CANOES: detecting rare copy number variants from whole exome sequencing data

We present CANOES, an algorithm for the detection of rare copy number variants from exome sequencing data. CANOES models read counts using a negative binomial distribution and estimates variance of the read counts using a regression-based approach based on selected reference samples in a given dataset. We test CANOES on a family-based exome sequencing dataset, and show that its sensitivity and specificity is comparable to that of XHMM. Moreover, the method is complementary to Gaussian approximation-based methods (e.g. XHMM or CoNIFER). When CANOES is used in combination with these methods, it will be possible to produce high accuracy calls, as demonstrated by a much reduced and more realistic de novo rate in results from trio data

Mechanisms of congenital heart disease caused by NAA15 haploinsufficiency

Rationale: NAA15 is a component of the N-terminal (Nt) acetyltransferase complex, NatA. The mechanism by which NAA15 haploinsufficiency causes congenital heart disease (CHD) remains unknown. To better understand molecular processes by which NAA15 haploinsufficiency perturbs cardiac development, we introduced NAA15 variants into human induced pluripotent stem cells (iPSCs) and assessed the consequences of these mutations on RNA and protein expression. Objective: We aim to understand the role of NAA15 haploinsufficiency in cardiac development by investigating proteomic effects on NatA complex activity, and identifying proteins dependent upon a full amount of NAA15. Methods and Results: We introduced heterozygous LoF, compound heterozygous and missense residues (R276W) in iPS cells using CRISPR/Cas9. Haploinsufficient NAA15 iPS cells differentiate into cardiomyocytes, unlike NAA15-null iPS cells, presumably due to altered composition of NatA. Mass spectrometry (MS) analyses reveal ~80% of identified iPS cell NatA targeted proteins displayed partial or complete Nt-acetylation. Between null and haploinsufficient NAA15 cells Nt-acetylation levels of 32 and 9 NatA-specific targeted proteins were reduced, respectively. Similar acetylation loss in few proteins occurred in NAA15 R276W iPSCs. In addition, steady-state protein levels of 562 proteins were altered in both null and haploinsufficient NAA15 cells; eighteen were ribosomal-associated proteins. At least four proteins were encoded by genes known to cause autosomal dominant CHD. Conclusions: These studies define a set of human proteins that requires a full NAA15 complement for normal synthesis and development. A 50% reduction in the amount of NAA15 alters levels of at least 562 proteins and Nt-acetylation of only 9 proteins. One or more modulated proteins are likely responsible for NAA15-haploinsufficiency mediated CHD. Additionally, genetically engineered iPS cells provide a platform for evaluating the consequences of amino acid sequence variants of unknown significance on NAA15 function

Targeted and genome-wide sequencing reveal single nucleotide variations impacting specificity of Cas9 in human stem cells

CRISPR/Cas9 has demonstrated a high-efficiency in site-specific gene targeting. However, potential off-target effects of the Cas9 nuclease represent a major safety concern for any therapeutic application. Here, we knock out the Tafazzin gene by CRISPR/Cas9 in human-induced pluripotent stem cells with 54% efficiency. We combine whole-genome sequencing and deep-targeted sequencing to characterise the off-target effects of Cas9 editing. Whole-genome sequencing of Cas9-modified hiPSC clones detects neither gross genomic alterations nor elevated mutation rates. Deep sequencing of in silico predicted off-target sites in a population of Cas9-treated cells further confirms high specificity of Cas9. However, we identify a single high-efficiency off-target site that is generated by a common germline single-nucleotide variant (SNV) in our experiment. Based on in silico analysis, we estimate a likelihood of SNVs creating off-target sites in a human genome to be ~1.5–8.5%, depending on the genome and site-selection method, but also note that mutations might be generated at these sites only at low rates and may not have functional consequences. Our study demonstrates the feasibility of highly specific clonal ex vivo gene editing using CRISPR/Cas9 and highlights the value of whole-genome sequencing before personalised CRISPR design

Single-Cell Resolution of Temporal Gene Expression during Heart Development

Activation of complex molecular programs in specific cell lineages governs mammalian heart development, from a primordial linear tube to a four-chamber organ. To characterize lineage-specific, spatiotemporal developmental programs, we performed single-cell RNA sequencing of >1,200 murine cells isolated at seven time points spanning embryonic day 9.5 (primordial heart tube) to postnatal day 21 (mature heart). Using unbiased transcriptional data, we classified cardiomyocytes, endothelial cells, and fibroblast-enriched cells, thus identifying markers for temporal and chamber-specific developmental programs. By harnessing these datasets, we defined developmental ages of human and mouse pluripotent stem-cell-derived cardiomyocytes and characterized lineage-specific maturation defects in hearts of mice with heterozygous mutations in Nkx2.5 that cause human heart malformations. This spatiotemporal transcriptome analysis of heart development reveals lineage-specific gene programs underlying normal cardiac development and congenital heart disease

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

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

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

Titin mutations in iPS cells define sarcomere insufficiency as a cause of dilated cardiomyopathy

Human mutations that truncate the massive sarcomere protein titin [TTN-truncating variants (TTNtvs)] are the most common genetic cause for dilated cardiomyopathy (DCM), a major cause of heart failure and premature death. Here we show that cardiac microtissues engineered from human induced pluripotent stem (iPS) cells are a powerful system for evaluating the pathogenicity of titin gene variants. We found that certain missense mutations, like TTNtvs, diminish contractile performance and are pathogenic. By combining functional analyses with RNA sequencing, we explain why truncations in the A-band domain of TTN cause DCM, whereas truncations in the I band are better tolerated. Finally, we demonstrate that mutant titin protein in iPS cell–derived cardiomyocytes results in sarcomere insufficiency, impaired responses to mechanical and β-adrenergic stress, and attenuated growth factor and cell signaling activation. Our findings indicate that titin mutations cause DCM by disrupting critical linkages between sarcomerogenesis and adaptive remodeling