJB1:PRKACA fusion can be used as a diagnostic tool for both pure and mFL-HCC.

Integrated analysis of germline and somatic variants in ovarian cancer

We report the first large-scale exome-wide analysis of the combined germline-somatic landscape in ovarian cancer. Here we analyse germline and somatic alterations in 429 ovarian carcinoma cases and 557 controls. We identify 3,635 high confidence, rare truncation and 22,953 missense variants with predicted functional impact. We find germline truncation variants and large deletions across Fanconi pathway genes in 20% of cases. Enrichment of rare truncations is shown in BRCA1, BRCA2 and PALB2. In addition, we observe germline truncation variants in genes not previously associated with ovarian cancer susceptibility (NF1, MAP3K4, CDKN2B and MLL3). Evidence for loss of heterozygosity was found in 100 and 76% of cases with germline BRCA1 and BRCA2 truncations, respectively. Germline-somatic interaction analysis combined with extensive bioinformatics annotation identifies 222 candidate functional germline truncation and missense variants, including two pathogenic BRCA1 and 1 TP53 deleterious variants. Finally, integrated analyses of germline and somatic variants identify significantly altered pathways, including the Fanconi, MAPK and MLL pathways.

Abstract IA20: Genomics of a STAT1 knockout mouse model of human ER+ breast cancer

Estrogen receptor alpha positive luminal breast cancers are the most frequent subtype of breast cancer. Previous work has established that Stat1-/- mouse mammary tumor model recapitulates signaling, expression and phenotypic alterations observed in this subtype of human breast cancers. To identify transforming events that contribute to tumorigenesis, we performed whole genome sequencing of 22 Stat1-/- primary mammary tumors and cell lines. We discovered a novel hotspot of somatic mutations in 100% of tumors that resulted in a truncated form of the prolactin receptor (Prlr). Targeted sequence analysis identified similar mutations in 77.8% of ductal carcinoma in situ. Co-expression of truncated and full-length Prlr in normal cells led to activation of oncogenic Stat3 and Stat5 as well as cellular transformation. In conclusion, truncating mutations of Prlr drive tumor development in a model of human ERa+ breast cancer and should be considered as novel antitumor targets.

Citation Format: Elaine Mardis, Obi L. Griffith, Ruby Chan Szeman, Malachi Griffith, Kilannin Krysiak, Zachary Skidmore, Jasreet Hundal, Julie A. Allen, Arthur Cora, Alexander P. Miceli, Heather Schmidt, Lee Trani, Krishna-Latha Kanchi, Christopher A. Miller, David E. Larson, Robert S. Fulton, Richard K. Wilson, Robert D. Schreiber. Genomics of a STAT1 knockout mouse model of human ER+ breast cancer. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Breast Cancer Research; Oct 17-20, 2015; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(2_Suppl):Abstract nr IA20.

Abstract A1-06: Recurrent mutations of hormone-positive breast cancer and association with outcome

Background: Relationships between recurrent somatic mutations and outcome in estrogen receptor positive (ER+) breast cancer have not been extensively studied as the original discovery efforts were from either heterogeneously treated patients or follow up was too brief. Targeted massively parallel sequencing (MPS) analysis was therefore conducted on DNA extracted from archived formalin-fixed breast primaries from a cohort of over 600 patents from British Columbia treated with five years of adjuvant tamoxifen monotherapy and followed for over 10 years (Nielsen et al CCR 16:5222, 2010).

Methods: Genes were selected for targeted sequencing by meta-analysis of five large-scale breast cancer sequencing studies and manual review of breast cancer literature. In total, 83 genes were identified and 3286 probes were designed to tile across all known exons. Minimum starting input DNA was 50ng (mean=189.1ng). Illumina sequencing libraries were constructed, indexed, pooled, and enriched for target sequences by hybrid-capture followed by paired-end 100bp reads. The Genome Modeling System was used to perform single-tumor somatic variant prediction. Variant calls were filtered to include only targeted regions and exclude variants with global minor allele frequencies greater than 0.1% in unmatched non-tumor samples from 1000 genomes, NHLBI exome, and TCGA datasets. Kaplan-Meier univariate and multivariate survival analyses (including mutation status, clinical features and intrinsic subtype by qPCR) were performed for breast-cancer-specific and relapse free survival.

Results: A total of 625 samples met minimum quality controls of 80% targeted space covered at 20X or greater. On average, each sample had 332M aligned bases and a mean coverage of 134.3X. In total, 3,628 variants were identified including 2,066 missense, 188 nonsense, and 298 frame shift insertions or deletions. Novel hot spots for recurrent mutation were identified in several genes including a splice site mutation in CBFB. Results indicate significant associations between mutation status and improved survival for MAP3K1, ERBB3, ARID1B, PIK3CA and SMG1 or worse survival for DDR1, NF1, FOXC1 and TP53. Six Y537S/C, two E380Q and 5 potentially novel ligand-binding-domain mutations were identified in ESR1. Such mutations were recently reported to be associated with resistance to hormone therapy but were discovered here in as many as 2.1% of pre-treatment samples. Analysis will be presented regarding the use of relapse events to differentiate passenger from driver events.

Conclusion: Multiple recurrently mutated genes have both positive and negative associations with prognosis in tamoxifen monotherapy treated breast cancer populations. Associations with poor outcome suggest that DDR1, NF1 and FOXC1 are high priorities for pharmacological interventions.

Citation Format: Obi L. Griffith, Malachi Griffith, Nicholas C. Spies, Jingqin Luo, Jasreet Hundal, Christopher A. Miller, David E. Larson, Robert Fulton, Shuzhen Liu, Samuel Leung, Richard K. Wilson, Torsten O. Nielsen, Elaine R. Mardis, Matthew J. Ellis. Recurrent mutations of hormone-positive breast cancer and association with outcome. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A1-06.

Abstract PR03: Genomic approaches for risk assessment in acute myeloid leukemia

Acute myeloid leukemia is heterogeneous with respect to clinical outcome and molecular pathogenesis. Approximately 20% of AML cases are refractory to induction chemotherapy, and about 50% of patients ultimately relapse within a time interval that ranges from months to years. At the molecular level, diverse chromosomal abnormalities and genetic mutations have been observed across patients1. Although several clinical factors (age, white blood cell count), cytogenetic aberrations (t[15;17] translocation, loss of chromosome 5) 2-4, and genetic mutations (DNMT3A, FLT3) have been associated with differences in survival 5,6, these factors are of limited prognostic utility. Moreover, few studies have integrated sequence data with clinical and cytogentic factors to build predictive models of patient outcome.

Here, we sought to identify genomic predictors of refractory disease or early relapse. We used whole genome and exome sequencing to analyze the genomes of 71 adult de novo AML patients treated with anthracycline and cytarabine-based induction chemotherapy. Of these, 34 had refractory disease or relapsed within 6 months, 12 relapsed in 6-12 months, and 25 had a long first remission (&gt;12 months). We also developed an enhanced exome sequencing (EES) approach to identify and follow leukemia-associated variants over time. In 12 additional patients that achieved morphologic remission after induction chemotherapy, we used EES to identify and track variants at time of diagnosis, time of morphologic remission (roughly 30 days later), and a final time point corresponding to eventual relapse (n=8) or extended remission (n=4).

No novel coding or non-coding variants present at the time of diagnosis were found to be predictive of refractory disease or early relapse. Using EES, however, we were able to detect leukemia-associated variants in the initial remission bone marrow in all eight patients who eventually relapsed. One persistent leukemia-associated variant was also detected in one patient still in remission, but all other variants in that patient were eliminated. We also detected 64 somatic variants that became enriched following chemotherapy, but were not detected in the original leukemic cells. These may represent relapse-specific variants or oligoclonal hematopoiesis after bone marrow recovery. Overall, our data suggest that the persistence of leukemia-associated variants after bone marrow recovery from cytotoxic therapy is strongly correlated with relapse, and may be used to complement more traditional, morphologic measures of leukemic cell clearance.

1. Cancer Genome Atlas Research N. Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. The New England Journal of Medicine 2013;368:2059-74.

2. Byrd JC, Mrozek K, Dodge RK, et al. Pretreatment cytogenetic abnormalities are predictive of induction success, cumulative incidence of relapse, and overall survival in adult patients with de novo acute myeloid leukemia: results from Cancer and Leukemia Group B (CALGB 8461). Blood 2002;100:4325-36.

3. Grimwade D, Hills RK, Moorman AV, et al. Refinement of cytogenetic classification in acute myeloid leukemia: determination of prognostic significance of rare recurring chromosomal abnormalities among 5876 younger adult patients treated in the United Kingdom Medical Research Council trials. Blood 2010;116:354-65.

4. Schlenk RF, Dohner K, Krauter J, et al. Mutations and treatment outcome in cytogenetically normal acute myeloid leukemia. The New England Journal of Medicine 2008;358:1909-18.

5. Kihara R, Nagata Y, Kiyoi H, et al. Comprehensive analysis of genetic alterations and their prognostic impacts in adult acute myeloid leukemia patients. Leukemia 2014;28:1586-95.

6. Ley TJ, Ding L, Walter MJ, et al. DNMT3A mutations in acute myeloid leukemia. The New England Journal of Medicine 2010;363:2424-33.

This abstract is also presented as a poster at the Translation of the Cancer Genome conference.

Citation Format: Jeffery M. Klco, Christopher A. Miller, Malachi Griffith, Allegra Petti, David H. Spencer, Shamika Ketkar-Kulkarni, Lukas D. Wartman, Matthew Christopher, Tamara L. Lamprecht, Jacqueline E. Payton, Jack Baty, Sharon E. Heath, Obi L. Griffith, Dong Shen, Jasreet Hundal, Gue Su Chang, Robert S. Fulton, Michelle O'laughlin, Catrina Fronick, Vincent Magrini, Ryan Demeter, David E. Larson, Shashikant Kulkarni, Bradley A. Ozenberger, John S. Welch, Matthew J. Walker, Timothy A. Graubert, Peter Westervelt, Jerald P. Radich, Daniel C. Link, Elaine R. Mardis, John F. DiPersio, Richard K. Wilson. Genomic approaches for risk assessment in acute myeloid leukemia. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr PR03.

Abstract A1-13: Ultra-deep whole-genome sequencing reveals clinically relevant low-frequency subclones in an acute myeloid leukemia

Most tumors are heterogeneous, and the presence of distinct subclonal populations has been shown to be common in every type of cancer assayed to date. Even very low-frequency populations may harbor mutations that offer a selective advantage during therapy, a fact that carries profound clinical implications. Despite their importance, the landscape of low-frequency clonal SNVs remains largely unexplored, due to standard sequencing assays that only achieve mean coverages of 75-100x in exomes, or 30-50x in whole genomes. While these approaches are adequate for characterizing samples with high cellularity, normal cytogenetics, and homogeneous tumor cell populations, most tumors are impure, aneuploid, and heterogeneous to various degrees.

To reassess optimal tumor sequencing and analysis strategies, we performed ultra-deep sequencing of an acute myeloid leukemia (AML) with complex sub-clonal architecture, and known canonical driver mutations in DNMT3A, NPM1, FLT3, and IDH1. This patient's tumor, matched normal, and post-chemotherapy relapse sample were whole-genome sequenced to ~350x coverage, whole exome sequenced to ~300X coverage, and a panel of 260 recurrently mutated AML genes were sequenced to ~10,000X coverage. We then tested 10 alignment algorithms and 7 state-of-the-art somatic single-nucleotide variant callers on these data. To validate the calls, 200,000 putative SNVs were assayed on a custom targeted capture array to mean depths of ~1000x. This exceptionally comprehensive data set allowed the investigation of the use of multiple sequencing libraries of varying fragment size distributions, the effect of alignment algorithm choice on variant calling, optimal strategies for the combination of multiple variant callers and the effect of increasing sequence depth on subclonal definition.

This deep sequencing and validation resulted in a many-fold increase in variant calls, and led to the discovery of additional known or suspected driver mutations in FLT3, IDH2, TP53, RUNX1, FOXP1 and KRT1. We also observed an 80-fold increase in the number of single-nucleotide variants detected at a VAF of less than 10%, including many at a frequency of 1% or lower. We applied the sciClone algorithm to trace the clonal evolution of this tumor through treatment and relapse, showing that many variants previously thought to be relapse-specific were in fact present in the tumor at very low levels. One of these subclones, containing a mutation in IDH2, became heavily enriched after the therapy-induced bottleneck and grew into the dominant clone in the relapse tumor.

We demonstrate that the widely used practices of obtaining ~100X exome sequencing or 30-50X whole genome sequencing are inadequate to characterize tumors with even moderate heterogeneity, impurity, contamination, aneuploidy, or combinations of these. Similarly, current analysis strategies relying on a single alignment algorithm and variant caller, using data from a single sequence library, suffer from poor sensitivity and specificity. This dataset, generated from the most deeply sequenced and cross-validated tumor described to date, will serve as an invaluable community resource for benchmarking algorithms by providing an extremely high confidence set of low frequency mutations.

Citation Format: Christopher A. Miller, Malachi Griffith, Avinash Ramu, Zachery L. Skidmore, Obi L. Griffith, Vincent Magrini, Ryan Demeter, Ha Dang, Jason Walker, David E. Larson, Robert S. Fulton, Christopher Maher, Elaine R. Mardis, Timothy J. Ley, Richard K. Wilson. Ultra-deep whole-genome sequencing reveals clinically relevant low-frequency subclones in an acute myeloid leukemia. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A1-13.

Abstract PR11: Genomic approaches for risk assessment in acute myeloid leukemia

Acute myeloid leukemia is heterogeneous with respect to clinical outcome and molecular pathogenesis. Approximately 20% of AML cases are refractory to induction chemotherapy, and about 50% of patients ultimately relapse within a time interval that ranges from months to years. At the molecular level, diverse chromosomal abnormalities and genetic mutations have been observed across patients1. Although several clinical factors (age, white blood cell count), cytogenetic aberrations (t[15;17] translocation, loss of chromosome 5) 2-4, and genetic mutations (DNMT3A, FLT3) have been associated with differences in survival 5,6, these factors are of limited prognostic utility. Moreover, few studies have integrated sequence data with clinical and cytogentic factors to build predictive models of patient outcome.

Here, we sought to identify genomic predictors of refractory disease or early relapse. We used whole genome and exome sequencing to analyze the genomes of 71 adult de novo AML patients treated with anthracycline and cytarabine-based induction chemotherapy. Of these, 34 had refractory disease or relapsed within 6 months, 12 relapsed in 6-12 months, and 25 had a long first remission (&gt;12 months). We also developed an enhanced exome sequencing (EES) approach to identify and follow leukemia-associated variants over time. In 12 additional patients that achieved morphologic remission after induction chemotherapy, we used EES to identify and track variants at time of diagnosis, time of morphologic remission (roughly 30 days later), and a final time point corresponding to eventual relapse (n=8) or extended remission (n=4).

No novel coding or non-coding variants present at the time of diagnosis were found to be predictive of refractory disease or early relapse. Using EES, however, we were able to detect leukemia-associated variants in the initial remission bone marrow in all eight patients who eventually relapsed. One persistent leukemia-associated variant was also detected in one patient still in remission, but all other variants in that patient were eliminated. We also detected 64 somatic variants that became enriched following chemotherapy, but were not detected in the original leukemic cells. These may represent relapse-specific variants or oligoclonal hematopoiesis after bone marrow recovery. Overall, our data suggest that the persistence of leukemia-associated variants after bone marrow recovery from cytotoxic therapy is strongly correlated with relapse, and may be used to complement more traditional, morphologic measures of leukemic cell clearance.

1. Cancer Genome Atlas Research N. Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. The New England Journal of Medicine 2013;368:2059-74.

2. Byrd JC, Mrozek K, Dodge RK, et al. Pretreatment cytogenetic abnormalities are predictive of induction success, cumulative incidence of relapse, and overall survival in adult patients with de novo acute myeloid leukemia: results from Cancer and Leukemia Group B (CALGB 8461). Blood 2002;100:4325-36.

3. Grimwade D, Hills RK, Moorman AV, et al. Refinement of cytogenetic classification in acute myeloid leukemia: determination of prognostic significance of rare recurring chromosomal abnormalities among 5876 younger adult patients treated in the United Kingdom Medical Research Council trials. Blood 2010;116:354-65.

4. Schlenk RF, Dohner K, Krauter J, et al. Mutations and treatment outcome in cytogenetically normal acute myeloid leukemia. The New England Journal of Medicine 2008;358:1909-18.

5. Kihara R, Nagata Y, Kiyoi H, et al. Comprehensive analysis of genetic alterations and their prognostic impacts in adult acute myeloid leukemia patients. Leukemia 2014;28:1586-95.

6. Ley TJ, Ding L, Walter MJ, et al. DNMT3A mutations in acute myeloid leukemia. The New England Journal of Medicine 2010;363:2424-33.

Citation Format: Jeffery M. Klco, Christopher A. Miller, Malachi Griffith, Allegra Petti, David H. Spencer, Shamika Ketkar-Kulkarni, Lukas D. Wartman, Matthew Christopher, Tamara L. Lamprecht, Jacqueline E. Payton, Jack Baty, Sharon E. Heath, Obi L. Griffith, Dong Shen, Jasreet Hundal, Gue Su Chang, Robert S. Fulton, Michelle O'laughlin, Catrina Fronick, Vincent Magrini, Ryan Demeter, David E. Larson, Shashikant Kulkarni, Bradley A. Ozenberger, John S. Welch, Matthew J. Walker, Timothy A. Graubert, Peter Westervelt, Jerald P. Radich, Daniel C. Link, Elaine R. Mardis, John F. DiPersio, Richard K. Wilson. Genomic approaches for risk assessment in acute myeloid leukemia. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr PR11.

Association Between Mutation Clearance After Induction Therapy and Outcomes in Acute Myeloid Leukemia

IMPORTANCE

Tests that predict outcomes for patients with acute myeloid leukemia (AML) are imprecise, especially for those with intermediate risk AML.

OBJECTIVES

To determine whether genomic approaches can provide novel prognostic information for adult patients with de novo AML.

DESIGN, SETTING, AND PARTICIPANTS

Whole-genome or exome sequencing was performed on samples obtained at disease presentation from 71 patients with AML (mean age, 50.8 years) treated with standard induction chemotherapy at a single site starting in March 2002, with follow-up through January 2015. In addition, deep digital sequencing was performed on paired diagnosis and remission samples from 50 patients (including 32 with intermediate-risk AML), approximately 30 days after successful induction therapy. Twenty-five of the 50 were from the cohort of 71 patients, and 25 were new, additional cases.

EXPOSURES

Whole-genome or exome sequencing and targeted deep sequencing. Risk of identification based on genetic data.

MAIN OUTCOMES AND MEASURES

Mutation patterns (including clearance of leukemia-associated variants after chemotherapy) and their association with event-free survival and overall survival.

RESULTS

Analysis of comprehensive genomic data from the 71 patients did not improve outcome assessment over current standard-of-care metrics. In an analysis of 50 patients with both presentation and documented remission samples, 24 (48%) had persistent leukemia-associated mutations in at least 5% of bone marrow cells at remission. The 24 with persistent mutations had significantly reduced event-free and overall survival vs the 26 who cleared all mutations. Patients with intermediate cytogenetic risk profiles had similar findings. [table: see text].

CONCLUSIONS AND RELEVANCE

The detection of persistent leukemia-associated mutations in at least 5% of bone marrow cells in day 30 remission samples was associated with a significantly increased risk of relapse, and reduced overall survival. These data suggest that this genomic approach may improve risk stratification for patients with AML.

Abstract 4109: Clonal evolution of metastatic colorectal cancer

Introduction: Death from colorectal cancer (CRC) occurs via sequelae of metastases. Our lack of understanding of the mechanisms driving metastatic formation is a critical barrier to the identification and direct targeting of critical genes and pathways. This is further complicated by tumor heterogeneity and subclonal architecture. To reconstruct the patterns of tumor evolution and metastasis in CRC, we have conducted the first comprehensive clonality analysis of ten patients.

Methods: Primary tumor, metastases in multiple liver segments, and matched normal tissues were procured from consented patients during operative resection. Deep exome (∼200x coverage) and whole genome sequencing (∼50x coverage) were used to identify somatic mutations and estimate variant allele frequency (VAF) for somatic single nucleotide variants (SNVs). Clonal architecture and evolution models were derived from the SNVs by VAF-based clustering, clonal ordering, and phylogeny analysis.

Results: Non-silent somatic alterations were enriched in genes known to be involved in CRC and other major cancers, including APC, TP53, KRAS, PIK3CA and TCF7L2. Each patient had a founding clone originating from the primary tumor (carrying non-silent mutations in at least one cancer driver gene) that survived to metastasis, possibly following evolution and acquisition of additional somatic mutations. Branched evolution was common and spatially-distinct liver metastases within the same patient sometimes arose from different (sub)clones in the primary tumor. Unique subclones appeared to arise in all metastatic samples, and in some cases, were shared among various metastases of the same patient. This suggests that one metastasis seeded another or an ancestor common to those metastases was present in the primary tumor or elsewhere, but not observed due to spatial heterogeneity. In several cases, mutations in the dominant clone of the primary tumor were absent from metastases, suggesting these were subclonal events in more aggressive cancer cells that arose in the primary tumor after metastasis. These additional somatic events may involve (possibly novel) cancer driver genes.

Conclusions: Understanding the genomic events driving tumor evolution and metastasis is critical for explaining why existing therapies fail and determining optimal treatment strategies. Our analyses have outlined several clonal evolution patterns in metastatic CRC. We are currently using ultra-deep targeted and multi-region sequencing to validate genomic alterations in our CRC cohort to refine clonal evolution models and evaluate which subclones may be biologically relevant to disease progression and treatment resistance. Additionally, by revealing critical altered genes and pathways associated with metastatic clones we can improve our understanding of the mechanisms driving metastasis in CRC that may lead to novel targeted cancer therapies.

Citation Format: Ha X. Dang, Julie Grossman, Brian S. White, Matthew Strand, David E. Larson, Jason Walker, Elizabeth Pittman, Timothy Fleming, Peter S. Goedegebuure, Robert S. Fulton, Christopher A. Miller, Malachi Griffith, Kian H. Lim, Timothy J. Ley, Richard K. Wilson, Elaine R. Mardis, A.Craig Lockhart, Ryan C. Fields, Christopher A. Maher. Clonal evolution of metastatic colorectal cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4109. doi:10.1158/1538-7445.AM2015-4109

Genome Modeling System: A Knowledge Management Platform for Genomics

In this work, we present the Genome Modeling System (GMS), an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395) and matched lymphoblastoid line (HCC1395BL). These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms.

Abstract S1-02: Prognostic effects of gene mutation in estrogen receptor positive breast cancer

Background: Relationships between recurrent somatic mutations and outcome in estrogen receptor positive (ER+) breast cancer has not been extensively studied as the original discovery efforts were from either heterogeneously treated patients or follow up was too brief. Targeted massively parallel sequencing (MPS) analysis was therefore conducted on DNA extracted from archived formalin-fixed breast primaries from a cohort of over 600 patents from British Columbia treated with five years of adjuvant tamoxifen monotherapy and followed for over 10 years (Nielsen et al CCR 16:5222, 2010).

Methods: Genes were selected for targeted sequencing by meta-analysis of five large-scale breast cancer sequencing studies and manual review of breast cancer literature. In total 83 genes were identified and 3286 probes were designed to tile across all known exons. Minimum starting input DNA was 50ng (mean=189.1ng). Illumina sequencing libraries were constructed, indexed, pooled, and enriched for target sequences by hybrid-capture followed by paired-end 100bp reads. The Genome Modeling System was used to perform single-tumor somatic variant prediction. Variant calls were filtered to include only targeted regions and exclude variants with global mutant allele frequencies greater than 0.1% in 1000 genomes or NHLBI exome datasets. Kaplan-Meier analysis and multivariable analysis (clinical features and intrinsic subtype by qPCR) was performed for breast-cancer-specific and relapse free survival.

Results: A total of 638 samples met minimum quality controls of 80% targeted space covered at 20X or greater. On average each sample had 332M of aligned bases and a mean coverage of 134.3X. In total 7,159 variants were identified including 3,696 missense, 494 nonsense, and 1,047 frameshift insertions or deletions. Preliminary results indicate significant associations between mutation status and improved survival for PIK3CA, ARID1B, ERBB3, MAP3K1 and GATA3 or worse survival for PTEN, DDR1, TP53 and JAK2. Five Y537N/C, two E380Q and 5 potentially novel ligand-binding-domain mutations were identified in ESR1. Such mutations were recently reported to be associated with resistance to hormone therapy but were discovered here in as much as 1.9% of pre-treatment samples. Analysis will be presented regarding the use of relapse events to differentiate passenger from driver mutations.

Conclusion. Multiple recurrently mutated genes have both positive and negative associations with prognosis in tamoxifen montherapy treated breast cancer populations. Associations with poor outcome suggest that PTEN, DDR1, and JAK2 are high priorities for pharmacological interventions.

Table 1: Mutations and survival in ER+ breast cancerGeneP-ValueHazard RatioPTEN0.0022.11PIK3CA0.0070.69DDR10.0082.41ARID1B0.010.57ERBB30.020.36MAP3K10.010.5TP530.041.48GATA30.040.44JAK20.052.1

Citation Format: Obi L Griffith, Malachi Griffith, Jingqin Luo, Jasreet Hundall, Christopher A Miller, David E Larson, Robert Fulton, Richard K Wilson, Shuzhen Liu, Samuel Leung, Torsten O Nielsen, Elaine R Mardis, Matthew J Ellis. Prognostic effects of gene mutation in estrogen receptor positive breast cancer [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr S1-02.

TYK2 protein-coding variants protect against rheumatoid arthritis and autoimmunity, with no evidence of major pleiotropic effects on non-autoimmune complex traits

Despite the success of genome-wide association studies (GWAS) in detecting a large number of loci for complex phenotypes such as rheumatoid arthritis (RA) susceptibility, the lack of information on the causal genes leaves important challenges to interpret GWAS results in the context of the disease biology. Here, we genetically fine-map the RA risk locus at 19p13 to define causal variants, and explore the pleiotropic effects of these same variants in other complex traits. First, we combined Immunochip dense genotyping (n = 23,092 case/control samples), Exomechip genotyping (n = 18,409 case/control samples) and targeted exon-sequencing (n = 2,236 case/controls samples) to demonstrate that three protein-coding variants in TYK2 (tyrosine kinase 2) independently protect against RA: P1104A (rs34536443, OR = 0.66, P = 2.3x10^-21), A928V (rs35018800, OR = 0.53, P = 1.2x10^-9), and I684S (rs12720356, OR = 0.86, P = 4.6x10^-7). Second, we show that the same three TYK2 variants protect against systemic lupus erythematosus (SLE, P_omnibus = 6x10^-18), and provide suggestive evidence that two of the TYK2 variants (P1104A and A928V) may also protect against inflammatory bowel disease (IBD; P_omnibus = 0.005). Finally, in a phenome-wide association study (PheWAS) assessing >500 phenotypes using electronic medical records (EMR) in >29,000 subjects, we found no convincing evidence for association of P1104A and A928V with complex phenotypes other than autoimmune diseases such as RA, SLE and IBD. Together, our results demonstrate the role of TYK2 in the pathogenesis of RA, SLE and IBD, and provide supporting evidence for TYK2 as a promising drug target for the treatment of autoimmune diseases.

Identification of functional variants for cleft lip with or without cleft palate in or near PAX7, FGFR2, and NOG by targeted sequencing of GWAS loci

Although genome-wide association studies (GWASs) for nonsyndromic orofacial clefts have identified multiple strongly associated regions, the causal variants are unknown. To address this, we selected 13 regions from GWASs and other studies, performed targeted sequencing in 1,409 Asian and European trios, and carried out a series of statistical and functional analyses. Within a cluster of strongly associated common variants near NOG, we found that one, rs227727, disrupts enhancer activity. We furthermore identified significant clusters of non-coding rare variants near NTN1 and NOG and found several rare coding variants likely to affect protein function, including four nonsense variants in ARHGAP29. We confirmed 48 de novo mutations and, based on best biological evidence available, chose two of these for functional assays. One mutation in PAX7 disrupted the DNA binding of the encoded transcription factor in an in vitro assay. The second, a non-coding mutation, disrupted the activity of a neural crest enhancer downstream of FGFR2 both in vitro and in vivo. This targeted sequencing study provides strong functional evidence implicating several specific variants as primary contributory risk alleles for nonsyndromic clefting in humans.

Re-sequencing expands our understanding of the phenotypic impact of variants at GWAS loci

Genome-wide association studies (GWAS) have identified >500 common variants associated with quantitative metabolic traits, but in aggregate such variants explain at most 20–30% of the heritable component of population variation in these traits. To further investigate the impact of genotypic variation on metabolic traits, we conducted re-sequencing studies in >6,000 members of a Finnish population cohort (The Northern Finland Birth Cohort of 1966 [NFBC]) and a type 2 diabetes case-control sample (The Finland-United States Investigation of NIDDM Genetics [FUSION] study). By sequencing the coding sequence and 5′ and 3′ untranslated regions of 78 genes at 17 GWAS loci associated with one or more of six metabolic traits (serum levels of fasting HDL-C, LDL-C, total cholesterol, triglycerides, plasma glucose, and insulin), and conducting both single-variant and gene-level association tests, we obtained a more complete understanding of phenotype-genotype associations at eight of these loci. At all eight of these loci, the identification of new associations provides significant evidence for multiple genetic signals to one or more phenotypes, and at two loci, in the genes ABCA1 and CETP, we found significant gene-level evidence of association to non-synonymous variants with MAF<1%. Additionally, two potentially deleterious variants that demonstrated significant associations (rs138726309, a missense variant in G6PC2, and rs28933094, a missense variant in LIPC) were considerably more common in these Finnish samples than in European reference populations, supporting our prior hypothesis that deleterious variants could attain high frequencies in this isolated population, likely due to the effects of population bottlenecks. Our results highlight the value of large, well-phenotyped samples for rare-variant association analysis, and the challenge of evaluating the phenotypic impact of such variants.

Abnormal serum levels of various metabolites, including measures relevant to cholesterol, other fats, and sugars, are known to be risk factors for cardiovascular disease and type 2 diabetes. Identification of the genes that play a role in generating such abnormalities could advance the development of new treatment and prevention strategies for these disorders. Investigations of common genetic variants carried out in large sets of research subjects have successfully pinpointed such genes within many regions of the human genome. However, these studies often have not led to the identification of the specific genetic variations affecting metabolic traits. To attempt to detect such causal variations, we sequenced genes in 17 genomic regions implicated in metabolic traits in >6,000 people from Finland. By conducting statistical analyses relating specific variations (individually and grouped by gene) to the measures for these metabolic traits observed in the study subjects, we added to our understanding of how genotypes affect these traits. Our findings support a long-held hypothesis that the unique history of the Finnish population provides important advantages for analyzing the relationship between genetic variations and biomedically important traits.

The next-generation sequencing revolution and its impact on genomics

Genomics is a relatively new scientific discipline, having DNA sequencing as its core technology. As technology has improved the cost and scale of genome characterization over sequencing's 40-year history, the scope of inquiry has commensurately broadened. Massively parallel sequencing has proven revolutionary, shifting the paradigm of genomics to address biological questions at a genome-wide scale. Sequencing now empowers clinical diagnostics and other aspects of medical care, including disease risk, therapeutic identification, and prenatal testing. This Review explores the current state of genomics in the massively parallel sequencing era.

Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia

BACKGROUND

Many mutations that contribute to the pathogenesis of acute myeloid leukemia (AML) are undefined. The relationships between patterns of mutations and epigenetic phenotypes are not yet clear.

METHODS

We analyzed the genomes of 200 clinically annotated adult cases of de novo AML, using either whole-genome sequencing (50 cases) or whole-exome sequencing (150 cases), along with RNA and microRNA sequencing and DNA-methylation analysis.

RESULTS

AML genomes have fewer mutations than most other adult cancers, with an average of only 13 mutations found in genes. Of these, an average of 5 are in genes that are recurrently mutated in AML. A total of 23 genes were significantly mutated, and another 237 were mutated in two or more samples. Nearly all samples had at least 1 nonsynonymous mutation in one of nine categories of genes that are almost certainly relevant for pathogenesis, including transcription-factor fusions (18% of cases), the gene encoding nucleophosmin (NPM1) (27%), tumor-suppressor genes (16%), DNA-methylation-related genes (44%), signaling genes (59%), chromatin-modifying genes (30%), myeloid transcription-factor genes (22%), cohesin-complex genes (13%), and spliceosome-complex genes (14%). Patterns of cooperation and mutual exclusivity suggested strong biologic relationships among several of the genes and categories.

CONCLUSIONS

We identified at least one potential driver mutation in nearly all AML samples and found that a complex interplay of genetic events contributes to AML pathogenesis in individual patients. The databases from this study are widely available to serve as a foundation for further investigations of AML pathogenesis, classification, and risk stratification. (Funded by the National Institutes of Health.).

The origin and evolution of mutations in acute myeloid leukemia

Most mutations in cancer genomes are thought to be acquired after the initiating event, which may cause genomic instability and drive clonal evolution. However, for acute myeloid leukemia (AML), normal karyotypes are common, and genomic instability is unusual. To better understand clonal evolution in AML, we sequenced the genomes of M3-AML samples with a known initiating event (PML-RARA) versus the genomes of normal karyotype M1-AML samples and the exomes of hematopoietic stem/progenitor cells (HSPCs) from healthy people. Collectively, the data suggest that most of the mutations found in AML genomes are actually random events that occurred in HSPCs before they acquired the initiating mutation; the mutational history of that cell is "captured" as the clone expands. In many cases, only one or two additional, cooperating mutations are needed to generate the malignant founding clone. Cells from the founding clone can acquire additional cooperating mutations, yielding subclones that can contribute to disease progression and/or relapse.

Do Obese Eat Faster Than Lean Subjects? Food Intake Studies in Pima Indian Men

Food intake rate has previously been derived from observation of eating behavior in laboratory settings or in public eating establishments. Although it has been suggested that obese individuals eat faster than lean individuals, observations of such an "obese eating style" have yielded mixed results. In the present study, the relationship between ad-libitum food intake rate and obesity was evaluated over 4 days on a metabolic ward in 28 healthy Pima Indian men (Mean +/- SD; 29 +/- 7 y, 100.4 +/- 27.1 kg, 33 +/- 10% body fat) using an automated food selection system containing a large variety of foods. Total energy intake averaged 18829 +/- 3299 kJ/d consisting of 47 +/- 4, 40 +/- 3, and 13 +/- 1 percent of carbohydrate, fat and protein, respectively. The average meal duration was 25 +/- 7 min. Food intake rate was 68 +/- 21 g/min while carbohydrate, fat and protein intake rates were 23 +/- 6, 9 +/- 3 and 6 +/- 2 g/min, respectively. Food intake rate correlated negatively with % body fat (r = -0.61, P < 0.01). Similar relationships were found between the intake rates of carbohydrate, fat and protein and body fatness. Only prospective studies will indicate whether a slow food intake rate may contribute to the etiology of obesity by possibly reducing satiety.

Background mutations in parental cells account for most of the genetic heterogeneity of induced pluripotent stem cells

To assess the genetic consequences of induced pluripotent stem cell (iPSC) reprogramming, we sequenced the genomes of ten murine iPSC clones derived from three independent reprogramming experiments, and compared them to their parental cell genomes. We detected hundreds of single nucleotide variants (SNVs) in every clone, with an average of 11 in coding regions. In two experiments, all SNVs were unique for each clone and did not cluster in pathways, but in the third, all four iPSC clones contained 157 shared genetic variants, which could also be detected in rare cells (<1 in 500) within the parental MEF pool. These data suggest that most of the genetic variation in iPSC clones is not caused by reprogramming per se, but is rather a consequence of cloning individual cells, which "captures" their mutational history. These findings have implications for the development and therapeutic use of cells that are reprogrammed by any method.

Clonal architecture of secondary acute myeloid leukemia

BACKGROUND

The myelodysplastic syndromes are a group of hematologic disorders that often evolve into secondary acute myeloid leukemia (AML). The genetic changes that underlie progression from the myelodysplastic syndromes to secondary AML are not well understood.

METHODS

We performed whole-genome sequencing of seven paired samples of skin and bone marrow in seven subjects with secondary AML to identify somatic mutations specific to secondary AML. We then genotyped a bone marrow sample obtained during the antecedent myelodysplastic-syndrome stage from each subject to determine the presence or absence of the specific somatic mutations. We identified recurrent mutations in coding genes and defined the clonal architecture of each pair of samples from the myelodysplastic-syndrome stage and the secondary-AML stage, using the allele burden of hundreds of mutations.

RESULTS

Approximately 85% of bone marrow cells were clonal in the myelodysplastic-syndrome and secondary-AML samples, regardless of the myeloblast count. The secondary-AML samples contained mutations in 11 recurrently mutated genes, including 4 genes that have not been previously implicated in the myelodysplastic syndromes or AML. In every case, progression to acute leukemia was defined by the persistence of an antecedent founding clone containing 182 to 660 somatic mutations and the outgrowth or emergence of at least one subclone, harboring dozens to hundreds of new mutations. All founding clones and subclones contained at least one mutation in a coding gene.

CONCLUSIONS

Nearly all the bone marrow cells in patients with myelodysplastic syndromes and secondary AML are clonally derived. Genetic evolution of secondary AML is a dynamic process shaped by multiple cycles of mutation acquisition and clonal selection. Recurrent gene mutations are found in both founding clones and daughter subclones. (Funded by the National Institutes of Health and others.).

Clonal evolution in relapsed acute myeloid leukaemia revealed by whole-genome sequencing

Most patients with acute myeloid leukemia (AML) die from progressive disease after relapse, which is associated with clonal evolution at the cytogenetic level^1,2. To determine the mutational spectrum associated with relapse, we sequenced the primary tumor and relapse genomes from 8 AML patients, and validated hundreds of somatic mutations using deep sequencing; this allowed us to precisely define clonality and clonal evolution patterns at relapse. Besides discovering novel, recurrently mutated genes (e.g. WAC, SMC3, DIS3, DDX41, and DAXX) in AML, we found two major clonal evolution patterns during AML relapse: 1) the founding clone in the primary tumor gained mutations and evolved into the relapse clone, or 2) a subclone of the founding clone survived initial therapy, gained additional mutations, and expanded at relapse. In all cases, chemotherapy failed to eradicate the founding clone. The comparison of relapse-specific vs. primary tumor mutations in all 8 cases revealed an increase in transversions, probably due to DNA damage caused by cytotoxic chemotherapy. These data demonstrate that AML relapse is associated with the addition of new mutations and clonal evolution, which is shaped in part by the chemotherapy that the patients receive to establish and maintain remissions.

Massively parallel sequencing approaches for characterization of structural variation

The emergence of next-generation sequencing (NGS) technologies offers an incredible opportunity to comprehensively study DNA sequence variation in human genomes. Commercially available platforms from Roche (454), Illumina (Genome Analyzer and Hiseq 2000), and Applied Biosystems (SOLiD) have the capability to completely sequence individual genomes to high levels of coverage. NGS data is particularly advantageous for the study of structural variation (SV) because it offers the sensitivity to detect variants of various sizes and types, as well as the precision to characterize their breakpoints at base pair resolution. In this chapter, we present methods and software algorithms that have been developed to detect SVs and copy number changes using massively parallel sequencing data. We describe visualization and de novo assembly strategies for characterizing SV breakpoints and removing false positives.

SomaticSniper: identification of somatic point mutations in whole genome sequencing data

MOTIVATION

The sequencing of tumors and their matched normals is frequently used to study the genetic composition of cancer. Despite this fact, there remains a dearth of available software tools designed to compare sequences in pairs of samples and identify sites that are likely to be unique to one sample.

RESULTS

In this article, we describe the mathematical basis of our SomaticSniper software for comparing tumor and normal pairs. We estimate its sensitivity and precision, and present several common sources of error resulting in miscalls.

AVAILABILITY AND IMPLEMENTATION

Binaries are freely available for download at http://gmt.genome.wustl.edu/somatic-sniper/current/, implemented in C and supported on Linux and Mac OS X.

CONTACT

delarson@wustl.edu; lding@wustl.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Direct evidence for a three-dimensional magnetic flux rope flanked by two active magnetic reconnection X lines at Earth's magnetopause

We report the direct detection by three THEMIS spacecraft of a magnetic flux rope flanked by two active X lines producing colliding plasma jets near the center of the flux rope. The observed density depletion and open magnetic field topology inside the flux rope reveal important three-dimensional effects. There was also evidence for nonthermal electron energization within the flux rope core where the fluxes of 1-4 keV superthermal electrons were higher than those in the converging reconnection jets. The observed ion and electron energizations differ from current theoretical predictions.

Use of whole-genome sequencing to diagnose a cryptic fusion oncogene

CONTEXT

Whole-genome sequencing is becoming increasingly available for research purposes, but it has not yet been routinely used for clinical diagnosis.

OBJECTIVE

To determine whether whole-genome sequencing can identify cryptic, actionable mutations in a clinically relevant time frame.

DESIGN, SETTING, AND PATIENT

We were referred a difficult diagnostic case of acute promyelocytic leukemia with no pathogenic X-RARA fusion identified by routine metaphase cytogenetics or interphase fluorescence in situ hybridization (FISH). The case patient was enrolled in an institutional review board-approved protocol, with consent specifically tailored to the implications of whole-genome sequencing. The protocol uses a "movable firewall" that maintains patient anonymity within the entire research team but allows the research team to communicate medically relevant information to the treating physician.

MAIN OUTCOME MEASURES

Clinical relevance of whole-genome sequencing and time to communicate validated results to the treating physician.

RESULTS

Massively parallel paired-end sequencing allowed identification of a cytogenetically cryptic event: a 77-kilobase segment from chromosome 15 was inserted en bloc into the second intron of the RARA gene on chromosome 17, resulting in a classic bcr3 PML-RARA fusion gene. Reverse transcription polymerase chain reaction sequencing subsequently validated the expression of the fusion transcript. Novel FISH probes identified 2 additional cases of t(15;17)-negative acute promyelocytic leukemia that had cytogenetically invisible insertions. Whole-genome sequencing and validation were completed in 7 weeks and changed the treatment plan for the patient.

CONCLUSION

Whole-genome sequencing can identify cytogenetically invisible oncogenes in a clinically relevant time frame.

Sequencing a mouse acute promyelocytic leukemia genome reveals genetic events relevant for disease progression

Acute promyelocytic leukemia (APL) is a subtype of acute myeloid leukemia (AML). It is characterized by the t(15;17)(q22;q11.2) chromosomal translocation that creates the promyelocytic leukemia-retinoic acid receptor α (PML-RARA) fusion oncogene. Although this fusion oncogene is known to initiate APL in mice, other cooperating mutations, as yet ill defined, are important for disease pathogenesis. To identify these, we used a mouse model of APL, whereby PML-RARA expressed in myeloid cells leads to a myeloproliferative disease that ultimately evolves into APL. Sequencing of a mouse APL genome revealed 3 somatic, nonsynonymous mutations relevant to APL pathogenesis, of which 1 (Jak1 V657F) was found to be recurrent in other affected mice. This mutation was identical to the JAK1 V658F mutation previously found in human APL and acute lymphoblastic leukemia samples. Further analysis showed that JAK1 V658F cooperated in vivo with PML-RARA, causing a rapidly fatal leukemia in mice. We also discovered a somatic 150-kb deletion involving the lysine (K)-specific demethylase 6A (Kdm6a, also known as Utx) gene, in the mouse APL genome. Similar deletions were observed in 3 out of 14 additional mouse APL samples and 1 out of 150 human AML samples. In conclusion, whole genome sequencing of mouse cancer genomes can provide an unbiased and comprehensive approach for discovering functionally relevant mutations that are also present in human leukemias.

DNMT3A mutations in acute myeloid leukemia

BACKGROUND

The genetic alterations responsible for an adverse outcome in most patients with acute myeloid leukemia (AML) are unknown.

METHODS

Using massively parallel DNA sequencing, we identified a somatic mutation in DNMT3A, encoding a DNA methyltransferase, in the genome of cells from a patient with AML with a normal karyotype. We sequenced the exons of DNMT3A in 280 additional patients with de novo AML to define recurring mutations.

RESULTS

A total of 62 of 281 patients (22.1%) had mutations in DNMT3A that were predicted to affect translation. We identified 18 different missense mutations, the most common of which was predicted to affect amino acid R882 (in 37 patients). We also identified six frameshift, six nonsense, and three splice-site mutations and a 1.5-Mbp deletion encompassing DNMT3A. These mutations were highly enriched in the group of patients with an intermediate-risk cytogenetic profile (56 of 166 patients, or 33.7%) but were absent in all 79 patients with a favorable-risk cytogenetic profile (P<0.001 for both comparisons). The median overall survival among patients with DNMT3A mutations was significantly shorter than that among patients without such mutations (12.3 months vs. 41.1 months, P<0.001). DNMT3A mutations were associated with adverse outcomes among patients with an intermediate-risk cytogenetic profile or FLT3 mutations, regardless of age, and were independently associated with a poor outcome in Cox proportional-hazards analysis.

CONCLUSIONS

DNMT3A mutations are highly recurrent in patients with de novo AML with an intermediate-risk cytogenetic profile and are independently associated with a poor outcome. (Funded by the National Institutes of Health and others.).

Computer simulation of cellular patterning within the Drosophila pupal eye

We present a computer simulation and associated experimental validation of assembly of glial-like support cells into the interweaving hexagonal lattice that spans the Drosophila pupal eye. This process of cell movements organizes the ommatidial array into a functional pattern. Unlike earlier simulations that focused on the arrangements of cells within individual ommatidia, here we examine the local movements that lead to large-scale organization of the emerging eye field. Simulations based on our experimental observations of cell adhesion, cell death, and cell movement successfully patterned a tracing of an emerging wild-type pupal eye. Surprisingly, altering cell adhesion had only a mild effect on patterning, contradicting our previous hypothesis that the patterning was primarily the result of preferential adhesion between IRM-class surface proteins. Instead, our simulations highlighted the importance of programmed cell death (PCD) as well as a previously unappreciated variable: the expansion of cells' apical surface areas, which promoted rearrangement of neighboring cells. We tested this prediction experimentally by preventing expansion in the apical area of individual cells: patterning was disrupted in a manner predicted by our simulations. Our work demonstrates the value of combining computer simulation with in vivo experiments to uncover novel mechanisms that are perpetuated throughout the eye field. It also demonstrates the utility of the Glazier-Graner-Hogeweg model (GGH) for modeling the links between local cellular interactions and emergent properties of developing epithelia as well as predicting unanticipated results in vivo.

Genome remodelling in a basal-like breast cancer metastasis and xenograft

Massively parallel DNA sequencing technologies provide an unprecedented ability to screen entire genomes for genetic changes associated with tumor progression. Here we describe the genomic analyses of four DNA samples from an African-American patient with basal-like breast cancer: peripheral blood, the primary tumor, a brain metastasis, and a xenograft derived from the primary tumor. The metastasis contained two de novo mutations and a large deletion not present in the primary tumor, and was significantly enriched for 20 shared mutations. The xenograft retained all primary tumor mutations, and displayed a mutation enrichment pattern that paralleled the metastasis (16 of 20 genes). Two overlapping large deletions, encompassing CTNNA1, were present in all three tumor samples. The differential mutation frequencies and structural variation patterns in metastasis and xenograft compared to the primary tumor suggest that secondary tumors may arise from a minority of cells within the primary.

CMDS: a population-based method for identifying recurrent DNA copy number aberrations in cancer from high-resolution data

MOTIVATION

DNA copy number aberration (CNA) is a hallmark of genomic abnormality in tumor cells. Recurrent CNA (RCNA) occurs in multiple cancer samples across the same chromosomal region and has greater implication in tumorigenesis. Current commonly used methods for RCNA identification require CNA calling for individual samples before cross-sample analysis. This two-step strategy may result in a heavy computational burden, as well as a loss of the overall statistical power due to segmentation and discretization of individual sample's data. We propose a population-based approach for RCNA detection with no need of single-sample analysis, which is statistically powerful, computationally efficient and particularly suitable for high-resolution and large-population studies.

RESULTS

Our approach, correlation matrix diagonal segmentation (CMDS), identifies RCNAs based on a between-chromosomal-site correlation analysis. Directly using the raw intensity ratio data from all samples and adopting a diagonal transformation strategy, CMDS substantially reduces computational burden and can obtain results very quickly from large datasets. Our simulation indicates that the statistical power of CMDS is higher than that of single-sample CNA calling based two-step approaches. We applied CMDS to two real datasets of lung cancer and brain cancer from Affymetrix and Illumina array platforms, respectively, and successfully identified known regions of CNA associated with EGFR, KRAS and other important oncogenes. CMDS provides a fast, powerful and easily implemented tool for the RCNA analysis of large-scale data from cancer genomes.

Recurring mutations found by sequencing an acute myeloid leukemia genome

BACKGROUND

The full complement of DNA mutations that are responsible for the pathogenesis of acute myeloid leukemia (AML) is not yet known.

METHODS

We used massively parallel DNA sequencing to obtain a very high level of coverage (approximately 98%) of a primary, cytogenetically normal, de novo genome for AML with minimal maturation (AML-M1) and a matched normal skin genome.

RESULTS

We identified 12 acquired (somatic) mutations within the coding sequences of genes and 52 somatic point mutations in conserved or regulatory portions of the genome. All mutations appeared to be heterozygous and present in nearly all cells in the tumor sample. Four of the 64 mutations occurred in at least 1 additional AML sample in 188 samples that were tested. Mutations in NRAS and NPM1 had been identified previously in patients with AML, but two other mutations had not been identified. One of these mutations, in the IDH1 gene, was present in 15 of 187 additional AML genomes tested and was strongly associated with normal cytogenetic status; it was present in 13 of 80 cytogenetically normal samples (16%). The other was a nongenic mutation in a genomic region with regulatory potential and conservation in higher mammals; we detected it in one additional AML tumor. The AML genome that we sequenced contains approximately 750 point mutations, of which only a small fraction are likely to be relevant to pathogenesis.

CONCLUSIONS

By comparing the sequences of tumor and skin genomes of a patient with AML-M1, we have identified recurring mutations that may be relevant for pathogenesis.

BreakDancer: an algorithm for high-resolution mapping of genomic structural variation

Detection and characterization of genomic structural variation are important for understanding the landscape of genetic variation in human populations and in complex diseases such as cancer. Recent studies demonstrate the feasibility of detecting structural variation using next-generation, short-insert, paired-end sequencing reads. However, the utility of these reads is not entirely clear, nor are the analysis methods under which accurate detection can be achieved. The algorithm BreakDancer predicts a wide variety of structural variants including indels, inversions, and translocations. We examined BreakDancer's performance in simulation, comparison with other methods, analysis of an acute myeloid leukemia sample, and the 1,000 Genomes trio individuals. We found that it substantially improved the detection of small and intermediate size indels from 10 bp to 1 Mbp that are difficult to detect via a single conventional approach.