The rate and spectrum of mosaic mutations during embryogenesis revealed by RNA sequencing of 49 tissues

Application of multiple mosaic callers improves post-zygotic mutation detection from exome sequencing data

PURPOSE

The gold standard for identification of post-zygotic variants (PZVs) is droplet digital polymerase chain reaction or high-depth sequencing across multiple tissues types. These approaches are yet to be systematically implemented for monogenic disorders. We developed PZV detection pipelines for correct classification of de novo variants.

METHOD

Our pipelines detect PZV in parents (gonosomal mosaicism [pGoM]) and children (somatic mosaicism, "M3"). We applied them to research exome sequencing (ES) data from the Australian Cerebral Palsy Biobank (n = 145 trios) and Simons Simplex Collection (n = 405 families). Candidate mosaic variants were validated using deep amplicon sequencing or droplet digital polymerase chain reaction.

RESULTS

69.2% (M3trio), 63.9% (M3single), and 92.7% (pGoM) of detected variants were validated, with 48.6%, 56.7%, and 26.2% of variants, respectively, meeting strict criteria for mosaicism. In the Australian Cerebral Palsy Biobank, 16.6% of probands and 20.7% of parents had at least 1 true-positive somatic or pGoM variant, respectively. A large proportion of PZVs detected in Simons Simplex Collection parents (79.8%) and child (94.5%) were not previously reported. We reclassified 3.7% to 8.0% of germline de novo variants as mosaic.

CONCLUSION

Many PZVs were incorrectly classified as germline variants or missed by previous approaches. Systematic application of our pipelines could increase genetic diagnostic rate, improve estimates of recurrence risk in families, and benefit novel disease gene identification.

Severity of effect considerations regarding the use of mutation as a toxicological endpoint for risk assessment: A report from the 8th International Workshop on Genotoxicity Testing (IWGT)

Exposure levels without appreciable human health risk may be determined by dividing a point of departure on a dose-response curve (e.g., benchmark dose) by a composite adjustment factor (AF). An "effect severity" AF (ESAF) is employed in some regulatory contexts. An ESAF of 10 may be incorporated in the derivation of a health-based guidance value (HBGV) when a "severe" toxicological endpoint, such as teratogenicity, irreversible reproductive effects, neurotoxicity, or cancer was observed in the reference study. Although mutation data have been used historically for hazard identification, this endpoint is suitable for quantitative dose-response modeling and risk assessment. As part of the 8th International Workshops on Genotoxicity Testing, a sub-group of the Quantitative Analysis Work Group (WG) explored how the concept of effect severity could be applied to mutation. To approach this question, the WG reviewed the prevailing regulatory guidance on how an ESAF is incorporated into risk assessments, evaluated current knowledge of associations between germline or somatic mutation and severe disease risk, and mined available data on the fraction of human germline mutations expected to cause severe disease. Based on this review and given that mutations are irreversible and some cause severe human disease, in regulatory settings where an ESAF is used, a majority of the WG recommends applying an ESAF value between 2 and 10 when deriving a HBGV from mutation data. This recommendation may need to be revisited in the future if direct measurement of disease-causing mutations by error-corrected next generation sequencing clarifies selection of ESAF values.

Pan-cancer discovery of somatic mutations from RNA sequencing data

Identification of somatic mutations (SMs) is essential for characterizing cancer genomes. While DNA-seq is the prevalent method for identifying SMs, RNA-seq provides an alternative strategy to discover tumor mutations in the transcribed genome. Here, we have developed a machine learning based pipeline to discover SMs based on RNA-seq data (designated as RNA-SMs). Subsequently, we have conducted a pan-cancer analysis to systematically identify RNA-SMs from over 8,000 tumors in The Cancer Genome Atlas (TCGA). In this way, we have identified over 105,000 novel SMs that had not been reported in previous TCGA studies. These novel SMs have significant clinical implications in designing targeted therapy for improved patient outcomes. Further, we have combined the SMs identified by both RNA-seq and DNA-seq analyses to depict an updated mutational landscape across 32 cancer types. This new online SM atlas, OncoDB ( https://oncodb.org ), offers a more complete view of gene mutations that underline the development and progression of various cancers.

De novo detection of somatic mutations in high-throughput single-cell profiling data sets

Characterization of somatic mutations at single-cell resolution is essential to study cancer evolution, clonal mosaicism and cell plasticity. Here, we describe SComatic, an algorithm designed for the detection of somatic mutations in single-cell transcriptomic and ATAC-seq (assay for transposase-accessible chromatin sequence) data sets directly without requiring matched bulk or single-cell DNA sequencing data. SComatic distinguishes somatic mutations from polymorphisms, RNA-editing events and artefacts using filters and statistical tests parameterized on non-neoplastic samples. Using >2.6 million single cells from 688 single-cell RNA-seq (scRNA-seq) and single-cell ATAC-seq (scATAC-seq) data sets spanning cancer and non-neoplastic samples, we show that SComatic detects mutations in single cells accurately, even in differentiated cells from polyclonal tissues that are not amenable to mutation detection using existing methods. Validated against matched genome sequencing and scRNA-seq data, SComatic achieves F1 scores between 0.6 and 0.7 across diverse data sets, in comparison to 0.2-0.4 for the second-best performing method. In summary, SComatic permits de novo mutational signature analysis, and the study of clonal heterogeneity and mutational burdens at single-cell resolution.

Bacillus amyloliquefaciens A-1 inhibiting fungal spoilage in agricultural products is improved by metabolic engineering of enhancing surfactin yield

Fungi and subsequent mycotoxins contamination in agricultural products have caused enormous losses and great harm to human and animal health. Biological control has attracted the attention of researchers due to its advantages, including mild conditions, low cost, high efficiency and low nutrient loss. In this study, a newly isolated strain Bacillus amyloliquefaciens A-1 (A-1), was screened for its ability to inhibit the growth and Aflatoxin B1 (AFB1) production of Aspergillus flavus NRRL 3357. Electron microscopy results revealed that mycelium and conidia of A. flavus were destroyed by A-1, affecting hyphae, cell walls, cell membranes and organelles. RNA-seq analysis indicated disturbance in gene expression profiles of A. flavus, including amino acid degradation and starch and sucrose metabolism pathways. Importantly, the biosynthesis of AFB1 was significantly inhibited by the down-regulation of key regulatory genes, aflR and aflS, and the simultaneous down-regulation of most structural genes. Genome analysis predicted six secondary metabolites biosynthetic gene clusters. Then, four surfactin synthesized by cluster C were identified as the main active substance of A-1 using HPLC-Q-TOF-MS. The addition of alanine, threonine, Fe2+ increased surfactin production. Notably, the overexpression of comX also improved surfactin production. The vivo test results indicated that A-1 could significantly inhibit the decay of pear by Aspergillus westerdijkiae, and the mildew of maize and peanuts. Especially, the overexpression of comX in A-1 could enhance the inhibitory activity. In conclusion, the inhibition mechanism of A-1 was revealed, and comX was found can improve the production of surfactin and subsequent activities, which provides the scientific basis for the development of biocontrol agents to reduce spoilage in agricultural products.

Immune selection determines tumor antigenicity and influences response to checkpoint inhibitors

In cancer, evolutionary forces select for clones that evade the immune system. Here we analyzed >10,000 primary tumors and 356 immune-checkpoint-treated metastases using immune dN/dS, the ratio of nonsynonymous to synonymous mutations in the immunopeptidome, to measure immune selection in cohorts and individuals. We classified tumors as immune edited when antigenic mutations were removed by negative selection and immune escaped when antigenicity was covered up by aberrant immune modulation. Only in immune-edited tumors was immune predation linked to CD8 T cell infiltration. Immune-escaped metastases experienced the best response to immunotherapy, whereas immune-edited patients did not benefit, suggesting a preexisting resistance mechanism. Similarly, in a longitudinal cohort, nivolumab treatment removes neoantigens exclusively in the immunopeptidome of nonimmune-edited patients, the group with the best overall survival response. Our work uses dN/dS to differentiate between immune-edited and immune-escaped tumors, measuring potential antigenicity and ultimately helping predict response to treatment.

Spectrum and tissue distribution of RB1 pathogenic alleles in mosaic retinoblastoma patients

To characterize the spectrum of mosaic RB1 pathogenic alleles and map the distribution of mutant cells in available tissues from mosaic patients. Next-generation sequencing was performed on blood samples from 263 retinoblastoma families to identify mosaic RB1 variant alleles. A variety of available tissues were sampled to determine tissue distribution and fraction of mutant cells in five mosaic patients who consented to participate in mosaic pathogenic allele research. Twelve identified mosaic RB1 variants were all "null" pathogenic alleles and displayed reduced expressivity. The use of next-generation deep sequencing increased the sensitivity of mosaicism detection to 0.03% in the case of tissue DNA. In the five mosaic participants, we observed coherent but uneven, bilateral asymmetrical distribution of mutant cells across various tissues. They all carried early-embryonic mosaic pathogenic alleles and had significantly higher variant fractions in blood than in other tissues. Variant fractions of ipsilateral tissue samples were not concordant higher or lower compared with the contralateral side. Only ipsilateral conjunctival and oral epithelial cells showed concordance in mosaicism levels. No associations were observed between the laterality of affected eyes and variant fractions of any tissue type. NGS allows the detection of low-level mosaicism. Mosaic RB1 pathogenic alleles are prone to occur at very early stages of human embryonic development. With respect to genetic counseling, risk prediction should take into account unrecognized mosaicism. The underlying tissue distribution patterns of mosaic RB1 variant alleles remain to be determined.

Microenvironmental changes co-occur with mosaic somatic clonal expansions in normal skin and esophagus tissues

The presence of somatic mutations, previously identified in cancers, are being increasingly recognized in normal tissues. While the role of microenvironment (ME) in tumor progression is well understood, the changes that occur in the microenvironment of normal tissues that harbor somatic mutations has not been systematically studied. Here, using normal RNA-Seq data accrued from 6544 samples across 27 tissue types from Genotype-Tissue Expression (GTEx) project, we studied the association of microenvironmental changes in the presence of somatic clonal expansions of previously implicated cancer genes. We focused our analysis on skin and esophagus since they have the highest number of samples and mutation burden together. We observed changes in microenvironmental cell-types previously implicated in tumor progression including endothelial cells, epithelial cells, pericytes, fibroblasts, chondrocytes, among others. The Epithelial-Mesenchymal-Transition (EMT) pathway is dysregulated in both skin and esophagus, along with increased hypoxia scores in samples with clonal expansions. These results suggest that microenvironmental changes play an important role in clonal expansions and potentially the initiating stages of cancer progression. Studying these changes may provide new avenues for early intervention of cancer, for targeted therapies, or enhance activities of conventional therapies.

RNA-SSNV: A Reliable Somatic Single Nucleotide Variant Identification Framework for Bulk RNA-Seq Data

The usage of expressed somatic mutations may have a unique advantage in identifying active cancer driver mutations. However, accurately calling mutations from RNA-seq data is difficult due to confounding factors such as RNA-editing, reverse transcription, and gap alignment. In the present study, we proposed a framework (named RNA-SSNV, https://github.com/pmglab/RNA-SSNV) to call somatic single nucleotide variants (SSNV) from tumor bulk RNA-seq data. Based on a comprehensive multi-filtering strategy and a machine-learning classification model trained with comprehensively curated features, RNA-SSNV achieved the best precision–recall rate (0.880–0.884) in a testing dataset and robustly retained 0.94 AUC for the precision–recall curve in three validation adult-based TCGA (The Cancer Genome Atlas) datasets. We further showed that the somatic mutations called by RNA-SSNV tended to have a higher functional impact and therapeutic power in known driver genes. Furthermore, VAF (variant allele fraction) analysis revealed that subclonal harboring expressed mutations had evolutional selection advantage and RNA had higher detection power to rescue DNA-omitted mutations. In sum, RNA-SSNV will be a useful approach to accurately call expressed somatic mutations for a more insightful analysis of cancer drive genes and carcinogenic mechanisms.

Ultrasensitive profiling of UV-induced mutations identifies thousands of subclinical facial tumors in tuberous sclerosis complex

BackgroundTuberous sclerosis complex (TSC) is a neurogenetic syndrome due to loss-of-function mutations in TSC2 or TSC1, characterized by tumors at multiple body sites, including facial angiofibroma (FAF). Here, an ultrasensitive assessment of the extent and range of UV-induced mutations in TSC facial skin was performed.MethodsA multiplex high-sensitivity PCR assay (MHPA) was developed, enabling mutation detection at extremely low (<0.1%) variant allele frequencies (VAFs).ResultsMHPA assays were developed for both TSC2 and TP53, and applied to 81 samples, including 66 skin biopsies. UV-induced second-hit mutation causing inactivation of TSC2 was pervasive in TSC facial skin with an average of 4.8 mutations per 2-mm biopsy at median VAF 0.08%, generating more than 150,000 incipient facial tumors (subclinical "micro-FAFs") in the average TSC subject. The MHPA analysis also led to the identification of a refined UV-related indel signature and a recurrent complex mutation pattern, consisting of both a single-nucleotide or dinucleotide variant and a 1- to 9-nucleotide deletion, in cis.ConclusionTSC facial skin can be viewed as harboring a patchwork of clonal fibroblast proliferations (micro-FAFs) with indolent growth, a small proportion of which develop into clinically observable FAF. Our observations also expand the spectrum of UV-related mutation signatures.FundingThis work was supported by the TSC Alliance; the Engles Family Fund for Research in TSC and LAM; and the NIH, National Heart, Lung, and Blood Institute (U01HL131022-04 and Intramural Research Program).

Familial long-read sequencing increases yield of de novo mutations

Studies of de novo mutation (DNM) have typically excluded some of the most repetitive and complex regions of the genome because these regions cannot be unambiguously mapped with short-read sequencing data. To better understand the genome-wide pattern of DNM, we generated long-read sequence data from an autism parent-child quad with an affected female where no pathogenic variant had been discovered in short-read Illumina sequence data. We deeply sequenced all four individuals by using three sequencing platforms (Illumina, Oxford Nanopore, and Pacific Biosciences) and three complementary technologies (Strand-seq, optical mapping, and 10X Genomics). Using long-read sequencing, we initially discovered and validated 171 DNMs across two children-a 20% increase in the number of de novo single-nucleotide variants (SNVs) and indels when compared to short-read callsets. The number of DNMs further increased by 5% when considering a more complete human reference (T2T-CHM13) because of the recovery of events in regions absent from GRCh38 (e.g., three DNMs in heterochromatic satellites). In total, we validated 195 de novo germline mutations and 23 potential post-zygotic mosaic mutations across both children; the overall true substitution rate based on this integrated callset is at least 1.41 × 10-8 substitutions per nucleotide per generation. We also identified six de novo insertions and deletions in tandem repeats, two of which represent structural variants. We demonstrate that long-read sequencing and assembly, especially when combined with a more complete reference genome, increases the number of DNMs by >25% compared to previous studies, providing a more complete catalog of DNM compared to short-read data alone.

Postzygotic mosaicism of a novel PTPN11 mutation in monozygotic twins discordant for metachondromatosis

Genetic mosaicism caused by postzygotic mutations is of a great interest due to its role in human disease. Monozygotic twins arising from a single zygote are considered as genetically identical, and any differences likely to be caused by postzygotic events. Thus, phenotypically discordant monozygotic twins offer a unique opportunity to study genotype-phenotype correlation. Here, we present a three-generation family starting from a pair of monozygotic twins discordant for metachondromatosis due to postzygotic p.(Gln175His) variant in the PTPN11 gene. Both phenotypically discordant monozygotic twins harbor p.(Gln175His), however significant differences in mosaic ratio is observed not only between twins, but also within different tissue types within one individual. Phenotypic manifestation of p.(Gln175His) in examined family clearly depends on allele variant fraction (VAF). Individuals harboring constitutional mutation (VAF 50%) present typical metachondromatosis. Milder phenotype is observed in twin harboring high-level mosaicism in the tissue of ectodermal origin (VAF 45%), but not in a blood (VAF 5%). Finally, her twin sister harboring low-level mosaicism in blood (VAF 2%) and nonblood (VAF 12%) tissues is phenotypically normal. Our results provide insights into biological role of mosaicism in disease and further support the usefulness of nonblood tissues as an optimal source of DNA for the identification of postzygotic mutations in phenotypically discordant monozygotic twins.

Somatic Genetic Mosaicism in the Apolipoprotein E-null Mouse Aorta

In addition to genetic and epigenetic inheritance, somatic variation may contribute to cardiovascular disease (CVD) risk. CVD-associated somatic mutations have been reported in human clonal hematopoiesis, but evidence in the atheroma is lacking. To probe for somatic variation in atherosclerosis, we sought single-nucleotide private variants (PVs) in whole-exome sequencing (WES) data of aorta, liver, and skeletal muscle of two C57BL/6J coisogenic male ApoE null/wild-type (WT) sibling pairs, and RNA-seq data of one of the two pairs. Relative to the C57BL/6 reference genome, we identified 9 and 11 ApoE null aorta- and liver-specific PVs that were shared by all WES and RNA-seq datasets. Corresponding PVs in WT sibling aorta and liver were 1 and 0, respectively, and not overlapping with ApoE null PVs. Pyrosequencing analysis of 4 representative PVs in 17 ApoE null aortas and livers confirmed tissue-specific shifts toward the alternative allele, in addition to significant deviations from mendelian allele ratios. Notably, all aorta and liver PVs were present in the dbSNP database and were predominantly transition mutations within atherosclerosis-related genes. The majority of PVs were in discrete clusters approximately 3 Mb and 65 to 73 Mb away from hypermutable immunoglobin loci in chromosome 6. These features were largely shared with previously reported CVD-associated somatic mutations in human clonal hematopoiesis. The observation that SNPs exhibit tissue-specific somatic DNA mosaicism in ApoE null mice is potentially relevant for genetic association study design. The proximity of PVs to hypermutable loci suggests testable mechanistic hypotheses.

Somatic mosaics in hereditary tumor predisposition syndromes

Historically, it is estimated that 5-10% of cancer patients carry a causative genetic variant for a tumor predisposition syndrome. These conditions have high clinical relevance as they are actionable regarding risk-specific surveillance, predictive genetic testing, reproductive options, and - in some cases - risk reducing surgery or targeted therapy. Every individual is born with on average 0.5-1 exonic mosaic variants prevalent in single or multiple tissues. Depending on the tissues affected, mosaic conditions can abrogate the clinical phenotype of a tumor predisposition syndrome and can even go unrecognized, because it can be impossible or difficult to detect them with routine genetic testing in blood/leucocytes. On the other hand, it is estimated that at least 4% of presumed de novo variants are the result of low-level mosaicism (variant allele frequency <10%) in a parent, while around 7% are true mosaic variants with a higher variant allele frequency, which can sometimes be confused for heterozygous variants. Clonal hematopoiesis however can simulate a mosaic tumor predisposition in genetic diagnostics and has to be taken into account, especially for TP53 variants. Depending on the technique, variant allele frequencies of 2-3% can be detected for single nucleotide variants by next generation sequencing, copy number variants with variant allele frequencies of 5-30% can be detected by array-based technologies or MLPA. Mosaic tumor predisposition syndromes are more common than previously thought and may often remain undiagnosed. The clinical suspicion and diagnostic procedure for several cases with mosaic tumor predisposition syndromes are presented.

Rates and patterns of clonal oncogenic mutations in the normal human brain

While oncogenic mutations have been found in non-diseased, proliferative non-neural tissues, their prevalence in the human brain is unknown. Targeted sequencing of genes implicated in brain tumors in 418 samples derived from 110 individuals of varying ages, without tumor diagnoses, detected oncogenic somatic single-nucleotide variants (sSNVs) in 5.4% of the brains, including IDH1 R132H. These mutations were largely present in subcortical white matter and enriched in glial cells, and surprisingly, were less common in older individuals. A depletion of high-allele frequency sSNVs representing macroscopic clones with age was replicated by analysis of bulk RNAseq data from 1,816 non-diseased brain samples ranging from fetal to old age. We also describe large clonal copy number variants, and that sSNVs show mutational signatures resembling those found in gliomas, suggesting that mutational processes of the normal brain drive early glial oncogenesis. This study helps understand the origin and early evolution of brain tumors.

Pedigree-based and phylogenetic methods support surprising patterns of mutation rate and spectrum in the gray mouse lemur

Mutations are the raw material on which evolution acts, and knowledge of their frequency and genomic distribution is crucial for understanding how evolution operates at both long and short timescales. At present, the rate and spectrum of de novo mutations have been directly characterized in relatively few lineages. Our study provides the first direct mutation-rate estimate for a strepsirrhine (i.e., the lemurs and lorises), which comprises nearly half of the primate clade. Using high-coverage linked-read sequencing for a focal quartet of gray mouse lemurs (Microcebus murinus), we estimated the mutation rate to be among the highest calculated for a mammal at 1.52 × 10-8 (95% credible interval: 1.28 × 10-8-1.78 × 10-8) mutations/site/generation. Further, we found an unexpectedly low count of paternal mutations, and only a modest overrepresentation of mutations at CpG sites. Despite the surprising nature of these results, we found both the rate and spectrum to be robust to the manipulation of a wide range of computational filtering criteria. We also sequenced a technical replicate to estimate a false-negative and false-positive rate for our data and show that any point estimate of a de novo mutation rate should be considered with a large degree of uncertainty. For validation, we conducted an independent analysis of context-dependent substitution types for gray mouse lemur and five additional primate species for which de novo mutation rates have also been estimated. These comparisons revealed general consistency of the mutation spectrum between the pedigree-based and the substitution-rate analyses for all species compared.

Clinical relevance of postzygotic mosaicism in Cornelia de Lange syndrome and purifying selection of NIPBL variants in blood

Postzygotic mosaicism (PZM) in NIPBL is a strong source of causality for Cornelia de Lange syndrome (CdLS) that can have major clinical implications. Here, we further delineate the role of somatic mosaicism in CdLS by describing a series of 11 unreported patients with mosaic disease-causing variants in NIPBL and performing a retrospective cohort study from a Spanish CdLS diagnostic center. By reviewing the literature and combining our findings with previously published data, we demonstrate a negative selection against somatic deleterious NIPBL variants in blood. Furthermore, the analysis of all reported cases indicates an unusual high prevalence of mosaicism in CdLS, occurring in 13.1% of patients with a positive molecular diagnosis. It is worth noting that most of the affected individuals with mosaicism have a clinical phenotype at least as severe as those with constitutive pathogenic variants. However, the type of genetic change does not vary between germline and somatic events and, even in the presence of mosaicism, missense substitutions are located preferentially within the HEAT repeat domain of NIPBL. In conclusion, the high prevalence of mosaicism in CdLS as well as the disparity in tissue distribution provide a novel orientation for the clinical management and genetic counselling of families.

The challenge and promise of estimating the de novo mutation rate from whole-genome comparisons among closely related individuals

Germline mutations are the raw material for natural selection, driving species evolution and the generation of earth's biodiversity. Without this driver of genetic diversity, life on earth would stagnate. Yet, it is a double-edged sword. An excess of mutations can have devastating effects on fitness and population viability. It is therefore one of the great challenges of molecular ecology to determine the rate and mechanisms by which these mutations accrue across the tree of life. Advances in high-throughput sequencing technologies are providing new opportunities for characterizing the rates and mutational spectra within species and populations thus informing essential evolutionary parameters such as the timing of speciation events, the intricacies of historical demography, and the degree to which lineages are subject to the burdens of mutational load. Here, we will focus on both the challenge and promise of whole-genome comparisons among parents and their offspring from known pedigrees for the detection of germline mutations as they arise in a single generation. The potential of these studies is high, but the field is still in its infancy and much uncertainty remains. Namely, the technical challenges are daunting given that pedigree-based genome comparisons are essentially searching for needles in a haystack given the very low signal to noise ratio. Despite the challenges, we predict that rapidly developing methods for whole-genome comparisons hold great promise for integrating empirically derived estimates of de novo mutation rates and mutation spectra across many molecular ecological applications.

Brain Somatic Mutation in Aging and Alzheimer's Disease

Somatic mutations arise postzygotically, producing genetic differences between cells in an organism. Well established as a driver of cancer, somatic mutations also exist in nonneoplastic cells, including in the brain. Technological advances in nucleic acid sequencing have enabled recent break-throughs that illuminate the roles of somatic mutations in aging and degenerative diseases of the brain. Somatic mutations accumulate during aging in human neurons, a process termed genosenium. A number of recent studies have examined somatic mutations in Alzheimer’s disease (AD), primarily from the perspective of genes causing familial AD. We have also gained new information on genome-wide mutations, providing insights into the cellular events driving somatic mutation and cellular dysfunction. This review highlights recent concepts, methods, and findings in the progress to understand the role of brain somatic mutation in aging and AD.

Variable degree of mosaicism for tetrasomy 18p in phenotypically discordant monozygotic twins-Diagnostic implications

Background

Phenotypically discordant monozygotic twins (PDMZTs) offer a unique opportunity to study post‐zygotic genetic variation and provide insights into the linkage between genotype and phenotype. We report a comprehensive analysis of a pair of PDMZTs.

Methods

Dysmorphic features and delayed neuro‐motor development were observed in the proband, whereas her twin sister was phenotypically normal. Four tissues (blood, skin, hair follicles, and buccal mucosa) from both twins were studied using four complementary methods, including whole‐exome sequencing, karyotyping, array CGH, and SNP array.

Results

In the proband, tetrasomy 18p affecting all studied tissues except for blood was identified. Karyotyping of fibroblasts revealed isochromosome 18p [i(18p)] in all metaphases. The corresponding analysis of the phenotypically normal sister surprisingly revealed low‐level mosaicism (5.4%) for i(18p) in fibroblasts.

Conclusion

We emphasize that when mosaicism is suspected, multiple tissues should be studied and we highlight the usefulness of non‐invasive sampling of hair follicles and buccal mucosa as a convenient source of non‐mesoderm‐derived DNA, which complements the analysis of mesoderm using blood. Moreover, low‐level mosaic tetrasomy 18p is well tolerated and such low‐level mosaicism, readily detected by karyotyping, can be missed by other methods. Finally, mosaicism for low‐level tetrasomy 18p might be more common in the general population than it is currently recognized, due to detection limitations.