Sequencing the coding regions, the exome, of the human genome is one of the major current strategies to identify low frequency and rare variants associated with human disease traits. So far, the most widely used commercial exome capture reagents have mainly targeted the consensus coding sequence (CCDS) database. We report the design of an extended set of targets for capturing the complete human exome, based on annotation from the GENCODE consortium. The extended set covers an additional 5594 genes and 10.3 Mb compared with the current CCDS-based sets. The additional regions include potential disease genes previously inaccessible to exome resequencing studies, such as 43 genes linked to ion channel activity and 70 genes linked to protein kinase activity. In total, the new GENCODE exome set developed here covers 47.9 Mb and performed well in sequence capture experiments. In the sample set used in this study, we identified over 5000 SNP variants more in the GENCODE exome target (24%) than in the CCDS-based exome sequencing.

Massively parallel sequencing is rapidly becoming a widely used method in genetic diagnostics. However, there is still no clear consensus as to which approach can most efficiently identify the pathogenic mutations carried by a given patient, while avoiding false negative and false positive results. We developed a targeted exome approach (MyoPanel2) in order to optimize genetic diagnosis of neuromuscular disorders. Using this approach, we were able to analyse 306 genes known to be mutated in myopathies as well as in related disorders, obtaining 98.8% target sequence coverage at 20 ×. Moreover, MyoPanel2 was able to detect 99.7% of 11,467 known mutations responsible for neuromuscular disorders. We have then used several quality control parameters to compare performance of the targeted exome approach with that of whole exome sequencing. The results of this pilot study of 140 DNA samples suggest that targeted exome sequencing approach is an efficient genetic diagnostic test for most neuromuscular diseases.

We apply our statistically deterministic machine learning/clustering algorithm *K-means (recently developed in https://ssrn.com/abstract=2908286) to 10,656 published exome samples for 32 cancer types. A majority of cancer types exhibit a mutation clustering structure. Our results are in-sample stable. They are also out-of-sample stable when applied to 1389 published genome samples across 14 cancer types. In contrast, we find in- and out-of-sample instabilities in cancer signatures extracted from exome samples via nonnegative matrix factorization (NMF), a computationally-costly and non-deterministic method. Extracting stable mutation structures from exome data could have important implications for speed and cost, which are critical for early-stage cancer diagnostics, such as novel blood-test methods currently in development.

Single-cell genome sequencing methods are challenged by poor physical coverage and high error rates, making it difficult to distinguish real biological variants from technical artifacts. To address this problem, we developed a method called SNES that combines flow-sorting of single G1/0 or G2/M nuclei, time-limited multiple-displacement-amplification, exome capture, and next-generation sequencing to generate high coverage (96%) data from single human cells. We validated our method in a fibroblast cell line, and show low allelic dropout and false-positive error rates, resulting in high detection efficiencies for single nucleotide variants (92%) and indels (85%) in single cells.

Many exome sequencing studies of Mendelian disorders fail to optimally exploit family information. Classical genetic linkage analysis is an effective method for eliminating a large fraction of the candidate causal variants discovered, even in small families that lack a unique linkage peak. We demonstrate that accurate genetic linkage mapping can be performed using SNP genotypes extracted from exome data, removing the need for separate array-based genotyping. We provide software to facilitate such analyses.

Evaluation of the clinician's role in the optimal interpretation of clinical exome sequencing (ES) results.

With the widespread adoption of next generation sequencing technologies by the genetics community and the rapid decrease in costs per base, exome sequencing has become a standard within the repertoire of genetic experiments for both research and diagnostics. Although bioinformatics now offers standard solutions for the analysis of exome sequencing data, many challenges still remain; especially the increasing scale at which exome data are now being generated has given rise to novel challenges in how to efficiently store, analyze and interpret exome data of this magnitude. In this review we discuss some of the recent developments in bioinformatics for exome sequencing and the directions that this is taking us to. With these developments, exome sequencing is paving the way for the next big challenge, the application of whole genome sequencing.

Genotyping chips for rare and low-frequent variants have recently gained popularity with the introduction of exome chips, but the utility of these chips remains unclear. These chips were designed using exome sequencing data from mainly American-European individuals, enriched for a narrow set of common diseases. In addition, it is well-known that the statistical power of detecting associations with rare and low-frequent variants is much lower compared to studies exclusively involving common variants. We developed a simulation program adaptable to any exome chip design to empirically evaluate the power of the exome chips. We implemented the main properties of the Illumina HumanExome BeadChip array. The simulated data sets were used to assess the power of exome chip based studies for varying effect sizes and causal variant scenarios. We applied two widely-used statistical approaches for rare and low-frequency variants, which collapse the variants into genetic regions or genes. Under optimal conditions, we found that a sample size between 20,000 to 30,000 individuals were needed in order to detect modest effect sizes (0.5% < PAR > 1%) with 80% power. For small effect sizes (PAR <0.5%), 60,000-100,000 individuals were needed in the presence of non-causal variants. In conclusion, we found that at least tens of thousands of individuals are necessary to detect modest effects under optimal conditions. In addition, when using rare variant chips on cohorts or diseases they were not originally designed for, the identification of associated variants or genes will be even more challenging.

Carotid body tumor (CBT) is a form of head and neck paragangliomas (HNPGLs) arising at the bifurcation of carotid arteries. Paragangliomas are commonly associated with germline and somatic mutations involving at least one of more than thirty causative genes. However, the specific functionality of a number of these genes involved in the formation of paragangliomas has not yet been fully investigated.

The rat genome was sequenced in 2004 with the aim to improve human health altered by disease and environmental influences through gene discovery and animal model validation. Here, we report development and testing of a probe set for whole exome sequencing (WES) to detect sequence variants in exons and UTRs of the rat genome. Using an in-silico approach, we designed probes targeting the rat exome and compared captured mutations in cancer-related genes from four chemically induced rat tumor cell lines (C6, FAT7, DSL-6A/C1, NBTII) to validated cancer genes in the human database, Catalogue of Somatic Mutations in Cancer (COSMIC) as well as normal rat DNA. Paired, fresh frozen (FF) and formalin-fixed, paraffin-embedded (FFPE) liver tissue from naive rats were sequenced to confirm known dbSNP variants and identify any additional variants.

High throughput sequencing has greatly advanced disease gene identification, especially in heterogeneous entities. Despite falling costs this is still an expensive and laborious technique, particularly when studying large cohorts. To address this problem we applied Exome Pool-Seq as an economic and fast screening technology in neurodevelopmental disorders (NDDs). Sequencing of 96 individuals can be performed in eight pools of 12 samples on less than one Illumina sequencer lane. In a pilot study with 96 cases we identified 27 variants, likely or possibly affecting function. Twenty five of these were identified in 923 established NDD genes (based on SysID database, status November 2016) (ACTB, AHDC1, ANKRD11, ATP6V1B2, ATRX, CASK, CHD8, GNAS, IFIH1, KCNQ2, KMT2A, KRAS, MAOA, MED12, MED13L, RIT1, SETD5, SIN3A, TCF4, TRAPPC11, TUBA1A, WAC, ZBTB18, ZMYND11), two in 543 (SysID) candidate genes (ZNF292, BPTF), and additionally a de novo loss-of-function variant in LRRC7, not previously implicated in NDDs. Most of them were confirmed to be de novo, but we also identified X-linked or autosomal-dominantly or autosomal-recessively inherited variants. With a detection rate of 28%, Exome Pool-Seq achieves comparable results to individual exome analyses but reduces costs by >85%. Compared with other large scale approaches using Molecular Inversion Probes (MIP) or gene panels, it allows flexible re-analysis of data. Exome Pool-Seq is thus well suited for large-scale, cost-efficient and flexible screening in characterized but heterogeneous entities like NDDs.

Intragenic exonic deletions are known to contribute to genetic diseases and are often flanked by regions of homology.

Human exome resequencing using commercial target capture kits has been and is being used for sequencing large numbers of individuals to search for variants associated with various human diseases. We rigorously evaluated the capabilities of two solution exome capture kits. These analyses help clarify the strengths and limitations of those data as well as systematically identify variables that should be considered in the use of those data.

Hypospadias results from the impaired urethral development, which is influenced by androgens, but its genetic etiology is still unknown. Through whole exome sequencing analysis, we identified NR5A1, SRD5A2, and AR as mutational hotspots in the etiology of severe hypospadias, as these genes are related to androgen signaling. Additionally, rare damaging variants in cilia-related outer dynein arm heavy chain (ODNAH) genes (DNAH5, DNAH8, DNAH9, DNAH11, and DNAH17) (p = 8.5 × 10-47) were significantly enriched in hypospadias cases. The Dnah8 KO mice exhibited significantly decreased testosterone levels, which had an impact on urethral development and disrupted steroid biosynthesis. Combined with trios data, transcriptomic, and phenotypical and proteomic characterization of a mouse model, our work links ciliary genes with hypospadias. Overall, a panel of ODNAH genes with rare damaging variants was identified in 24% of hypospadias patients, providing significant insights into the underlying pathogenesis of hypospadias as well as genetic counseling.

Atrial fibrillation (AF) is a morbid and heritable arrhythmia. Over 35 genes have been reported to underlie AF, most of which were described in small candidate gene association studies. Replication remains lacking for most, and therefore the contribution of coding variation to AF susceptibility remains poorly understood. We examined whole exome sequencing data in a large community-based sample of 1,734 individuals with and 9,423 without AF from the Framingham Heart Study, Cardiovascular Health Study, Atherosclerosis Risk in Communities Study, and NHLBI-GO Exome Sequencing Project and meta-analyzed the results. We also examined whether genetic variation was enriched in suspected AF genes (N = 37) in AF cases versus controls. The mean age ranged from 59 to 73 years; 8,656 (78%) were of European ancestry. None of the 99,404 common variants evaluated was significantly associated after adjusting for multiple testing. Among the most significantly associated variants was a common (allele frequency = 86%) missense variant in SYNPO2L (rs3812629, p.Pro707Leu, [odds ratio 1.27, 95% confidence interval 1.13-1.43, P = 6.6x10-5]) which lies at a known AF susceptibility locus and is in linkage disequilibrium with a top marker from prior analyses at the locus. We did not observe significant associations between rare variants and AF in gene-based tests. Individuals with AF did not display any statistically significant enrichment for common or rare coding variation in previously implicated AF genes. In conclusion, we did not observe associations between coding genetic variants and AF, suggesting that large-effect coding variation is not the predominant mechanism underlying AF. A coding variant in SYNPO2L requires further evaluation to determine whether it is causally related to AF. Efforts to identify biologically meaningful coding variation underlying AF may require large sample sizes or populations enriched for large genetic effects.

Core promoter controls the initiation of transcription. Core promoter sequence change can disrupt transcriptional regulation, lead to impairment of gene expression and ultimately diseases. Therefore, comprehensive characterization of core promoters is essential to understand normal and abnormal gene expression in biomedical studies. Here we report the development of EVDC (Exome-based Variant Detection in Core promoters) method for genome-scale analysis of core-promoter sequence variation. This method is based on the fact that exome sequences contain the sequences not only from coding exons but also from non-coding region including core promoters generated by random fragmentation in exome sequencing process. Using exome data from three cell types of CD4+ T cells, CD19+ B cells and neutrophils of a single individual, we characterized the features of core promoter-mapped exome sequences, and analysed core-promoter variation in this individual genome. We also compared the core promoters between YRI (Yoruba in Ibadan, Nigeria) and the CEU (Utah residents of European decedent) populations using the exome data generated by the 1000 Genome project, and observed much higher variation in YRI population than in CEU population. Our study demonstrates that the EVDC method provides a simple but powerful means for genome-wile de novo characterization of core promoter sequence variation.

Sample pooling enabled by dedicated indexes is a common strategy for cost-effective and robust high-throughput sequencing. Index misassignment leading to mutual contamination between pooled samples has however been described as a general problem of the latest Illumina sequencing instruments utilizing exclusion amplification. Using real-life data from multiple tumour sequencing projects, we demonstrate that index misassignment can induce artefactual variant calls closely resembling true, high-quality somatic variants. These artefactual calls potentially impact cancer applications utilizing low allelic frequencies, such as in clonal analysis of tumours. We discuss the available countermeasures with an emphasis on improved library indexing methods, and provide software that can assist in the identification of variants that may be consequences of index misassignment.

The genetic characteristics of rectal neuroendocrine tumors (R-NETs) were poorly understood. Depicting the genetic characteristics may provide a biological basis for prognosis prediction and novel treatment development. Tissues of 18 R-NET patients were analyzed using whole-exome sequencing. The median tumor mutation burden (TMB) and microsatellite instability (MSI) were 1.15 Muts/MB (range, 0.03-23.28) and 0.36 (range, 0.00-10.97), respectively. Genes involved in P53 signaling, PI3K-AKT signaling, DNA damage repair, WNT signaling, etc. were frequently altered. Higher TMB (P = 0.078), higher CNV (P = 0.110), somatic mutation of CCDC168 (P = 0.049), HMCN1 (P = 0.040), MYO10 (P = 0.007), and amplification of ZC3H13 (P < 0.001) were associated with shorter OS. Potentially targetable gene alterations (PTGAs) were seen in 72% of the patients. FGFR1 amplification (22%) was the most common PTGA followed by BARD1 and BRCA2 mutation (each 17%). As for gene variations associated with the efficacy of immune checkpoint blockade (ICB), FAT1 alteration (39%) and PTEN depletion (28%) were commonly observed. In conclusion, frequently altered oncogenic pathways might contribute to the development and progression of R-NETs. Gene alterations significantly associated with prognosis might be potential novel targets. Targeted therapy might be a promising strategy as targetable alterations were prevalent in R-NETs. FAT1 alteration and PTEN depletion might be the main genetic alterations influencing the response to ICB besides overall low TMB and MSI in R-NETs.

We had analyzed 10 exome sequencing data and single nucleotide polymorphism chips for blood cancer provided by the PGM21 (The National Project for Personalized Genomic Medicine) Award program. We had removed sample G06 because the pair is not correct and G10 because of possible contamination. In-house software somatic copy-number and heterozygosity alteration estimation (SCHALE) was used to detect one loss of heterozygosity region in G05. We had discovered 27 functionally important mutations. Network and pathway analyses gave us clues that NPM1, GATA2, and CEBPA were major driver genes. By comparing with previous somatic mutation profiles, we had concluded that the provided data originated from acute myeloid leukemia. Protein structure modeling showed that somatic mutations in IDH2, RASGEF1B, and MSH4 can affect protein structures.

Acrodysostosis is a dominantly-inherited, multisystem disorder characterized by skeletal, endocrine, and neurological abnormalities. To identify the molecular basis of acrodysostosis, we performed exome sequencing on five genetically independent cases. Three different missense mutations in PDE4D, which encodes cyclic AMP (cAMP)-specific phosphodiesterase 4D, were found to be heterozygous in three of the cases. Two of the mutations were demonstrated to have occurred de novo, providing strong genetic evidence of causation. Two additional cases were heterozygous for de novo missense mutations in PRKAR1A, which encodes the cAMP-dependent regulatory subunit of protein kinase A and which has been recently reported to be the cause of a form of acrodysostosis resistant to multiple hormones. These findings demonstrate that acrodysostosis is genetically heterogeneous and underscore the exquisite sensitivity of many tissues to alterations in cAMP homeostasis.