Comprehensive single-cell genome analysis at nucleotide resolution using the PTA Analysis Toolbox

Detection of somatic mutations in single cells has been severely hampered by technical limitations of whole-genome amplification. Novel technologies including primary template-directed amplification (PTA) significantly improved the accuracy of single-cell whole-genome sequencing (WGS) but still generate hundreds of artifacts per amplification reaction. We developed a comprehensive bioinformatic workflow, called the PTA Analysis Toolbox (PTATO), to accurately detect single base substitutions, insertions-deletions (indels), and structural variants in PTA-based WGS data. PTATO includes a machine learning approach and filtering based on recurrence to distinguish PTA artifacts from true mutations with high sensitivity (up to 90%), outperforming existing bioinformatic approaches. Using PTATO, we demonstrate that hematopoietic stem cells of patients with Fanconi anemia, which cannot be analyzed using regular WGS, have normal somatic single base substitution burdens but increased numbers of deletions. Our results show that PTATO enables studying somatic mutagenesis in the genomes of single cells with unprecedented sensitivity and accuracy.

The Dynamics of Somatic Mutagenesis During Life in Humans

From conception to death, human cells accumulate somatic mutations in their genomes. These mutations can contribute to the development of cancer and non-malignant diseases and have also been associated with aging. Rapid technological developments in sequencing approaches in the last few years and their application to normal tissues have greatly advanced our knowledge about the accumulation of these mutations during healthy aging. Whole genome sequencing studies have revealed that there are significant differences in mutation burden and patterns across tissues, but also that the mutation rates within tissues are surprisingly constant during adult life. In contrast, recent lineage-tracing studies based on whole-genome sequencing have shown that the rate of mutation accumulation is strongly increased early in life before birth. These early mutations, which can be shared by many cells in the body, may have a large impact on development and the origin of somatic diseases. For example, cancer driver mutations can arise early in life, decades before the detection of the malignancy. Here, we review the recent insights in mutation accumulation and mutagenic processes in normal tissues. We compare mutagenesis early and later in life and discuss how mutation rates and patterns evolve during aging. Additionally, we outline the potential impact of these mutations on development, aging and disease.

Sperm DNA damage causes genomic instability in early embryonic development

Genomic instability is common in human embryos, but the underlying causes are largely unknown. Here, we examined the consequences of sperm DNA damage on the embryonic genome by single-cell whole-genome sequencing of individual blastomeres from bovine embryos produced with sperm damaged by γ-radiation. Sperm DNA damage primarily leads to fragmentation of the paternal chromosomes followed by random distribution of the chromosomal fragments over the two sister cells in the first cell division. An unexpected secondary effect of sperm DNA damage is the induction of direct unequal cleavages, which include the poorly understood heterogoneic cell divisions. As a result, chaotic mosaicism is common in embryos derived from fertilizations with damaged sperm. The mosaic aneuploidies, uniparental disomies, and de novo structural variation induced by sperm DNA damage may compromise fertility and lead to rare congenital disorders when embryos escape developmental arrest.

Prioritization of genes driving congenital phenotypes of patients with de novo genomic structural variants

BACKGROUND

Genomic structural variants (SVs) can affect many genes and regulatory elements. Therefore, the molecular mechanisms driving the phenotypes of patients carrying de novo SVs are frequently unknown.

METHODS

We applied a combination of systematic experimental and bioinformatic methods to improve the molecular diagnosis of 39 patients with multiple congenital abnormalities and/or intellectual disability harboring apparent de novo SVs, most with an inconclusive diagnosis after regular genetic testing.

RESULTS

In 7 of these cases (18%), whole-genome sequencing analysis revealed disease-relevant complexities of the SVs missed in routine microarray-based analyses. We developed a computational tool to predict the effects on genes directly affected by SVs and on genes indirectly affected likely due to the changes in chromatin organization and impact on regulatory mechanisms. By combining these functional predictions with extensive phenotype information, candidate driver genes were identified in 16/39 (41%) patients. In 8 cases, evidence was found for the involvement of multiple candidate drivers contributing to different parts of the phenotypes. Subsequently, we applied this computational method to two cohorts containing a total of 379 patients with previously detected and classified de novo SVs and identified candidate driver genes in 189 cases (50%), including 40 cases whose SVs were previously not classified as pathogenic. Pathogenic position effects were predicted in 28% of all studied cases with balanced SVs and in 11% of the cases with copy number variants.

CONCLUSIONS

These results demonstrate an integrated computational and experimental approach to predict driver genes based on analyses of WGS data with phenotype association and chromatin organization datasets. These analyses nominate new pathogenic loci and have strong potential to improve the molecular diagnosis of patients with de novo SVs.

Mapping and phasing of structural variation in patient genomes using nanopore sequencing

Despite improvements in genomics technology, the detection of structural variants (SVs) from short-read sequencing still poses challenges, particularly for complex variation. Here we analyse the genomes of two patients with congenital abnormalities using the MinION nanopore sequencer and a novel computational pipeline-NanoSV. We demonstrate that nanopore long reads are superior to short reads with regard to detection of de novo chromothripsis rearrangements. The long reads also enable efficient phasing of genetic variations, which we leveraged to determine the parental origin of all de novo chromothripsis breakpoints and to resolve the structure of these complex rearrangements. Additionally, genome-wide surveillance of inherited SVs reveals novel variants, missed in short-read data sets, a large proportion of which are retrotransposon insertions. We provide a first exploration of patient genome sequencing with a nanopore sequencer and demonstrate the value of long-read sequencing in mapping and phasing of SVs for both clinical and research applications.

Molecular dissection of germline chromothripsis in a developmental context using patient-derived iPS cells

Background

Germline chromothripsis causes complex genomic rearrangements that are likely to affect multiple genes and their regulatory contexts. The contribution of individual rearrangements and affected genes to the phenotypes of patients with complex germline genomic rearrangements is generally unknown.

Methods

To dissect the impact of germline chromothripsis in a relevant developmental context, we performed trio-based RNA expression analysis on blood cells, induced pluripotent stem cells (iPSCs), and iPSC-derived neuronal cells from a patient with de novo germline chromothripsis and both healthy parents. In addition, Hi-C and 4C-seq experiments were performed to determine the effects of the genomic rearrangements on transcription regulation of genes in the proximity of the breakpoint junctions.

Results

Sixty-seven genes are located within 1 Mb of the complex chromothripsis rearrangements involving 17 breakpoints on four chromosomes. We find that three of these genes (FOXP1, DPYD, and TWIST1) are both associated with developmental disorders and differentially expressed in the patient. Interestingly, the effect on TWIST1 expression was exclusively detectable in the patient’s iPSC-derived neuronal cells, stressing the need for studying developmental disorders in the biologically relevant context. Chromosome conformation capture analyses show that TWIST1 lost genomic interactions with several enhancers due to the chromothripsis event, which likely led to deregulation of TWIST1 expression and contributed to the patient’s craniosynostosis phenotype.

Conclusions

We demonstrate that a combination of patient-derived iPSC differentiation and trio-based molecular profiling is a powerful approach to improve the interpretation of pathogenic complex genomic rearrangements. Here we have applied this approach to identify misexpression of TWIST1, FOXP1, and DPYD as key contributors to the complex congenital phenotype resulting from germline chromothripsis rearrangements.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-017-0399-z) contains supplementary material, which is available to authorized users.