Gene discovery informatics toolkit defines candidate genes for unexplained infertility and prenatal or infantile mortality

Lethal phenotypes in Mendelian disorders

PURPOSE

Existing resources that characterize the essentiality status of genes are based on either proliferation assessment in human cell lines, viability evaluation in mouse knockouts, or constraint metrics derived from human population sequencing studies. Several repositories document phenotypic annotations for rare disorders; however, there is a lack of comprehensive reporting on lethal phenotypes.

METHODS

We queried Online Mendelian Inheritance in Man for terms related to lethality and classified all Mendelian genes according to the earliest age of death recorded for the associated disorders, from prenatal death to no reports of premature death. We characterized the genes across these lethality categories, examined the evidence on viability from mouse models and explored how this information could be used for novel gene discovery.

RESULTS

We developed the Lethal Phenotypes Portal to showcase this curated catalog of human essential genes. Differences in the mode of inheritance, physiological systems affected, and disease class were found for genes in different lethality categories, as well as discrepancies between the lethal phenotypes observed in mouse and human.

CONCLUSION

We anticipate that this resource will aid clinicians in the diagnosis of early lethal conditions and assist researchers in investigating the properties that make these genes essential for human development.

Computational identification of disease models through cross-species phenotype comparison

The use of standardised phenotyping screens to identify abnormal phenotypes in mouse knockouts, together with the use of ontologies to describe such phenotypic features, allows the implementation of an automated and unbiased pipeline to identify new models of disease by performing phenotype comparisons across species. Using data from the International Mouse Phenotyping Consortium (IMPC), approximately half of mouse mutants are able to mimic, at least partially, the human ortholog disease phenotypes as computed by the PhenoDigm algorithm. We found the number of phenotypic abnormalities in the mouse and the corresponding Mendelian disorder, the pleiotropy and severity of the disease, and the viability and zygosity status of the mouse knockout to be associated with the ability of mouse models to recapitulate the human disorder. An analysis of the IMPC impact on disease gene discovery through a publication-tracking system revealed that the resource has been implicated in at least 109 validated rare disease-gene associations over the last decade.

Improving prenatal diagnosis through standards and aggregation

Advances in sequencing and imaging technologies enable enhanced assessment in the prenatal space, with a goal to diagnose and predict the natural history of disease, to direct targeted therapies, and to implement clinical management, including transfer of care, election of supportive care, and selection of surgical interventions. The current lack of standardization and aggregation stymies variant interpretation and gene discovery, which hinders the provision of prenatal precision medicine, leaving clinicians and patients without an accurate diagnosis. With large amounts of data generated, it is imperative to establish standards for data collection, processing, and aggregation. Aggregated and homogeneously processed genetic and phenotypic data permits dissection of the genomic architecture of prenatal presentations of disease and provides a dataset on which data analysis algorithms can be tuned to the prenatal space. Here we discuss the importance of generating aggregate data sets and how the prenatal space is driving the development of interoperable standards and phenotype-driven tools.

Miscarriage risk assessment: a bioinformatic approach to identifying candidate lethal genes and variants

PURPOSE

Miscarriage, often resulting from a variety of genetic factors, is a common pregnancy outcome. Preconception genetic carrier screening (PGCS) identifies at-risk partners for newborn genetic disorders; however, PGCS panels currently lack miscarriage-related genes. In this study, we evaluated the potential impact of both known and candidate genes on prenatal lethality and the effectiveness of PGCS in diverse populations.

METHODS

We analyzed 125,748 human exome sequences and mouse and human gene function databases. Our goals were to identify genes crucial for human fetal survival (lethal genes), to find variants not present in a homozygous state in healthy humans, and to estimate carrier rates of known and candidate lethal genes in various populations and ethnic groups.

RESULTS

This study identified 138 genes in which heterozygous lethal variants are present in the general population with a frequency of 0.5% or greater. Screening for these 138 genes could identify 4.6% (in the Finnish population) to 39.8% (in the East Asian population) of couples at risk of miscarriage. This explains the cause of pregnancy loss in approximately 1.1-10% of cases affected by biallelic lethal variants.

CONCLUSION

This study has identified a set of genes and variants potentially associated with lethality across different ethnic backgrounds. The variation of these genes across ethnic groups underscores the need for a comprehensive, pan-ethnic PGCS panel that includes genes related to miscarriage.

Lethal phenotypes in Mendelian disorders

Essential genes are those whose function is required for cell proliferation and/or organism survival. A gene's intolerance to loss-of-function can be allocated within a spectrum, as opposed to being considered a binary feature, since this function might be essential at different stages of development, genetic backgrounds or other contexts. Existing resources that collect and characterise the essentiality status of genes are based on either proliferation assessment in human cell lines, embryonic and postnatal viability evaluation in different model organisms, and gene metrics such as intolerance to variation scores derived from human population sequencing studies. There are also several repositories available that document phenotypic annotations for rare disorders in humans such as the Online Mendelian Inheritance in Man (OMIM) and the Human Phenotype Ontology (HPO) knowledgebases. This raises the prospect of being able to use clinical data, including lethality as the most severe phenotypic manifestation, to further our characterisation of gene essentiality. Here we queried OMIM for terms related to lethality and classified all Mendelian genes into categories, according to the earliest age of death recorded for the associated disorders, from prenatal death to no reports of premature death. To showcase this curated catalogue of human essential genes, we developed the Lethal Phenotypes Portal (https://lethalphenotypes.research.its.qmul.ac.uk), where we also explore the relationships between these lethality categories, constraint metrics and viability in cell lines and mouse. Further analysis of the genes in these categories reveals differences in the mode of inheritance of the associated disorders, physiological systems affected and disease class. We highlight how the phenotypic similarity between genes in the same lethality category combined with gene family/group information can be used for novel disease gene discovery. Finally, we explore the overlaps and discrepancies between the lethal phenotypes observed in mouse and human and discuss potential explanations that include differences in transcriptional regulation, functional compensation and molecular disease mechanisms. We anticipate that this resource will aid clinicians in the diagnosis of early lethal conditions and assist researchers in investigating the properties that make these genes essential for human development.

Biallelic ATP2B1 variants as a likely cause of a novel neurodevelopmental malformation syndrome with primary hypoparathyroidism

ATP2B1 encodes plasma membrane calcium-transporting-ATPase1 and plays an essential role in maintaining intracellular calcium homeostasis that regulates diverse signaling pathways. Heterozygous de novo missense and truncating ATP2B1 variants are associated with a neurodevelopmental phenotype of variable expressivity. We describe a proband with distinctive craniofacial gestalt, Pierre-Robin sequence, neurodevelopmental and growth deficit, periventricular heterotopia, brachymesophalangy, cutaneous syndactyly, and persistent hypocalcemia from primary hypoparathyroidism. Proband-parent trio exome sequencing identified compound heterozygous ATP2B1 variants: a maternally inherited splice-site (c.3060+2 T > G) and paternally inherited missense c.2938 G > T; p.(Val980Leu). Reverse-transcription-PCR on the proband's fibroblast-derived mRNA showed aberrantly spliced ATP2B1 transcripts targeted for nonsense-mediated decay. All correctly-spliced ATP2B1 mRNA encoding p.(Val980Leu) functionally causes decreased cellular Ca2+ extrusion. Immunoblotting showed reduced fibroblast ATP2B1. We conclude that biallelic ATP2B1 variants are the likely cause of the proband's phenotype, strengthening the association of ATP2B1 as a neurodevelopmental gene and expanding the phenotypic characterization of a biallelic loss-of-function genotype.

Essential genes: a cross-species perspective

Protein coding genes exhibit different degrees of intolerance to loss-of-function variation. The most intolerant genes, whose function is essential for cell or/and organism survival, inform on fundamental biological processes related to cell proliferation and organism development and provide a window on the molecular mechanisms of human disease. Here we present a brief overview of the resources and knowledge gathered around gene essentiality, from cancer cell lines to model organisms to human development. We outline the implications of using different sources of evidence and definitions to determine which genes are essential and highlight how information on the essentiality status of a gene can inform novel disease gene discovery and therapeutic target identification.

Why do humans need thrombospondin-1?

Matricellular proteins comprise several families of secreted proteins that function in higher animals at the interface between cells and their surrounding extracellular matrix. Targeted gene disruptions that result in loss of viability in mice have revealed critical roles for several matricellular proteins in murine embryonic development, including two members of the cellular communication network (CCN) gene family. In contrast, mice lacking single or multiple members of the thrombospondin (THBS) gene family remain viable and fertile. The frequency of loss of function mutants, identified using human deep exome sequencing data, provided evidence that some of the essential genes in mice, including Ccn1, are also essential genes in humans. However, a deficit in loss of function mutants in humans indicated that THBS1 is also highly loss-intolerant. In addition to roles in embryonic development or adult reproduction, genes may be loss-intolerant in humans because their function is needed to survive environmental stresses that are encountered between birth and reproduction. Laboratory mice live in a protected environment that lacks the exposures to pathogens and injury that humans routinely face. However, subjecting Thbs1-/- mice to defined stresses has provided valuable insights into functions of thrombospondin-1 that could account for the loss-intolerance of THBS1 in humans. Stress response models using transgenic mice have identified protective functions of thrombospondin-1 in the cardiovascular system (red) and immune defenses (blue) that could account for its intolerance to loss of function mutants in humans.

Deficit of homozygosity among 1.52 million individuals and genetic causes of recessive lethality

Genotypes causing pregnancy loss and perinatal mortality are depleted among living individuals and are therefore difficult to find. To explore genetic causes of recessive lethality, we searched for sequence variants with deficit of homozygosity among 1.52 million individuals from six European populations. In this study, we identified 25 genes harboring protein-altering sequence variants with a strong deficit of homozygosity (10% or less of predicted homozygotes). Sequence variants in 12 of the genes cause Mendelian disease under a recessive mode of inheritance, two under a dominant mode, but variants in the remaining 11 have not been reported to cause disease. Sequence variants with a strong deficit of homozygosity are over-represented among genes essential for growth of human cell lines and genes orthologous to mouse genes known to affect viability. The function of these genes gives insight into the genetics of intrauterine lethality. We also identified 1077 genes with homozygous predicted loss-of-function genotypes not previously described, bringing the total set of genes completely knocked out in humans to 4785.

Preconception Genetic Carrier Screening for Miscarriage Risk Assessment: A Bioinformatic Approach to Identifying Candidate Lethal Genes and Variants

Purpose

Miscarriage, due to genetically heterogeneous etiology, is a common outcome of pregnancy. Preconception genetic carrier screening (PGCS) identifies at-risk partners for newborn genetic disorders; however, PGCS panels currently lack miscarriage-related genes. Here we assessed the theoretical impact of known and candidate genes on prenatal lethality and the PGCS among diverse populations.

Methods

Human exome sequencing and mouse gene function databases were analyzed to define genes essential for human fetal survival (lethal genes), identify variants that are absent in a homozygous state in healthy human population, and to estimate carrier rates for known and candidate lethal genes.

Results

Among 138 genes, potential lethal variants are present in the general population with a frequency of 0.5% or greater. Preconception screening for these 138 genes would identify from 4.6% (Finnish population) to 39.8% (East Asian population) of couples that are at-risk for miscarriage, explaining a cause for pregnancy loss for ∼1.1-10% of conceptions affected by biallelic lethal variants.

Conclusion

This study identified a set of genes and variants potentially associated with lethality across different ethnic backgrounds. The diversity of these genes amongst the various ethnic groups highlights the importance of designing a pan-ethnic PGCS panel comprising miscarriage-related genes.

Mendelian gene identification through mouse embryo viability screening

BACKGROUND

The diagnostic rate of Mendelian disorders in sequencing studies continues to increase, along with the pace of novel disease gene discovery. However, variant interpretation in novel genes not currently associated with disease is particularly challenging and strategies combining gene functional evidence with approaches that evaluate the phenotypic similarities between patients and model organisms have proven successful. A full spectrum of intolerance to loss-of-function variation has been previously described, providing evidence that gene essentiality should not be considered as a simple and fixed binary property.

METHODS

Here we further dissected this spectrum by assessing the embryonic stage at which homozygous loss-of-function results in lethality in mice from the International Mouse Phenotyping Consortium, classifying the set of lethal genes into one of three windows of lethality: early, mid, or late gestation lethal. We studied the correlation between these windows of lethality and various gene features including expression across development, paralogy and constraint metrics together with human disease phenotypes. We explored a gene similarity approach for novel gene discovery and investigated unsolved cases from the 100,000 Genomes Project.

RESULTS

We found that genes in the early gestation lethal category have distinct characteristics and are enriched for genes linked with recessive forms of inherited metabolic disease. We identified several genes sharing multiple features with known biallelic forms of inborn errors of the metabolism and found signs of enrichment of biallelic predicted pathogenic variants among early gestation lethal genes in patients recruited under this disease category. We highlight two novel gene candidates with phenotypic overlap between the patients and the mouse knockouts.

CONCLUSIONS

Information on the developmental period at which embryonic lethality occurs in the knockout mouse may be used for novel disease gene discovery that helps to prioritise variants in unsolved rare disease cases.

Prevalence, parameters, and pathogenic mechanisms for splice-altering acceptor variants that disrupt the AG exclusion zone

Predicting the pathogenicity of acceptor splice-site variants outside the essential AG is challenging, due to high sequence diversity of the extended splice-site region. Critical analysis of 24,445 intronic extended acceptor splice-site variants reported in ClinVar and the Leiden Open Variation Database (LOVD) demonstrates 41.9% of pathogenic variants create an AG dinucleotide between the predicted branchpoint and acceptor (AG-creating variants in the AG exclusion zone), 28.4% result in loss of a pyrimidine at the -3 position, and 15.1% result in loss of one or more pyrimidines in the polypyrimidine tract. Pathogenicity of AG-creating variants was highly influenced by their position. We define a high-risk zone for pathogenicity: > 6 nucleotides downstream of the predicted branchpoint and >5 nucleotides upstream from the acceptor, where 93.1% of pathogenic AG-creating variants arise and where naturally occurring AG dinucleotides are concordantly depleted (5.8% of natural AGs). SpliceAI effectively predicts pathogenicity of AG-creating variants, achieving 95% sensitivity and 69% specificity. We highlight clinical examples showing contrasting mechanisms for mis-splicing arising from AG variants: (1) cryptic acceptor created; (2) splicing silencer created: an introduced AG silences the acceptor, resulting in exon skipping, intron retention, and/or use of an alternative existing cryptic acceptor; and (3) splicing silencer disrupted: loss of a deep intronic AG activates inclusion of a pseudo-exon. In conclusion, we establish AG-creating variants as a common class of pathogenic extended acceptor variant and outline factors conferring critical risk for mis-splicing for AG-creating variants in the AG exclusion zone, between the branchpoint and acceptor.

The sequences of 150,119 genomes in the UK Biobank

Detailed knowledge of how diversity in the sequence of the human genome affects phenotypic diversity depends on a comprehensive and reliable characterization of both sequences and phenotypic variation. Over the past decade, insights into this relationship have been obtained from whole-exome sequencing or whole-genome sequencing of large cohorts with rich phenotypic data^1,2. Here we describe the analysis of whole-genome sequencing of 150,119 individuals from the UK Biobank³. This constitutes a set of high-quality variants, including 585,040,410 single-nucleotide polymorphisms, representing 7.0% of all possible human single-nucleotide polymorphisms, and 58,707,036 indels. This large set of variants allows us to characterize selection based on sequence variation within a population through a depletion rank score of windows along the genome. Depletion rank analysis shows that coding exons represent a small fraction of regions in the genome subject to strong sequence conservation. We define three cohorts within the UK Biobank: a large British Irish cohort, a smaller African cohort and a South Asian cohort. A haplotype reference panel is provided that allows reliable imputation of most variants carried by three or more sequenced individuals. We identified 895,055 structural variants and 2,536,688 microsatellites, groups of variants typically excluded from large-scale whole-genome sequencing studies. Using this formidable new resource, we provide several examples of trait associations for rare variants with large effects not found previously through studies based on whole-exome sequencing and/or imputation.

Prioritization of putatively detrimental variants in euploid miscarriages

Miscarriage is the spontaneous termination of a pregnancy before 24 weeks of gestation. We studied the genome of euploid miscarried embryos from mothers in the range of healthy adult individuals to understand genetic susceptibility to miscarriage not caused by chromosomal aneuploidies. We developed GP , a pipeline that we used to prioritize 439 unique variants in 399 genes, including genes known to be associated with miscarriages. Among the prioritized genes we found STAG2 coding for the cohesin complex subunit, for which inactivation in mouse is lethal, and TLE4 a target of Notch and Wnt, physically interacting with a region on chromosome 9 associated to miscarriages.

Population-level deficit of homozygosity unveils CPSF3 as an intellectual disability syndrome gene

Predicting the pathogenicity of biallelic missense variants can be challenging. Here, we use a deficit of observed homozygous carriers of missense variants, versus an expected number in a set of 153,054 chip-genotyped Icelanders, to identify potentially pathogenic genotypes. We follow three missense variants with a complete deficit of homozygosity and find that their pathogenic effect in homozygous state ranges from severe childhood disease to early embryonic lethality. One of these variants is in CPSF3, a gene not previously linked to disease. From a set of clinically sequenced Icelanders, and by sequencing archival samples targeted through the Icelandic genealogy, we find four homozygous carriers. Additionally, we find two homozygous carriers of Mexican descent of another missense variant in CPSF3. All six homozygous carriers of missense variants in CPSF3 show severe intellectual disability, seizures, microcephaly, and abnormal muscle tone. Here, we show how the absence of certain homozygous genotypes from a large population set can elucidate causes of previously unexplained recessive diseases and early miscarriage.

Standardized practices for RNA diagnostics using clinically accessible specimens reclassifies 75% of putative splicing variants

PURPOSE

Genetic variants causing aberrant premessenger RNA splicing are increasingly being recognized as causal variants in genetic disorders. In this study, we devise standardized practices for polymerase chain reaction (PCR)-based RNA diagnostics using clinically accessible specimens (blood, fibroblasts, urothelia, biopsy).

METHODS

A total of 74 families with diverse monogenic conditions (31% prenatal-congenital onset, 47% early childhood, and 22% teenage-adult onset) were triaged into PCR-based RNA testing, with comparative RNA sequencing for 19 cases.

RESULTS

Informative RNA assay data were obtained for 96% of cases, enabling variant reclassification for 75% variants that can be used for genetic counseling (71%), to inform clinical care (32%) and prenatal counseling (41%). Variant-associated mis-splicing was highly reproducible for 28 cases with samples from ≥2 affected individuals or heterozygotes and 10 cases with ≥2 biospecimens. PCR amplicons encompassing another segregated heterozygous variant was vital for clinical interpretation of 22 of 79 variants to phase RNA splicing events and discern complete from partial mis-splicing.

CONCLUSION

RNA diagnostics enabled provision of a genetic diagnosis for 64% of recruited cases. PCR-based RNA diagnostics has capacity to analyze 81.3% of clinically significant genes, with long amplicons providing an advantage over RNA sequencing to phase RNA splicing events. The Australasian Consortium for RNA Diagnostics (SpliceACORD) provide clinically-endorsed, standardized protocols and recommendations for interpreting RNA assay data.

Heterozygous loss of WBP11 function causes multiple congenital defects in humans and mice

The genetic causes of multiple congenital anomalies are incompletely understood. Here, we report novel heterozygous predicted loss-of-function (LoF) and predicted damaging missense variants in the WW domain binding protein 11 (WBP11) gene in seven unrelated families with a variety of overlapping congenital malformations, including cardiac, vertebral, tracheo-esophageal, renal and limb defects. WBP11 encodes a component of the spliceosome with the ability to activate pre-messenger RNA splicing. We generated a Wbp11 null allele in mouse using CRISPR-Cas9 targeting. Wbp11 homozygous null embryos die prior to E8.5, indicating that Wbp11 is essential for development. Fewer Wbp11 heterozygous null mice are found than expected due to embryonic and postnatal death. Importantly, Wbp11 heterozygous null mice are small and exhibit defects in axial skeleton, kidneys and esophagus, similar to the affected individuals, supporting the role of WBP11 haploinsufficiency in the development of congenital malformations in humans. LoF WBP11 variants should be considered as a possible cause of VACTERL association as well as isolated Klippel-Feil syndrome, renal agenesis or esophageal atresia.

An overview of germline variations in genes of primary immunodeficiences through integrative analysis of ClinVar, HGMD® and dbSNP databases

Primary immunodeficiencies (PID) are a diverse group of genetic disorders caused by inadequate development and function of immune system. Identifying genetic etiology is important for genetic counselling and treatment decisions. Clinical relevance of genetic variants is a complex problem depending on gene-specific and variant specific genotype-phenotype interactions. To address this challenge, we aimed to characterize the pathogenic landscape of PID genes by combining the analysis of germline variations reported in ClinVar and HGMD^® and identification of damaging variations available in dbSNP. We generated a joint ClinVar/HGMD database, which included 111,940 variants, among them 32,452 were classified as pathogenic/likely pathogenic. From a total of 5,415,794 bi- or multiallelic variants in PID genes recorded in dbSNP, we retrieved 38,291 high impact (HI) biallelic variants with presumably disruptive impact in the protein, of them 25,500 variants were not present in ClinVar/HGMD. Using a functional prediction algorithm, we additionally identified 28,507 deleterious and 56,016 neutral missense variants among dbSNP variants and created a collection of damaging and neutral variations in PID genes, not currently present in ClinVar/HGMD, with their allele frequencies and mappings to protein domains. The distribution of pathogenic variants from ClinVar/HGMD, HI variants and deleterious missense variants from dbSNP was analyzed in the context of hereditary pattern and gene specific metrics, such as pLI and haploinsufficiency. Our report summarized data on complex gene-specific variability in PID genes and might be useful for the identification of the most promising variants and gene regions for further study.

The genetic architecture of sporadic and multiple consecutive miscarriage

Miscarriage is a common, complex trait affecting ~15% of clinically confirmed pregnancies. Here we present the results of large-scale genetic association analyses with 69,054 cases from five different ancestries for sporadic miscarriage, 750 cases of European ancestry for multiple (≥3) consecutive miscarriage, and up to 359,469 female controls. We identify one genome-wide significant association (rs146350366, minor allele frequency (MAF) 1.2%, P = 3.2 × 10-8, odds ratio (OR) = 1.4) for sporadic miscarriage in our European ancestry meta-analysis and three genome-wide significant associations for multiple consecutive miscarriage (rs7859844, MAF = 6.4%, P = 1.3 × 10-8, OR = 1.7; rs143445068, MAF = 0.8%, P = 5.2 × 10-9, OR = 3.4; rs183453668, MAF = 0.5%, P = 2.8 × 10-8, OR = 3.8). We further investigate the genetic architecture of miscarriage with biobank-scale Mendelian randomization, heritability, and genetic correlation analyses. Our results show that miscarriage etiopathogenesis is partly driven by genetic variation potentially related to placental biology, and illustrate the utility of large-scale biobank data for understanding this pregnancy complication.

Preconception genome medicine: current state and future perspectives to improve infertility diagnosis and reproductive and health outcomes based on individual genomic data

BACKGROUND

Our genetic code is now readable, writable and hackable. The recent escalation of genome-wide sequencing (GS) applications in population diagnostics will not only enable the assessment of risks of transmitting well-defined monogenic disorders at preconceptional stages (i.e. carrier screening), but also facilitate identification of multifactorial genetic predispositions to sub-lethal pathologies, including those affecting reproductive fitness. Through GS, the acquisition and curation of reproductive-related findings will warrant the expansion of genetic assessment to new areas of genomic prediction of reproductive phenotypes, pharmacogenomics and molecular embryology, further boosting our knowledge and therapeutic tools for treating infertility and improving women's health.

OBJECTIVE AND RATIONALE

In this article, we review current knowledge and potential development of preconception genome analysis aimed at detecting reproductive and individual health risks (recessive genetic disease and medically actionable secondary findings) as well as anticipating specific reproductive outcomes, particularly in the context of IVF. The extension of reproductive genetic risk assessment to the general population and IVF couples will lead to the identification of couples who carry recessive mutations, as well as sub-lethal conditions prior to conception. This approach will provide increased reproductive autonomy to couples, particularly in those cases where preimplantation genetic testing is an available option to avoid the transmission of undesirable conditions. In addition, GS on prospective infertility patients will enable genome-wide association studies specific for infertility phenotypes such as predisposition to premature ovarian failure, increased risk of aneuploidies, complete oocyte immaturity or blastocyst development failure, thus empowering the development of true reproductive precision medicine.

SEARCH METHODS

Searches of the literature on PubMed Central included combinations of the following MeSH terms: human, genetics, genomics, variants, male, female, fertility, next generation sequencing, genome exome sequencing, expanded carrier screening, secondary findings, pharmacogenomics, controlled ovarian stimulation, preconception, genetics, genome-wide association studies, GWAS.

OUTCOMES

Through PubMed Central queries, we identified a total of 1409 articles. The full list of articles was assessed for date of publication, limiting the search to studies published within the last 15 years (2004 onwards due to escalating research output of next-generation sequencing studies from that date). The remaining articles' titles were assessed for pertinence to the topic, leaving a total of 644 articles. The use of preconception GS has the potential to identify inheritable genetic conditions concealed in the genome of around 4% of couples looking to conceive. Genomic information during reproductive age will also be useful to anticipate late-onset medically actionable conditions with strong genetic background in around 2-4% of all individuals. Genetic variants correlated with differential response to pharmaceutical treatment in IVF, and clear genotype-phenotype associations are found for aberrant sperm types, oocyte maturation, fertilization or pre- and post-implantation embryonic development. All currently known capabilities of GS at the preconception stage are reviewed along with persisting and forthcoming barriers for the implementation of precise reproductive medicine.

WIDER IMPLICATIONS

The expansion of sequencing analysis to additional monogenic and polygenic traits may enable the development of cost-effective preconception tests capable of identifying underlying genetic causes of infertility, which have been defined as 'unexplained' until now, thus leading to the development of a true personalized genomic medicine framework in reproductive health.

Neurogenetic fetal akinesia and arthrogryposis: genetics, expanding genotype-phenotypes and functional genomics

BACKGROUND

Fetal akinesia and arthrogryposis are clinically and genetically heterogeneous and have traditionally been refractive to genetic diagnosis. The widespread availability of affordable genome-wide sequencing has facilitated accurate genetic diagnosis and gene discovery in these conditions.

METHODS

We performed next generation sequencing (NGS) in 190 probands with a diagnosis of arthrogryposis multiplex congenita, distal arthrogryposis, fetal akinesia deformation sequence or multiple pterygium syndrome. This sequencing was a combination of bespoke neurogenetic disease gene panels and whole exome sequencing. Only class 4 and 5 variants were reported, except for two cases where the identified variants of unknown significance (VUS) are most likely to be causative for the observed phenotype. Co-segregation studies and confirmation of variants identified by NGS were performed where possible. Functional genomics was performed as required.

RESULTS

Of the 190 probands, 81 received an accurate genetic diagnosis. All except two of these cases harboured class 4 and/or 5 variants based on the American College of Medical Genetics and Genomics guidelines. We identified phenotypic expansions associated with CACNA1S, CHRNB1, GMPPB and STAC3. We describe a total of 50 novel variants, including a novel missense variant in the recently identified gene for arthrogryposis with brain malformations-SMPD4.

CONCLUSIONS

Comprehensive gene panels give a diagnosis for a substantial proportion (42%) of fetal akinesia and arthrogryposis cases, even in an unselected cohort. Recently identified genes account for a relatively large proportion, 32%, of the diagnoses. Diagnostic-research collaboration was critical to the diagnosis and variant interpretation in many cases, facilitated genotype-phenotype expansions and reclassified VUS through functional genomics.

Deep learning decodes the principles of differential gene expression

Identifying the molecular mechanisms that control differential gene expression (DE) is a major goal of basic and disease biology. We develop a systems biology model to predict DE, and mine the biological basis of the factors that influence predicted gene expression, in order to understand how it may be generated. This model, called DEcode, utilizes deep learning to predict DE based on genome-wide binding sites on RNAs and promoters. Ranking predictive factors from the DEcode indicates that clinically relevant expression changes between thousands of individuals can be predicted mainly through the joint action of post-transcriptional RNA-binding factors. We also show the broad potential applications of DEcode to generate biological insights, by predicting DE between tissues, differential transcript-usage, and drivers of aging throughout the human lifespan, of gene coexpression relationships on a genome-wide scale, and of frequently DE genes across diverse conditions. Researchers can freely utilize DEcode to identify influential molecular mechanisms for any human expression data - www.differentialexpression.org.

Hardy-Weinberg Equilibrium in the Large Scale Genomic Sequencing Era

Hardy-Weinberg Equilibrium (HWE) is used to estimate the number of homozygous and heterozygous variant carriers based on its allele frequency in populations that are not evolving. Deviations from HWE in large population databases have been used to detect genotyping errors, which can result in extreme heterozygote excess (HetExc). However, HetExc might also be a sign of natural selection since recessive disease causing variants should occur less frequently in a homozygous state in the population, but may reach high allele frequency in a heterozygous state, especially if they are advantageous. We developed a filtering strategy to detect these variants and applied it on genome data from 137,842 individuals. The main limitations of this approach were quality of genotype calls and insufficient population sizes, whereas population structure and inbreeding can reduce sensitivity, but not precision, in certain populations. Nevertheless, we identified 161 HetExc variants in 149 genes, most of which were specific to African/African American populations (∼79.5%). Although the majority of them were not associated with known diseases, or were classified as clinically "benign," they were enriched in genes associated with autosomal recessive diseases. The resulting dataset also contained two known recessive disease causing variants with evidence of heterozygote advantage in the sickle-cell anemia (HBB) and cystic fibrosis (CFTR). Finally, we provide supporting in silico evidence of a novel heterozygote advantageous variant in the chromodomain helicase DNA binding protein 6 gene (CHD6; involved in influenza virus replication). We anticipate that our approach will aid the detection of rare recessive disease causing variants in the future.

Human and mouse essentiality screens as a resource for disease gene discovery

The identification of causal variants in sequencing studies remains a considerable challenge that can be partially addressed by new gene-specific knowledge. Here, we integrate measures of how essential a gene is to supporting life, as inferred from viability and phenotyping screens performed on knockout mice by the International Mouse Phenotyping Consortium and essentiality screens carried out on human cell lines. We propose a cross-species gene classification across the Full Spectrum of Intolerance to Loss-of-function (FUSIL) and demonstrate that genes in five mutually exclusive FUSIL categories have differing biological properties. Most notably, Mendelian disease genes, particularly those associated with developmental disorders, are highly overrepresented among genes non-essential for cell survival but required for organism development. After screening developmental disorder cases from three independent disease sequencing consortia, we identify potentially pathogenic variants in genes not previously associated with rare diseases. We therefore propose FUSIL as an efficient approach for disease gene discovery.