Analysis of genetic inheritance in a family quartet by whole-genome sequencing

Implications of germline copy-number variations in psychiatric disorders: review of large-scale genetic studies

Copy number variants (CNVs), defined as genome sequences of ≥50 bp that differ in copy number from that in a reference genome, are a common form of structural variation. Germline CNVs account for some of the missing heritability that single nucleotide polymorphisms could not account for. Recent technological advances have had a huge impact on CNV research. Microarray technology enables relatively low-cost, high-throughput, genome-wide measurements, and short-read sequencing technology enables the detection of short CNVs that cannot be detected by microarrays. As a result, large-scale genetic studies have been able to identify a variety of common and rare germline CNVs and their associations with diseases. Rare germline CNVs have been reported to be associated with neuropsychiatric disorders. In this review, we focused on germline CNVs and briefly described their functional characteristics, formation mechanisms, detection methods, related databases, and the latest findings. Finally, we introduced recent large-scale genetic studies to assess associations of CNVs with diseases, especially psychiatric disorders, and discussed the use of CNV-based animal models to investigate the molecular and cellular mechanisms underlying these disorders. The development and implementation of improved detection methods, such as long-read single-molecule sequencing, are expected to provide additional insight into the molecular basis of psychiatric disorders and other complex diseases, thus facilitating basic and clinical research on CNVs.

Quantifying Influences on Intragenomic Mutation Rate

We report work to quantify the impact on the probability of human genome polymorphism both of recombination and of sequence context at different scales. We use population-based analyses of data on human genetic variants obtained from the public Ensembl database. For recombination, we calculate the variance due to recombination and the probability that a recombination event causes a mutation. We employ novel statistical procedures to take account of the spatial auto-correlation of recombination and mutation rates along the genome. Our results support the view that genomic diversity in recombination hotspots arises largely from a direct effect of recombination on mutation rather than predominantly from the effect of selective sweeps. We also use the statistic of variance due to context to compare the effect on the probability of polymorphism of contexts of various sizes. We find that when the 12 point mutations are considered separately, variance due to context increases significantly as we move from 3-mer to 5-mer and from 5-mer to 7-mer contexts. However, when all mutations are considered in aggregate, these differences are outweighed by the effect of interaction between the central base and its immediate neighbors. This interaction is itself dominated by the transition mutations, including, but not limited to, the CpG effect. We also demonstrate strand-asymmetry of contextual influence in intronic regions, which is hypothesized to be a result of transcription coupled DNA repair. We consider the extent to which the measures we have used can be used to meaningfully compare the relative magnitudes of the impact of recombination and context on mutation.

Plant Genome Editing and the Relevance of Off-Target Changes

Site-directed nucleases (SDNs) used for targeted genome editing are powerful new tools to introduce precise genetic changes into plants. Like traditional approaches, such as conventional crossing and induced mutagenesis, genome editing aims to improve crop yield and nutrition. Next-generation sequencing studies demonstrate that across their genomes, populations of crop species typically carry millions of single nucleotide polymorphisms and many copy number and structural variants. Spontaneous mutations occur at rates of ∼10-8 to 10-9 per site per generation, while variation induced by chemical treatment or ionizing radiation results in higher mutation rates. In the context of SDNs, an off-target change or edit is an unintended, nonspecific mutation occurring at a site with sequence similarity to the targeted edit region. SDN-mediated off-target changes can contribute to a small number of additional genetic variants compared to those that occur naturally in breeding populations or are introduced by induced-mutagenesis methods. Recent studies show that using computational algorithms to design genome editing reagents can mitigate off-target edits in plants. Finally, crops are subject to strong selection to eliminate off-type plants through well-established multigenerational breeding, selection, and commercial variety development practices. Within this context, off-target edits in crops present no new safety concerns compared to other breeding practices. The current generation of genome editing technologies is already proving useful to develop new plant varieties with consumer and farmer benefits. Genome editing will likely undergo improved editing specificity along with new developments in SDN delivery and increasing genomic characterization, further improving reagent design and application.

Detection of genome-wide low-frequency mutations with Paired-End and Complementary Consensus Sequencing (PECC-Seq) revealed end-repair-derived artifacts as residual errors

To improve the accuracy and the cost-efficiency of next-generation sequencing in ultralow-frequency mutation detection, we developed the Paired-End and Complementary Consensus Sequencing (PECC-Seq), a PCR-free duplex consensus sequencing approach. PECC-Seq employed shear points as endogenous barcodes to identify consensus sequences from the overlap in the shortened, complementary DNA strand-derived paired-end reads for sequencing error correction. With the high accuracy of PECC-Seq, we identified the characteristic base substitution errors introduced by the end-repair process of mechanical fragmentation-based library preparations, which were prominent at the terminal 7 bp of the library fragments in the 5'-NpCpA-3' and 5'-NpCpT-3' trinucleotide context. As demonstrated at the human genome scale (TK6 cells), after removing these potential end-repair artifacts from the terminal 7 bp, PECC-Seq could reduce the sequencing error frequency to mid-10^-7 with a relatively low sequencing depth. For TA base pairs, the background error rate could be suppressed to mid-10^-8. In mutagen-treated (6 μg/mL methyl methanesulfonate or 12 μg/mL N-nitroso-N-ethylurea) TK6, increases in mutagen treatment-related mutant frequencies could be detected, indicating the potential of PECC-Seq in detecting genome-wide ultra-rare mutations. In addition, our finding on the patterns of end-repair artifacts may provide new insights into further reducing technical errors not only for PECC-Seq, but also for other next-generation sequencing techniques.

Ranbow: A fast and accurate method for polyploid haplotype reconstruction

Reconstructing haplotypes from sequencing data is one of the major challenges in genetics. Haplotypes play a crucial role in many analyses, including genome-wide association studies and population genetics. Haplotype reconstruction becomes more difficult for higher numbers of homologous chromosomes, as it is often the case for polyploid plants. This complexity is compounded further by higher heterozygosity, which denotes the frequent presence of variants between haplotypes. We have designed Ranbow, a new tool for haplotype reconstruction of polyploid genome from short read sequencing data. Ranbow integrates all types of small variants in bi- and multi-allelic sites to reconstruct haplotypes. To evaluate Ranbow and currently available competing methods on real data, we have created and released a real gold standard dataset from sweet potato sequencing data. Our evaluations on real and simulated data clearly show Ranbow’s superior performance in terms of accuracy, haplotype length, memory usage, and running time. Specifically, Ranbow is one order of magnitude faster than the next best method. The efficiency and accuracy of Ranbow makes whole genome haplotype reconstruction of complex genome with higher ploidy feasible.

We focus on the problem of reconstructing haplotypes for polyploid genomes. Our approach explored using short read sequence data from a highly heterozygous hexaploid genome. We observed that short read data from strongly heterozygous organisms open up a way for haplotype reconstruction by supplying overlap information between reads. We therefore investigated the role of heterozygosity and ploidy number. Though higher heterozygosity provides more useful reads for reconstructing haplotypes, polyploidy increases the challenge in assembling reads into longer sequences. We called this the problem of “Ambiguity of Merging” fragments. We addressed this problem by designing a new algorithm called Ranbow. Ranbow was evaluated on real and simulated data from the genomes of tetraploid Capsella bursa-pastoris (Shepherd’s Purse) and hexaploid Ipomoea batatas (sweet potato). We were able to show that our method achieved high accuracy and long assembled haplotypes in a feasible amount of time, performing at a level consistently superior to other algorithms.

A Rare Mutation in SPLUNC1 Affects Bacterial Adherence and Invasion in Meningococcal Disease

BACKGROUND

Neisseria meningitidis (Nm) is a nasopharyngeal commensal carried by healthy individuals. However, invasive infections occurs in a minority of individuals, with devastating consequences. There is evidence that common polymorphisms are associated with invasive meningococcal disease (IMD), but the contributions of rare variants other than those in the complement system have not been determined.

METHODS

We identified familial cases of IMD in the UK meningococcal disease study and the European Union Life-Threatening Infectious Disease Study. Candidate genetic variants were identified by whole-exome sequencing of 2 patients with familial IMD. Candidate variants were further validated by in vitro assays.

RESULTS

Exomes of 2 siblings with IMD identified a novel heterozygous missense mutation in BPIFA1/SPLUNC1. Sequencing of 186 other nonfamilial cases identified another unrelated IMD patient with the same mutation. SPLUNC1 is an innate immune defense protein expressed in the nasopharyngeal epithelia; however, its role in invasive infections is unknown. In vitro assays demonstrated that recombinant SPLUNC1 protein inhibits biofilm formation by Nm, and impedes Nm adhesion and invasion of human airway cells. The dominant negative mutant recombinant SPLUNC1 (p.G22E) showed reduced antibiofilm activity, increased meningococcal adhesion, and increased invasion of cells, compared with wild-type SPLUNC1.

CONCLUSIONS

A mutation in SPLUNC1 affecting mucosal attachment, biofilm formation, and invasion of mucosal epithelial cells is a new genetic cause of meningococcal disease.

Missing heritability in Parkinson's disease: the emerging role of non-coding genetic variation

Parkinson's disease (PD) is a neurodegenerative disorder caused by a complex interplay of genetic and environmental factors. For the stratification of PD patients and the development of advanced clinical trials, including causative treatments, a better understanding of the underlying genetic architecture of PD is required. Despite substantial efforts, genome-wide association studies have not been able to explain most of the observed heritability. The majority of PD-associated genetic variants are located in non-coding regions of the genome. A systematic assessment of their functional role is hampered by our incomplete understanding of genotype-phenotype correlations, for example through differential regulation of gene expression. Here, the recent progress and remaining challenges for the elucidation of the role of non-coding genetic variants is reviewed with a focus on PD as a complex disease with multifactorial origins. The function of gene regulatory elements and the impact of non-coding variants on them, and the means to map these elements on a genome-wide level, will be delineated. Moreover, examples of how the integration of functional genomic annotations can serve to identify disease-associated pathways and to prioritize disease- and cell type-specific regulatory variants will be given. Finally, strategies for functional validation and considerations for suitable model systems are outlined. Together this emphasizes the contribution of rare and common genetic variants to the complex pathogenesis of PD and points to remaining challenges for the dissection of genetic complexity that may allow for better stratification, improved diagnostics and more targeted treatments for PD in the future.

Adapting Biased Gene Conversion theory to account for intensive GC-content deterioration in the human genome by novel mutations

We examined seventy million well-characterized human mutations, and their impact on G+C-compositional dynamics, in order to understand the formation and maintenance of major genomic nucleotide sequence patterns. Among novel mutations, those that change a strong (S) base pair G:C/C:G to a weak (W) pair A:T/T:A occur at nearly twice the frequency of the opposite mutations. Such imbalance puts strong downward pressure on overall GC-content. However, along protracted paths to fixation, S→W mutations are much less likely to propagate than W→S mutations. The magnitude of relative propagation disadvantages for S→W mutations is inexplicable by any currently-accepted model. This fact forced us to re-examine the quantitative features of Biased Gene Conversion (BGC) theory. Revised parameters of BGC that, per average individual, convert 7–14 W base pairs into S pairs, would account for the S-content turnover differences between new and old mutations, and make BGC an instrumental force for nucleotide dynamics and evolution. BGC should thus be considered seriously in both theories and biomedical practice. In particular, BGC should be taken into account during allele imputations, where missing SNP alleles are computationally predicted based on the information about several neighboring alleles. Finally, we analyzed the effect of neighboring nucleotide context on the mutation frequencies, dynamics, and GC-composition turnover. For this purpose, we examined genomic regions having extremely biased nucleotide compositions (enriched for S-, W-, purine/pyrimidine strand asymmetry, or AC/GT-strand asymmetry). It was found that point mutations in these regions preferentially degrade the nucleotide inhomogeneities, decreasing the sequence biases. Degradation of sequence bias is highest for novel mutations, and considerably lower for older mutations (those widespread across populations). Besides BGC, there may be additional, still uncharacterized molecular mechanisms that either preserve genomic regions with biased nucleotide compositions from mutational degradation or fail to degrade such inhomogeneities in specific chromosomal regions.

Secuenciación de nueva generación (NGS) de ADN: presente y futuro en la práctica clínica

Introducción: el término secuenciación de nueva generación (NGS) hace referencia a las tecnologías diseñadas para analizar gran cantidad de ADN de forma masiva y paralela. Abordamos en esta revisión los conceptos básicos de estas tecnologías, las consideraciones de su uso clínico actual y perspectivas a futuro. Desarrollo: las pruebas basadas en NGS han revolucionado el estudio de los genomas pues permiten la lectura de millones de secuencias de ADN de forma masiva y paralela en un menor lapso de tiempo y a menor costo por base. Estas pruebas incluyen la secuenciación de panel de genes, la secuenciación completa del exoma y la secuenciación completa del genoma. El análisis de sus resultados es complejo y requiere de un proceso bioinformático y clínico exhaustivo para su adecuada interpretación. Las limitaciones de las pruebas NGS incluyen aspectos técnicos como la cobertura, profundidad y longitud de las secuencias, las cuales se pueden solventar implementando buenas prácticas de laboratorio. Conclusiones: las pruebas basadas en la secuenciación por NGS son herramientas diagnósticas que deben partir de una aproximación clínica adecuada para su uso razonado, correcta interpretación y toma de decisiones acertadas. Es de gran trascendencia que los médicos tengan la información básica para poder solicitar e interpretar estas pruebas dada su relevancia clínica actual.

De novo mutations across 1,465 diverse genomes reveal mutational insights and reductions in the Amish founder population

De novo mutations (DNMs), or mutations that appear in an individual despite not being seen in their parents, are an important source of genetic variation whose impact is relevant to studies of human evolution, genetics, and disease. Utilizing high-coverage whole-genome sequencing data as part of the Trans-Omics for Precision Medicine (TOPMed) Program, we called 93,325 single-nucleotide DNMs across 1,465 trios from an array of diverse human populations, and used them to directly estimate and analyze DNM counts, rates, and spectra. We find a significant positive correlation between local recombination rate and local DNM rate, and that DNM rate explains a substantial portion (8.98 to 34.92%, depending on the model) of the genome-wide variation in population-level genetic variation from 41K unrelated TOPMed samples. Genome-wide heterozygosity does correlate with DNM rate, but only explains <1% of variation. While we are underpowered to see small differences, we do not find significant differences in DNM rate between individuals of European, African, and Latino ancestry, nor across ancestrally distinct segments within admixed individuals. However, we did find significantly fewer DNMs in Amish individuals, even when compared with other Europeans, and even after accounting for parental age and sequencing center. Specifically, we found significant reductions in the number of C→A and T→C mutations in the Amish, which seem to underpin their overall reduction in DNMs. Finally, we calculated near-zero estimates of narrow sense heritability (h2), which suggest that variation in DNM rate is significantly shaped by nonadditive genetic effects and the environment.

The Clinical Genome and Ancestry Report: An interactive web application for prioritizing clinically implicated variants from genome sequencing data with ancestry composition

Genome sequencing is positioned as a routine clinical work-up for diverse clinical conditions. A commonly used approach to highlight candidate variants with potential clinical implication is to search over locus- and gene-centric knowledge databases. Most web-based applications allow a federated query across diverse databases for a single variant; however, sifting through a large number of genomic variants with combination of filtering criteria is a substantial challenge. Here we describe the Clinical Genome and Ancestry Report (CGAR), an interactive web application developed to follow clinical interpretation workflows by organizing variants into seven categories: (1) reported disease-associated variants, (2) rare- and high-impact variants in putative disease-associated genes, (3) secondary findings that the American College of Medical Genetics and Genomics recommends reporting back to patients, (4) actionable pharmacogenomic variants, (5) focused reports for candidate genes, (6) de novo variant candidates for trio analysis, and (7) germline and somatic variants implicated in cancer risk, diagnosis, treatment and prognosis. For each variant, a comprehensive list of external links to variant-centric and phenotype databases are provided. Furthermore, genotype-derived ancestral composition is used to highlight allele frequencies from a matched population since some disease-associated variants show a wide variation between populations. CGAR is an open-source software and is available at https://tom.tch.harvard.edu/apps/cgar/.

Investigation of de novo variation in pediatric cardiomyopathy

Pediatric cardiomyopathies can be caused by variants in genes encoding the sarcomere and cytoskeleton in cardiomyocytes. Variants are typically inherited in an autosomal dominant manner with variable expressivity. De novo variants have been reported, however their overall frequency is largely unknown. We sought to determine the rate of de novo, pathogenic and likely pathogenic (P/LP) variants in children with a diagnosis of hypertrophic, dilated, or restrictive cardiomyopathy (HCM, DCM, or RCM), and to compare disease outcomes between individuals with and without a de novo variant. A retrospective record review identified 126 individuals with HCM (55%), DCM (37%), or RCM (8%) ≤18 years of age who had genetic testing. Overall, 50 (40%) had positive genetic testing and 18% of P/LP variants occurred de novo. The rate of de novo variation in those with RCM (80%) was higher than in those with HCM (9%) or DCM (20%). There was evidence of germline mosaicism in one family with RCM. Individuals with de novo variants were more likely than those without to have a history of arrhythmia (p = .049), sudden cardiac arrest (p = .024), hospitalization (p = .041), and cardiac transplantation (p = .030). The likelihood of de novo variation and impact on family risk and screening should be integrated into genetic counseling.

A rare loss-of-function variant of ADAM17 is associated with late-onset familial Alzheimer disease

Common variants of about 20 genes contributing to AD risk have so far been identified through genome-wide association studies (GWAS). However, there is still a large proportion of heritability that might be explained by rare but functionally important variants. One of the so far identified genes with rare AD causing variants is ADAM10. Using whole-genome sequencing we now identified a single rare nonsynonymous variant (SNV) rs142946965 [p.R215I] in ADAM17 co-segregating with an autosomal-dominant pattern of late-onset AD in one family. Subsequent genotyping and analysis of available whole-exome sequencing data of additional case/control samples from Germany, UK, and USA identified five variant carriers among AD patients only. The mutation inhibits pro-protein cleavage and the formation of the active enzyme, thus leading to loss-of-function of ADAM17 alpha-secretase. Further, we identified a strong negative correlation between ADAM17 and APP gene expression in human brain and present in vitro evidence that ADAM17 negatively controls the expression of APP. As a consequence, p.R215I mutation of ADAM17 leads to elevated Aß formation in vitro. Together our data supports a causative association of the identified ADAM17 variant in the pathogenesis of AD.

A practical introduction to sequentially Markovian coalescent methods for estimating demographic history from genomic data

A common goal of population genomics and molecular ecology is to reconstruct the demographic history of a species of interest. A pair of powerful tools based on the sequentially Markovian coalescent have been developed to infer past population sizes using genome sequences. These methods are most useful when sequences are available for only a limited number of genomes and when the aim is to study ancient demographic events. The results of these analyses can be difficult to interpret accurately, because doing so requires some understanding of their theoretical basis and of their sensitivity to confounding factors. In this practical review, we explain some of the key concepts underpinning the pairwise and multiple sequentially Markovian coalescent methods (PSMC and MSMC, respectively). We relate these concepts to the use and interpretation of these methods, and we explain how the choice of different parameter values by the user can affect the accuracy and precision of the inferences. Based on our survey of 100 PSMC studies and 30 MSMC studies, we describe how the two methods are used in practice. Readers of this article will become familiar with the principles, practice, and interpretation of the sequentially Markovian coalescent for inferring demographic history.

Speciation history of European (Anguilla anguilla) and American eel (A. rostrata), analysed using genomic data

Speciation in the ocean could differ from terrestrial environments due to fewer barriers to gene flow. Hence, sympatric speciation might be common, with American and European eel being candidates for exemplifying this. They show disjunct continental distributions on both sides of the Atlantic, but spawn in overlapping regions of the Sargasso Sea from where juveniles are advected to North American, European and North African coasts. Hybridization and introgression are known to occur, with hybrids almost exclusively observed in Iceland. Different speciation scenarios have been suggested, involving either vicariance or sympatric ecological speciation. Using RAD sequencing and whole-genome sequencing data from parental species and F1 hybrids, we analysed speciation history based on the joint allele frequency spectrum (JAFS) and pairwise sequentially Markovian coalescent (PSMC) plots. JAFS supported a model involving a split without gene flow 150,000-160,000 generations ago, followed by secondary contact 87,000-92,000 generations ago, with 64% of the genome experiencing restricted gene flow. This supports vicariance rather than sympatric speciation, likely associated with Pleistocene glaciation cycles and ocean current changes. Whole-genome PSMC analysis of F1 hybrids from Iceland suggested divergence 200,000 generations ago and indicated subsequent gene flow rather than strict isolation. Finally, simulations showed that results from both approaches (JAFS and PSMC) were congruent. Hence, there is strong evidence against sympatric speciation in North Atlantic eels. These results reiterate the need for careful consideration of cases of possible sympatric speciation, as even in seemingly barrier-free oceanic environments palaeoceanographic factors may have promoted vicariance and allopatric speciation.

Population size influences the type of nucleotide variations in humans

Background

It is well known that the effective size of a population (N_e) is one of the major determinants of the amount of genetic variation within the population. However, it is unclear whether the types of genetic variations are also dictated by the effective population size. To examine this, we obtained whole genome data from over 100 populations of the world and investigated the patterns of mutational changes.

Results

Our results revealed that for low frequency variants, the ratio of AT→GC to GC→AT variants (β) was similar across populations, suggesting the similarity of the pattern of mutation in various populations. However, for high frequency variants, β showed a positive correlation with the effective population size of the populations. This suggests a much higher proportion of high frequency AT→GC variants in large populations (e.g. Africans) compared to those with small population sizes (e.g. Asians). These results imply that the substitution patterns vary significantly between populations. These findings could be explained by the effect of GC-biased gene conversion (gBGC), which favors the fixation of G/C over A/T variants in populations. In large population, gBGC causes high β. However, in small populations, genetic drift reduces the effect of gBGC resulting in reduced β. This was further confirmed by a positive relationship between N_e and β for homozygous variants.

Conclusions

Our results highlight the huge variation in the types of homozygous and high frequency polymorphisms between world populations. We observed the same pattern for deleterious variants, implying that the homozygous polymorphisms associated with recessive genetic diseases will be more enriched with G or C in populations with large N_e (e.g. Africans) than in populations with small N_e (e.g. Europeans).

Cell lineage inference from SNP and scRNA-Seq data

Several recent studies focus on the inference of developmental and response trajectories from single cell RNA-Seq (scRNA-Seq) data. A number of computational methods, often referred to as pseudo-time ordering, have been developed for this task. Recently, CRISPR has also been used to reconstruct lineage trees by inserting random mutations. However, both approaches suffer from drawbacks that limit their use. Here, we develop a method to detect significant, cell type specific, sequence mutations from scRNA-Seq data. We show that only a few mutations are enough for reconstructing good branching models. Integrating these mutations with expression data further improves the accuracy of the reconstructed models. As we show, the majority of mutations we identify are likely RNA editing events indicating that such information can be used to distinguish cell types.

Adaptation in structured populations and fuzzy boundaries between hard and soft sweeps

Selective sweeps, the genetic footprint of positive selection, have been extensively studied in the past decades, with dozens of methods developed to identify swept regions. However, these methods suffer from both false positive and false negative reports, and the candidates identified with different methods are often inconsistent with each other. We propose that a biological cause of this problem can be population subdivision, and a technical cause can be incomplete, or inaccurate, modeling of the dynamic process associated with sweeps. Here we used simulations to show how these effects interact and potentially cause bias. In particular, we show that sweeps maybe misclassified as either hard or soft, when the true time stage of a sweep and that implied, or pre-supposed, by the model do not match. We call this "temporal misclassification". Similarly, "spatial misclassification (softening)" can occur when hard sweeps, which are imported by migration into a new subpopulation, are falsely identified as soft. This can easily happen in case of local adaptation, i.e. when the sweeping allele is not under positive selection in the new subpopulation, and the underlying model assumes panmixis instead of substructure. The claim that most sweeps in the evolutionary history of humans were soft, may have to be reconsidered in the light of these findings.

Estimating the Genome-wide Mutation Rate with Three-Way Identity by Descent

The two primary methods for estimating the genome-wide mutation rate have been counting de novo mutations in parent-offspring trios and comparing sequence data between closely related species. With parent-offspring trio analysis it is difficult to control for genotype error, and resolution is limited because each trio provides information from only two meioses. Inter-species comparison is difficult to calibrate due to uncertainty in the number of meioses separating species, and it can be biased by selection and by changing mutation rates over time. An alternative class of approaches for estimating mutation rates that avoids these limitations is based on identity by descent (IBD) segments that arise from common ancestry within the past few thousand years. Existing IBD-based methods are limited to highly inbred samples, or lack robustness to genotype error and error in the estimated demographic history. We present an IBD-based method that uses sharing of IBD segments among sets of three individuals to estimate the mutation rate. Our method is applicable to accurately phased genotype data, such as parent-offspring trio data phased using Mendelian rules of inheritance. Unlike standard parent-offspring analysis, our method utilizes distant relationships and is robust to genotype error. We apply our method to data from 1,307 European-ancestry individuals in the Framingham Heart Study sequenced by the NHLBI TOPMed project. We obtain an estimate of 1.29 × 10^-8 mutations per base pair per meiosis with a 95% confidence interval of [1.02 × 10^-8, 1.56 × 10^-8].

Pedigree-based estimation of human mobile element retrotransposition rates

Germline mutation rates in humans have been estimated for a variety of mutation types, including single-nucleotide and large structural variants. Here, we directly measure the germline retrotransposition rate for the three active retrotransposon elements: L1, Alu, and SVA. We used three tools for calling mobile element insertions (MEIs) (MELT, RUFUS, and TranSurVeyor) on blood-derived whole-genome sequence (WGS) data from 599 CEPH individuals, comprising 33 three-generation pedigrees. We identified 26 de novo MEIs in 437 births. The retrotransposition rate estimates for Alu elements, one in 40 births, is roughly half the rate estimated using phylogenetic analyses, a difference in magnitude similar to that observed for single-nucleotide variants. The L1 retrotransposition rate is one in 63 births and is within range of previous estimates (1:20-1:200 births). The SVA retrotransposition rate, one in 63 births, is much higher than the previous estimate of one in 900 births. Our large, three-generation pedigrees allowed us to assess parent-of-origin effects and the timing of insertion events in either gametogenesis or early embryonic development. We find a statistically significant paternal bias in Alu retrotransposition. Our study represents the first in-depth analysis of the rate and dynamics of human retrotransposition from WGS data in three-generation human pedigrees.

Large, three-generation human families reveal post-zygotic mosaicism and variability in germline mutation accumulation

The number of de novo mutations (DNMs) found in an offspring's genome increases with both paternal and maternal age. But does the rate of mutation accumulation in human gametes differ across families? Using sequencing data from 33 large, three-generation CEPH families, we observed significant variability in parental age effects on DNM counts across families, ranging from 0.19 to 3.24 DNMs per year. Additionally, we found that ~3% of DNMs originated following primordial germ cell specification in a parent, and differed from non-mosaic germline DNMs in their mutational spectra. We also discovered that nearly 10% of candidate DNMs in the second generation were post-zygotic, and present in both somatic and germ cells; these gonosomal mutations occurred at equivalent frequencies on both parental haplotypes. Our results demonstrate that rates of germline mutation accumulation vary among families with similar ancestry, and confirm that post-zygotic mosaicism is a substantial source of human DNM.

Taking Systems Medicine to Heart

Systems medicine is a holistic approach to deciphering the complexity of human physiology in health and disease. In essence, a living body is constituted of networks of dynamically interacting units (molecules, cells, organs, etc) that underlie its collective functions. Declining resilience because of aging and other chronic environmental exposures drives the system to transition from a health state to a disease state; these transitions, triggered by acute perturbations or chronic disturbance, manifest as qualitative shifts in the interactions and dynamics of the disease-perturbed networks. Understanding health-to-disease transitions poses a high-dimensional nonlinear reconstruction problem that requires deep understanding of biology and innovation in study design, technology, and data analysis. With a focus on the principles of systems medicine, this Review discusses approaches for deciphering this biological complexity from a novel perspective, namely, understanding how disease-perturbed networks function; their study provides insights into fundamental disease mechanisms. The immediate goals for systems medicine are to identify early transitions to cardiovascular (and other chronic) diseases and to accelerate the translation of new preventive, diagnostic, or therapeutic targets into clinical practice, a critical step in the development of personalized, predictive, preventive, and participatory (P4) medicine.

Ensuring the Safety of Sunscreens, and Their Efficacy in Preventing Skin Cancers: Challenges and Controversies for Clinicians, Formulators, and Regulators

When people think about sun-protection or prevention of skin cancer, sunscreens readily come to mind. Sunscreen effectiveness is tested in vivo by the ability to prevent erythema of skin, yet testing methods vary between markets, and many sunscreens fail to achieve their claims. This article discusses the mechanism of action of sunscreens, Sun Protection Factor (SPF), safety concerns and the challenges for regulators. Many sunscreens that prevent erythema do not provide adequate protection as they contain anti-inflammatory agents; others have ingredients whose risks have not been fully evaluated. This article reviews the imperfect science behind sunscreens and points out the gaps in knowledge regarding safety, efficacy, public knowledge, and perception. Regulations vary between countries and only adds to the confusion. To truly prevent skin cancer, clinicians, formulators and regulators need to come together to research more and improve public education.

Family-Based Quantitative Trait Meta-Analysis Implicates Rare Noncoding Variants in DENND1A in Polycystic Ovary Syndrome

CONTEXT

Polycystic ovary syndrome (PCOS) is among the most common endocrine disorders of premenopausal women, affecting 5% to15% of this population depending on the diagnostic criteria applied. It is characterized by hyperandrogenism, ovulatory dysfunction, and polycystic ovarian morphology. PCOS is highly heritable, but only a small proportion of this heritability can be accounted for by the common genetic susceptibility variants identified to date.

OBJECTIVE

The objective of this study was to test whether rare genetic variants contribute to PCOS pathogenesis.

DESIGN, PATIENTS, AND METHODS

We performed whole-genome sequencing on DNA from 261 individuals from 62 families with one or more daughters with PCOS. We tested for associations of rare variants with PCOS and its concomitant hormonal traits using a quantitative trait meta-analysis.

RESULTS

We found rare variants in DENND1A (P = 5.31 × 10-5, adjusted P = 0.039) that were significantly associated with reproductive and metabolic traits in PCOS families.

CONCLUSIONS

Common variants in DENND1A have previously been associated with PCOS diagnosis in genome-wide association studies. Subsequent studies indicated that DENND1A is an important regulator of human ovarian androgen biosynthesis. Our findings provide additional evidence that DENND1A plays a central role in PCOS and suggest that rare noncoding variants contribute to disease pathogenesis.

Development of the variant calling algorithm, ADIScan, and its use to estimate discordant sequences between monozygotic twins

Calling variants from next-generation sequencing (NGS) data or discovering discordant sequences between two NGS data sets is challenging. We developed a computer algorithm, ADIScan1, to call variants by comparing the fractions of allelic reads in a tester to the universal reference genome. We then created ADIScan2 by modifying the algorithm to directly compare two sets of NGS data and predict discordant sequences between two testers. ADIScan1 detected >99.7% of variants called by GATK with an additional 724 393 SNVs. ADIScan2 identified ∼500 candidates of discordant sequences in each of two pairs of the monozygotic twins. About 200 of these candidates were included in the ∼2800 predicted by VarScan2. We verified 66 true discordant sequences among the candidates that ADIScan2 and VarScan2 exclusively predicted. ADIScan2 detected many discordant sequences overlooked by VarScan2 and Mutect, which specialize in detecting low frequency mutations in genetically heterogeneous cancerous tissues. Numbers of verified sequences alone were >5 times more than expected based on recently estimated mutation rates from whole genome sequences. Estimated post-zygotic mutation rates were 1.68 × 10⁻⁷ in this study. ADIScan1 and 2 would complement existing tools in screening causative mutations of diverse genetic diseases and comparing two sets of genome sequences, respectively.

Bending of DNA duplexes with mutation motifs

Mutations can be induced by environmental factors but also arise spontaneously during DNA replication or due to deamination of methylated cytosines at CpG dinucleotides. Sites where mutations occur with higher frequency than would be expected by chance are termed hotspots while sites that contain mutations rarely are termed coldspots. Mutations are permanently scanned and repaired by repair systems. Among them, the mismatch repair targets base pair mismatches, which are discriminated from canonical base pairs by probing altered elasticity of DNA. Using biased molecular dynamics simulations, we investigated the elasticity of coldspots and hotspots motifs detected in human genes associated with inherited disorders, and also of motifs with Czech population hotspots and de novo mutations. Main attention was paid to mutations leading to G/T and A+/C pairs. We observed that hotspots without CpG/CpHpG sequences are less flexible than coldspots, which indicates that flexible sequences are more effectively repaired. In contrary, hotspots with CpG/CpHpG sequences exhibited increased flexibility as coldspots. Their mutability is more likely related to spontaneous deamination of methylated cytosines leading to C > T mutations, which are primarily targeted by base excision repair. We corroborated conclusions based on computer simulations by measuring melting curves of hotspots and coldspots containing G/T mismatch.

PsyMuKB: An Integrative De Novo Variant Knowledge Base for Developmental Disorders

De novo variants (DNVs) are one of the most significant contributors to severe early-onset genetic disorders such as autism spectrum disorder, intellectual disability, and other developmental and neuropsychiatric (DNP) disorders. Presently, a plethora of DNVs have been identified using next-generation sequencing, and many efforts have been made to understand their impact at the gene level. However, there has been little exploration of the effects at the isoform level. The brain contains a high level of alternative splicing and regulation, and exhibits a more divergent splicing program than other tissues. Therefore, it is crucial to explore variants at the transcriptional regulation level to better interpret the mechanisms underlying DNP disorders. To facilitate a better usage and improve the isoform-level interpretation of variants, we developed NeuroPsychiatric Mutation Knowledge Base (PsyMuKB). It contains a comprehensive, carefully curated list of DNVs with transcriptional and translational annotations to enable identification of isoform-specific mutations. PsyMuKB allows a flexible search of genes or variants and provides both table-based descriptions and associated visualizations, such as expression, transcript genomic structures, protein interactions, and the mutation sites mapped on the protein structures. It also provides an easy-to-use web interface, allowing users to rapidly visualize the locations and characteristics of mutations and the expression patterns of the impacted genes and isoforms. PsyMuKB thus constitutes a valuable resource for identifying tissue-specific DNVs for further functional studies of related disorders. PsyMuKB is freely accessible at http://psymukb.net.

Methylwogonin exerts anticancer effects in A375 human malignant melanoma cells through apoptosis induction, DNA damage, cell invasion inhibition and downregulation of the mTOR/PI3K/Akt signalling pathway

INTRODUCTION

The main purpose of the present research was to study the anticancer effects of methylwogonin in A375 human malignant melanoma cells by evaluating its effects on apoptosis, DNA fragmentation, cancer cell invasion and the mTOR/PI3K/AKT signalling pathway.

MATERIAL AND METHODS

Effects on cell cytotoxicity were evaluated by MTT assay while a clonogenic assay determined the effects of methylwogonin on colony formation. Fluorescence microscopy evaluated apoptotic effects of methylwogonin in these cells using acridine orange/propidium iodide and Hoechst 33342 staining dyes. Gel electrophoresis evaluated the effects of methylwogonin on DNA fragmentation while the Matrigel invasion assay evaluated the effects of the drug on cancer cell invasion. Effects of methylwogonin on the mTOR/PI3K/AKT signalling pathway were evaluated by western blot assay.

RESULTS

Methylwogonin induces concentration-dependent as well as time-dependent growth inhibitory effects inducing significant cytotoxicity in these cancer cells. Methylwogonin led to dose-dependent inhibition of colony formation in A375 human malignant melanoma cells. The number of cell colonies decreased significantly as the methylwogonin dose increased from 0, 50, 150, to 300 μM. Methylwogonin treatment of cells at lower doses led to yellow fluorescence (early apoptosis), which changed to red/orange fluorescence, indicating late apoptosis at higher doses. Similar results were obtained using Hoechst 33342 staining, revealing that 50, 150 and 300 μM doses of methylwogonin led to significant morphological changes including chromatin condensation, fragmented nuclei and cellular shrinkage. DNA ladder formation was also observed, and this effect increased with increasing doses of methylwogonin. Methylwogonin also inhibited cancer cell invasion in a dose-dependent manner.

CONCLUSIONS

Different doses of methylwogonin led to concentration-dependent downregulation of phosphorylated PI3K, AKT and mTOR.

The Genomic Origins of Small Mitochondrial RNAs: Are They Transcribed by the Mitochondrial DNA or by Mitochondrial Pseudogenes within the Nucleus (NUMTs)?

Several studies have linked mitochondrial genetic variation to phenotypic modifications; albeit the identity of the mitochondrial polymorphisms involved remains elusive. The search for these polymorphisms led to the discovery of small noncoding RNAs, which appear to be transcribed by the mitochondrial DNA ("small mitochondrial RNAs"). This contention is, however, controversial because the nuclear genome of most animals harbors mitochondrial pseudogenes (NUMTs) of identical sequence to regions of mtDNA, which could alternatively represent the source of these RNAs. To discern the likely contributions of the mitochondrial and nuclear genome to transcribing these small mitochondrial RNAs, we leverage data from six vertebrate species exhibiting markedly different levels of NUMT sequence. We explore whether abundances of small mitochondrial RNAs are associated with levels of NUMT sequence across species, or differences in tissue-specific mtDNA content within species. Evidence for the former would support the hypothesis these RNAs are primarily transcribed by NUMT sequence, whereas evidence for the latter would provide strong evidence for the counter hypothesis that these RNAs are transcribed directly by the mtDNA. No association exists between the abundance of small mitochondrial RNAs and NUMT levels across species. Moreover, a sizable proportion of transcripts map exclusively to the mtDNA sequence, even in species with highest NUMT levels. Conversely, tissue-specific abundances of small mitochondrial RNAs are strongly associated with the mtDNA content. These results support the hypothesis that small mitochondrial RNAs are primarily transcribed by the mitochondrial genome and that this capacity is conserved across Amniota and, most likely, across most metazoan lineages.

Exome-wide assessment of the functional impact and pathogenicity of multinucleotide mutations

Approximately 2% of de novo single-nucleotide variants (SNVs) appear as part of clustered mutations that create multinucleotide variants (MNVs). MNVs are an important source of genomic variability as they are more likely to alter an encoded protein than a SNV, which has important implications in disease as well as evolution. Previous studies of MNVs have focused on their mutational origins and have not systematically evaluated their functional impact and contribution to disease. We identified 69,940 MNVs and 91 de novo MNVs in 6688 exome-sequenced parent–offspring trios from the Deciphering Developmental Disorders Study comprising families with severe developmental disorders. We replicated the previously described MNV mutational signatures associated with DNA polymerase zeta, an error-prone translesion polymerase, and the APOBEC family of DNA deaminases. We estimate the simultaneous MNV germline mutation rate to be 1.78 × 10⁻¹⁰ mutations per base pair per generation. We found that most MNVs within a single codon create a missense change that could not have been created by a SNV. MNV-induced missense changes were, on average, more physicochemically divergent, were more depleted in highly constrained genes (pLI ≥ 0.9), and were under stronger purifying selection compared with SNV-induced missense changes. We found that de novo MNVs were significantly enriched in genes previously associated with developmental disorders in affected children. This shows that MNVs can be more damaging than SNVs even when both induce missense changes, and are an important variant type to consider in relation to human disease.

Heterogeneity of primordial germ cells

Primordial germ cells (PGCs) must complete a complex and dynamic developmental program during embryogenesis to establish the germline. This process is highly conserved and involves a diverse array of tasks required of PGCs, including migration, survival, sex differentiation, and extensive epigenetic reprogramming. A common theme across many organisms is that PGC success is heterogeneous: only a portion of all PGCs complete all these steps while many other PGCs are eliminated from further germline contribution. The differences that distinguish successful PGCs as a population are not well understood. Here, we examine variation that exists in PGCs as they navigate the many stages of this developmental journey. We explore potential sources of PGC heterogeneity and their potential implications in affecting germ cell behaviors. Lastly, we discuss the potential for PGC development to function as a multistage selection process that assesses heterogeneity in PGCs to refine germline quality.

Family history of cancer and risk of paediatric and young adult's testicular cancer: A Norwegian cohort study

Background

The aim of this study was to examine the association of a family history of cancer with the risk of testicular cancer in young adults.

Methods

This is a prospective cohort study including 1,974,287 males born 1951–2015, of whom 2686 were diagnosed with TC before the age of 30.

Results

A history of TC in male relatives was significantly associated with a diagnosis of TC among children and young adults, including brothers (6.3-fold), sons (4.7-fold), fathers (4.4-fold), paternal uncles (2.0-fold) and maternal uncles (1.9-fold). Individuals with a father diagnosed with a carcinoma or sarcoma showed an elevated risk (1.1-fold and 1.8-fold, respectively). A family history of mesothelioma was positively associated with a risk of TC [(father (2.8-fold), mother (4.6-fold) and maternal uncles and aunt (4.4-fold)]. Elevated risks were also observed when siblings were diagnosed with malignant melanoma (1.4-fold). The risk of TC was also increased when fathers (11.1-fold), paternal (4.9-fold) and maternal uncles and aunts (4.6-fold) were diagnosed with malignant neuroepithelial-tumours.

Conclusion

We found an increased risk of TC among children and young adults with a family history of TC, carcinoma, mesothelioma, sarcoma, malignant melanoma and malignant neuroepithelial tumours. Hereditary cancer syndromes might underlie some of the associations reported in this study.

Mendelian Inconsistent Signatures from 1314 Ancestrally Diverse Family Trios Distinguish Biological Variation from Sequencing Error

Next-generation sequencing enables advances in the clinical application of genomics by providing high-throughput detection of genomic variation. However, next-generation sequencing technologies, especially whole-genome sequencing (WGS), are often associated with a high false-positive rate. Trio-based WGS can contribute significantly towards improved quality control methods. Mendelian-inconsistent calls (MIC) in parent–child trios are commonly attributed to erroneous sequencing calls, as the true de novo mutation rate is extremely low compared with MIC incidence. Here, we analyzed WGS data from 1314 mother, father, and child trios across ethnically diverse populations with the goal of characterizing MIC. Genotype calls in a trio can be used to assign different signatures to MIC. MIC occur more frequently within repeats but show varying distribution and error mechanisms across repeat types. MIC are enriched within poly-A/T runs in short interspersed nuclear elements. Alignability scores, allele balance, and relative parental read depth vary among MIC signatures and these differences should be considered when designing filters for MIC reduction. MIC cluster in germline deletions and these MIC also segregate with population. Our results provide a basis for making decisions on how each MIC type should be evaluated before discarding them as errors or including them in alternative applications. With the reduction of sequencing cost, family trio whole genome and exome analysis are being performed more routinely in clinical practice. We provide a reference that can be used for annotating MIC with their frequencies in a larger population to aid in the filtering of candidate de novo mutations.

Genetic predisposition to colorectal cancer: syndromes, genes, classification of genetic variants and implications for precision medicine

This article reviews genes and syndromes associated with predisposition to colorectal cancer (CRC), with an overview of gene variant classification. We include updates on the application of preventive and therapeutic measures, focusing on the use of non-steroidal anti-inflammatory drugs (NSAIDs) and immunotherapy. Germline pathogenic variants in genes conferring high or moderate risk to cancer are detected in 6-10% of all CRCs and 20% of those diagnosed before age 50. CRC syndromes can be subdivided into nonpolyposis and polyposis entities, the most common of which are Lynch syndrome and familial adenomatous polyposis, respectively. In addition to known and novel genes associated with highly penetrant CRC risk, identification of pathogenic germline variants in genes associated with moderate-penetrance cancer risk and/or hereditary cancer syndromes not traditionally linked to CRC may have an impact on genetic testing, counseling, and surveillance. The use of multigene panels in genetic testing has exposed challenges in the classification of variants of uncertain significance. We provide an overview of the main classification systems and strategies for improving these. Finally, we highlight approaches for integrating chemoprevention in the care of individuals with genetic predisposition to CRC and use of targeted agents and immunotherapy for treatment of mismatch repair-deficient and hypermutant tumors. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Estimating carrier frequencies of newborn screening disorders using a whole-genome reference panel of 3552 Japanese individuals

Incidence rates of Mendelian diseases vary among ethnic groups, and frequencies of variant types of causative genes also vary among human populations. In this study, we examined to what extent we can predict population frequencies of recessive disorders from genomic data, and explored better strategies for variant interpretation and classification. We used a whole-genome reference panel from 3552 general Japanese individuals constructed by the Tohoku Medical Megabank Organization (ToMMo). Focusing on 32 genes for 17 congenital metabolic disorders included in newborn screening (NBS) in Japan, we identified reported and predicted pathogenic variants through variant annotation, interpretation, and multiple ways of classifications. The estimated carrier frequencies were compared with those from the Japanese NBS data based on 1,949,987 newborns from a previous study. The estimated carrier frequency based on genomic data with a recent guideline of variant interpretation for the PAH gene, in which defects cause hyperphenylalaninemia (HPA) and phenylketonuria (PKU), provided a closer estimate to that by the observed incidence than the other methods. In contrast, the estimated carrier frequencies for SLC25A13, which causes citrin deficiency, were much higher compared with the incidence rate. The results varied greatly among the 11 NBS diseases with single responsible genes; the possible reasons for departures from the carrier frequencies by reported incidence rates were discussed. Of note, (1) the number of pathogenic variants increases by including additional lines of evidence, (2) common variants with mild effects also contribute to the actual frequency of patients, and (3) penetrance of each variant remains unclear.

Whole Exome Sequencing Identifies a Novel Predisposing Gene, MAPKAP1, for Familial Mixed Mood Disorder

Background: Mood disorder is ranked seventh among the worldwide causes of non-fatal disease burden and is generally believed to be a heritable disease. However, there is still a substantial portion of the heritability yet to be discovered, despite the success of genome-wide association studies (GWAS) for mood disorder. A proportion of the missing heritability may be accounted for by rare coding variants segregating in families enriched with mood disorder.

Methods: To identify novel variants segregating with mood disorder, we performed whole-exome sequencing on genomic DNA for a multigenerational family with nine members affected with mood disorder. We prioritized potential causal variants within the family based on segregation with mood disorder, predicted functional effects, and prevalence in human populations. In addition, for the top-ranked candidate variant, we conducted validation in vivo to explore the pathogenesis of mood disorder.

Results: We identified and ranked 26 candidate variants based on their segregation pattern and functional annotations. The top-ranked variant, rs78809014, is located in intron 7 of the MAPKAP1 gene. The expression levels of MAPKAP1 in peripheral blood of both major depression disorder (MDD) patients and depressive-like mice ventral dentate gyrus were significantly higher than that in the corresponding controls. In addition, the expression level of MAPKAP1 were correlated with antidepressant response.

Conclusions: Although the exact mechanisms in the family remain to be elucidated, our data strongly indicate a probable role of the variant, rs78809014, in the regulatory process of the expression of MAPKAP1 and thus in the development of mood disorder in familial mood disorder.

Empirical evaluation of variant calling accuracy using ultra-deep whole-genome sequencing data

In the design of whole-genome sequencing (WGS) studies, sequencing depth is a crucial parameter to define variant calling accuracy and study cost, with no standard recommendations having been established. We empirically evaluated the variant calling accuracy of the WGS pipeline using ultra-deep WGS data (approximately 410×). We randomly sampled sequence reads and constructed a series of simulation WGS datasets with a variety of gradual depths (n = 54; from 0.05× to 410×). Next, we evaluated the genotype concordances of the WGS data with those in the SNP microarray data or the WGS data using all the sequence reads. In addition, we assessed the accuracy of HLA allele genotyping using the WGS data with multiple software tools (PHLAT, HLA-VBseq, HLA-HD, and SNP2HLA). The WGS data with higher depths showed higher concordance rates, and >13.7× depth achieved as high as >99% of concordance. Comparisons with the WGS data using all the sequence reads showed that SNVs achieved >95% of concordance at 17.6× depth, whereas indels showed only 60% concordance. For the accuracy of HLA allele genotyping using the WGS data, 13.7× depth showed sufficient accuracy while performance heterogeneity among the software tools was observed (the highest concordance of 96.9% was observed with HLA-HD). Improvement in HLA genotyping accuracy by further increasing the depths was limited. These results suggest a medium degree of the WGS depth setting (approximately 15×) to achieve both accurate SNV calling and cost-effectiveness, whereas relatively higher depths are required for accurate indel calling.

A suite of automated sequence analyses reduces the number of candidate deleterious variants and reveals a difference between probands and unaffected siblings

PURPOSE

Develop an automated exome analysis workflow that can produce a very small number of candidate variants yet still detect different numbers of deleterious variants between probands and unaffected siblings.

METHODS

Ninety-seven outbred nuclear families from the Undiagnosed Diseases Program/Network included single probands and the corresponding unaffected sibling(s). Single-nucleotide polymorphism (SNP) chip and exome analyses were performed on all, with proband and unaffected sibling considered independently as the target. The total burden of candidate genetic variants was summed for probands and siblings over all considered disease models.

RESULTS

Exome analysis workflow include automated programs for ethnicity-matched genotype calling, salvage pathway for Mendelian inconsistency, compound heterozygous recessive detection, BAM file regional curation, population frequency filtering, pedigree-aware BAM file noise evaluation, and exon deletion filtration. This workflow relied heavily on BAM file analysis. A greater average pathogenic variant number was found compared with unaffected siblings. This was significant (p < 0.05) when using published recommended thresholds, and implies that causal variants are retained in many probands' lists.

CONCLUSION

Using Mendelian and non-Mendelian models, this agnostic exome analysis shows a difference between a small group of probands and their unaffected siblings. This workflow produces candidate lists small enough to pursue with laboratory validation.

A rigorous measure of genome-wide genetic shuffling that takes into account crossover positions and Mendel's second law

Comparative studies in evolutionary genetics rely critically on evaluation of the total amount of genetic shuffling that occurs during gamete production. Such studies have been hampered by the absence of a direct measure of this quantity. Existing measures consider crossing-over by simply counting the average number of crossovers per meiosis. This is qualitatively inadequate, because the positions of crossovers along a chromosome are also critical: a crossover toward the middle of a chromosome causes more shuffling than a crossover toward the tip. Moreover, traditional measures fail to consider shuffling from independent assortment of homologous chromosomes (Mendel's second law). Here, we present a rigorous measure of genome-wide shuffling that does not suffer from these limitations. We define the parameter [Formula: see text] as the probability that the alleles at two randomly chosen loci are shuffled during gamete production. This measure can be decomposed into separate contributions from crossover number and position and from independent assortment. Intrinsic implications of this metric include the fact that [Formula: see text] is larger when crossovers are more evenly spaced, which suggests a selective advantage of crossover interference. Utilization of [Formula: see text] is enabled by powerful emergent methods for determining crossover positions either cytologically or by DNA sequencing. Application of our analysis to such data from human male and female reveals that (i) [Formula: see text] in humans is close to its maximum possible value of 1/2 and that (ii) this high level of shuffling is due almost entirely to independent assortment, the contribution of which is ∼30 times greater than that of crossovers.

DCA for genome-wide epistasis analysis: the statistical genetics perspective

Direct coupling analysis (DCA) is a now widely used method to leverage statistical information from many similar biological systems to draw meaningful conclusions on each system separately. DCA has been applied with great success to sequences of homologous proteins, and also more recently to whole-genome population-wide sequencing data. We here argue that the use of DCA on the genome scale is contingent on fundamental issues of population genetics. DCA can be expected to yield meaningful results when a population is in the quasi-linkage equilibrium (QLE) phase studied by Kimura and others, but not, for instance, in a phase of clonal competition. We discuss how the exponential (Potts model) distributions emerge in QLE, and compare couplings to correlations obtained in a study of about 3000 genomes of the human pathogen Streptococcus pneumoniae.

Prenatal diagnosis for de novo mutations: Experience from a tertiary center over a 10-year period

Background

This study summarizes the results of prenatal diagnosis due to a history of de novo mutation in a previous pregnancy, in a tertiary center in Israel, over a 10‐year period.

Methods

We sorted all cases of de novo mutations from a pool of 2,260 pregnancies for which prenatal molecular diagnosis was applied, between the years 2008 and 2017. We identified 122 molecular prenatal diagnosis performed for de novo mutations, in 90 women.

Results

While the total number of yearly prenatal diagnoses stayed stable, a linear increase was detected in the number of cases for which the procedure was done due to a previous de novo mutation: from 3 cases in 2008 to 24 cases in 2017. The most common diseases were Rett syndrome (19), neurofibromatosis Type‐1 (12) and Tuberous sclerosis (5). Recurrence occurred in 3 of the 90 women (3.3%) and hotspot mutations were identified in two genes accounting for 11 cases. We did not find a difference in paternal age at first occurrence of the de novo mutation between the study group and the control group.

Conclusion

The large increase in the annual number of prenatal diagnoses performed due to a previous pregnancy with a de novo mutation reflects the growing understanding regarding the role of these mutations in the pathogenesis of genetic diseases.

Multiplex assay for multiomics advances in personalized-precision medicine

Building the future of precision medicine is the main focus in cancer domain. Clinical trials are moving toward an array of studies that are more adapted to precision medicine. In this domain, there is an enhanced need for biomarkers, monitoring devices, and data-analysis methods. Omics profiling using whole genome, epigenome, transcriptome, proteome, and metabolome can offer detailed information of the human body in an integrative manner. Omes profiles reflect more accurately real-time physiological status. Personalized omics analyses both disease as a whole and the main disease processes, for a better understanding of the individualized health. Through this, multi-omic approaches for health monitoring, preventative medicine, and personalized treatment can be targeted simultaneously and can lead clinicians to have a comprehensive view on the diseasome.

Phenotype-Driven Virtual Panel Is an Effective Method to Analyze WES Data of Neurological Disease

Objective: Whole Exome Sequencing (WES) is an effective diagnostic method for complicated and multi-system involved rare diseases. However, annotation and analysis of the WES result, especially for single case analysis still remain a challenge. Here, we introduce a method called phenotype-driven designing "virtual panel" to simplify the procedure and assess the diagnostic rate of this method. Methods: WES was performed in samples of 30 patients, core phenotypes of probands were then extracted and inputted into an in-house software, "Mingjian" to calculate and generate associated gene list of a virtual panel. Mingjian is a self-updating genetic disease computer supportive diagnostic system that based on the databases of HPO, OMIM, HGMD. The virtual panel that generated by Mingjian system was then used to filter and annotate candidate mutations. Sanger sequencing and co-segregation analysis among the family were then used to confirm the filtered mutants. Result: We first used phenotype-driven designing "virtual panel" to analyze the WES data of a patient whose core phenotypes are ataxia, seizures, esotropia, puberty and gonadal disorders, and global developmental delay. Two mutations, c.430T > C and c.640G > C in PMM2 were identified by this method. This result was also confirmed by Sanger sequencing among the family. The same analysing method was then used in the annotation of WES data of other 29 neurological rare disease patients. The diagnostic rate was 65.52%, which is significantly higher than the diagnostic rate before. Conclusion: Phenotype-driven designing virtual panel could achieve low-cost individualized analysis. This method may decrease the time-cost of annotation, increase the diagnostic efficiency and the diagnostic rate.

Introduction to Bioinformatics

How the scientific community looks at molecular biology today is very different from that 50 years ago. During this time technological developments have led to many significant findings that have shook one of the most important foundations of molecular biology: the central dogma. In this chapter, we will mention how these changes occurred and gave birth to a very important field of today's science, bioinformatics. We will also mention briefly the newest topics of molecular biology regarding bioinformatics technologies and skills.

Quantification of somatic mutation flow across individual cell division events by lineage sequencing

Mutation data reveal the dynamic equilibrium between DNA damage and repair processes in cells and are indispensable to the understanding of age-related diseases, tumor evolution, and the acquisition of drug resistance. However, available genome-wide methods have a limited ability to resolve rare somatic variants and the relationships between these variants. Here, we present lineage sequencing, a new genome sequencing approach that enables somatic event reconstruction by providing quality somatic mutation call sets with resolution as high as the single-cell level in subject lineages. Lineage sequencing entails sampling single cells from a population and sequencing subclonal sample sets derived from these cells such that knowledge of relationships among the cells can be used to jointly call variants across the sample set. This approach integrates data from multiple sequence libraries to support each variant and precisely assigns mutations to lineage segments. We applied lineage sequencing to a human colon cancer cell line with a DNA polymerase epsilon (POLE) proofreading deficiency (HT115) and a human retinal epithelial cell line immortalized by constitutive telomerase expression (RPE1). Cells were cultured under continuous observation to link observed single-cell phenotypes with single-cell mutation data. The high sensitivity, specificity, and resolution of the data provide a unique opportunity for quantitative analysis of variation in mutation rate, spectrum, and correlations among variants. Our data show that mutations arrive with nonuniform probability across sublineages and that DNA lesion dynamics may cause strong correlations between certain mutations.

Appropriate Assignment of Fossil Calibration Information Minimizes the Difference between Phylogenetic and Pedigree Mutation Rates in Humans

Studies that measured mutation rates in human populations using pedigrees have reported values that differ significantly from rates estimated from the phylogenetic comparison of humans and chimpanzees. Consequently, exchanges between mutation rate values across different timescales lead to conflicting divergence time estimates. It has been argued that this variation of mutation rate estimates across hominoid evolution is in part caused by incorrect assignment of calibration information to the mean coalescent time among loci, instead of the true genetic isolation (speciation) time between humans and chimpanzees. In this study, we investigated the feasibility of estimating the human pedigree mutation rate using phylogenetic data from the genomes of great apes. We found that, when calibration information was correctly assigned to the human⁻chimpanzee speciation time (and not to the coalescent time), estimates of phylogenetic mutation rates were statistically equivalent to the estimates previously reported using studies of human pedigrees. We conclude that, within the range of biologically realistic ancestral generation times, part of the difference between whole-genome phylogenetic and pedigree mutation rates is due to inappropriate assignment of fossil calibration information to the mean coalescent time instead of the speciation time. Although our results focus on the human⁻chimpanzee divergence, our findings are general, and relevant to the inference of the timescale of the tree of life.

High prevalence of focal and multi-focal somatic genetic variants in the human brain

Somatic mutations during stem cell division are responsible for several cancers. In principle, a similar process could occur during the intense cell proliferation accompanying human brain development, leading to the accumulation of regionally distributed foci of mutations. Using dual platform >5000-fold depth sequencing of 102 genes in 173 adult human brain samples, we detect and validate somatic mutations in 27 of 54 brains. Using a mathematical model of neurodevelopment and approximate Bayesian inference, we predict that macroscopic islands of pathologically mutated neurons are likely to be common in the general population. The detected mutation spectrum also includes DNMT3A and TET2 which are likely to have originated from blood cell lineages. Together, these findings establish developmental mutagenesis as a potential mechanism for neurodegenerative disorders, and provide a novel mechanism for the regional onset and focal pathology in sporadic cases.

Development of sequence-based markers for seed protein content in pigeonpea

Pigeonpea is an important source of dietary protein to over a billion people globally, but genetic enhancement of seed protein content (SPC) in the crop has received limited attention for a long time. Use of genomics-assisted breeding would facilitate accelerating genetic gain for SPC. However, neither genetic markers nor genes associated with this important trait have been identified in this crop. Therefore, the present study exploited whole genome re-sequencing (WGRS) data of four pigeonpea genotypes (~ 12X coverage) to identify sequence-based markers and associated candidate genes for SPC. By combining a common variant filtering strategy on available WGRS data with knowledge of gene functions in relation to SPC, 108 sequence variants from 57 genes were identified. These genes were assigned to 19 GO molecular function categories with 56% belonging to only two categories. Furthermore, Sanger sequencing confirmed presence of 75.4% of the variants in 37 genes. Out of 30 sequence variants converted into CAPS/dCAPS markers, 17 showed high level of polymorphism between low and high SPC genotypes. Assay of 16 of the polymorphic CAPS/dCAPS markers on an F₂ population of the cross ICP 5529 (high SPC) × ICP 11605 (low SPC), resulted in four of the CAPS/dCAPS markers significantly (P < 0.05) co-segregated with SPC. In summary, four markers derived from mutations in four genes will be useful for enhancing/regulating SPC in pigeonpea crop improvement programs.