Critical points for an accurate human genome analysis

Next‐generation sequencing is radically changing how DNA diagnostic laboratories operate. What started as a single‐gene profession is now developing into gene panel sequencing and whole‐exome and whole‐genome sequencing (WES/WGS) analyses. With further advances in sequencing technology and concomitant price reductions, WGS will soon become the standard and be routinely offered. Here, we focus on the critical steps involved in performing WGS, with a particular emphasis on points where WGS differs from WES, the important variables that should be taken into account, and the quality control measures that can be taken to monitor the process. The points discussed here, combined with recent publications on guidelines for reporting variants, will facilitate the routine implementation of WGS into a diagnostic setting.     

Evaluation of whole genome amplification protocols for array and oligonucleotide CGH.

Genome-based technologies such as genomic arrays and next generation sequencing are poised to make significant contributions to clinical oncology. However, translation of these technologies to the clinic will require that they produce high-quality reproducible data from small archived tumor specimens and biopsies. Herein, we report on a systematic and comprehensive microarray analysis comparing multiple whole genome amplification methods using a variety of difficult clinical specimens, including formalin-fixed and paraffin-embedded tissues. Quantitative analysis and clustering suggest that Sigma's whole genome amplification protocol performed best on all specimens and, moreover, worked well with a formalin-fixed, paraffin-embedded biopsy.     

Shallow whole genome sequencing for robust copy number profiling of formalin-fixed paraffin-embedded breast cancers

Pathology archives with linked clinical data are an invaluable resource for translational research, with the limitation that most cancer samples are formalin-fixed paraffin-embedded (FFPE) tissues. Therefore, FFPE tissues are an important resource for genomic profiling studies but are under-utilised due to the low amount and quality of extracted nucleic acids. We profiled the copy number landscape of 356 breast cancer patients using DNA extracted FFPE tissues by shallow whole genome sequencing. We generated a total of 491 sequencing libraries from 2 kits and obtained data from 98.4% of libraries with 86.4% being of good quality. We generated libraries from as low as 3.8?ng of input DNA and found that the success was independent of input DNA amount and quality, processing site and age of the fixed tissues. Since copy number alterations (CNA) play a major role in breast cancer, it is imperative that we are able to use FFPE archives and we have shown in this study that sWGS is a robust method to do such profiling.     

Dispatches from Biotech beginning BeginNGS: Rapid newborn genome sequencing to end the diagnostic and therapeutic odyssey

In this Dispatch from Biotech, we briefly review the urgent need for extensive expansion of newborn screening (NBS) by genomic sequencing, and the reasons why early attempts had limited success. During the next decade transformative developments will continue in society and in the pharmaceutical, biotechnology, informatics, and medical sectors that enable prompt addition of genetic disorders to NBS by rapid whole genome sequencing (rWGS) upon introduction of new therapies that qualify them according to the Wilson and Jungner criteria (Wilson, J. M. G., & Jungner, G., World Health Organization. (1968). Principles and Practice of Screening for Disease. World Health Organization. Retrieved from https://apps.who.int/iris/handle/10665/37650 ). Herein we describe plans, progress, and clinical trial designs for BeginNGS (Newborn Genome Sequencing to end the diagnostic and therapeutic odyssey), a new international, pre-competitive, public–private consortium that proposes to implement a self-learning healthcare delivery system for screening all newborns for over 400 hundred genetic diseases, diagnostic confirmation, implementation of effective treatment, and acceleration of orphan drug development. We invite investigators and stakeholders worldwide to join the consortium in a prospective, multi-center, international trial of the clinical utility and cost effectiveness of BeginNGS.     

Robust identification of deletions in exome and genome sequence data based on clustering of Mendelian errors

Multiple tools have been developed to identify copy number variants (CNVs) from whole exome (WES) and whole genome sequencing (WGS) data. Current tools such as XHMM for WES and CNVnator for WGS identify CNVs based on changes in read depth. For WGS, other methods to identify CNVs include utilizing discordant read pairs and split reads and genome‐wide local assembly with tools such as Lumpy and SvABA, respectively. Here, we introduce a new method to identify deletion CNVs from WES and WGS trio data based on the clustering of Mendelian errors (MEs). Using our Mendelian Error Method (MEM), we identified 127 deletions (inherited and de novo) in 2,601 WES trios from the Pediatric Cardiac Genomics Consortium, with a validation rate of 88% by digital droplet PCR. MEM identified additional de novo deletions compared with XHMM, and a significant enrichment of 15q11.2 deletions compared with controls. In addition, MEM identified eight cases of uniparental disomy, sample switches, and DNA contamination. We applied MEM to WGS data from the Genome In A Bottle Ashkenazi trio and identified deletions with 97% specificity. MEM provides a robust, computationally inexpensive method for identifying deletions, and an orthogonal approach for verifying deletions called by other tools.     

Comparison of Exome and Genome Sequencing Technologies for the Complete Capture of Protein‐Coding Regions

For next‐generation sequencing technologies, sufficient base‐pair coverage is the foremost requirement for the reliable detection of genomic variants. We investigated whether whole‐genome sequencing (WGS) platforms offer improved coverage of coding regions compared with whole‐exome sequencing (WES) platforms, and compared single‐base coverage for a large set of exome and genome samples. We find that WES platforms have improved considerably in the last years, but at comparable sequencing depth, WGS outperforms WES in terms of covered coding regions. At higher sequencing depth (95x–160x), WES successfully captures 95% of the coding regions with a minimal coverage of 20x, compared with 98% for WGS at 87‐fold coverage. Three different assessments of sequence coverage bias showed consistent biases for WES but not for WGS. We found no clear differences for the technologies concerning their ability to achieve complete coverage of 2,759 clinically relevant genes. We show that WES performs comparable to WGS in terms of covered bases if sequenced at two to three times higher coverage. This does, however, go at the cost of substantially more sequencing biases in WES approaches. Our findings will guide laboratories to make an informed decision on which sequencing platform and coverage to choose.     

RRBS‐Analyser: A Comprehensive Web Server for Reduced Representation Bisulfite Sequencing Data Analysis

In reduced representation bisulfite sequencing (RRBS), genomic DNA is digested with the restriction enzyme and then subjected to next‐generation sequencing, which enables detection and quantification of DNA methylation at whole‐genome scale with low cost. However, the data processing, interpretation, and analysis of the huge amounts of data generated pose a bioinformatics challenge. We developed RRBS‐Analyser, a comprehensive genome‐scale DNA methylation analysis server based on RRBS data. RRBS‐Analyser can assess sequencing quality, generate detailed statistical information, align the bisulfite‐treated short reads to reference genome, identify and annotate the methylcytosines (5mCs) and associate them with different genomic features in CG, CHG, and CHH content. RRBS‐Analyser supports detection, annotation, and visualization of differentially methylated regions (DMRs) for multiple samples from nine reference organisms. Moreover, RRBS‐Analyser provides researchers with detailed annotation of DMR‐containing genes, which will greatly aid subsequent studies. The input of RRBS‐Analyser can be raw FASTQ reads, generic SAM format, or self‐defined format containing individual 5mC sites. RRBS‐Analyser can be widely used by researchers wanting to unravel the complexities of DNA methylome in the epigenetic community. RRBS‐Analyser is freely available at http://122.228.158.106/RRBSAnalyser/ .     

不同样本测序前处理方案对冠状病毒基因组高通量测序结果的影响

目的以基因组最大RNA病毒(冠状病毒)为代表,研究不同测序前样本处理模式对高通量测序获得病毒全基因组序列信息质量的影响。方法以细胞培养的人冠状病毒HCoV-OC43样本为代表,分为4种测序前样本处理模式,即:未处理组、核酸提取前DNase和RNase处理组、核酸提取后DNase处理组、核酸提取前DNase和RNase处理且核酸提取后DNase处理组。不同模式处理后的核酸分为两份,一份直接RNA测序(未扩增),另一份经序列非依赖的单引物扩增(SISPA)后DNA测序。结果尽管不同处理方式下获得的病毒基因组覆盖率差别不大,但是样本核酸提取后经DNase处理组直接测序获得了最高的基因覆盖度和测序准确性,而SISPA扩增可有效提高病毒测序读长(reads)比例与基因组各位点的测序深度。结论本研究为优化冠状病毒等RNA病毒全基因组测序策略提供了技术参考。     

Living laboratory: whole‐genome sequencing as a learning healthcare enterprise

With the proliferation of affordable large‐scale human genomic data come profound and vexing questions about management of such data and their clinical uncertainty. These issues challenge the view that genomic research on human beings can (or should) be fully segregated from clinical genomics, either conceptually or practically. Here, we argue that the sharp distinction between clinical care and research is especially problematic in the context of large‐scale genomic sequencing of people with suspected genetic conditions. Core goals of both enterprises (e.g. understanding genotype–phenotype relationships; generating an evidence base for genomic medicine) are more likely to be realized at a population scale if both those ordering and those undergoing sequencing for diagnostic reasons are routinely and longitudinally studied. Rather than relying on expensive and lengthy randomized clinical trials and meta‐analyses, we propose leveraging nascent clinical‐research hybrid frameworks into a broader, more permanent instantiation of exploratory medical sequencing. Such an investment could enlighten stakeholders about the real‐life challenges posed by whole‐genome sequencing, such as establishing the clinical actionability of genetic variants, returning ‘off‐target’ results to families, developing effective service delivery models and monitoring long‐term outcomes.     

A Robust Approach for Blind Detection of Balanced Chromosomal Rearrangements with Whole‐Genome Low‐Coverage Sequencing

Balanced chromosomal rearrangement (or balanced chromosome abnormality, BCA) is a common chromosomal structural variation. Next‐generation sequencing has been reported to detect BCA‐associated breakpoints with the aid of karyotyping. However, the complications associated with this approach and the requirement for cytogenetics information has limited its application. Here, we provide a whole‐genome low‐coverage sequencing approach to detect BCA events independent of knowing the affected regions and with low false positives. First, six samples containing BCAs were used to establish a detection protocol and assess the efficacy of different library construction approaches. By clustering anomalous read pairs and filtering out the false‐positive results with a control cohort and the concomitant mapping information, we could directly detect BCA events for each sample. Through optimizing the read depth, BCAs in all samples could be blindly detected with only 120 million read pairs per sample for data from a small‐insert library and 30 million per sample for data from nonsize‐selected mate‐pair library. This approach was further validated using another 13 samples that contained BCAs. Our approach advances the application of high‐throughput whole‐genome low‐coverage analysis for robust BCA detection—especially for clinical samples—without the need for karyotyping.     

Diagnostic whole genome sequencing and split‐read mapping for nucleotide resolution breakpoint identification in CNTNAP2 deficiency syndrome

Whole genome sequencing (WGS) has the potential to report on all types of genetic abnormality, thus converging diagnostic testing on a single methodology. Although WGS at sufficient depth for robust detection of point mutations is still some way from being affordable for diagnostic purposes, low‐coverage WGS is already an excellent method for detecting copy number variants (“CNVseq”). We report on a family in which individuals presented with a presumed autosomal recessive syndrome of severe intellectual disability and epilepsy. Array comparative genomic hybridization (CGH) analysis had revealed a homozygous deletion apparently lying within intron 3 of CNTNAP2. Since this was too small for confirmation by FISH, CNVseq was used, refining the extent of this mutation to approximately 76.8 kb, encompassing CNTNAP2 exon 3 (an out‐of‐frame deletion). To characterize the precise breakpoints and provide a rapid molecular diagnostic test, we resequenced the CNVseq library at medium coverage and performed split read mapping. This yielded information for a multiplex polymerase chain reaction (PCR) assay, used for cascade screening and/or prenatal diagnosis in this family. This example demonstrates a rapid, low‐cost approach to converting molecular cytogenetic findings into robust PCR‐based tests. © 2014 The Authors. American Journal of Medical Genetics Part A Published by Wiley Periodicals, Inc.     

Can We Afford to Sequence Every Newborn Baby's Genome?

Whole‐exome sequencing and whole‐genome sequencing are gradually entering into the clinical arena. Drops in sequencing prices have led some to suggest that these analyses could be extended to the screening of whole populations or subsets thereof. Herein, we argue that this optimism is presently still unfounded. While cost estimates take into account the generation of sequence data, they fail to properly evaluate both the price of accurate and efficient interpretation and of the proper return of genomic information to the consulting individuals. Thus, short of inventing new, cost‐effective ways of achieving these goals, the latter are likely to ruin our healthcare systems. We posit that due to lack of available resources, generalization of this practice remains, for the time being, unrealistic.     

Next generation sequencing for whole genome analysis and surveillance of influenza A viruses

BackgroundThe Wadsworth Center, New York State Department of Health (NYSDOH), conducts routine diagnosis and surveillance of influenza viruses. Whole genome sequencing (WGS) with next generation sequencing (NGS) was initiated to provide more rapid, detailed, thorough, and accurate analysis.ObjectivesTo optimize and implement a method for routine WGS of influenza A viruses. To use WGS to monitor influenza A viruses for reassortment, mutations associated with antiviral resistance and antigenicity changes, as well as those potentially affecting virulence and tropism.Study designMultiple extraction and amplification methods were investigated and optimized for the production of template to be used for NGS. Additionally, software options were considered for data analysis. Initial WGS influenza projects have included the comparison of mixed population sequence data obtained with NGS, Sanger dideoxy sequencing, and pyrosequencing, the comparison of sequences obtained from paired primary/cultured samples, the analysis of sequence changes over several influenza seasons, and phylogenetic analysis.ResultsProcedures were optimized for extraction and amplification such that WGS could be successfully performed on both cultured isolates and primary specimens. Data is presented on 15 A/H1pdm09 and 44 A/H3N2 samples. Analysis of influenza A viruses identified and confirmed variant and mixed populations affecting antigenicity and antiviral susceptibility in both primary specimens and cultured isolates.ConclusionsAn influenza A whole genome PCR method has been optimized for the reliable production of template for NGS. The WGS method has been successfully implemented for enhanced comprehensive surveillance and the generation of detailed clinical data on drug resistance and virulence. Data obtained with this method will also aid in future vaccine selection.     

Comprehensive Genome Profiling of Single Sperm Cells by Multiple Annealing and Looping‐Based Amplification Cycles and Next‐Generation Sequencing from Carriers of Robertsonian Translocation

Robertsonian translocation (RT) is a common cause for male infertility, recurrent pregnancy loss, and birth defects. Studying meiotic recombination in RT‐carrier patients helps decipher the mechanism and improve the clinical management of infertility and birth defects caused by RT. Here we present a new method to study spermatogenesis on a single‐gamete basis from two RT carriers. By using a combined single‐cell whole‐genome amplification and sequencing protocol, we comprehensively profiled the chromosomal copy number of 88 single sperms from two RT‐carrier patients. With the profiled information, chromosomal aberrations were identified on a whole‐genome, per‐sperm basis. We found that the previously reported interchromosomal effect might not exist with RT carriers. It is suggested that single‐cell genome sequencing enables comprehensive chromosomal aneuploidy screening and provides a powerful tool for studying gamete generation from patients carrying chromosomal diseases.     

Detecting PKD1 variants in polycystic kidney disease patients by single‐molecule long‐read sequencing

A genetic diagnosis of autosomal‐dominant polycystic kidney disease (ADPKD) is challenging due to allelic heterogeneity, high GC content, and homology of the PKD1 gene with six pseudogenes. Short‐read next‐generation sequencing approaches, such as whole‐genome sequencing and whole‐exome sequencing, often fail at reliably characterizing complex regions such as PKD1. However, long‐read single‐molecule sequencing has been shown to be an alternative strategy that could overcome PKD1 complexities and discriminate between homologous regions of PKD1 and its pseudogenes. In this study, we present the increased power of resolution for complex regions using long‐read sequencing to characterize a cohort of 19 patients with ADPKD. Our approach provided high sensitivity in identifying PKD1 pathogenic variants, diagnosing 94.7% of the patients. We show that reliable screening of ADPKD patients in a single test without interference of PKD1 homologous sequences, commonly introduced by residual amplification of PKD1 pseudogenes, by direct long‐read sequencing is now possible. This strategy can be implemented in diagnostics and is highly suitable to sequence and resolve complex genomic regions that are of clinical relevance.     

Simple and Efficient Identification of Rare Recessive Pathologically Important Sequence Variants from Next Generation Exome Sequence Data

Massively parallel (“next generation”) DNA sequencing (NGS) has quickly become the method of choice for seeking pathogenic mutations in rare uncharacterized monogenic diseases. Typically, before DNA sequencing, protein‐coding regions are enriched from patient genomic DNA, representing either the entire genome (“exome sequencing”) or selected mapped candidate loci. Sequence variants, identified as differences between the patient's and the human genome reference sequences, are then filtered according to various quality parameters. Changes are screened against datasets of known polymorphisms, such as dbSNP and the 1000 Genomes Project, in the effort to narrow the list of candidate causative variants. An increasing number of commercial services now offer to both generate and align NGS data to a reference genome. This potentially allows small groups with limited computing infrastructure and informatics skills to utilize this technology. However, the capability to effectively filter and assess sequence variants is still an important bottleneck in the identification of deleterious sequence variants in both research and diagnostic settings. We have developed an approach to this problem comprising a user‐friendly suite of programs that can interactively analyze, filter and screen data from enrichment‐capture NGS data. These programs (“Agile Suite”) are particularly suitable for small‐scale gene discovery or for diagnostic analysis.     

An Evaluation of Copy Number Variation Detection Tools from Whole‐Exome Sequencing Data

Copy number variation (CNV) has been found to play an important role in human disease. Next‐generation sequencing technology, including whole‐genome sequencing (WGS) and whole‐exome sequencing (WES), has become a primary strategy for studying the genetic basis of human disease. Several CNV calling tools have recently been developed on the basis of WES data. However, the comparative performance of these tools using real data remains unclear. An objective evaluation study of these tools in practical research situations would be beneficial. Here, we evaluated four well‐known WES‐based CNV detection tools (XHMM, CoNIFER, ExomeDepth, and CONTRA) using real data generated in house. After evaluation using six metrics, we found that the sensitive and accurate detection of CNVs in WES data remains challenging despite the many algorithms available. Each algorithm has its own strengths and weaknesses. None of the exome‐based CNV calling methods performed well in all situations; in particular, compared with CNVs identified from high coverage WGS data from the same samples, all tools suffered from limited power. Our evaluation provides a comprehensive and objective comparison of several well‐known detection tools designed for WES data, which will assist researchers in choosing the most suitable tools for their research needs.     

Effective Variant Detection by Targeted Deep Sequencing of DNA Pools: An Example from Parkinson's Disease

Next‐generation sequencing technologies will dominate the next phase of discoveries in human genetics, but considerable costs may still represent a limitation for studies involving large sample sets. Targeted capture of genomic regions may be combined with deep sequencing of DNA pools to efficiently screen sample cohorts for disease‐relevant mutations. We designed a 200 kb HaloPlex kit for PCR‐based capture of all coding exons in 71 genes relevant to Parkinson's disease and other neurodegenerative disorders. DNA from 387 patients with Parkinson's disease was combined into 39 pools, each representing 10 individuals, before library preparation with barcoding and Illumina sequencing. In this study, we focused the analysis on six genes implicated in Mendelian Parkinson's disease, emphasizing quality metrics and evaluation of the method, including validation of variants against individual genotyping and Sanger sequencing. Our data showed 97% sensitivity to detect a single nonreference allele in pools, rising to 100% where pools achieved sequence depth above 80x for the relevant position. Pooled sequencing detected 18 rare nonsynonymous variants, of which 17 were validated by independent methods, corresponding to a specificity of 94%. We argue that this design represents an effective and reliable approach with possible applications for both complex and Mendelian genetics.