Whole-Exome Sequencing to Identify a Novel LMNA Gene Mutation Associated with Inherited Cardiac Conduction Disease

Background

Inherited cardiac conduction diseases (CCD) are rare but are caused by mutations in a myriad of genes. Recently, whole-exome sequencing has successfully led to the identification of causal mutations for rare monogenic Mendelian diseases.

Objective

To investigate the genetic background of a family affected by inherited CCD.

Methods and Results

We used whole-exome sequencing to study a Chinese family with multiple family members affected by CCD. Using the pedigree information, we proposed a heterozygous missense mutation (c.G695T, Gly232Val) in the lamin A/C (LMNA) gene as a candidate mutation for susceptibility to CCD in this family. The mutation is novel and is expected to affect the conformation of the coiled-coil rod domain of LMNA according to a structural model prediction. Its pathogenicity in lamina instability was further verified by expressing the mutation in a cellular model.

Conclusions

Our results suggest that whole-exome sequencing is a feasible approach to identifying the candidate genes underlying inherited conduction diseases.     

Deep Sequencing to Identify the Causes of Viral Encephalitis

Deep sequencing allows for a rapid, accurate characterization of microbial DNA and RNA sequences in many types of samples. Deep sequencing (also called next generation sequencing or NGS) is being developed to assist with the diagnosis of a wide variety of infectious diseases. In this study, seven frozen brain samples from deceased subjects with recent encephalitis were investigated. RNA from each sample was extracted, randomly reverse transcribed and sequenced. The sequence analysis was performed in a blinded fashion and confirmed with pathogen-specific PCR. This analysis successfully identified measles virus sequences in two brain samples and herpes simplex virus type-1 sequences in three brain samples. No pathogen was identified in the other two brain specimens. These results were concordant with pathogen-specific PCR and partially concordant with prior neuropathological examinations, demonstrating that deep sequencing can accurately identify viral infections in frozen brain tissue.     

Genetic Testing of Korean Familial Hypercholesterolemia Using Whole-Exome Sequencing

Familial hypercholesterolemia (FH) is a genetic disorder with an increased risk of early-onset coronary artery disease. Although some clinically diagnosed FH cases are caused by mutations in LDLR, APOB, or PCSK9, mutation detection rates and profiles can vary across ethnic groups. In this study, we aimed to provide insight into the spectrum of FH-causing mutations in Koreans. Among 136 patients referred for FH, 69 who met Simon Broome criteria with definite family history were enrolled. By whole-exome sequencing (WES) analysis, we confirmed that the 3 known FH-related genes accounted for genetic causes in 23 patients (33.3%). A substantial portion of the mutations (19 of 23 patients, 82.6%) resulted from 17 mutations and 2 copy number deletions in LDLR gene. Two mutations each in the APOB and PCSK9 genes were verified. Of these anomalies, two frameshift deletions in LDLR and one mutation in PCSK9 were identified as novel causative mutations. In particular, one novel mutation and copy number deletion were validated by co-segregation in their relatives. This study confirmed the utility of genetic diagnosis of FH through WES.     

Homozygosity Haplotype and Whole-Exome Sequencing Analysis to Identify Potentially Functional Rare Variants Involved in Multiple Sclerosis among Sardinian Families

Multiple Sclerosis (MS) is a complex multifactorial autoimmune disease, whose sex- and age-adjusted prevalence in Sardinia (Italy) is among the highest worldwide. To date, 233 loci were associated with MS and almost 20% of risk heritability is attributable to common genetic variants, but many low-frequency and rare variants remain to be discovered. Here, we aimed to contribute to the understanding of the genetic basis of MS by investigating potentially functional rare variants. To this end, we analyzed thirteen multiplex Sardinian families with Immunochip genotyping data. For five families, Whole Exome Sequencing (WES) data were also available. Firstly, we performed a non-parametric Homozygosity Haplotype analysis for identifying the Region from Common Ancestor (RCA). Then, on these potential disease-linked RCA, we searched for the presence of rare variants shared by the affected individuals by analyzing WES data. We found: (i) a variant (43181034 T > G) in the splicing region on exon 27 of CUL9; (ii) a variant (50245517 A > C) in the splicing region on exon 16 of ATP9A; (iii) a non-synonymous variant (43223539 A > C), on exon 9 of TTBK1; (iv) a non-synonymous variant (42976917 A > C) on exon 9 of PPP2R5D; and v) a variant (109859349-109859354) in 3′UTR of MYO16.     

Characterization of X Chromosome Inactivation Using Integrated Analysis of Whole-Exome and mRNA Sequencing

In females, X chromosome inactivation (XCI) is an epigenetic, gene dosage compensatory mechanism by inactivation of one copy of X in cells. Random XCI of one of the parental chromosomes results in an approximately equal proportion of cells expressing alleles from either the maternally or paternally inherited active X, and is defined by the XCI ratio. Skewed XCI ratio is suggestive of non-random inactivation, which can play an important role in X-linked genetic conditions. Current methods rely on indirect, semi-quantitative DNA methylation-based assay to estimate XCI ratio. Here we report a direct approach to estimate XCI ratio by integrated, family-trio based whole-exome and mRNA sequencing using phase-by-transmission of alleles coupled with allele-specific expression analysis. We applied this method to in silico data and to a clinical patient with mild cognitive impairment but no clear diagnosis or understanding molecular mechanism underlying the phenotype. Simulation showed that phased and unphased heterozygous allele expression can be used to estimate XCI ratio. Segregation analysis of the patient''s exome uncovered a de novo, interstitial, 1.7 Mb deletion on Xp22.31 that originated on the paternally inherited X and previously been associated with heterogeneous, neurological phenotype. Phased, allelic expression data suggested an 83∶20 moderately skewed XCI that favored the expression of the maternally inherited, cytogenetically normal X and suggested that the deleterious affect of the de novo event on the paternal copy may be offset by skewed XCI that favors expression of the wild-type X. This study shows the utility of integrated sequencing approach in XCI ratio estimation.     

Whole-Exome Sequencing in a South American Cohort Links ALDH1A3, FOXN1 and Retinoic Acid Regulation Pathways to Autism Spectrum Disorders

Autism spectrum disorders (ASDs) are a range of complex neurodevelopmental conditions principally characterized by dysfunctions linked to mental development. Previous studies have shown that there are more than 1000 genes likely involved in ASD, expressed mainly in brain and highly interconnected among them. We applied whole exome sequencing in Colombian—South American trios. Two missense novel SNVs were found in the same child: ALDH1A3 (RefSeq NM_000693: c.1514T>C (p.I505T)) and FOXN1 (RefSeq NM_003593: c.146C>T (p.S49L)). Gene expression studies reveal that Aldh1a3 and Foxn1 are expressed in ~E13.5 mouse embryonic brain, as well as in adult piriform cortex (PC; ~P30). Conserved Retinoic Acid Response Elements (RAREs) upstream of human ALDH1A3 and FOXN1 and in mouse Aldh1a3 and Foxn1 genes were revealed using bioinformatic approximation. Chromatin immunoprecipitation (ChIP) assay using Retinoid Acid Receptor B (Rarb) as the immunoprecipitation target suggests RA regulation of Aldh1a3 and Foxn1 in mice. Our results frame a possible link of RA regulation in brain to ASD etiology, and a feasible non-additive effect of two apparently unrelated variants in ALDH1A3 and FOXN1 recognizing that every result given by next generation sequencing should be cautiously analyzed, as it might be an incidental finding.     

Use of Whole-Exome Sequencing for the Diagnosis of Atypical Birt-Hogg-Dube Syndrome

Destruction of the lung parenchyma may result in the forma- tion of cysts, cavities and bullae. Definition of the type of destructive lesion is best achieved by high-resolution computed tomography （HRCT） scans of the chest （Trotman- Dickenson, 2014）. The loss of lung parenchyma may result in respiratory compromise and pneumothoraces. In the case of cystic lung destruction, multiple causes have been identified, with the cysts being a manifestation of inherited and non- inherited diseases （Sahn and Heffner, 2000）. Compared with sporadic cases, familial lung cysts/spontaneous pneumothorax are rare and are manifestation of some Mendelian genetic diseases.     

Discovery and Statistical Genotyping of Copy-Number Variation from Whole-Exome Sequencing Depth

Sequencing of gene-coding regions (the exome) is increasingly used for studying human disease, for which copy-number variants (CNVs) are a critical genetic component. However, detecting copy number from exome sequencing is challenging because of the noncontiguous nature of the captured exons. This is compounded by the complex relationship between read depth and copy number; this results from biases in targeted genomic hybridization, sequence factors such as GC content, and batching of samples during collection and sequencing. We present a statistical tool (exome hidden Markov model [XHMM]) that uses principal-component analysis (PCA) to normalize exome read depth and a hidden Markov model (HMM) to discover exon-resolution CNV and genotype variation across samples. We evaluate performance on 90 schizophrenia trios and 1,017 case-control samples. XHMM detects a median of two rare (<1%) CNVs per individual (one deletion and one duplication) and has 79% sensitivity to similarly rare CNVs overlapping three or more exons discovered with microarrays. With sensitivity similar to state-of-the-art methods, XHMM achieves higher specificity by assigning quality metrics to the CNV calls to filter out bad ones, as well as to statistically genotype the discovered CNV in all individuals, yielding a trio call set with Mendelian-inheritance properties highly consistent with expectation. We also show that XHMM breakpoint quality scores enable researchers to explicitly search for novel classes of structural variation. For example, we apply XHMM to extract those CNVs that are highly likely to disrupt (delete or duplicate) only a portion of a gene.     

Identification of Small Exonic CNV from Whole-Exome Sequence Data and Application to Autism Spectrum Disorder

Copy number variation (CNV) is an important determinant of human diversity and plays important roles in susceptibility to disease. Most studies of CNV carried out to date have made use of chromosome microarray and have had a lower size limit for detection of about 30 kilobases (kb). With the emergence of whole-exome sequencing studies, we asked whether such data could be used to reliably call rare exonic CNV in the size range of 1–30 kilobases (kb), making use of the eXome Hidden Markov Model (XHMM) program. By using both transmission information and validation by molecular methods, we confirmed that small CNV encompassing as few as three exons can be reliably called from whole-exome data. We applied this approach to an autism case-control sample (n = 811, mean per-target read depth = 161) and observed a significant increase in the burden of rare (MAF ≤1%) 1–30 kb CNV, 1–30 kb deletions, and 1–10 kb deletions in ASD. CNV in the 1–30 kb range frequently hit just a single gene, and we were therefore able to carry out enrichment and pathway analyses, where we observed enrichment for disruption of genes in cytoskeletal and autophagy pathways in ASD. In summary, our results showed that XHMM provided an effective means to assess small exonic CNV from whole-exome data, indicated that rare 1–30 kb exonic deletions could contribute to risk in up to 7% of individuals with ASD, and implicated a candidate pathway in developmental delay syndromes.     

Detecting Identity by Descent and Homozygosity Mapping in Whole-Exome Sequencing Data

The detection of genetic segments of Identical by Descent (IBD) in Genome-Wide Association Studies has proven successful in pinpointing genetic relatedness between reportedly unrelated individuals and leveraging such regions to shortlist candidate genes. These techniques depend on high-density genotyping arrays and their effectiveness in diverse sequence data is largely unknown. Due to decreasing costs and increasing effectiveness of high throughput techniques for whole-exome sequencing, an influx of exome sequencing data has become available. Studies using exomes and IBD-detection methods within known pedigrees have shown that IBD can be useful in finding hidden genetic candidates where known relatives are available. We set out to examine the viability of using IBD-detection in whole exome sequencing data in population-wide studies. In doing so, we extend GERMLINE, a method to detect IBD from exome sequencing data by finding small slices of matching alleles between pairs of individuals and extending them into full IBD segments. This algorithm allows for efficient population-wide detection in dense data. We apply this algorithm to a cohort of Crohn''s Disease cases where whole-exome and GWAS array data is available. We confirm that GWAS-based detected segments are highly accurate and predictive of underlying shared variation. Where segments inferred from GWAS are expected to be of high accuracy, we compare exome-based detection accuracy of multiple detection strategies. We find detection accuracy to be prohibitively low in all assessments, both in terms of segment sensitivity and specificity. Even after isolating relatively long segments beyond 10cM, exome-based detection continued to offer poor specificity/sensitivity tradeoffs. We hypothesize that the variable coverage and platform biases of exome capture account for this decreased accuracy and look toward whole genome sequencing data as a higher quality source for detecting population-wide IBD.     

应用全外显子测序和显微切割技术识别1 例肺癌患者高频突变基因的异质性探索

目的:通过对一例肺鳞癌患者全外显子测序来识别这例肺癌的可能致病基因,并通过显微切割初步探索这例肺癌肿瘤细胞的起源与演化。方法:利用全外显子测序技术对肺癌肿瘤组织和相应癌旁组织测序;用COSMIC肿瘤数据库比较分析统计出肺癌可能致病基因;用激光显微切割技术提取五个不同部位肿瘤细胞;巢式PCR扩增,一代测序验证基因分型。结果:发现了这例肺癌病人的7个高频突变基因:LPHN2、TP53、MYH2、TGM2、C10orf137、MS4A3和EP300;这些基因在10×镜下和20×镜下经显微切割的肺癌组织的5个不同部位上的基因分型不同。结论:我们通过全外显子测序发现了这例肺癌的7个可能致病基因,并初步探索了这例肺癌肿瘤细胞是多克隆起源的。     

Whole-Exome Sequencing Efficiently Detects Rare Mutations in Autosomal Recessive Nonsyndromic Hearing Loss

Identification of the pathogenic mutations underlying autosomal recessive nonsyndromic hearing loss (ARNSHL) is difficult, since causative mutations in 39 different genes have so far been reported. After excluding mutations in the most common ARNSHL gene, GJB2, via Sanger sequencing, we performed whole-exome sequencing (WES) in 30 individuals from 20 unrelated multiplex consanguineous families with ARNSHL. Agilent SureSelect Human All Exon 50 Mb kits and an Illumina Hiseq2000 instrument were used. An average of 93%, 84% and 73% of bases were covered to 1X, 10X and 20X within the ARNSHL-related coding RefSeq exons, respectively. Uncovered regions with WES included those that are not targeted by the exome capture kit and regions with high GC content. Twelve homozygous mutations in known deafness genes, of which eight are novel, were identified in 12 families: MYO15A-p.Q1425X, -p.S1481P, -p.A1551D; LOXHD1-p.R1494X, -p.E955X; GIPC3-p.H170N; ILDR1-p.Q274X; MYO7A-p.G2163S; TECTA-p.Y1737C; TMC1-p.S530X; TMPRSS3-p.F13Lfs*10; TRIOBP-p.R785Sfs*50. Each mutation was within a homozygous run documented via WES. Sanger sequencing confirmed co-segregation of the mutation with deafness in each family. Four rare heterozygous variants, predicted to be pathogenic, in known deafness genes were detected in 12 families where homozygous causative variants were already identified. Six heterozygous variants that had similar characteristics to those abovementioned variants were present in 15 ethnically-matched individuals with normal hearing. Our results show that rare causative mutations in known ARNSHL genes can be reliably identified via WES. The excess of heterozygous variants should be considered during search for causative mutations in ARNSHL genes, especially in small-sized families.     

A Bayesian Framework to Identify Methylcytosines from High-Throughput Bisulfite Sequencing Data

High-throughput bisulfite sequencing technologies have provided a comprehensive and well-fitted way to investigate DNA methylation at single-base resolution. However, there are substantial bioinformatic challenges to distinguish precisely methylcytosines from unconverted cytosines based on bisulfite sequencing data. The challenges arise, at least in part, from cell heterozygosis caused by multicellular sequencing and the still limited number of statistical methods that are available for methylcytosine calling based on bisulfite sequencing data. Here, we present an algorithm, termed Bycom, a new Bayesian model that can perform methylcytosine calling with high accuracy. Bycom considers cell heterozygosis along with sequencing errors and bisulfite conversion efficiency to improve calling accuracy. Bycom performance was compared with the performance of Lister, the method most widely used to identify methylcytosines from bisulfite sequencing data. The results showed that the performance of Bycom was better than that of Lister for data with high methylation levels. Bycom also showed higher sensitivity and specificity for low methylation level samples (<1%) than Lister. A validation experiment based on reduced representation bisulfite sequencing data suggested that Bycom had a false positive rate of about 4% while maintaining an accuracy of close to 94%. This study demonstrated that Bycom had a low false calling rate at any methylation level and accurate methylcytosine calling at high methylation levels. Bycom will contribute significantly to studies aimed at recalibrating the methylation level of genomic regions based on the presence of methylcytosines.     

Whole-Exome Sequencing Identifies Mutated C12orf57 in Recessive Corpus Callosum Hypoplasia

The corpus callosum is the principal cerebral commissure connecting the right and left hemispheres. The development of the corpus callosum is under tight genetic control, as demonstrated by abnormalities in its development in more than 1,000 genetic syndromes. We recruited more than 25 families in which members affected with corpus callosum hypoplasia (CCH) lacked syndromic features and had consanguineous parents, suggesting recessive causes. Exome sequence analysis identified C12orf57 mutations at the initiator methionine codon in four different families. C12orf57 is ubiquitously expressed and encodes a poorly annotated 126 amino acid protein of unknown function. This protein is without significant paralogs but has been tightly conserved across evolution. Our data suggest that this conserved gene is required for development of the human corpus callosum.     

Comparison of Accuracy of Whole-Exome Sequencing with Formalin-Fixed Paraffin-Embedded and Fresh Frozen Tissue Samples

Formalin fixing with paraffin embedding (FFPE) has been a standard sample preparation method for decades, and archival FFPE samples are still very useful resources. Nonetheless, the use of FFPE samples in cancer genome analysis using next-generation sequencing, which is a powerful technique for the identification of genomic alterations at the nucleotide level, has been challenging due to poor DNA quality and artificial sequence alterations. In this study, we performed whole-exome sequencing of matched frozen samples and FFPE samples of tissues from 4 cancer patients and compared the next-generation sequencing data obtained from these samples. The major differences between data obtained from the 2 types of sample were the shorter insert size and artificial base alterations in the FFPE samples. A high proportion of short inserts in the FFPE samples resulted in overlapping paired reads, which could lead to overestimation of certain variants; >20% of the inserts in the FFPE samples were double sequenced. A large number of soft clipped reads was found in the sequencing data of the FFPE samples, and about 30% of total bases were soft clipped. The artificial base alterations, C>T and G>A, were observed in FFPE samples only, and the alteration rate ranged from 200 to 1,200 per 1M bases when sequencing errors were removed. Although high-confidence mutation calls in the FFPE samples were compatible to that in the frozen samples, caution should be exercised in terms of the artifacts, especially for low-confidence calls. Despite the clearly observed artifacts, archival FFPE samples can be a good resource for discovery or validation of biomarkers in cancer research based on whole-exome sequencing.