Genome Analysis Toolkit Research Articles

Peripheral blood microbial signatures in current and former smokers

The human microbiome has a role in the development of multiple diseases. Individual microbiome profiles are highly personalized, though many species are shared. Understanding the relationship between the human microbiome and disease may inform future individualized treatments. We hypothesize the blood microbiome signature may be a surrogate for some lung microbial characteristics. We sought associations between the blood microbiome signature and lung-relevant host factors. Based on reads not mapped to the human genome, we detected microbial nucleic acids through secondary use of peripheral blood RNA-sequencing from 2,590 current and former smokers with and without chronic obstructive pulmonary disease (COPD) from the COPDGene study. We used the Genome Analysis Toolkit (GATK) microbial pipeline PathSeq to infer microbial profiles. We tested associations between the inferred profiles and lung disease relevant phenotypes and examined links to host gene expression pathways. We replicated our analyses using a second independent set of blood RNA-seq data from 1,065 COPDGene study subjects and performed a meta-analysis across the two studies. The four phyla with highest abundance across all subjects were Proteobacteria, Actinobacteria, Firmicutes and Bacteroidetes. In our meta-analysis, we observed associations (q-value < 0.05) between Acinetobacter, Serratia, Streptococcus and Bacillus inferred abundances and Modified Medical Research Council (mMRC) dyspnea score. Current smoking status was associated (q < 0.05) with Acinetobacter, Serratia and Cutibacterium abundance. All 12 taxa investigated were associated with at least one white blood cell distribution variable. Abundance for nine of the 12 taxa was associated with sex, and seven of the 12 taxa were associated with race. Host-microbiome interaction analysis revealed clustering of genera associated with mMRC dyspnea score and smoking status, through shared links to several host pathways. This study is the first to identify a bacterial microbiome signature in the peripheral blood of current and former smokers. Understanding the relationships between systemic microbial signatures and lung-related phenotypes may inform novel interventions and aid understanding of the systemic effects of smoking.

Molecular characterization, phylogenetic and variation analyses of SARS-CoV-2 strains in Turkey.

Aims: We present the sequence and single-nucleotide polymorphism (SNP) analysis for 47 complete genomes for SARS-CoV-2 isolates on Turkish patients. Methods: The Illumina MiSeq platform was used for sequencing the libraries. The SNPs were detected by using Genome Analysis Toolkit – HaplotypeCaller v.3.8.0 and were inspected on GenomeBrowse v2.1.2. Results: All viral genome sequences of our isolates were located in lineage B under the different clusters, such as B.1 (n = 3), B.1.1 (n = 28) and B.1.9 (n = 16). According to the Global Initiative on Sharing All Influenza Data nomenclature, all of our complete genomes were placed in G, GR and GH clades. In our study, 549 total and 53 unique SNPs were detected. Conclusion: The results indicate that the SARS-CoV-2 sequences of our isolates have great similarity with all Turkish and European sequences.

Transmission event of SARS-CoV-2 delta variant reveals multiple vaccine breakthrough infections

BackgroundThis study aims to identify the causative strain of SARS-CoV-2 in a cluster of vaccine breakthroughs. Vaccine breakthrough by a highly transmissible SARS-CoV-2 strain is a risk to global public health.MethodsNasopharyngeal swabs from suspected vaccine breakthrough cases were tested for SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) by qPCR (quantitative polymerase chain reaction) for Wuhan-Hu1 and alpha variant. Positive samples were then sequenced by Swift Normalase Amplicon Panels to determine the causal variant. GATK (genome analysis toolkit) variants were filtered with allele fraction ≥80 and min read depth 30x.ResultsViral sequencing revealed an infection cluster of 6 vaccinated patients infected with the delta (B.1.617.2) SARS-CoV-2 variant. With no history of vaccine breakthrough, this suggests the delta variant may possess immune evasion in patients that received the Pfizer BNT162b2, Moderna mRNA-1273, and Covaxin BBV152.ConclusionsDelta variant may pose the highest risk out of any currently circulating SARS-CoV-2 variants, with previously described increased transmissibility over alpha variant and now, possible vaccine breakthrough.FundingParts of this work was supported by the National Institute of Allergy and Infectious Diseases (1U19AI144297) and Baylor College of Medicine internal funding.

Identification of Novel UBE3A Mutation Causing Angelman Syndrome

The Angelman Syndrome (AS) is neurodevelopmental disease associated with maternal disruption of the UBE3A gene and is mainly characterized by global developmental delay, sever mental retardation with absence of speech, seizures, dysmorphic facial features, and distinct behavioral profile. In this study a pedigree with one affected member with neurodevelopmental disease who was a result of an unconsanguineous marriage were investigated by Whole Exome Sequencing (WES). DNA was extracted from whole blood and library was prepared using Agilent V6 capturing system. WES was performed on Illumina HiSeq 4000 platform. Genome Analysis Toolkit (GATK) was used for variant calling. Classification of selected variants was done based on ACMG guideline for variant interpretation 2015. WES revealed that the proband has previously unreported nonsense variant (c.2459T&gt;G) in UBE3A gene that causes the substitution of Leu (TTA) with stop codon (TGA), confirming the diagnosis of Angelman syndrome. The patient had delayed motor development, speech impairment, an attention deficit, and an abnormal electroencephalogram (EEG), but no seizures by the age of 2 years. This study emphasis the role of WES in the early diagnosis and better management for AS patient.

OVarFlow: a resource optimized GATK\xa04 based Open source Variant calling workFlow

BackgroundThe advent of next generation sequencing has opened new avenues for basic and applied research. One application is the discovery of sequence variants causative of a phenotypic trait or a disease pathology. The computational task of detecting and annotating sequence differences of a target dataset between a reference genome is known as "variant calling". Typically, this task is computationally involved, often combining a complex chain of linked software tools. A major player in this field is the Genome Analysis Toolkit (GATK). The "GATK Best Practices" is a commonly referred recipe for variant calling. However, current computational recommendations on variant calling predominantly focus on human sequencing data and ignore ever-changing demands of high-throughput sequencing developments. Furthermore, frequent updates to such recommendations are counterintuitive to the goal of offering a standard workflow and hamper reproducibility over time.ResultsA workflow for automated detection of single nucleotide polymorphisms and insertion-deletions offers a wide range of applications in sequence annotation of model and non-model organisms. The introduced workflow builds on the GATK Best Practices, while enabling reproducibility over time and offering an open, generalized computational architecture. The workflow achieves parallelized data evaluation and maximizes performance of individual computational tasks. Optimized Java garbage collection and heap size settings for the GATK applications SortSam, MarkDuplicates, HaplotypeCaller, and GatherVcfs effectively cut the overall analysis time in half.ConclusionsThe demand for variant calling, efficient computational processing, and standardized workflows is growing. The Open source Variant calling workFlow (OVarFlow) offers automation and reproducibility for a computationally optimized variant calling task. By reducing usage of computational resources, the workflow removes prior existing entry barriers to the variant calling field and enables standardized variant calling.

Rare cases of medulloblastoma with hypermutation.

BackgroundMedulloblastoma is the most common malignant brain tumor of childhood and is considered a tumor with low mutational burden (~1 Mut/Mb). Therefore, though the medulloblastoma genomes have been extensively characterized in literature, reports on potential hypermutations and underlying mutagenic processes in medulloblastomas are limited.AimIn this report, we studied the landscape of mutational burden in primary and recurrent medulloblastoma. Furthermore, we wanted to understand the differences in underlying mutagenic mechanisms in medulloblastoma with low and high mutational burdens.MethodsFifty‐three primary and recurrent medulloblastoma genomic sequence were downloaded from the European Genome Archive as BAM files. Thirty‐three cases were obtained from formalin‐fixed paraffin‐embedded tissues from pathology diagnostic archives of Spectrum Health and Cooperative Human Tissue Network. Somatic mutations were called using Mutect2, following best practices guidelines for Genome Analysis Toolkit V4. Mutational signatures were analyzed using deconstructSigs.ResultsWe identified nine medulloblastoma cases with high mutational burden (>5 Mut/Mb). Of them, five cases met the criteria of hypermutation (>10Mut/Mb), two of the five tumors had canonical mutations in the POLE proof‐reading domain, where a large proportion of mutations in these tumor genomes contributed to signature 10. The hypermutated cases also demonstrated mutational signatures 14, 15, and 21, indicating the role of mis match repair deficiency in their mutagenesis. Of the four known molecular subgroups in medulloblastoma–SHH, WNT, Group 3, and Group 4—both the POLE‐mutated cases belonged to the SHH subgroup. This report identifies rare cases of hypermutation in medulloblastoma driven by defects in DNA repair mechanisms.ConclusionHypermutation in medulloblastoma can impact therapeutic decisions, especially at recurrence in otherwise fatal high risk SHH‐medulloblastomas. A defect in DNA repair leading to SHH ‐medulloblastoma is yet another important mechanism that should be further investigated in the genesis of these tumors. Therefore, this report provides important scientific and clinical rationale for future research looking for incidence of hypermutation in large cohorts of medulloblastoma patients.

CABE-RY: A PAM-flexible dual-mutation base editor for reliable modeling of multi-nucleotide variants

Multi-nucleotide variants (MNVs) represent an important type of genetic variation and have biological and clinical significance. To simulate MNVs, we designed four dual-mutation base editors combining hA3A(Y130F), TadA8e(V106W), and protospacer adjacent motif (PAM)-flexible SpRY and selected cytosine and adenine base editor-SpRY (CABE-RY), which had the best editing performance, for further study. Characterization and comparison showed that CABE-RY had a smaller DNA editing window and lower RNA off-target edits than the corresponding single base editors. Thus, we have established a versatile tool to efficiently simulate MNVs over the genome, which could be very useful for functional studies on MNVs in humans.

Discovering single nucleotide variants and indels from bulk and single-cell ATAC-seq.

Genetic variants and de novo mutations in regulatory regions of the genome are typically discovered by whole-genome sequencing (WGS), however WGS is expensive and most WGS reads come from non-regulatory regions. The Assay for Transposase-Accessible Chromatin (ATAC-seq) generates reads from regulatory sequences and could potentially be used as a low-cost ‘capture’ method for regulatory variant discovery, but its use for this purpose has not been systematically evaluated. Here we apply seven variant callers to bulk and single-cell ATAC-seq data and evaluate their ability to identify single nucleotide variants (SNVs) and insertions/deletions (indels). In addition, we develop an ensemble classifier, VarCA, which combines features from individual variant callers to predict variants. The Genome Analysis Toolkit (GATK) is the best-performing individual caller with precision/recall on a bulk ATAC test dataset of 0.92/0.97 for SNVs and 0.87/0.82 for indels within ATAC-seq peak regions with at least 10 reads. On bulk ATAC-seq reads, VarCA achieves superior performance with precision/recall of 0.99/0.95 for SNVs and 0.93/0.80 for indels. On single-cell ATAC-seq reads, VarCA attains precision/recall of 0.98/0.94 for SNVs and 0.82/0.82 for indels. In summary, ATAC-seq reads can be used to accurately discover non-coding regulatory variants in the absence of whole-genome sequencing data and our ensemble method, VarCA, has the best overall performance.

Co-Occurrence of Familial Non-Medullary Thyroid Cancer (FNMTC) and Hereditary Non-Polyposis Colorectal Cancer (HNPCC) Associated Tumors-A Cohort Study.

Familial non-medullary thyroid cancer (FNMTC) is a form of endocrine malignancy exhibiting an autosomal dominant mode of inheritance with largely unknown germline molecular mechanism. Hereditary nonpolyposis colorectal cancer syndrome (HNPCC) is another hereditary autosomal dominant cancer syndrome which, if proven to be caused by germline mutations in mismatch repair genes (MMR)—MLHL, MSH2, MSH6, PMS2, and EPCAM—is called Lynch syndrome (LS). LS results in hereditary predisposition to a number of cancers, especially colorectal and endometrial cancers. Tumors in LS are characterized by microsatellite instability (MSI) and/or loss of MMR protein expression in immunohistochemistry (IHC). MSI is a rare event in thyroid cancer (TC), although it is known to occur in up to 2.5% of sporadic follicular TC cases. There are limited data on the role of germline MMR variants FNMTC. The goal of this study was to analyze the potential clinical and molecular association between HNPCC and FNMTC. We performed a cohort study analyzing the demographic, clinical, and pathologic data of 43 kindreds encompassing 383 participants (104 affected, 279 unaffected), aged 43.5 [7-99] years with FNMTC, and performed high-throughput whole-exome sequencing (WES) of peripheral blood DNA samples of selected 168 participants (54 affected by FNMTC and 114 unaffected). Total affected by thyroid cancer members per family ranged between 2 and 9 patients. FNMTC was more prevalent in women (68.3%) and characterized by a median tumor size of 1.0 [0.2-5.0] cm, multifocal growth in 44%, and gross extrathyroidal extension in 11.3%. Central neck lymph node metastases were found in 40.3% of patients at presentation, 12.9% presented with lateral neck lymph node metastases, and none had distant metastases. Family history screening revealed one Caucasian family meeting the clinical criteria for FNMTC and HNPCC, with five members affected by FNMTC and at least eight individuals reportedly unaffected by HNPCC-associated tumors. In addition, two family members were affected by melanoma. Genome Analysis Tool Kit (GATK) pipeline was used in variant analysis. Among 168 sequenced participants, a heterozygous missense variant in the MSH2 gene (rs373226409; c.2120G>A; p.Cys707Tyr) was detected exclusively in FNMTC- HNPCC- kindred. In this family, the sequencing was performed in one member affected by FNMTC, HPNCC-associated tumors and melanoma, one member affected solely by HNPCC-associated tumor, and one member with FNMTC only, as well as seven unaffected family members. The variant was present in all three affected adults, and in two unaffected children of the affected member, under the age of 18 years, and was absent in non-affected adults. This variant is predicted to be damaging/pathogenic in 17/20 in-silico models. However, immunostaining performed on the thyroid tumor tissue of two affected by FNMTC family members revealed intact nuclear expression of MSH2, and microsatellite stable status in both tumors that were tested. Although the MSH2 p.Cys707Tyr variant is rare with a minor allele frequency (MAF) of 0.00006 in Caucasians; it is more common in the South Asian population at 0.003 MAF. Therefore, the MSH2 variant observed in this family is unlikely to be an etiologic factor of thyroid cancer and a common genetic association between FNMTC and HNPCC has not yet been identified. This is the first report known to us on the co-occurrence of FNMTC and HNPCC. The co-occurrence of FNMTC and HNPCC-associated tumors is a rare event and although presented in a single family in our large FNMTC cohort, a common genetic background between the two comorbidities could not be established.

The Clinical Implication and Prognostic Impact of Dynamic Molecular Evolution in Acute Myeloid Leukemia

BackgroundAlthough the majority of acute myeloid leukemia (AML) patients may achieve complete remission (CR) after induction chemotherapy, about half of these patients relapse with a grave prognosis. Serial studies to assess the dynamic changes of molecular aberrations during follow-ups can help clarify the underlying mechanisms of leukemia progression. The advance and progress in the high throughput next generation sequencing provide us a good chance to comprehensively analyze gene mutations longitudinally during clinical follow-ups.MethodWe used TruSight myeloid panel (Illumina, USA), focusing on 54 genes related to myeloid neoplasms, to investigate the gene mutations of the bone marrow mononuclear cells from 154 adult de novo AML patients who obtained CR but relapsed and had adequate samples for paired samples analyses. The HiSeq platform (Illumina) was applied which had a median reading depth of 12000X. The variant calling was accomplished by CallSomaticVariants 3.6.2 (Illumina) or Genome Analysis Tool Kit (GATK) HaplotypeCaller. For detection of the large insertion of FLT3 and KMT2A, Pindel v0.2.5b8 was used specifically for chromosome 13 and 11, respectively, with default setting. Complete serial cytogenetic data were available in 92 (59.7%) patients.ResultsAt diagnosis, 98% patients had at least one genetic alteration including 44.7% patients had both cytogenetic abnormalities and molecular gene mutations, 48.0% patients had only gene mutations and 5.3% patients had only cytogenetic abnormalities. The most prevalent gene mutations at diagnosis were NRAS mutations (19.4%), followed by FLT3 -ITD (16.9%), NPM1 (16.9%), and DNMT3A (16.2%) mutations. The first relapse of these patients occurred at a median of 7.5 months (range, 1.2-64.4 months) after achieving CR and 75.3% of them had early relapses within one year from CR. At relapse, 77.3% patients had genetic evolution, including 12.0% with cytogenetic evolution, 37.0% with molecular gene evolution, and 28.3% with both cytogenetic and molecular gene evolution. Comparing the gene mutations between diagnosis and relapse, IDH1 (stability 100%), SRSF2 (100%), STAG2 (100%), SMC3 (100%), NPM1 (96%), ASXL1 (90%), and TP53 (85.7%) mutations remained stable during disease evolution; in contrast, some gene mutations were unstable, such as NRAS (28%), SF3B1 (50%), FLT3 (60%), and KRAS (60%) mutations. Sixty-seven (43.5%) of 154 patients had CR samples at 30±15 days after the first standard induction chemotherapy. Among them, 23 (34.3%) patients with persistent leukemia associated gene mutations (variant allele frequency at median 3.3%, range, 1.3-18.3%) at CR after first induction chemotherapy; these patients had a significant poorer overall survival (OS) than those without detectable gene mutations at CR (19.5±3.0 vs. 25.1±8.4 months, P=0.019). The 154 patients could be separated into two groups according to the patterns of clonal genetic evolution at disease evolution: Group 1 of patients had stable mutations (n=57, 37.0%) or gain of novel mutations (n=32, 20.8%) at relapse (type 1 of evolution); Group 2 had clonal sweeping, such as loss of previously harbored mutations (n=43, 27.9%) or mixed gain and loss of mutations (n=22, 14.3%), at disease progression (type 2). Type 2 evolution was positively associated with inv(16) (P=0.010), NRAS (P<0.001), and CEBPA mutations (P<0.001) but negatively associated with FLT3 -ITD (P=0.032) at diagnosis. In univariate analysis, type 1 evolution pattern predicted a shorter OS than type 2 (19.5 ±2.1 vs. 25.1±3.9 months, P= 0.034). In multivariate Cox proportional hazards regression analysis for OS, which included those prognostic factors with P < 0.1 in univariate analysis, type 1 was still an independent poor prognostic factor (relative risk 1.58, 95% confidence interval 1.03-2.44, P = 0.038).ConclusionThe majority of de novo AML patients had genetic evolutions at relapse, including cytogenetic changes, molecular genetic evolutions, or both. The persistence of leukemia associated gene mutations at CR was associated with a significant poorer OS. Genetic evolution patterns were heterogeneous in AML and type 2 clonal evolution was associated with distinct genetic alterations and better outcomes. DisclosuresChen:Celgene International Sàrl: Research Funding. Tsai:Celgene International Sàrl: Research Funding. Tang:Celgene International Sàrl: Research Funding. Kuo:Celgene International Sàrl: Research Funding. Lin:Celgene International Sàrl: Research Funding. Yao:Celgene International Sàrl: Research Funding. Li:Celgene International Sàrl: Research Funding. Huang:Celgene International Sàrl: Research Funding. Ko:Celgene International Sàrl: Research Funding. Hsu:Celgene International Sàrl: Research Funding. Lin:Celgene International Sàrl: Research Funding. Wu:Celgene International Sàrl: Research Funding. Chen:Celgene International Sàrl: Research Funding. Tsai:Celgene International Sàrl: Research Funding. Hou:Celgene International Sàrl: Research Funding. Tien:Celgene International Sàrl: Research Funding.

Combined Analysis of Whole Exome Sequencing Data in Philadelphia-Negative Myeloproliferative (Ph-negative MPNs) and Myelodysplastic/Myeloproliferative Neoplasms (MDS/MPNs) Reveals Novel Recurrently Mutated Genes

Introduction: Development of massive sequencing of whole exomes (WES; whole exome sequencing) has revolutionized DNA sequencing, leading to several studies detailing the genetic profile of patients with several types of neoplasms, including MPNs and MDS/MPNs. One important challenge is to identify recurrently mutated genes that may play a role in disease pathogenesis. It is important to consider that cohort size is critical in the analysis to determine putative oncogenic driver genes, and most cohorts published in MPNs and MDS/MPNs have a limited sample size. One possibility to circumvent this limitations is to combine datasets of different studies. Herein we report the combined analysis of WES data of 403 patients with these disorders, including 124 patients from our center and 279 cases that were previously reported in the literature.Patients and Methods:We analyzed a combined cohort of 403 patients in this study with a diagnosis of Ph-negative MPN or MDS/MPN. For the 124 patients included from our center, reads were aligned and processed following Genome Analysis Toolkit best practices, and somatic variants were called combining the output of SomaticSniper, Mutect and Pindel. Regarding public data, we selected 6 studies that evaluated patients with MPNs and MDS/MPNs through WES and where sample-level data on all individual mutations that were identified were available. Data on identified mutations was extracted from supplementary material of the articles. Combined data on genomic mutations from the whole cohort was used to predict driver genes using softwares MutSigCV and IntOGen (www.intogen.org). Genes considered as being significantly mutated were genes with q-value <0.1 and/or genes with a mutational hotspot.Results:Diagnosis of the cohort included essential thrombocythemia (ET; N=110), polycythemia vera (PV; N=93), myelofibrosis (MF; N=98), chronic myelomonocytic leukemia (CMML; N=82), atypical CML (aCML; N=15) and more rare disorders (MPN-unclassified [N=2], MDS/MPN-unclassified [N=2] and refractory anemia with ring sideroblasts and thrombocytosis [N=1]). There were a total of 7519 identified mutations, with a median of 9 nonsilent coding mutations per sample (range 0-311 mutations). There were 2 patients (both with a diagnosis of ET) who had no somatic mutations identifed. Analysis of the mutational data using both MutSigCV and IntOGen algorithms revealed a total of 26 genes considered as putative driver genes in these neoplasms: JAK2, TET2, ASXL1, SRSF2, CALR, DNMT3A, SF3B1, CBL, NRAS, EZH2, U2AF1, RUNX1, KRAS, CUX1, MPL, ZRSR2, TP53, IDH2, PHF6, SH2B3, BCL11A, GATA2, ZBTB33, ETNK1, IDH1 and PPM1D (Figure) . A mutation in at least one these genes was found in 92.5% of samples. Among these 26 genes, 2 genes were not previously reported to be mutated in these diseases (ZBTB33 and BCL11A), and one gene was previously reported to be associated with other types of neoplastic diseases (PPM1D). ZBTB33 encodes the transcriptional regulator Kaiso and was found to be mutated in 6 samples (MF=2, ET=2, PV=1, CMML=1). Three mutations were frameshift indels, and three mutations were missense mutations, one of them (p.I37T) located in the POZ/BTB domain that regulates protein homodimerization. The second gene that was found to be recurrently mutated is BCL11A, which encodes a zinc-finger protein. There were 6 cases of BCL11A mutations, most of them in MDS/MPNs (CMML=3, aCML=2, MF=1). Mutations were all missense and clustered in two asparagine residues located at positions 391 and 756. Finally, four patients (CMML=2, PV=1, MF=1) presented with truncating mutations in the last exon of the PPM1D gene. These mutations have been reported to be activating, leading to an increase in activity of the Wip1 phosphatase and suppression of p53 activity. PPM1D mutations have been reported to be associated with clonal hematopoiesis, MDS and solid tumors. To the best of our knowledge this is one of the first reports detailing their presence in MPNs.Conclusions: Combining datasets across different studies has the potential to increase power and saturate discovery of recurrently mutated genes. This permits prioritization of genes for functional analysis to confirm their role in disease pathogenesis. Larger cohorts than the ones analyzed here may provide even more meaningful data on putative driver genes in MPNs and MDS/MPNs. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Analysis of Patterns of Co-Occurrence and Mutual Exclusivity of Gene Mutations in Philadelphia-Negative Myeloproliferative (Ph-negative MPNs) and Myelodysplastic/Myeloproliferative Neoplasms (MDS/MPNs)

Introduction: Next-generation sequencing (NGS) has led to the generation of massive amounts of sequencing data from cancer samples, including MPNs and MDS/MPNs. Current publications a vast heterogeneity among tumor genotypes across different patients. However, analysis of patterns of mutations correlation can reveal some genes that are more likely to co-occur in the same patients, while other genes tend to be mutually exclusive and are almost never found in the same case. Analysis of patterns of co-occurrence and mutual exclusivity of gene mutations can lead to insights in the pathogenesis of these diseases and can help identify putative novel driver genes that are mutually exclusive from known driver genes.Patients and Methods:We analyzed data of 646 patients with MPN or MDS/MPN, including 210 patients from our center and 436 patients with data that was available in the literature. Patients from our center were analyzed through either WES (N=123) or targeted sequencing panel of 253 genes involved in myeloid malignancies (N=87). Among the 436 cases selected from published studies in the literature, 278 had been analyzed by WES and 158 were evaluated by large sequencing panels containing the majority of myeloid related genes. We sought to analyze a common denominator of 26 genes that found to be recurrently patients: JAK2, TET2, ASXL1, SRSF2, CALR, DNMT3A, SF3B1, CBL, NRAS, KRAS, PTPN11, EZH2, U2AF1, RUNX1, CUX1, MPL, ZRSR2, TP53, IDH2, SH2B3,PHF6, GATA2, IDH1, SETBP1, ETV6, STAG2 . For the 210 patients included from our center, reads were aligned and processed following Genome Analysis Toolkit best practices, and somatic variants were called combining the output of SomaticSniper, Mutect and Pindel for WES data and Mutect/Mutect2 for targeted panel data. Regarding public data, we selected 7 studies that evaluated patients with MPNs and MDS/MPNs through WES/targeted sequencing and where sample-level data on all individual mutations that were identified were available. Pairwise analysis of occurrence and mutual exclusivity used Fisher tests with p-values adjusted for false discovery rate using the Benjamini-Hochberg method with a q-value cutoof of 0.1, while Multi-Dendrix (Raphael Lab, Brown University) was used for determination of groups of mutual exclusive genes.Results:Diagnosis of the cohort included essential thrombocythemia (ET; N=134), polycythemia vera (PV; N=113), myelofibrosis (MF; N=123), chronic myelomonocytic leukemia (CMML; N=228), atypical CML (aCML; N=15) and more rare disorders (MPN-unclassified [N=4], MDS/MPN-unclassified [N=10], refractory anemia with ring sideroblasts and thrombocytosis [N=18] and chronic neutrophilic leukemia [N=1]). Since some genes tend to co-occur more frequently with a specific disease type (e.g. JAK2 in Polycythemia Vera) we analyzed cases of MPNs and MDS/MPNs separately. Results are summarized in the Table. Among patients with MPNs, some novel associations appear: ASXL1 tends to co-occur with CUX1, EZH2, SRSF2 and U2AF1, while CALR and TET2 mutations tend to be mutually exclusive. SRSF2 mutations tend to co-occur with TET2 and CUX1 mutations, and U2AF1 with STAG2 mutations. In patients with MDS/MPNs, different associations are seen, including a tendency for mutual exclusivity of ASXL1 and DNMT3A mutations (Odds Ratio [OR]=0.09) and TET2 and SF3B1 mutations (OR=0.21), while TET2 t ends to co-occur with KRAS, SRSF2 and ZRSR2, while MPL associates strongly with U2AF1 mutations (OR=9.97). Analysis of sets of mutual exclusive genes with Multi-Dendrix revealed the following sets of genes that tend to be mutually exclusive (considering the whole cohort): Set 1- CALR, CBL, CUX1, JAK2, NRAS, RUNX1; Set 2 - GATA2, IDH2, MPL, SETBP1, TET2; Set 3- EZH2, SF3B1, SRSF2, TP53, U2AF1, ZRSR2; Set 4- ASXL1, DNMT3A, IDH1, KRAS, PHF6. Set 2 is illustrated in Figure 1.Conclusions:Despite a vast array of different mutations and possible combinations in MPNs and MDS/MPNs, it is clear that some combinations of gene mutations occur more frequently than others, while some genes almost never co-occur together. Analysis of the functional consequences of frequent gene associations might lead to improvements in diagnostic and molecular classification of these neoplasms. Larger cohorts, in the range of thousands of patients, are needed to better determine the more prevalent patterns of co-association and mutual exclusivity. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Monogenic Childhood Diabetes: Dissecting Clinical Heterogeneity by Next-Generation Sequencing in Maturity-Onset Diabetes of the Young

Diabetes is a common disorder with a heterogeneous clinical presentation and an enormous burden on health care worldwide. About 1-6% of patients with diabetes suffer from maturity-onset diabetes of the young (MODY), the most common form of monogenic diabetes with autosomal dominant inheritance. MODY is genetically and clinically heterogeneous and caused by genetic variations in pancreatic β-cell development and insulin secretion. We report here new findings from targeted next-generation sequencing (NGS) of 13 MODY-related genes. A sample of 22 unrelated pediatric patients with MODY and 13 unrelated healthy controls were recruited from a Turkish population. Targeted NGS was performed with Miseq 4000 (Illumina) to identify genetic variations in 13 MODY-related genes: HNF4A, GCK, HNF1A, PDX1, HNF1B, NEUROD1, KLF11, CEL, PAX4, INS, BLK, ABCC8, and KCNJ11. The NGS data were analyzed adhering to the Genome Analysis ToolKit (GATK) best practices pipeline, and variant filtering and annotation were performed. In the patient sample, we identified 43 MODY-specific genetic variations that were not present in the control group, including 11 missense mutations and 4 synonymous mutations. Importantly, and to the best of our knowledge, the missense mutations NEUROD1 p.D202E, KFL11 p.R461Q, BLK p.G248R, and KCNJ11 p.S385F were first associated with MODY in the present study. These findings contribute to the worldwide knowledge base on MODY and molecular correlates of clinical heterogeneity in monogenic childhood diabetes. Further comparative population genetics and functional genomics studies are called for, with an eye to discovery of novel diagnostics and personalized medicine in MODY. Because MODY is often misdiagnosed as type 1 or type 2 diabetes mellitus, advances in MODY diagnostics with NGS stand to benefit diabetes overall clinical care as well.

Detection and characterization of genome-wide genetic variation associated with the early-ripening phenotype of grape mutants

Single nucleotide polymorphisms (SNPs), insertion-deletion mutations (InDels) and structural variation (SV) play an important role in the generation of mutant genotypes. In this study, we conducted whole genome resequencing analysis of ‘Kyoho’, ‘Zana’ and their early-ripening bud sports, ‘Fengzao’ and ‘90–1′, respectively, to identify variants related to the early ripening trait. First, we determined the variants between ‘Kyoho’ vs. ‘Fengzao’ and ‘Zana’ vs. ‘90–1′ comparison groups using Genome Analysis Tool Kit (GATK) and samtools. Then, 324 genes harboring 1,135 SNPs and InDels were identified, based on sequencing depth and variant allele frequency. We also detected 39,112 and 35,825 SVs specific to ‘Fengzao’ and ‘90–1′, based on their comparison with ‘Kyoho’ and ‘Zana’ sequence data, respectively. Among these SVs, 89 were common to both ‘Fengzao’ and ‘90–1′. Then, variants were found in the coding sequences (CDSs) or upstream regions of 204 genes, of which 96 mapped to early ripening-related quantitative trait loci (QTLs). Subsequently, transcriptome analysis of ‘Kyoho’ and ‘Fengzao’ genotypes at four development stages revealed that 69 genes affected by variants were differentially expressed at one or more time points. Finally, five SNPs were validated in ‘Kyoho’ and ‘Fengzao’ by Sanger sequencing. Overall, abundant genetic variation was detected in ‘Kyoho’ and ‘Fengzao’ genomes, which may play a role in their early ripening phenotype.

Rare, Protein-Altering Variants in AS3MT and Arsenic Metabolism Efficiency: A Multi-Population Association Study.

Background:Common genetic variation in the arsenic methyltransferase (AS3MT) gene region is known to be associated with arsenic metabolism efficiency (AME), measured as the percentage of dimethylarsinic acid (DMA%) in the urine. Rare, protein-altering variants in AS3MT could have even larger effects on AME, but their contribution to AME has not been investigated.Objectives:We estimated the impact of rare, protein-coding variation in AS3MT on AME using a multi-population approach to facilitate the discovery of population-specific and shared causal rare variants.Methods:We generated targeted DNA sequencing data for the coding regions of AS3MT for three arsenic-exposed cohorts with existing data on arsenic species measured in urine: Health Effects of Arsenic Longitudinal Study (HEALS, ), Strong Heart Study (SHS, ), and New Hampshire Skin Cancer Study (NHSCS, ). We assessed the collective effects of rare (allele frequency ), protein-altering AS3MT variants on DMA%, using multiple approaches, including a test of the association between rare allele carrier status (yes/no) and DMA% using linear regression (adjusted for common variants in 10q24.32 region, age, sex, and population structure).Results:We identified 23 carriers of rare-protein-altering AS3MT variant across all cohorts (13 in HEALS and 5 in both SHS and NHSCS), including 6 carriers of predicted loss-of-function variants. DMA% was 6–10% lower in carriers compared with noncarriers in HEALS [ (95% CI: , )], SHS [ (95% CI: , )], and NHSCS [ (95% CI: , )]. In meta-analyses across cohorts, DMA% was 8.7% lower in carriers [ (95% CI: , )].Discussion:Rare, protein-altering variants in AS3MT were associated with lower mean DMA%, an indicator of reduced AME. Although a small percentage of the population (0.5–0.7%) carry these variants, they are associated with a 6–10% decrease in DMA% that is consistent across multiple ancestral and environmental backgrounds. https://doi.org/10.1289/EHP8152

MitoFlex: an efficient, high-performance toolkit for animal mitogenome assembly, annotation and visualization.

MitoFlex is a linux-based mitochondrial genome analysis toolkit, which provides a complete workflow of raw data filtering, de novo assembly, mitochondrial genome identification and annotation for animal High Throughput Sequencing data. The overall performance was compared between MitoFlex and its analogue MitoZ, in terms of protein-coding gene recovery, memory consumption and processing speed. MitoFlex is available at https://github.com/Prunoideae/MitoFlex under GPLv3 license. Supplementary data are available at Bioinformatics online.

Identification of novel mutations of SLC4A11 gene in patients with congenital hereditary endothelial dystrophy

Objective: To identify the potential pathogenic variants in patients with congenital hereditary endothelial dystrophy (CHED). Methods: A retrospective study. Six CHED patients were recruited from the Department of Ophthalmology at the Eye and ENT Hospital of Fudan University from August 2017 to September 2018. They were all males, and were 7 to 29 years old at the time of consultation, with an average age of 20.5 years. Whole-exome sequencing was performed on the six CHED patients. The Genome Analysis Tool Kit Best Practices pipeline and an in-house bioinformatics pipeline were applied for variants analyses, according to the 2015 American College of Medical Genetics and Genomics (ACMG) guidelines. Potential pathogenic variants were further validated by Sanger sequencing. Results: Six mutations in the SLC4A11 gene were identified in four out of six CHED patients, including four missense mutations (p.Arg869Cys, p.Pro773Leu, p.Arg869His, p.Arg755Trp), one frameshift mutation (p. Phe713fs), and one splicing site mutation (c.1330+1G>T). The frameshift mutation was pathogenic, while the pathogenicity of the splicing site mutation was unknown. Conclusions: We identified six CHED-associated mutations in this study. The frameshift mutation (p. Phe713fs) and the splicing site mutation (c.1330+1G>T) were novel. (Chin J Ophthalmol, 2021, 57: 133-138).

79 Placental somatic mutation is associated with tissue infarction

Whether small-scale somatic mutation (single nucleotide and small insertion-deletion variants) is associated with placental dysfunction is unknown. Our goal was to explore genetic variation in relation to histopathologic findings suggestive of placental insufficiency using whole genome sequencing. This is a pilot case-control study. From the Stillbirth Collaborative Research Network, we identified 25 fetuses affected by varying degrees of placental insufficiency including healthy live births, growth restricted live births, and stillbirths due to placental insufficiency. Four frozen biopsies from every placenta and one frozen fetal tissue sample (brain or muscle) from each stillbirth underwent whole genome sequencing. Single nucleotide and insertion-deletion variants were called using the best practices workflow of the Genome Analysis Toolkit, and functional variants (moderate-high impact on protein product) were counted. Frozen placental samples had paired paraffin-embedded samples allowing for assessment of the relationship between somatic mutation rates and specific histology findings. We identified 25 eligible pregnancies (n=10 healthy live births, n=7 growth-restricted live births, and n=8 stillbirths) with a total of 100 placental samples. Median sequencing depth ranged from 20-38X for placental samples and 18-56X for fetal tissue samples. Considerable somatic variation was present in all placental samples. When restricted to mosaic variants present in a single biopsy and after accounting for total genome coverage, placental samples with diffuse infarcts had higher total and functional mutation rates than with no infarction (p=0.004, Table 1). While this relationship was not present among for other individual histological abnormalities, the mutation rates were higher if any abnormality was present (Table 2). Somatic mutation was present in all placental samples, with highest mutation rates seen in samples with diffuse infarction. Somatic mutation may have a role in placental hypoxia and requires further study.View Large Image Figure ViewerDownload Hi-res image Download (PPT)

Sharing genetic variants with the NGS pipeline is essential for effective genomic data sharing and reproducibility in health information exchange

Genetic variants causing underlying pharmacogenetic and disease phenotypes have been used as the basis for clinical decision-making. However, due to the lack of standards for next-generation sequencing (NGS) pipelines, reproducing genetic variants among institutions is still difficult. The aim of this study is to show how many important variants for clinical decisions can be individually detected using different pipelines. Genetic variants were derived from 105 breast cancer patient target DNA sequences via three different variant-calling pipelines. HaplotypeCaller, Mutect2 tumor-only mode in the Genome Analysis ToolKit (GATK), and VarScan were used in variant calling from the sequence read data processed by the same NGS preprocessing tools using Variant Effect Predictor. GATK HaplotypeCaller, VarScan, and MuTect2 found 25,130, 16,972, and 4232 variants, comprising 1491, 1400, and 321 annotated variants with ClinVar significance, respectively. The average number of ClinVar significant variants in the patients was 769.43, 16.50% of the variants were detected by only one variant caller. Despite variants with significant impact on clinical decision-making, the detected variants are different for each algorithm. To utilize genetic variants in the clinical field, a strict standard for NGS pipelines is essential.

Characteristics of Genetic Variations Associated With Lennox-Gastaut Syndrome in Korean Families.

Lennox-Gastaut syndrome (LGS) is a severe type of childhood-onset epilepsy characterized by multiple types of seizures, specific discharges on electroencephalography, and intellectual disability. Most patients with LGS do not respond well to drug treatment and show poor long-term prognosis. Approximately 30% of patients without brain abnormalities have unidentifiable causes. Therefore, accurate diagnosis and treatment of LGS remain challenging. To identify causative mutations of LGS, we analyzed the whole-exome sequencing data of 17 unrelated Korean families, including patients with LGS and LGS-like epilepsy without brain abnormalities, using the Genome Analysis Toolkit. We identified 14 mutations in 14 genes as causes of LGS or LGS-like epilepsy. 64 percent of the identified genes were reported as LGS or epilepsy-related genes. Many of these variations were novel and considered as pathogenic or likely pathogenic. Network analysis was performed to classify the identified genes into two network clusters: neuronal signal transmission or neuronal development. Additionally, knockdown of two candidate genes with insufficient evidence of neuronal functions, SLC25A39 and TBC1D8, decreased neurite outgrowth and the expression level of MAP2, a neuronal marker. These results expand the spectrum of genetic variations and may aid the diagnosis and management of individuals with LGS.