Child development and structural variation in the human genome

A Systematic Review of Host Genomic Variation and Neuropsychological Outcomes for Pediatric Cancer Survivors

Pediatric survivors of brain tumors and acute lymphoblastic leukemia (ALL) are at risk for long-term deficits in their neuropsychological functioning. Researchers have begun examining associations between germline single nucleotide polymorphisms (SNPs), which interact with cancer treatment, and neuropsychological outcomes. This review synthesizes the impact of treatment-related toxicity from germline SNPs by neuropsychological domain (i.e., working memory, processing speed, psychological functioning) in pediatric survivors. By focusing on specific neuropsychological domains, this review will examine outcome measurement and critique methodology. Fourteen studies were identified and included in this review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). All studies were published in peer-reviewed journals in English by November 24^th, 2021. Reviewed studies were not of sufficient quality for a meta-analysis due to varying measurement strategies, gaps in reported descriptive variables, and low power. All neuropsychological domains evaluated in this review had associations with SNPs, except fine motor and visual integration abilities. Only five SNPs had consistent neuropsychological findings in more than one study or cohort. Future research and replication studies should use validated measures of discrete skills that are central to empirically validated models of survivors' long-term outcomes (i.e., attention, working memory, processing speed). Researchers should examine SNPs across pathophysiological pathways to investigate additive genetic risk in pediatric cancer survivors. Two SNPs were identified that confer resiliency in neuropsychological functioning, and future work should investigate resiliency genotypes and their underlying biological mechanisms.

Construction of copy number variation landscape and characterization of associated genes in a Bangladeshi cohort of neurodevelopmental disorders

Introduction: Copy number variations (CNVs) play a critical role in the pathogenesis of neurodevelopmental disorders (NDD) among children. In this study, we aim to identify clinically relevant CNVs, genes and their phenotypic characteristics in an ethnically underrepresented homogenous population of Bangladesh. Methods: We have conducted chromosomal microarray analysis (CMA) for 212 NDD patients with male to female ratio of 2.2:1.0 to identify rare CNVs. To identify candidate genes within the rare CNVs, gene constraint metrics [i.e., "Critical-Exon Genes (CEGs)"] were applied to the population data. Autism Diagnostic Observation Schedule-Second Edition (ADOS-2) was followed in a subset of 95 NDD patients to assess the severity of autism and all statistical tests were performed using the R package. Results: Of all the samples assayed, 12.26% (26/212) and 57.08% (121/212) patients carried pathogenic and variant of uncertain significance (VOUS) CNVs, respectively. While 2.83% (6/212) patients' pathogenic CNVs were found to be located in the subtelomeric regions. Further burden test identified females are significant carriers of pathogenic CNVs compared to males (OR = 4.2; p = 0.0007). We have observed an increased number of Loss of heterozygosity (LOH) within cases with 23.85% (26/109) consanguineous parents. Our analyses on imprinting genes show, 36 LOH variants disrupting 69 unique imprinted genes and classified these variants as VOUS. ADOS-2 subset shows severe social communication deficit (p = 0.014) and overall ASD symptoms severity (p = 0.026) among the patients carrying duplication CNV compared to the CNV negative group. Candidate gene analysis identified 153 unique CEGs in pathogenic CNVs and 31 in VOUS. Of the unique genes, 18 genes were found to be in smaller (<1 MB) focal CNVs in our NDD cohort and we identified PSMC3 gene as a strong candidate gene for Autism Spectrum Disorder (ASD). Moreover, we hypothesized that KMT2B gene duplication might be associated with intellectual disability. Conclusion: Our results show the utility of CMA for precise genetic diagnosis and its integration into the diagnosis, therapy and management of NDD patients.

DNA methylation episignatures: insight into copy number variation

In this review we discuss epigenetic disorders that result from aberrations in genes linked to epigenetic regulation. We describe current testing methods for the detection of copy number variants (CNVs) in Mendelian disorders, dosage sensitivity, reciprocal phenotypes and the challenges of test selection and overlapping clinical features in genetic diagnosis. We discuss aberrations of DNA methylation and propose a role for episignatures as a novel clinical testing method in CNV disorders. Finally, we postulate that episignature mapping in CNV disorders may provide novel insights into the molecular mechanisms of disease and unlock key findings of the genome-wide impact on disease gene networks.

The missing heritability in type 1 diabetes

Type 1 diabetes (T1D) is a complex autoimmune disease characterized by an absolute deficiency of insulin. It affects more than 20 million people worldwide and imposes an enormous financial burden on patients. The underlying pathogenic mechanisms of T1D are still obscure, but it is widely accepted that both genetics and the environment play an important role in its onset and development. Previous studies have identified more than 60 susceptible loci associated with T1D, explaining approximately 80%-85% of the heritability. However, most identified variants confer only small increases in risk, which restricts their potential clinical application. In addition, there is still a so-called 'missing heritability' phenomenon. While the gap between known heritability and true heritability in T1D is small compared with that in other complex traits and disorders, further elucidation of T1D genetics has the potential to bring novel insights into its aetiology and provide new therapeutic targets. Many hypotheses have been proposed to explain the missing heritability, including variants remaining to be found (variants with small effect sizes, rare variants and structural variants) and interactions (gene-gene and gene-environment interactions; e.g. epigenetic effects). In the following review, we introduce the possible sources of missing heritability and discuss the existing related knowledge in the context of T1D.

DNA Methylation Episignatures in Neurodevelopmental Disorders Associated with Large Structural Copy Number Variants: Clinical Implications

Large structural chromosomal deletions and duplications, referred to as copy number variants (CNVs), play a role in the pathogenesis of neurodevelopmental disorders (NDDs) through effects on gene dosage. This review focuses on our current understanding of genomic disorders that arise from large structural chromosome rearrangements in patients with NDDs, as well as difficulties in overlap of clinical presentation and molecular diagnosis. We discuss the implications of epigenetics, specifically DNA methylation (DNAm), in NDDs and genomic disorders, and consider the implications and clinical impact of copy number and genomic DNAm testing in patients with suspected genetic NDDs. We summarize evidence of global methylation episignatures in CNV-associated disorders that can be used in the diagnostic pathway and may provide insights into the molecular pathogenesis of genomic disorders. Finally, we discuss the potential for combining CNV and DNAm assessment into a single diagnostic assay.

Non-coding regulatory elements: Potential roles in disease and the case of epilepsy

Non-coding DNA (ncDNA) refers to the portion of the genome that does not code for proteins and accounts for the greatest physical proportion of the human genome. ncDNA includes sequences that are transcribed into RNA molecules, such as ribosomal RNAs (rRNAs), microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and un-transcribed sequences that have regulatory functions, including gene promoters and enhancers. Variation in non-coding regions of the genome have an established role in human disease, with growing evidence from many areas, including several cancers, Parkinson's disease and autism. Here, we review the features and functions of the regulatory elements that are present in the non-coding genome and the role that these regions have in human disease. We then review the existing research in epilepsy and emphasise the potential value of further exploring non-coding regulatory elements in epilepsy. In addition, we outline the most widely used techniques for recognising regulatory elements throughout the genome, current methodologies for investigating variation and the main challenges associated with research in the field of non-coding DNA.

Characterizing sensitivity and coverage of clinical WGS as a diagnostic test for genetic disorders

BACKGROUND

Due to its reduced cost and incomparable advantages, WGS is likely to lead to changes in clinical diagnosis of rare and undiagnosed diseases. However, the sensitivity and breadth of coverage of clinical WGS as a diagnostic test for genetic disorders has not been fully evaluated.

METHODS

Here, the performance of WGS in NA12878, the YH cell line, and the Chinese trios were measured by assessing their sensitivity, PPV, depth and breadth of coverage using MGISEQ-2000. We also compared the performance of WES and WGS using NA12878. The sensitivity and PPV were tested using the family-based trio design for the Chinese trios. We further developed a systematic WGS pipeline for the analysis of 8 clinical cases.

RESULTS

In general, the sensitivity and PPV for SNV/indel detection increased with mean depth and reached a plateau at an ~ 40X mean depth using down-sampling samples of NA12878. With a mean depth of 40X, the sensitivity of homozygous and heterozygous SNPs of NA12878 was > 99.25% and > 99.50%, respectively, and the PPV was 99.97% and 98.96%. Homozygous and heterozygous indels showed lower sensitivity and PPV. The sensitivity and PPV were still not 100% even with a mean depth of ~ 150X. We also observed a substantial variation in the sensitivity of CNV detection across different tools, especially in CNVs with a size less than 1 kb. In general, the breadth of coverage for disease-associated genes and CNVs increased with mean depth. The sensitivity and coverage of WGS (~ 40X) was better than WES (~ 120X). Among the Chinese trios with an ~ 40X mean depth, the sensitivity among offspring was > 99.48% and > 96.36% for SNP and indel detection, and the PPVs were 99.86% and 97.93%. All 12 previously validated variants in the 8 clinical cases were successfully detected using our WGS pipeline.

CONCLUSIONS

The current standard of a mean depth of 40X may be sufficient for SNV/indel detection and identification of most CNVs. It would be advisable for clinical scientists to determine the range of sensitivity and PPV for different classes of variants for a particular WGS pipeline, which would be useful when interpreting and delivering clinical reports.

Whole-genome sequencing analysis of CNV using low-coverage and paired-end strategies is efficient and outperforms array-based CNV analysis

BACKGROUND

Copy number variation (CNV) analysis is an integral component of the study of human genomes in both research and clinical settings. Array-based CNV analysis is the current first-tier approach in clinical cytogenetics. Decreasing costs in high-throughput sequencing and cloud computing have opened doors for the development of sequencing-based CNV analysis pipelines with fast turnaround times. We carry out a systematic and quantitative comparative analysis for several low-coverage whole-genome sequencing (WGS) strategies to detect CNV in the human genome.

METHODS

We compared the CNV detection capabilities of WGS strategies (short insert, 3 kb insert mate pair and 5 kb insert mate pair) each at 1×, 3× and 5× coverages relative to each other and to 17 currently used high-density oligonucleotide arrays. For benchmarking, we used a set of gold standard (GS) CNVs generated for the 1000 Genomes Project CEU subject NA12878.

RESULTS

Overall, low-coverage WGS strategies detect drastically more GS CNVs compared with arrays and are accompanied with smaller percentages of CNV calls without validation. Furthermore, we show that WGS (at ≥1× coverage) is able to detect all seven GS deletion CNVs >100 kb in NA12878, whereas only one is detected by most arrays. Lastly, we show that the much larger 15 Mbp Cri du chat deletion can be readily detected with short-insert paired-end WGS at even just 1× coverage.

CONCLUSIONS

CNV analysis using low-coverage WGS is efficient and outperforms the array-based analysis that is currently used for clinical cytogenetics.

Comprehensive performance comparison of high-resolution array platforms for genome-wide Copy Number Variation (CNV) analysis in humans

BACKGROUND

High-resolution microarray technology is routinely used in basic research and clinical practice to efficiently detect copy number variants (CNVs) across the entire human genome. A new generation of arrays combining high probe densities with optimized designs will comprise essential tools for genome analysis in the coming years. We systematically compared the genome-wide CNV detection power of all 17 available array designs from the Affymetrix, Agilent, and Illumina platforms by hybridizing the well-characterized genome of 1000 Genomes Project subject NA12878 to all arrays, and performing data analysis using both manufacturer-recommended and platform-independent software. We benchmarked the resulting CNV call sets from each array using a gold standard set of CNVs for this genome derived from 1000 Genomes Project whole genome sequencing data.

RESULTS

The arrays tested comprise both SNP and aCGH platforms with varying designs and contain between ~0.5 to ~4.6 million probes. Across the arrays CNV detection varied widely in number of CNV calls (4-489), CNV size range (~40 bp to ~8 Mbp), and percentage of non-validated CNVs (0-86%). We discovered strikingly strong effects of specific array design principles on performance. For example, some SNP array designs with the largest numbers of probes and extensive exonic coverage produced a considerable number of CNV calls that could not be validated, compared to designs with probe numbers that are sometimes an order of magnitude smaller. This effect was only partially ameliorated using different analysis software and optimizing data analysis parameters.

CONCLUSIONS

High-resolution microarrays will continue to be used as reliable, cost- and time-efficient tools for CNV analysis. However, different applications tolerate different limitations in CNV detection. Our study quantified how these arrays differ in total number and size range of detected CNVs as well as sensitivity, and determined how each array balances these attributes. This analysis will inform appropriate array selection for future CNV studies, and allow better assessment of the CNV-analytical power of both published and ongoing array-based genomics studies. Furthermore, our findings emphasize the importance of concurrent use of multiple analysis algorithms and independent experimental validation in array-based CNV detection studies.

[Structural variations of the genome in autistic spectrum disorders with intellectual disability]

AIM

To analyze structural variations in the genome in children with autism and intellectual disability.

MATERIAL AND METHODS

Using high-resolution karyotyping (AffymetrixCytoScan HD Array) and original bioinformatic technology, 200 children with autism and intellectual disability were studied.

RESULTS AND CONCLUSION

Data on structural variations in the genome in children with autism and intellectual disability are provided. Causative genomic pathology (chromosome abnormalities and copy number variations - CNV) was determined in 97 cases (48.5%). Based on these

RESULTS

24 candidate genes for autism with intellectual disability were selected. In 16 cases (8%), the chromosome mosaicism manifested as aneuploidy of whole autosomes and sex chromosomes (gonosomes) was identified. In 87 children (43.5%), there were genomic variations, which are characteristic of the so-called «grey zone» of genetic pathology in mental illnesses. Bioinformatic analysis showed that these genomic variations had a pleiotropic effect on the phenotype.

Whole Genome Sequencing Identifies a 78 kb Insertion from Chromosome 8 as the Cause of Charcot-Marie-Tooth Neuropathy CMTX3

With the advent of whole exome sequencing, cases where no pathogenic coding mutations can be found are increasingly being observed in many diseases. In two large, distantly-related families that mapped to the Charcot-Marie-Tooth neuropathy CMTX3 locus at chromosome Xq26.3-q27.3, all coding mutations were excluded. Using whole genome sequencing we found a large DNA interchromosomal insertion within the CMTX3 locus. The 78 kb insertion originates from chromosome 8q24.3, segregates fully with the disease in the two families, and is absent from the general population as well as 627 neurologically normal chromosomes from in-house controls. Large insertions into chromosome Xq27.1 are known to cause a range of diseases and this is the first neuropathy phenotype caused by an interchromosomal insertion at this locus. The CMTX3 insertion represents an understudied pathogenic structural variation mechanism for inherited peripheral neuropathies. Our finding highlights the importance of considering all structural variation types when studying unsolved inherited peripheral neuropathy cases with no pathogenic coding mutations.

Understanding the pathological manifestations of aromatase excess syndrome: lessons for clinical diagnosis

CYP19A1

Aromatase excess syndrome is characterized by pre- or peripubertal onset of gynecomastia due to estrogen excess because of a gain-of-function mutation in the aromatase gene (CYP19A1). Subchromosomal recombination events including duplication, deletion, and inversion has been identified. The latter two recombinations recruit novel promoters for CYP19A1 through a unique mechanism. Gynecomastia continues for life, and although the general condition is well preserved, it may cause psychological issues. Minor symptoms (variably advanced bone age and short adult height), if present, are exclusively because of estrogen excess. Serum estradiol levels are elevated in 48% of affected males, but are not necessarily useful for diagnosis. Molecular analysis of CYP19A1 mutations is mandatory to confirm aromatase excess syndrome diagnosis. Furthermore, the use of an aromatase inhibitor can ameliorate gynecomastia.

Copy number variation is a fundamental aspect of the placental genome

Discovery of lineage-specific somatic copy number variation (CNV) in mammals has led to debate over whether CNVs are mutations that propagate disease or whether they are a normal, and even essential, aspect of cell biology. We show that 1,000N polyploid trophoblast giant cells (TGCs) of the mouse placenta contain 47 regions, totaling 138 Megabases, where genomic copies are underrepresented (UR). UR domains originate from a subset of late-replicating heterochromatic regions containing gene deserts and genes involved in cell adhesion and neurogenesis. While lineage-specific CNVs have been identified in mammalian cells, classically in the immune system where V(D)J recombination occurs, we demonstrate that CNVs form during gestation in the placenta by an underreplication mechanism, not by recombination nor deletion. Our results reveal that large scale CNVs are a normal feature of the mammalian placental genome, which are regulated systematically during embryogenesis and are propagated by a mechanism of underreplication.

Generally, every mammalian cell has the same complement of each part of its genome. However, copy number variation (CNV) can occur, where, compared to the rest of its genome, a cell has either more or less of a specific genomic region. It is unknown whether CNVs cause disease, or whether they are a normal aspect of cell biology. We investigated CNVs in polyploid trophoblast giant cells (TGCs) of the mouse placenta, which have up to 1,000 copies of the genome in each cell. We found that there are 47 regions with decreased copy number in TGCs, which we call underrepresented (UR) domains. These domains are marked in the TGC progenitor cells and we suggest that they gradually form during gestation due to slow replication versus fast replication of the rest of the genome. While UR domains contain cell adhesion and neuronal genes, they also contain significantly fewer genes than other genomic regions. Our results demonstrate that CNVs are a normal feature of the mammalian placental genome, which are regulated systematically during pregnancy.

Impacts of variation in the human genome on gene regulation

Recent advances in fast and inexpensive DNA sequencing have enabled the extensive study of genomic and transcriptomic variation in humans. Human genomic variation is composed of sequence and structural changes including single-nucleotide and multinucleotide variants, short insertions or deletions (indels), larger copy number variants, and similarly sized copy neutral inversions and translocations. It is now well established that any two genomes differ extensively and that structural changes constitute a prominent source of this variation. There have also been major technological advances in RNA sequencing to globally quantify and describe diversity in transcripts. Large consortia such as the 1000 Genomes Project and the ENCODE (ENCyclopedia Of DNA Elements) Project are producing increasingly comprehensive maps outlining the regions of the human genome containing variants and functional elements, respectively. Integration of genetic variation data and extensive annotation of functional genomic elements, along with the ability to measure global transcription, allow the impacts of genetic variants on gene expression to be resolved. There are several well-established models by which genetic variants affect gene regulation depending on the type, nature, and position of the variant with respect to the affected genes. These effects can be manifested in two ways: changes to transcript sequences and isoforms by coding variants, and changes to transcript abundance by dosage or regulatory variants. Here, we review the current state of how genetic variations impact gene regulation locally and globally in the human genome.