Development and Validation of Clinical Whole-Exome and Whole-Genome Sequencing for Detection of Germline Variants in Inherited Disease

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 wholeexome 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

Development and performance of a targeted whole exome sequencing enrichment kit for the dog (Canis Familiaris Build 3.1)

Whole exome sequencing is a technique that aims to selectively sequence all exons of protein-coding genes. A canine whole exome sequencing enrichment kit was designed based on the latest canine reference genome (build 3.1.72). Its performance was tested by sequencing 2 exome captures, each consisting of 4 pre-capture pooled, barcoded Illumina libraries on an Illumina HiSeq 2500. At an average sequencing depth of 102x, 83 to 86% of the target regions were completely sequenced with a minimum coverage of five and 90% of the reads mapped on the target regions. Additionally, it is shown that the reproducibility within and between captures is high and that pooling four samples per capture is a valid option. Overall, we have demonstrated the strong performance of this WES enrichment kit and are confident it will be a valuable tool in future disease association studies

An heuristic filtering tool to identify phenotype-associated genetic variants applied to human intellectual disability and canine coat colors

Background: Identification of one or several disease causing variant(s) from the large collection of variants present in an individual is often achieved by the sequential use of heuristic filters. The recent development of whole exome sequencing enrichment designs for several non-model species created the need for a species-independent, fast and versatile analysis tool, capable of tackling a wide variety of standard and more complex inheritance models. With this aim, we developed "Mendelian", an R-package that can be used for heuristic variant filtering. Results: The R-package Mendelian offers fast and convenient filters to analyze putative variants for both recessive and dominant models of inheritance, with variable degrees of penetrance and detectance. Analysis of trios is supported. Filtering against variant databases and annotation of variants is also included. This package is not species specific and supports parallel computation. We validated this package by reanalyzing data from a whole exome sequencing experiment on intellectual disability in humans. In a second example, we identified the mutations responsible for coat color in the dog. This is the first example of whole exome sequencing without prior mapping in the dog. Conclusion: We developed an R-package that enables the identification of disease-causing variants from the long list of variants called in sequencing experiments. The software and a detailed manual are available at https://github.com/BartBroeckx/Mendelian

Using linkage analysis of large pedigrees to guide association analyses

To date, genome-wide association studies have yielded discoveries of common variants that partly explain familial aggregation of diseases and traits. Researchers are now turning their attention to less common variants because the price of sequencing has dropped drastically. However, because sequencing of the whole genome in large samples is costly, great care must be taken to prioritize which samples and which genomic regions are selected for sequencing. We are interested in identifying genomic regions for deep sequencing using large multiplex families collected as part of earlier linkage studies. We incorporate linkage analysis into our search for Q1-associated alleles. Overall, we found that power was low for both whole-exome and linkage-guided sequencing analysis. By restricting sequencing to regions with high LOD peaks, we found fewer associated single-nucleotide polymorphisms than by using whole-exome sequencing. However, incorporating linkage analysis enabled us to detect more than half of the associated susceptibility loci (52%) that would have been identified by whole-exome sequencing while examining only 2.5% of the exome. This result suggests that incorporating linkage results from large multiplex families might greatly increase the efficiency of sequencing to detect trait-associated alleles in complex disease

Whole-Exome Sequencing Study of Thyrotropin-Secreting Pituitary Adenomas

学位記番号：医博甲169

희귀 신경근 질환의 유전체, 전사체 통합 분석 연구

학위논문(석사)--서울대학교 대학원 :의과대학 의과학과,2019. 8. 최무림.Whole exome sequencing (WES)은 비용 및 데이터 처리의 용이성으로 인하여 희귀질환 진단등에 매우 효과적인 방법이 되었다. 그러나 variant of unknown significances (VUS)를 해석하는 어려움과non-coding 변이형을 확인할 수 없다는 점 등의 이유로 WES 기반의 희귀질환 진단률은 대부분 50%를 넘지 못한다. 따라서, 본 연구에서는 희귀질환 진단의 보완적인 접근법으로 새로이 전사체 분석법을 도입할 것을 제시하고자 한다. 이를 위하여 서울대학교 어린이병원 소아신경과에서 임상적으로 진단되지 못한 근신경질환 환자 94 명을 대상으로 WES 분석을 실시하고, 이미 알려진 근신경질환의 원인 유전자 변이들을 분석하였다. 추가적으로, 기존에 WES 분석이 수행된 63명의 환자군과 이 외의 10명의 환자군을 추가하여 전사체 분석을 수행하였다. 전사체 데이터를 이용하여 damaging 변이 분석, allele-specific expression 분석, 환자군과 정상군에서 다르게 발현하는 유전자 (DEG) 및 비정상적인 splicing 양상을 탐색하는 분석을 수행하였다. 또한, non-negative matrix factorization 분석 기법을 통해 유전자 발현 프로파일을 기반으로 한 군집화를 수행하고, 각 군집을 특징 짓는 유전자 그룹을 도출하였다. 그 결과, WES 분석을 통하여 49%의 환자에서 후보 원인 변이를 확인하였으며, 그 중 83%의 환자에서는 알려진 근신경질환 원인 유전자의 변이를 확인하였다. 12명의 환자에서는 그 기능성이 확실하지 않은 구조 변이를 확인하였다. 전사체 데이터 기반의 변이 분석을 통하여, WES 을 수행하지 않은 5 명의 환자를 포함한 총 9 명의 환자에서 heterozygous 변이를 추가로 발견하였다. Allele-specific expression 분석을 통하여 2개의 후보 원인유전자를 발견하였고, DEG 분석 결과, 4명의 환자에서 잠재적인 원인 유전자 그룹을 선별할 수 있었다. 또한, 4 명의 환자에게서 DMD, TTN, MICU1 유전자들의 비정상적인 splicing이 확인되었다. non-negative matrix factorization 기반 군집화 분석 결과, 유전자 발현 양상을 기반으로 한 6개의 군집을 확인할 수 있었다. 본 연구를 통하여 전사체 분석법이 기존의 WES 기법 기반 분석의 효과적인 보완 기법이 될지의 여부를 확인하고자 하였다. 전사체 분석 결과, WES 기법을 통해 원인 유전자 변이가 확인된 환자들 중 9명에게서 같은 맥락의 전사체 이상을 확인할 수 있었으며, WES을 수행하지 않은 환자들 중 18명에게서도 잠재적인 원인 유전자 변이를 확인하였다. 따라서 전사체 분석법은 기존의 분석기법으로 원인 유전자 변이를 발견할 수 없는 증례의 진단에 유용한 도구로 사용될 수 있음을 시사한다.Introduction. Whole exome sequencing has become a robust and standard tool for rare diseases diagnosis thanks to advantages in cost and data handling. However, whole exome sequencing-based diagnosis rates typically do not exceed 50%, which can be attributed to the difficulty of interpreting variants of uncertain significance, as well as to the disregard of non-coding variants, including variants in intronic and regulatory regions in the genome. Therefore, I explored the utility of transcriptome sequencing as a compensatory approach in rare neuromuscular disorders diagnosis. Methods. Whole exome sequencing of 94 patients with undiagnosed neuromuscular disorders was collected from Seoul National University Childrens Hospital and analyzed for variants in known neuromuscular disease genes. Additional transcriptome sequencing was performed for 63 of the whole exome sequenced patients and for ten patients without genome data. Transcriptome data were utilized for cryptic damaging variants, differentially expression, aberrant splicing and allele specific expression analysis. Furthermore, non-negative matrix factorization was applied to identify expression-based clustering and cluster-specific gene ontology was derived. Results. Whole exome sequencing analysis identified candidate variants in 49% of patients, with 83% of them located within known disease genes. Structural variants with questionable pathogenicity were discovered in twelve cases. RNA-Sequencing based variant calling lead to further discovery of heterozygous candidate variants in nine samples, five of which did not undergo whole exome sequencing. Allele specific expression identified two likely candidate genes and differential gene expression analysis lead to the prioritization of sets of genes in an additional four samples. Lastly, aberrant splicing of DMD, TTN and MICU1 was detected in each of four samples. Non-negative matrix factorization-based clustering resulted in the identification of six clusters with distinct gene expression profiles. Discussion. Firstly, I aimed to evaluate whether transcriptome sequencing can provide additional evidence for the interpretation of whole exome sequencing variants. Overall, transcriptome sequencing was able to detect abnormalities associated with the previously identified mutation in less than 30% of positive whole exome sequencing cases. For samples without whole exome sequencing result, I successfully used transcriptome sequencing to identify potential pathogenic causes in 18 cases. In conclusion, transcriptome sequencing proved to be a useful tool for the diagnosis of whole exome sequencing negative samples, but did not prove to have great utility for the interpretation of pathogenic whole exome sequencing variants.1. INTRODUCTION.....................................................................................1 1.1. Advancement through next generation sequencing...................1 1.2. Genetics of neuromuscular disorders (NMD)..............................3 1.3. Transcriptome sequencing-based NMD diagnosis.......................8 2. METHODS............................................................................................12 2.1. Data collection.........................................................................12 2.2. Whole exome sequencing data analysis....................................13 2.3. Transcriptome sequencing analysis...........................................15 2.4. Non-negative matrix factorization based clustering...................19 3. RESULTS...............................................................................................22 3.1. Data collection.........................................................................22 3.2. Phenotype information.............................................................23 3.3. Whole exome sequencing results..............................................25 3.4. Transcriptome sequencing quality control..................................28 3.5. Transcriptome-based clustering.................................................31 3.6. Exome variants in transcriptome sequencing.............................35 3.7. Transcriptome-sequencing based diagnosis...............................39 4. DISCUSSION..........................................................................................48 5. REFERENCES.........................................................................................57 6. APPENDIX.............................................................................................63 6.1. Supplementary Figures..............................................................63 6.2. Supplementary Tables................................................................67 7. 국문초록.................................................................................................71Maste

Analysis of Archived Residual Newborn Screening Blood Spots After Whole Genome Amplification

Deidentified newborn screening bloodspot samples (NBS) represent a valuable potential resource for genomic research if impediments to whole exome sequencing of NBS deoxyribonucleic acid (DNA), including the small amount of genomic DNA in NBS material, can be overcome. For instance, genomic analysis of NBS could be used to define allele frequencies of disease-associated variants in local populations, or to conduct prospective or retrospective studies relating genomic variation to disease emergence in pediatric populations over time. In this study, we compared the recovery of variant calls from exome sequences of amplified NBS genomic DNA to variant calls from exome sequencing of non-amplified NBS DNA from the same individuals. Results: Using a standard alignment-based Genome Analysis Toolkit (GATK), we find 62,000-76,000 additional variants in amplified samples. After application of a unique kmer enumeration and variant detection method (RUFUS), only 38,000-47,000 additional variants are observed in amplified gDNA. This result suggests that roughly half of the amplification-introduced variants identified using GATK may be the result of mapping errors and read misalignment. Conclusions: Our results show that it is possible to obtain informative, high-quality data from exome analysis of whole genome amplified NBS with the important caveat that different data generation and analysis methods can affect variant detection accuracy, and the concordance of variant calls in whole-genome amplified and non-amplified exomes.National Institute of Health P01HD067244, NS076465, R01ES021006Nutritional Science