Background: Fetal congenital heart disease (CHD) is the most common congenital defect, with an incidence of 0.6-0.8%, accounting for 30-50% of infant congenital disease deaths. The pathogenesis of CHD is still unclear, so an active and effective prenatal diagnosis is very important for the prevention and control of CHD. Herein, a Chinese CHD patient with rare compound heterozygous mutations in the DNAH9 gene was reported, and the 3D structure and functional changes of DNAH9 protein were predicted. Case presentation: A 23-year-old pregnant woman came to our hospital for prenatal diagnosis at 27 weeks of gestation. Both she and her partner were unaffected. Fetal CHD was detected by ultrasound screening. Copy number variation sequencing (CNV-seq) revealed an 81 kb deletion at chr17p12 (11,486,795-11,568,385), including exons 1-15 of DNAH9 gene, which plays a key role in cardiac development. Then, whole exome sequencing (WES) was used and identified a nonsense mutation (c.10975C>T) in DNAH9, which resulted in the mutation of amino acid 3,659 from glutamine to termination. The 3D mutant protein structures were predicted using SWISS-MODEL and showed structural changes from functional β-sheet and α-helix to termination, respectively. Conclusion: We describe a case of fetal CHD caused by DNAH9 mutations and provide an effective diagnostic technique for identifying intragenic deletions. This diagnostic process can be implicated in prenatal diagnosis of CHD.
To determine the role of mosaicism in the pathogenesis and inheritance of Rett and Rett-like disorders.We recruited 471 Rett and Rett-like patients. Panel-sequencing targeting MECP2, CDKL5, and FOXG1 was performed. Mosaicism was quantified in 147 patients by a Bayesian genotyper. Candidates were validated by amplicon sequencing and digital PCR. Germline mosaicism of 21 fathers with daughters carrying pathogenic MECP2 variants was further quantified.Pathogenic variants of MECP2/CDKL5/FOXG1 were found in 324/471 (68.7%) patients. Somatic MECP2 mosaicism was confirmed in 5/471 (1.1%) patients, including 3/18 males (16.7%) and 2/453 females (0.4%). Three of the five patients with somatic MECP2 mosaicism had mosaicism at MECP2-Arg106. Germline MECP2 mosaicism was detected in 5/21 (23.8%) fathers.This is the first systematic screening of somatic and paternal germline MECP2 mosaicism at a cohort level. Our findings indicate that somatic MECP2 mosaicism contributes directly to the pathogenicity of Rett syndrome, especially in male patients. MECP2-Arg106 might be a mosaic hotspot. The high proportion of paternal germline MECP2 mosaicism indicates an underestimated mechanism underlying the paternal origin bias of MECP2 variants. Finally, this study provides an empirical foundation for future studies of genetic disorders caused by de novo variations of strong paternal origin.
Postzygotic single-nucleotide mutations (pSNMs) have been studied in cancer and a few other overgrowth human disorders at whole-genome scale and found to play critical roles. However, in clinically unremarkable individuals, pSNMs have never been identified at whole-genome scale largely due to technical difficulties and lack of matched control tissue samples, and thus the genome-wide characteristics of pSNMs remain unknown. We developed a new Bayesian-based mosaic genotyper and a series of effective error filters, using which we were able to identify 17 SNM sites from ∼80× whole-genome sequencing of peripheral blood DNAs from three clinically unremarkable adults. The pSNMs were thoroughly validated using pyrosequencing, Sanger sequencing of individual cloned fragments, and multiplex ligation-dependent probe amplification. The mutant allele fraction ranged from 5%-31%. We found that C→T and C→A were the predominant types of postzygotic mutations, similar to the somatic mutation profile in tumor tissues. Simulation data showed that the overall mutation rate was an order of magnitude lower than that in cancer. We detected varied allele fractions of the pSNMs among multiple samples obtained from the same individuals, including blood, saliva, hair follicle, buccal mucosa, urine, and semen samples, indicating that pSNMs could affect multiple sources of somatic cells as well as germ cells. Two of the adults have children who were diagnosed with Dravet syndrome. We identified two non-synonymous pSNMs in SCN1A, a causal gene for Dravet syndrome, from these two unrelated adults and found that the mutant alleles were transmitted to their children, highlighting the clinical importance of detecting pSNMs in genetic counseling.
Abstract Single-cell RNA sequencing (scRNA-seq) is generally used for profiling transcriptome of individual cells. The droplet-based 10X Genomics Chromium (10X) approach and the plate-based Smart-seq2 full-length method are two frequently used scRNA-seq platforms, yet there are only a few thorough and systematic comparisons of their advantages and limitations. Here, by directly comparing the scRNA-seq data generated by these two platforms from the same samples of CD45− cells, we systematically evaluated their features using a wide spectrum of analyses. Smart-seq2 detected more genes in a cell, especially low abundance transcripts as well as alternatively spliced transcripts, but captured higher proportion of mitochondrial genes. The composite of Smart-seq2 data also resembled bulk RNA-seq data more. For 10X-based data, we observed higher noise for mRNAs with low expression levels. Approximately 10%−30% of all detected transcripts by both platforms were from non-coding genes, with long non-coding RNAs (lncRNAs) accounting for a higher proportion in 10X. 10X-based data displayed more severe dropout problem, especially for genes with lower expression levels. However, 10X-data can detect rare cell types given its ability to cover a large number of cells. In addition, each platform detected distinct groups of differentially expressed genes between cell clusters, indicating the different characteristics of these technologies. Our study promotes better understanding of these two platforms and offers the basis for an informed choice of these widely used technologies.
Abstract Single cell RNA sequencing (scRNA-seq) is widely used for profiling transcriptomes of individual cells. The droplet-based 10X Genomics Chromium (10X) approach and the plate-based Smart-seq2 full-length method are two frequently-used scRNA-seq platforms, yet there are only a few thorough and systematic comparisons of their advantages and limitations. Here, by directly comparing the scRNA-seq data by the two platforms from the same samples of CD45-cells, we systematically evaluated their features using a wide spectrum of analysis. Smart-seq2 detected more genes in a cell, especially low abundance transcripts as well as alternatively spliced transcripts, but captured higher proportion of mitochondrial genes. The composite of Smart-seq2 data also resembled bulk RNA-seq data better. For 10X-based data, we observed higher noise for mRNA in the low expression level. Despite the poly(A) enrichment, approximately 10-30% of all detected transcripts by both platforms were from non-coding genes, with lncRNA accounting for a higher proportion in 10X. 10X-based data displayed more severe dropout problem, especially for genes with lower expression levels. However, 10X-data can better detect rare cell types given its ability to cover a large number of cells. In addition, each platform detected different sets of differentially expressed genes between cell clusters, indicating the complementary nature of these technologies. Our comprehensive benchmark analysis offers the basis for selecting the optimal scRNA-seq strategy based on the objectives of each study.
'%3e%3cpath fill='%23012169' d='M0 0v30h60V0z'/%3e%3cpath stroke='%23fff' stroke-width='6' d='m0 0 60 30m0-30L0 30'/%3e%3cpath stroke='%23C8102E' stroke-width='4' d='m0 0 60 30m0-30L0 30' clip-path='url(%23b)'/%3e%3cpath stroke='%23fff' stroke-width='10' d='M30 0v30M0 15h60'/%3e%3cpath stroke='%23C8102E' stroke-width='6' d='M30 0v30M0 15h60'/%3e%3c/g%3e%3c/svg%3e)