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Journal articles on the topic 'EXOME SEQUENCING DATA'

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Published: 11 September 2023

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1

Liu, Pengfei, Linyan Meng, Elizabeth A. Normand, Fan Xia, Xiaofei Song, Andrew Ghazi, Jill Rosenfeld, et al. "Reanalysis of Clinical Exome Sequencing Data." New England Journal of Medicine 380, no. 25 (June 20, 2019): 2478–80. http://dx.doi.org/10.1056/nejmc1812033.

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Gonsalves, Stephen G., David Ng, Jennifer J. Johnston, Jamie K. Teer, Peter D. Stenson, David N. Cooper, James C. Mullikin, and Leslie G. Biesecker. "Using Exome Data to Identify Malignant Hyperthermia Susceptibility Mutations." Anesthesiology 119, no. 5 (November 1, 2013): 1043–53. http://dx.doi.org/10.1097/aln.0b013e3182a8a8e7.

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Abstract Background: Malignant hyperthermia susceptibility (MHS) is a life-threatening, inherited disorder of muscle calcium metabolism, triggered by anesthetics and depolarizing muscle relaxants. An unselected cohort was screened for MHS mutations using exome sequencing. The aim of this study was to pilot a strategy for the RYR1 and CACNA1S genes. Methods: Exome sequencing was performed on 870 volunteers not ascertained for MHS. Variants in RYR1 and CACNA1S were annotated using an algorithm that filtered results based on mutation type, frequency, and information in mutation databases. Variants were scored on a six-point pathogenicity scale. Medical histories and pedigrees were reviewed for malignant hyperthermia and related disorders. Results: The authors identified 70 RYR1 and 53 CACNA1S variants among 870 exomes. Sixty-three RYR1 and 41 CACNA1S variants passed the quality and frequency metrics but the authors excluded synonymous variants. In RYR1, the authors identified 65 missense mutations, one nonsense, two that affected splicing, and one non–frameshift indel. In CACNA1S, 48 missense, one frameshift deletion, one splicing, and one non–frameshift indel were identified. RYR1 variants predicted to be pathogenic for MHS were found in three participants without medical or family histories of MHS. Numerous variants, previously described as pathogenic in mutation databases, were reclassified by the authors as being of unknown pathogenicity. Conclusions: Exome sequencing can identify asymptomatic patients at risk for MHS, although the interpretation of exome variants can be challenging. The use of exome sequencing in unselected cohorts is an important tool to understand the prevalence and penetrance of MHS, a critical challenge for the field.

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3

Hatzis, C. "Bioinformatics analysis pipeline for exome sequencing data." AACR Education book 2014, no. 1 (April 4, 2014): 131–34. http://dx.doi.org/10.1158/aacr.edb-14-6406.

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4

De Filippo, MR, G. Giurato, C. Cantarella, F. Rizzo, F. Cirillo, and A. Weisz. "Development of pipeline for exome sequencing data analysis." EMBnet.journal 18, A (April 29, 2012): 98. http://dx.doi.org/10.14806/ej.18.a.438.

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5

Romanel, Alessandro, Tuo Zhang, Olivier Elemento, and Francesca Demichelis. "EthSEQ: ethnicity annotation from whole exome sequencing data." Bioinformatics 33, no. 15 (March 27, 2017): 2402–4. http://dx.doi.org/10.1093/bioinformatics/btx165.

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Meng, Jia, Xiaodong Cui, Manjeet K. Rao, Yidong Chen, and Yufei Huang. "Exome-based analysis for RNA epigenome sequencing data." Bioinformatics 29, no. 12 (April 14, 2013): 1565–67. http://dx.doi.org/10.1093/bioinformatics/btt171.

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7

Samuels, David C., Leng Han, Jiang Li, Sheng Quanghu, Travis A. Clark, Yu Shyr, and Yan Guo. "Finding the lost treasures in exome sequencing data." Trends in Genetics 29, no. 10 (October 2013): 593–99. http://dx.doi.org/10.1016/j.tig.2013.07.006.

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8

Vosberg, Sebastian, Luise Hartmann, Stephanie Schneider, Klaus H. Metzeler, Bianka Ksienzyk, Kathrin Bräundl, Martin Neumann, et al. "Detection of Chromosomal Aberrations in Acute Myeloid Leukemia By Copy Number Alteration Analysis of Exome Sequencing Data." Blood 126, no. 23 (December 3, 2015): 3859. http://dx.doi.org/10.1182/blood.v126.23.3859.3859.

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Abstract Exome sequencing is widely used and established to detect tumor-specific sequence variants such as point mutations and small insertions/deletions. Beyond single nucleotide resolution, sequencing data can also be used to identify changes in sequence coverage between samples enabling the detection of copy number alterations (CNAs). Somatic CNAs represent gain or loss of genomic material in tumor cells like aneuploidies (e.g. monosomies and trisomies), duplications, or deletions. In order to test the feasibility of somatic CNA detection from exome data, we analyzed 13 acute myeloid leukemia (AML) patients with known cytogenetic alterations detected at diagnosis (n=8) and/or at relapse (n=11). Corresponding remission exomes from all patients were available as germline controls resulting in 19 comparisons of paired leukemia and remission exome data sets. Exome sequencing was performed on a HiSeq 2500 instrument (Illumina) with mean target coverage of >100x. Exons with divergent coverage were detected using a linear regression model on mean exon coverage, and CNAs were called by an exact segmentation algorithm (Rigaill et al. 2012, Bioinformatics). For all samples, cytogenetic information was available either form routine chromosomal analysis or fluorescent in situ hybridization (FISH). Blast count were known for all but one AML sample (n=19). Copy number-neutral cytogenetic alterations such as balanced translocations were excluded from the comparative analysis. By CNA-analysis of exomes we were able to detect chromosomal aberrations consistent with routine cytogenetics in 18 out of 19 (95%) AML samples. In particular, we confirmed 2 out of 2 monosomies (both -7), and 9 out of 10 trisomies (+4, n=1; +8, n=8; +21, n=1), e.g. trisomy 8 in figure 1A. Partial amplifications or deletions of chromosomes were confirmed in 10 out of 10 AML samples (dup(1q), n=3; dup(8q), n=1; del(5q), n=3; del(17p), n=1; del(20q), n=2), e.g. del(5q) in figure 1B. In the one case with inconsistent findings of chromosomal aberrations between exome and cytogenetic data there was a small subclone harboring the alteration described in only 4 out of 21 metaphases (19%). To assess the specificity of our CNA approach, we analyzed the exomes of 44 cytogenetically normal (CN) AML samples. Here we did not detect any CNAs larger than 5 Mb in the vast majority of these samples (43/44, 98%), only one large CNA was detected indicating a trisomy 8. Estimates of the clone size were highly correlated between CNA-analysis of exomes and the parameters from cytogenetics and cytomorphology (p=0.0076, Fisher's exact test, Figure 1C). In CNA-analysis of exomes, we defined the clone size based on the coverage ratio: . Clone size estimation by cytogenetics and cytomorphology was performed by calculating the mean of blast count and abnormal metaphase/interphase count. Of note, clones estimated by CNA-analysis of exomes tended to be slightly larger. This may result from purification by Ficoll gradient centrifugation prior to DNA extraction for sequencing and/or the fact that the fraction of cells analyzed by cytogenetics does not represent the true size of the malignant clone accurately because of differences in the mitotic index between normal and malignant cells. Overall, there was a high correlation between our CNA analysis of exome sequencing data and routine cytogenetics including limitations in the detection of small subclones. Our results confirm that high throughput sequencing is a versatile, valuable, and robust method to detect chromosomal changes resulting in copy number alterations in AML with high specificity and sensitivity (98% and 95%, respectively). Figure 1. (A) Detection of trisomy 8 with an estimated clone size of 100% (B) Detection of deletion on chromosome 5q with an estimated clone size of 90% (C) Correlation of clone size estimation by routine diagnostics and exome sequencing (p=0.0076) Figure 1. (A) Detection of trisomy 8 with an estimated clone size of 100%. / (B) Detection of deletion on chromosome 5q with an estimated clone size of 90%. / (C) Correlation of clone size estimation by routine diagnostics and exome sequencing (p=0.0076) Figure 2. Figure 2. Disclosures No relevant conflicts of interest to declare.

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Hintzsche, Jennifer D., William A. Robinson, and Aik Choon Tan. "A Survey of Computational Tools to Analyze and Interpret Whole Exome Sequencing Data." International Journal of Genomics 2016 (2016): 1–16. http://dx.doi.org/10.1155/2016/7983236.

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Whole Exome Sequencing (WES) is the application of the next-generation technology to determine the variations in the exome and is becoming a standard approach in studying genetic variants in diseases. Understanding the exomes of individuals at single base resolution allows the identification of actionable mutations for disease treatment and management. WES technologies have shifted the bottleneck in experimental data production to computationally intensive informatics-based data analysis. Novel computational tools and methods have been developed to analyze and interpret WES data. Here, we review some of the current tools that are being used to analyze WES data. These tools range from the alignment of raw sequencing reads all the way to linking variants to actionable therapeutics. Strengths and weaknesses of each tool are discussed for the purpose of helping researchers make more informative decisions on selecting the best tools to analyze their WES data.

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Valdés-Mas, Rafael, Silvia Bea, Diana A. Puente, Carlos López-Otín, and Xose S. Puente. "Estimation of Copy Number Alterations from Exome Sequencing Data." PLoS ONE 7, no. 12 (December 19, 2012): e51422. http://dx.doi.org/10.1371/journal.pone.0051422.

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11

Balabanski, Lubomir, Dimitar Serbezov, Dragomira Nikolova, Olga Antonova, Desislava Nesheva, Zora Hammoudeh, Radoslava Vazharova, et al. "Centenarian Exomes as a Tool for Evaluating the Clinical Relevance of Germline Tumor Suppressor Mutations." Technology in Cancer Research & Treatment 19 (January 1, 2020): 153303382091108. http://dx.doi.org/10.1177/1533033820911082.

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Objectives: The aim of the present study was to evaluate the clinical relevance of mutations in tumor suppressor genes using whole-exome sequencing data from centenarians and young healthy individuals. Methods: Two pools, one of centenarians and one of young individuals, were constructed and whole-exome sequencing was performed. We examined the whole-exome sequencing data of Bulgarian individuals for carriership of tumor suppressor gene variants. Results: Of all variants annotated in both pools, 5080 (0.06%) are variants in tumor suppressor genes but only 46 show significant difference in allele frequencies between the two studied groups. Four variants (0.004%) are pathogenic/risk factors according to single nucleotide polymorphism database: rs1566734 in PTPRJ, rs861539 in XRCC3, rs203462 in AKAP10, and rs486907 in RNASEL. Discussion: Based on their high minor allele frequencies and presence in the centenarian group, we could reclassify them from pathogenic/risk factors to benign. Our study shows that centenarian exomes can be used for re-evaluating the clinically uncertain variants.

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Liaudanski, A. D., R. S. Shulinski, Y. A. Mishuk, and L. N. Sivitskaya. "COMPARISON OF GENOTYPE PHASING METODS FOR THE HIGH THROUGHPUT SEQUENCING DATA OF CLINICAL EXOMES." Молекулярная и прикладная генетика 31 (December 8, 2021): 114–23. http://dx.doi.org/10.47612/1999-9127-2021-31-114-123.

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The aim of this investigation was to search for an algorithm for phasing of exome NGS data that would be optimal for analyzing the cis-/transposition of closely located polymorphic loci in patients with hereditary diseases. The NGS data on clinical exome sequences from 149 patients was collected and analyzed, and its primary processing was carried out. A combined reference panel for phasing and genotype imputation “Belref1000G” was created by adding 131 samples of Belarusian patients to the panel from the “1000 Genomes” project. The most effective methods of phasing have been determined: the Michigan Imputation Server (online service) allows achieving the highest accuracy of phasing data from clinical exomes in Belarus. In cases where an online format of phasing is not appropriate for whatever reason, Beagle software with the combined reference panel “Belref1000G” is recommended for use. Beagle software with the “1000G” reference panel should be used to obtain the longest phasing blocks.

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Kurt Çolak, Fatma. "Clinically significant exome-based copy number variants detected by re-evaluation of exome sequencing data." Dokuz Eylül Üniversitesi Tıp Fakültesi Dergisi 35, no. 1 (2021): 1–11. http://dx.doi.org/10.5505/deutfd.2021.29053.

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14

Tan, Renjie, Jixuan Wang, Xiaoliang Wu, Liran Juan, Tianjiao Zhang, Rui Ma, Qing Zhan, et al. "ERDS-Exome: A Hybrid Approach for Copy Number Variant Detection from Whole-Exome Sequencing Data." IEEE/ACM Transactions on Computational Biology and Bioinformatics 17, no. 3 (May 1, 2020): 796–803. http://dx.doi.org/10.1109/tcbb.2017.2758779.

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Kim, Jerry H., Gail P. Jarvik, Brian L. Browning, Ramakrishnan Rajagopalan, Adam S. Gordon, Mark J. Rieder, Peggy D. Robertson, Deborah A. Nickerson, Nickla A. Fisher, and Philip M. Hopkins. "Exome Sequencing Reveals Novel Rare Variants in the Ryanodine Receptor and Calcium Channel Genes in Malignant Hyperthermia Families." Anesthesiology 119, no. 5 (November 1, 2013): 1054–65. http://dx.doi.org/10.1097/aln.0b013e3182a8a998.

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Abstract Background: About half of malignant hyperthermia (MH) cases are associated with skeletal muscle ryanodine receptor 1 (RYR1) and calcium channel, voltage-dependent, L type, α1S subunit (CACNA1S) gene mutations, leaving many with an unknown cause. The authors chose to apply a sequencing approach to uncover causal variants in unknown cases. Sequencing the exome, the protein-coding region of the genome, has power at low sample sizes and identified the cause of over a dozen Mendelian disorders. Methods: The authors considered four families with multiple MH cases lacking mutations in RYR1 and CACNA1S by Sanger sequencing of complementary DNA. Exome sequencing in two affecteds per family, chosen for maximum genetic distance, were compared. Variants were ranked by allele frequency, protein change, and measures of conservation among mammals to assess likelihood of causation. Finally, putative pathogenic mutations were genotyped in other family members to verify cosegregation with MH. Results: Exome sequencing revealed one rare RYR1 nonsynonymous variant in each of three families (Asp1056His, Val2627Met, Val4234Leu), and one CACNA1S variant (Thr1009Lys) in the fourth family. These were not seen in variant databases or in our control population sample of 5,379 exomes. Follow-up sequencing in other family members verified cosegregation of alleles with MH. Conclusions: The authors found that using both exome sequencing and allele frequency data from large sequencing efforts may aid genetic diagnosis of MH. In a sample selected by the authors, this technique was more sensitive for variant detection in known genes than Sanger sequencing of complementary DNA, and allows for the possibility of novel gene discovery.

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Miyatake, Satoko, Eriko Koshimizu, Atsushi Fujita, Ryoko Fukai, Eri Imagawa, Chihiro Ohba, Ichiro Kuki, et al. "Detecting copy-number variations in whole-exome sequencing data using the eXome Hidden Markov Model: an ‘exome-first’ approach." Journal of Human Genetics 60, no. 4 (January 22, 2015): 175–82. http://dx.doi.org/10.1038/jhg.2014.124.

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17

Guo, Yan, Jirong Long, Jing He, Chung-I. Li, Qiuyin Cai, Xiao-Ou Shu, Wei Zheng, and Chun Li. "Exome sequencing generates high quality data in non-target regions." BMC Genomics 13, no. 1 (2012): 194. http://dx.doi.org/10.1186/1471-2164-13-194.

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18

Gazal, Steven, Simon Gosset, Edgard Verdura, Françoise Bergametti, Stéphanie Guey, Marie-Claude Babron, and Elisabeth Tournier-Lasserve. "Can whole-exome sequencing data be used for linkage analysis?" European Journal of Human Genetics 24, no. 4 (July 15, 2015): 581–86. http://dx.doi.org/10.1038/ejhg.2015.143.

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Magi, Alberto, Lorenzo Tattini, Ingrid Cifola, Romina D’Aurizio, Matteo Benelli, Eleonora Mangano, Cristina Battaglia, et al. "EXCAVATOR: detecting copy number variants from whole-exome sequencing data." Genome Biology 14, no. 10 (2013): R120. http://dx.doi.org/10.1186/gb-2013-14-10-r120.

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Oh, Sehyun, Ludwig Geistlinger, Marcel Ramos, Martin Morgan, Levi Waldron, and Markus Riester. "Reliable Analysis of Clinical Tumor-Only Whole-Exome Sequencing Data." JCO Clinical Cancer Informatics, no. 4 (September 2020): 321–35. http://dx.doi.org/10.1200/cci.19.00130.

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PURPOSE Allele-specific copy number alteration (CNA) analysis is essential to study the functional impact of single-nucleotide variants (SNVs) and the process of tumorigenesis. However, controversy over whether it can be performed with sufficient accuracy in data without matched normal profiles and a lack of open-source implementations have limited its application in clinical research and diagnosis. METHODS We benchmark allele-specific CNA analysis performance of whole-exome sequencing (WES) data against gold standard whole-genome SNP6 microarray data and against WES data sets with matched normal samples. We provide a workflow based on the open-source PureCN R/Bioconductor package in conjunction with widely used variant-calling and copy number segmentation algorithms for allele-specific CNA analysis from WES without matched normals. This workflow further classifies SNVs by somatic status and then uses this information to infer somatic mutational signatures and tumor mutational burden (TMB). RESULTS Application of our workflow to tumor-only WES data produces tumor purity and ploidy estimates that are highly concordant with estimates from SNP6 microarray data and matched normal WES data. The presence of cancer type–specific somatic mutational signatures was inferred with high accuracy. We also demonstrate high concordance of TMB between our tumor-only workflow and matched normal pipelines. CONCLUSION The proposed workflow provides, to our knowledge, the only open-source option with demonstrated high accuracy for comprehensive allele-specific CNA analysis and SNV classification of tumor-only WES. An implementation of the workflow is available on the Terra Cloud platform of the Broad Institute (Cambridge, MA).

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Cendes, Lucas L., Welliton de Souza, Iscia Lopes-Cendes, and Benilton S. Carvalho. "HPexome: An automated tool for processing whole-exome sequencing data." SoftwareX 11 (January 2020): 100478. http://dx.doi.org/10.1016/j.softx.2020.100478.

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Fu, Wenqing, Sharon R. Browning, Brian L. Browning, and Joshua M. Akey. "Robust Inference of Identity by Descent from Exome-Sequencing Data." American Journal of Human Genetics 99, no. 5 (November 2016): 1106–16. http://dx.doi.org/10.1016/j.ajhg.2016.09.011.

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Garret, Philippine, Céline Bris, Vincent Procaccio, Patrizia Amati‐Bonneau, Pierre Vabres, Nada Houcinat, Emilie Tisserant, et al. "Deciphering exome sequencing data: Bringing mitochondrial DNA variants to light." Human Mutation 40, no. 12 (August 26, 2019): 2430–43. http://dx.doi.org/10.1002/humu.23885.

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Chong, Irene Y., Naureen Starling, Alistair Rust, John Alexander, Lauren Aronson, Marta Llorca-Cardenosa, Ritika Chauhan, et al. "The Mutational Concordance of Fixed Formalin Paraffin Embedded and Fresh Frozen Gastro-Oesophageal Tumours Using Whole Exome Sequencing." Journal of Clinical Medicine 10, no. 2 (January 9, 2021): 215. http://dx.doi.org/10.3390/jcm10020215.

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1. Background: The application of massively parallel sequencing has led to the identification of aberrant druggable pathways and somatic mutations within therapeutically relevant genes in gastro-oesophageal cancer. Given the widespread use of formalin-fixed paraffin-embedded (FFPE) samples in the study of this disease, it would be beneficial, especially for the purposes of biomarker evaluation, to assess the concordance between comprehensive exome-wide sequencing data from archival FFPE samples originating from a prospective clinical study and those derived from fresh-frozen material. 2. Methods: We analysed whole-exome sequencing data to define the mutational concordance of 16 matched fresh-frozen and FFPE gastro-oesophageal tumours (N = 32) from a prospective clinical study. We assessed DNA integrity prior to sequencing and then identified coding mutations in genes that have previously been implicated in other cancers. In addition, we calculated the mutant-allele heterogeneity (MATH) for these samples. 3. Results: Although there was increased degradation of DNA in FFPE samples compared with frozen samples, sequencing data from only two FFPE samples failed to reach an adequate mapping quality threshold. Using a filtering threshold of mutant read counts of at least ten and a minimum of 5% variant allele frequency (VAF) we found that there was a high median mutational concordance of 97% (range 80.1–98.68%) between fresh-frozen and FFPE gastro-oesophageal tumour-derived exomes. However, the majority of FFPE tumours had higher mutant-allele heterogeneity (MATH) scores when compared with corresponding frozen tumours (p < 0.001), suggesting that FFPE-based exome sequencing is likely to over-represent tumour heterogeneity in FFPE samples compared to fresh-frozen samples. Furthermore, we identified coding mutations in 120 cancer-related genes, including those associated with chromatin remodelling and Wnt/β-catenin and Receptor Tyrosine Kinase signalling. 4. Conclusions: These data suggest that comprehensive genomic data can be generated from exome sequencing of selected DNA samples extracted from archival FFPE gastro-oesophageal tumour tissues within the context of prospective clinical trials.

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Chong, Irene Y., Naureen Starling, Alistair Rust, John Alexander, Lauren Aronson, Marta Llorca-Cardenosa, Ritika Chauhan, et al. "The Mutational Concordance of Fixed Formalin Paraffin Embedded and Fresh Frozen Gastro-Oesophageal Tumours Using Whole Exome Sequencing." Journal of Clinical Medicine 10, no. 2 (January 9, 2021): 215. http://dx.doi.org/10.3390/jcm10020215.

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1. Background: The application of massively parallel sequencing has led to the identification of aberrant druggable pathways and somatic mutations within therapeutically relevant genes in gastro-oesophageal cancer. Given the widespread use of formalin-fixed paraffin-embedded (FFPE) samples in the study of this disease, it would be beneficial, especially for the purposes of biomarker evaluation, to assess the concordance between comprehensive exome-wide sequencing data from archival FFPE samples originating from a prospective clinical study and those derived from fresh-frozen material. 2. Methods: We analysed whole-exome sequencing data to define the mutational concordance of 16 matched fresh-frozen and FFPE gastro-oesophageal tumours (N = 32) from a prospective clinical study. We assessed DNA integrity prior to sequencing and then identified coding mutations in genes that have previously been implicated in other cancers. In addition, we calculated the mutant-allele heterogeneity (MATH) for these samples. 3. Results: Although there was increased degradation of DNA in FFPE samples compared with frozen samples, sequencing data from only two FFPE samples failed to reach an adequate mapping quality threshold. Using a filtering threshold of mutant read counts of at least ten and a minimum of 5% variant allele frequency (VAF) we found that there was a high median mutational concordance of 97% (range 80.1–98.68%) between fresh-frozen and FFPE gastro-oesophageal tumour-derived exomes. However, the majority of FFPE tumours had higher mutant-allele heterogeneity (MATH) scores when compared with corresponding frozen tumours (p < 0.001), suggesting that FFPE-based exome sequencing is likely to over-represent tumour heterogeneity in FFPE samples compared to fresh-frozen samples. Furthermore, we identified coding mutations in 120 cancer-related genes, including those associated with chromatin remodelling and Wnt/β-catenin and Receptor Tyrosine Kinase signalling. 4. Conclusions: These data suggest that comprehensive genomic data can be generated from exome sequencing of selected DNA samples extracted from archival FFPE gastro-oesophageal tumour tissues within the context of prospective clinical trials.

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Guo, Yan, Quanghu Sheng, David C. Samuels, Brian Lehmann, Joshua A. Bauer, Jennifer Pietenpol, and Yu Shyr. "Comparative Study of Exome Copy Number Variation Estimation Tools Using Array Comparative Genomic Hybridization as Control." BioMed Research International 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/915636.

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Exome sequencing using next-generation sequencing technologies is a cost-efficient approach to selectively sequencing coding regions of the human genome for detection of disease variants. One of the lesser known yet important applications of exome sequencing data is to identify copy number variation (CNV). There have been many exome CNV tools developed over the last few years, but the performance and accuracy of these programs have not been thoroughly evaluated. In this study, we systematically compared four popular exome CNV tools (CoNIFER, cn.MOPS, exomeCopy, and ExomeDepth) and evaluated their effectiveness against array comparative genome hybridization (array CGH) platforms. We found that exome CNV tools are capable of identifying CNVs, but they can have problems such as high false positives, low sensitivity, and duplication bias when compared to array CGH platforms. While exome CNV tools do serve their purpose for data mining, careful evaluation and additional validation is highly recommended. Based on all these results, we recommend CoNIFER and cn.MOPs for nonpaired exome CNV detection over the other two tools due to a low false-positive rate, although none of the four exome CNV tools performed at an outstanding level when compared to array CGH.

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Gajapathy, Manavalan, Brandon Wilk, Donna Brown, and Elizabeth Worthey. "eP350: QuaC: Implementing quality control best practices for genome sequencing and exome sequencing data." Genetics in Medicine 24, no. 3 (March 2022): S219—S220. http://dx.doi.org/10.1016/j.gim.2022.01.385.

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Karasaki, Takahiro, Kazuhiro Nagayama, Hideki Kuwano, Jun-ichi Nitadori, Masaaki Sato, Masaki Anraku, Akihiro Hosoi, et al. "Prediction and prioritization of neoantigens: integration of RNA sequencing data with whole-exome sequencing." Cancer Science 108, no. 2 (February 2017): 170–77. http://dx.doi.org/10.1111/cas.13131.

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Mizrahi-Man, Orna, Marcos H. Woehrmann, Teresa A. Webster, Jeremy Gollub, Adrian Bivol, Sara M. Keeble, Katherine H. Aull, et al. "Novel genotyping algorithms for rare variants significantly improve the accuracy of Applied Biosystems™ Axiom™ array genotyping calls: Retrospective evaluation of UK Biobank array data." PLOS ONE 17, no. 11 (November 17, 2022): e0277680. http://dx.doi.org/10.1371/journal.pone.0277680.

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The UK Biobank genotyped about 500k participants using Applied Biosystems Axiom microarrays. Participants were subsequently sequenced by the UK Biobank Exome Sequencing Consortium. Axiom genotyping was highly accurate in comparison to sequencing results, for almost 100,000 variants both directly genotyped on the UK Biobank Axiom array and via whole exome sequencing. However, in a study using the exome sequencing results of the first 50k individuals as reference (truth), it was observed that the positive predictive value (PPV) decreased along with the number of heterozygous array calls per variant. We developed a novel addition to the genotyping algorithm, Rare Heterozygous Adjusted (RHA), to significantly improve PPV in variants with minor allele frequency below 0.01%. The improvement in PPV was roughly equal when comparing to the exome sequencing of 50k individuals, or to the more recent ~200k individuals. Sensitivity was higher in the 200k data. The improved calling algorithm, along with enhanced quality control of array probesets, significantly improved the positive predictive value and the sensitivity of array data, making it suitable for the detection of ultra-rare variants.

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Jang, Bum-Sup, and In Ah Kim. "Machine-learning algorithms predict breast cancer patient survival from UK Biobank whole-exome sequencing data." Biomarkers in Medicine 15, no. 16 (November 2021): 1529–39. http://dx.doi.org/10.2217/bmm-2021-0280.

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Aim: We tested whether machine-learning algorithm could find biomarkers predicting overall survival in breast cancer patients using blood-based whole-exome sequencing data. Materials & methods: Whole-exome sequencing data derived from 1181 female breast cancer patients within the UK Biobank was collected. We found feature genes (n = 50) regarding total mutation burden using the long short-term memory model. Then, we developed the XGBoost survival model with selected feature genes. Results: The XGBoost survival model performed acceptably, with a concordance index of 0.75 and a scaled Brier score of 0.146 in terms of overall survival prediction. The high-mutation group exhibited inferior overall survival compared with the low-mutation group in patients ≥56 years (log-rank test, p = 0.042). Conclusion: We showed that machine-learning algorithms can be used to predict overall survival in breast cancer patients from blood-based whole-exome sequencing data.

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Glotov, Oleg S., Alexander N. Chernov, and Andrey S. Glotov. "Human Exome Sequencing and Prospects for Predictive Medicine: Analysis of International Data and Own Experience." Journal of Personalized Medicine 13, no. 8 (August 8, 2023): 1236. http://dx.doi.org/10.3390/jpm13081236.

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Today, whole-exome sequencing (WES) is used to conduct the massive screening of structural and regulatory genes in order to identify the allele frequencies of disease-associated polymorphisms in various populations and thus detect pathogenic genetic changes (mutations or polymorphisms) conducive to malfunctional protein sequences. With its extensive capabilities, exome sequencing today allows both the diagnosis of monogenic diseases (MDs) and the examination of seemingly healthy populations to reveal a wide range of potential risks prior to disease manifestation (in the future, exome sequencing may outpace costly and less informative genome sequencing to become the first-line examination technique). This review establishes the human genetic passport as a new WES-based clinical concept for the identification of new candidate genes, gene variants, and molecular mechanisms in the diagnosis, prediction, and treatment of monogenic, oligogenic, and multifactorial diseases. Various diseases are addressed to demonstrate the extensive potential of WES and consider its advantages as well as disadvantages. Thus, WES can become a general test with a broad spectrum pf applications, including opportunistic screening.

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Park, Jason Y., Peter Clark, Eric Londin, Marialuisa Sponziello, Larry J. Kricka, and Paolo Fortina. "Clinical Exome Performance for Reporting Secondary Genetic Findings." Clinical Chemistry 61, no. 1 (January 1, 2015): 213–20. http://dx.doi.org/10.1373/clinchem.2014.231456.

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Abstract BACKGROUND Reporting clinically actionable incidental genetic findings in the course of clinical exome testing is recommended by the American College of Medical Genetics and Genomics (ACMG). However, the performance of clinical exome methods for reporting small subsets of genes has not been previously reported. METHODS In this study, 57 exome data sets performed as clinical (n = 12) or research (n = 45) tests were retrospectively analyzed. Exome sequencing data was examined for adequacy in the detection of potentially pathogenic variant locations in the 56 genes described in the ACMG incidental findings recommendation. All exons of the 56 genes were examined for adequacy of sequencing coverage. In addition, nucleotide positions annotated in HGMD (Human Gene Mutation Database) were examined. RESULTS The 56 ACMG genes have 18 336 nucleotide variants annotated in HGMD. None of the 57 exome data sets possessed a HGMD variant. The clinical exome test had inadequate coverage for >50% of HGMD variant locations in 7 genes. Six exons from 6 different genes had consistent failure across all 3 test methods; these exons had high GC content (76%–84%). CONCLUSIONS The use of clinical exome sequencing for the interpretation and reporting of subsets of genes requires recognition of the substantial possibility of inadequate depth and breadth of sequencing coverage at clinically relevant locations. Inadequate depth of coverage may contribute to false-negative clinical exome results.

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Laver, Thomas W., Elisa De Franco, Matthew B. Johnson, Kashyap A. Patel, Sian Ellard, Michael N. Weedon, Sarah E. Flanagan, and Matthew N. Wakeling. "SavvyCNV: Genome-wide CNV calling from off-target reads." PLOS Computational Biology 18, no. 3 (March 16, 2022): e1009940. http://dx.doi.org/10.1371/journal.pcbi.1009940.

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Identifying copy number variants (CNVs) can provide diagnoses to patients and provide important biological insights into human health and disease. Current exome and targeted sequencing approaches cannot detect clinically and biologically-relevant CNVs outside their target area. We present SavvyCNV, a tool which uses off-target read data from exome and targeted sequencing data to call germline CNVs genome-wide. Up to 70% of sequencing reads from exome and targeted sequencing fall outside the targeted regions. We have developed a new tool, SavvyCNV, to exploit this ‘free data’ to call CNVs across the genome. We benchmarked SavvyCNV against five state-of-the-art CNV callers using truth sets generated from genome sequencing data and Multiplex Ligation-dependent Probe Amplification assays. SavvyCNV called CNVs with high precision and recall, outperforming the five other tools at calling CNVs genome-wide, using off-target or on-target reads from targeted panel and exome sequencing. We then applied SavvyCNV to clinical samples sequenced using a targeted panel and were able to call previously undetected clinically-relevant CNVs, highlighting the utility of this tool within the diagnostic setting. SavvyCNV outperforms existing tools for calling CNVs from off-target reads. It can call CNVs genome-wide from targeted panel and exome data, increasing the utility and diagnostic yield of these tests. SavvyCNV is freely available at https://github.com/rdemolgen/SavvySuite.

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Hegde, Madhuri, Avni Santani, Rong Mao, Andrea Ferreira-Gonzalez, Karen E. Weck, and Karl V. Voelkerding. "Development and Validation of Clinical Whole-Exome and Whole-Genome Sequencing for Detection of Germline Variants in Inherited Disease." Archives of Pathology & Laboratory Medicine 141, no. 6 (March 31, 2017): 798–805. http://dx.doi.org/10.5858/arpa.2016-0622-ra.

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Context.— With the decrease in the cost of sequencing, the clinical testing paradigm has shifted from single gene to gene panel and now whole-exome and whole-genome sequencing. Clinical laboratories are rapidly implementing next-generation sequencing–based whole-exome and whole-genome sequencing. Because a large number of targets are covered by whole-exome and whole-genome sequencing, it is critical that a laboratory perform appropriate validation studies, develop a quality assurance and quality control program, and participate in proficiency testing. Objective.— To provide recommendations for whole-exome and whole-genome sequencing assay design, validation, and implementation for the detection of germline variants associated in inherited disorders. Data Sources.— An example of trio sequencing, filtration and annotation of variants, and phenotypic consideration to arrive at clinical diagnosis is discussed. Conclusions.— It is critical that clinical laboratories planning to implement whole-exome and whole-genome sequencing design and validate the assay to specifications and ensure adequate performance prior to implementation. Test design specifications, including variant filtering and annotation, phenotypic consideration, guidance on consenting options, and reporting of incidental findings, are provided. These are important steps a laboratory must take to validate and implement whole-exome and whole-genome sequencing in a clinical setting for germline variants in inherited disorders.

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Parsons, Donald W., Murali M. Chintagumpala, Stacey L. Berg, Dolores H. López-Terrada, Angshumoy Roy, Robin A. Kerstein, Sarah Scollon, et al. "Implementation and evaluation of clinical exome sequencing in childhood cancer care: The BASIC3 study." Journal of Clinical Oncology 31, no. 15_suppl (May 20, 2013): 10023. http://dx.doi.org/10.1200/jco.2013.31.15_suppl.10023.

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10023 Background: Advances in sequencing technologies allow for provision of genome-scale data to oncologists and geneticists caring for pediatric cancer patients. The goal of the BASIC3 (Baylor Advancing Sequencing into Childhood Cancer Care) study is to determine the clinical impact of incorporating CLIA-certified tumor and constitutional exome sequencing into the care of children with newly diagnosed solid tumors. Methods: Blood and frozen tumor samples obtained at initial surgery are submitted for clinical exome sequencing (target enrollment 280 patients). Results are deposited into the electronic medical record and disclosed to families by their oncologist and a genetic counselor. Identification of germline cancer susceptibility mutations is compared with standard testing practices. Oncologists are surveyed on prioritization of treatment options in the hypothetical event of tumor recurrence before and after receiving tumor exome results. Patients will be followed for two years to assess the clinical utility of exome data. Preferences for reporting this complex information are obtained by interviews and audiorecording of disclosure visits. Results: Initial results reveal that41 of 49 (84%) ethnically diverse families have consented to enroll on study. Adequate tumor samples were available from 35 of 41 patients (85%), including 11 of 15 (73%) patients with CNS tumors and 24 of 26 (92%) with non-CNS tumors. Pathogenic germline cancer susceptibility mutations (TP53, MSH2) were reported in 2 of the first 11 patients, with a medically-actionable mutation in a gene (SCN5A) unrelated to cancer in 1 patient and 0-4 (median of 2) recessive carrier mutations per patient. Between 9 and 33 protein altering mutations (median of 11) have been identified in tumors, including known cancer genes such as TP53 and others with no known link to pediatric cancer. Conclusions: A robust clinical pipeline for exome sequencing of blood and tumor samples has been successfully developed with significant parental interest. Data assessing the clinical utility of both the tumor and constitutional exomes and the preferences of oncologists and parents for reporting of these results are under study. Supported by NHGRI 1U01HG006485.

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Lu, Peng, Pengyun Wang, Lianbing Li, Chengqi Xu, Jing Crystal Liu, Xiangqian Guo, Dawei He, Huizhe Huang, and Zhi Cheng. "Exomic and Epigenomic Analyses in a Pair of Monozygotic Twins Discordant for Cryptorchidism." Twin Research and Human Genetics 20, no. 4 (June 13, 2017): 349–54. http://dx.doi.org/10.1017/thg.2017.33.

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Cryptorchidism represents one of the most common human congenital anomalies. In most cases, its etiology remains unclear and seems to be multifactorial. In the present study, a pair of monozygotic twins discordant for cryptorchidism was identified. Twin zygosity was confirmed by microsatellite genotyping. Whole exome sequencing and methylated DNA immunoprecipitation sequencing (MeDIP-Seq) of DNA extract from leucocytes were performed to, respectively, evaluate their exomes and epigenomes. No differences in exome sequencing data were found between the twins after validation. MeDIP-Seq analysis detected 5,410 differentially hypermethylated genes and 2,383 differentially hypomethylated genes. Bioinformatic analysis showed that these genes belonged to several biological processes and signaling pathways, including regulation of actin cytoskeleton, which has been previously implicated in the etiology of cryptorchidism. The findings of the present study suggest that non-genetic factors might contribute to the pathogenesis of cryptorchidism.

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Yauy, Kevin, Charles Van Goethem, Henri Pégeot, David Baux, Thomas Guignard, Corinne Thèze, Olivier Ardouin, et al. "Evaluating the Transition from Targeted to Exome Sequencing: A Guide for Clinical Laboratories." International Journal of Molecular Sciences 24, no. 8 (April 15, 2023): 7330. http://dx.doi.org/10.3390/ijms24087330.

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The transition from targeted to exome or genome sequencing in clinical contexts requires quality standards, such as targeted sequencing, in order to be fully adopted. However, no clear recommendations or methodology have emerged for evaluating this technological evolution. We developed a structured method based on four run-specific sequencing metrics and seven sample-specific sequencing metrics for evaluating the performance of exome sequencing strategies to replace targeted strategies. The indicators include quality metrics and coverage performance on gene panels and OMIM morbid genes. We applied this general strategy to three different exome kits and compared them with a myopathy-targeted sequencing method. After having achieved 80 million reads, all-tested exome kits generated data suitable for clinical diagnosis. However, significant differences in the coverage and PCR duplicates were observed between the kits. These are two main criteria to consider for the initial implementation with high-quality assurance. This study aims to assist molecular diagnostic laboratories in adopting and evaluating exome sequencing kits in a diagnostic context compared to the strategy used previously. A similar strategy could be used to implement whole-genome sequencing for diagnostic purposes.

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Verrou, Kleio-Maria, Georgios A. Pavlopoulos, and Panagiotis Moulos. "Protocol for unbiased, consolidated variant calling from whole exome sequencing data." STAR Protocols 3, no. 2 (June 2022): 101418. http://dx.doi.org/10.1016/j.xpro.2022.101418.

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Yauy, Kevin, Nicole de Leeuw, Helger G. Yntema, Rolph Pfundt, and Christian Gilissen. "Accurate detection of clinically relevant uniparental disomy from exome sequencing data." Genetics in Medicine 22, no. 4 (November 26, 2019): 803–8. http://dx.doi.org/10.1038/s41436-019-0704-x.

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Backenroth, Daniel, Jason Homsy, Laura R. Murillo, Joe Glessner, Edwin Lin, Martina Brueckner, Richard Lifton, Elizabeth Goldmuntz, Wendy K. Chung, and Yufeng Shen. "CANOES: detecting rare copy number variants from whole exome sequencing data." Nucleic Acids Research 42, no. 12 (April 25, 2014): e97-e97. http://dx.doi.org/10.1093/nar/gku345.

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Kim, Bo-Young, Jung Hoon Park, Hye-Yeong Jo, Soo Kyung Koo, and Mi-Hyun Park. "Optimized detection of insertions/deletions (INDELs) in whole-exome sequencing data." PLOS ONE 12, no. 8 (August 9, 2017): e0182272. http://dx.doi.org/10.1371/journal.pone.0182272.

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42

Guo, Yan, Shilin Zhao, Quanhu Sheng, Fei Ye, Jiang Li, Brian Lehmann, Jennifer Pietenpol, David C. Samuels, and Yu Shyr. "Multi-perspective quality control of Illumina exome sequencing data using QC3." Genomics 103, no. 5-6 (May 2014): 323–28. http://dx.doi.org/10.1016/j.ygeno.2014.03.006.

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Kim, Sung Min, Seong Yeon Yoo, Soo Hyun Nam, Jae Moon Lee, and Ki Wha Chung. "Identification of Korean-specific SNP markers from whole-exome sequencing data." International Journal of Legal Medicine 130, no. 3 (February 9, 2016): 669–77. http://dx.doi.org/10.1007/s00414-015-1313-0.

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Oesper, Layla, Gryte Satas, and Benjamin J. Raphael. "Quantifying tumor heterogeneity in whole-genome and whole-exome sequencing data." Bioinformatics 30, no. 24 (October 8, 2014): 3532–40. http://dx.doi.org/10.1093/bioinformatics/btu651.

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45

Magi, Alberto. "H3M2: Detection of runs of homozygosity from whole-exome sequencing data." Journal of Biotechnology 185 (September 2014): S15. http://dx.doi.org/10.1016/j.jbiotec.2014.07.053.

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Larson, Nicholas B., and Daniel J. Schaid. "Regularized Rare Variant Enrichment Analysis for Case-Control Exome Sequencing Data." Genetic Epidemiology 38, no. 2 (December 30, 2013): 104–13. http://dx.doi.org/10.1002/gepi.21783.

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Nishino, Jo, Shuichi Watanabe, Fuyuki Miya, Takashi Kamatani, Toshitaka Sugawara, Keith A. Boroevich, and Tatsuhiko Tsunoda. "Quantification of multicellular colonization in tumor metastasis using exome‐sequencing data." International Journal of Cancer 146, no. 9 (February 15, 2020): 2488–97. http://dx.doi.org/10.1002/ijc.32910.

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Tbeileh, Noura, Luika Timmerman, Aras N. Mattis, Kan Toriguchi, Yosuke Kasai, Carlos Corvera, Eric Nakakura, et al. "Metastatic colorectal adenocarcinoma tumor purity assessment from whole exome sequencing data." PLOS ONE 18, no. 4 (April 6, 2023): e0271354. http://dx.doi.org/10.1371/journal.pone.0271354.

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Tumors rich in stroma are associated with advanced stage and poor prognosis in colorectal adenocarcinoma (CRC). Abundance of stromal cells also has implications for genomic analysis of patient tumors as it may prevent detection of somatic mutations. As part of our efforts to interrogate stroma-cancer cell interactions and to identify actionable therapeutic targets in metastatic CRC, we aimed to determine the proportion of stroma embedded in hepatic CRC metastases by performing computational tumor purity analysis based on whole exome sequencing data (WES). Unlike previous studies focusing on histopathologically prescreened samples, we used an unbiased in-house collection of tumor specimens. WES from CRC liver metastasis samples were utilized to evaluate stromal content and to assess the performance of three in silico tumor purity tools, ABSOLUTE, Sequenza and PureCN. Matching tumor derived organoids were analyzed as a high purity control as they are enriched in cancer cells. Computational purity estimates were compared to those from a histopathological assessment conducted by a board-certified pathologist. According to all computational methods, metastatic specimens had a median tumor purity of 30% whereas the organoids were enriched for cancer cells with a median purity estimate of 94%. In line with this, variant allele frequencies (VAFs) of oncogenes and tumor suppressor genes were undetectable or low in most patient tumors, but higher in matching organoid cultures. Positive correlation was observed between VAFs and in silico tumor purity estimates. Sequenza and PureCN produced concordant results whereas ABSOLUTE yielded lower purity estimates for all samples. Our data shows that unbiased sample selection combined with molecular, computational, and histopathological tumor purity assessment is critical to determine the level of stroma embedded in metastatic colorectal adenocarcinoma.

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Ghosh, Rajarshi, Andrew Oler, Mark Rustad, Samuel Li, Jia Yan, Morgan Similuk, Steven Holland, and Magdalena Walkiewicz-Yvon. "P469: Clinical relevance of mosaic variants detected from exome sequencing data." Genetics in Medicine Open 1, no. 1 (2023): 100516. http://dx.doi.org/10.1016/j.gimo.2023.100516.

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Ghosh, Rajarshi, Andrew Oler, Mark Rustad, Samuel Li, Jia Yan, Morgan Similuk, Bryce Seifert, Katherine Calvo, Steven Holland, and Magdalena Walkiewicz. "Clinical relevance of somatic mosaic variants detected from exome sequencing data." Clinical Immunology 250 (May 2023): 109363. http://dx.doi.org/10.1016/j.clim.2023.109363.

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