Developmental and temporal characteristics of clonal sperm mosaicism.

Throughout development and aging, human cells accumulate mutations resulting in genomic mosaicism and genetic diversity at the cellular level. Mosaic mutations present in the gonads can affect both the individual and the offspring and subsequent generations. Here, we explore patterns and temporal stability of clonal mosaic mutations in male gonads by sequencing ejaculated sperm. Through 300× whole-genome sequencing of blood and sperm from healthy men, we find each ejaculate carries on average 33.3 ± 12.1 (mean ± SD) clonal mosaic variants, nearly all of which are detected in serial sampling, with the majority absent from sampled somal tissues. Their temporal stability and mutational signature suggest origins during embryonic development from a largely immutable stem cell niche. Clonal mosaicism likely contributes a transmissible, predicted pathogenic exonic variant for 1 in 15 men, representing a life-long threat of transmission for these individuals and a significant burden on human population health.

Loss of the neural-specific BAF subunit ACTL6B relieves repression of early response genes and causes recessive autism.

Synaptic activity in neurons leads to the rapid activation of genes involved in mammalian behavior. ATP-dependent chromatin remodelers such as the BAF complex contribute to these responses and are generally thought to activate transcription. However, the mechanisms keeping such "early activation" genes silent have been a mystery. In the course of investigating Mendelian recessive autism, we identified six families with segregating loss-of-function mutations in the neuronal BAF (nBAF) subunit ACTL6B (originally named BAF53b). Accordingly, ACTL6B was the most significantly mutated gene in the Simons Recessive Autism Cohort. At least 14 subunits of the nBAF complex are mutated in autism, collectively making it a major contributor to autism spectrum disorder (ASD). Patient mutations destabilized ACTL6B protein in neurons and rerouted dendrites to the wrong glomerulus in the fly olfactory system. Humans and mice lacking ACTL6B showed corpus callosum hypoplasia, indicating a conserved role for ACTL6B in facilitating neural connectivity. Actl6b knockout mice on two genetic backgrounds exhibited ASD-related behaviors, including social and memory impairments, repetitive behaviors, and hyperactivity. Surprisingly, mutation of Actl6b relieved repression of early response genes including AP1 transcription factors (Fos, Fosl2, Fosb, and Junb), increased chromatin accessibility at AP1 binding sites, and transcriptional changes in late response genes associated with early response transcription factor activity. ACTL6B loss is thus an important cause of recessive ASD, with impaired neuron-specific chromatin repression indicated as a potential mechanism.

Mutations in LNPK, Encoding the Endoplasmic Reticulum Junction Stabilizer Lunapark, Cause a Recessive Neurodevelopmental Syndrome.

The dynamic shape of the endoplasmic reticulum (ER) is a reflection of its wide variety of critical cell biological functions. Consequently, perturbation of ER-shaping proteins can cause a range of human phenotypes. Here, we describe three affected children (from two consanguineous families) who carry homozygous loss-of-function mutations in LNPK (previously known as KIAA1715); this gene encodes lunapark, which is proposed to serve as a curvature-stabilizing protein within tubular three-way junctions of the ER. All individuals presented with severe psychomotor delay, intellectual disability, hypotonia, epilepsy, and corpus callosum hypoplasia, and two of three showed mild cerebellar hypoplasia and atrophy. Consistent with a proposed role in neurodevelopmental disease, LNPK was expressed during brain development in humans and mice and was present in neurite-like processes in differentiating human neural progenitor cells. Affected cells showed the absence of full-length lunapark, aberrant ER structures, and increased luminal mass density. Together, our results implicate the ER junction stabilizer lunapark in establishing the corpus callosum.

Quantitative evolutionary proteomics of seminal fluid from primates with different mating systems.

BACKGROUND: Genomic data from various organisms have been used to study how sexual selection has shaped genetic diversity in reproductive proteins, and in particular, to elucidate how mating systems may have influenced evolution at the molecular and phenotypic levels. However, large-scale proteomic data including protein identifications and abundances are only now entering the field of evolutionary and comparative genomics. Variation in both protein sequence and expression level may play important roles in the evolution of sexual traits and behaviors. RESULTS: Here, we broadly analyze the components of seminal fluid from primates with diverse mating systems ranging from monogamous to polygynous, and include genomics, proteomics, phylogenetic and quantitative characters into our framework. Our analyses show that seminal fluid proteins are undergoing rapid evolution and some of these quickly evolving proteins may be influenced by sexual selection. Through evolutionary analyses and protein abundance differences, we identified 84 genes whose evolutionary rates or expression levels were correlated with mating system and other sexual characters. We found that many proteins differ in abundance between monogamous and polygynous primate mating systems. Many of these proteins are enriched in the copulatory plug pathway, which suggests that post-zygotic selective barriers are important regardless of mating system type. CONCLUSIONS: This work is the first to comprehensively compare seminal fluid proteins between human and non-human primates using high-throughput proteomics. Our findings highlight the impact of mating system variation on seminal fluid protein evolution and abundance.

Selection on plant male function genes identifies candidates for reproductive isolation of yellow monkeyflowers.

Understanding the genetic basis of reproductive isolation promises insight into speciation and the origins of biological diversity. While progress has been made in identifying genes underlying barriers to reproduction that function after fertilization (post-zygotic isolation), we know much less about earlier acting pre-zygotic barriers. Of particular interest are barriers involved in mating and fertilization that can evolve extremely rapidly under sexual selection, suggesting they may play a prominent role in the initial stages of reproductive isolation. A significant challenge to the field of speciation genetics is developing new approaches for identification of candidate genes underlying these barriers, particularly among non-traditional model systems. We employ powerful proteomic and genomic strategies to study the genetic basis of conspecific pollen precedence, an important component of pre-zygotic reproductive isolation among yellow monkeyflowers (Mimulus spp.) resulting from male pollen competition. We use isotopic labeling in combination with shotgun proteomics to identify more than 2,000 male function (pollen tube) proteins within maternal reproductive structures (styles) of M. guttatus flowers where pollen competition occurs. We then sequence array-captured pollen tube exomes from a large outcrossing population of M. guttatus, and identify those genes with evidence of selective sweeps or balancing selection consistent with their role in pollen competition. We also test for evidence of positive selection on these genes more broadly across yellow monkeyflowers, because a signal of adaptive divergence is a common feature of genes causing reproductive isolation. Together the molecular evolution studies identify 159 pollen tube proteins that are candidate genes for conspecific pollen precedence. Our work demonstrates how powerful proteomic and genomic tools can be readily adapted to non-traditional model systems, allowing for genome-wide screens towards the goal of identifying the molecular basis of genetically complex traits.

Trans genomic capture and sequencing of primate exomes reveals new targets of positive selection.

Comparison of protein-coding DNA sequences from diverse primates can provide insight into these species' evolutionary history and uncover the molecular basis for their phenotypic differences. Currently, the number of available primate reference genomes limits these genome-wide comparisons. Here we use targeted capture methods designed for human to sequence the protein-coding regions, or exomes, of four non-human primate species (three Old World monkeys and one New World monkey). Despite average sequence divergence of up to 4% from the human sequence probes, we are able to capture ~96% of coding sequences. Using a combination of mapping and assembly techniques, we generated high-quality full-length coding sequences for each species. Both the number of nucleotide differences and the distribution of insertion and deletion (indel) lengths indicate that the quality of the assembled sequences is very high and exceeds that of most reference genomes. Using this expanded set of primate coding sequences, we performed a genome-wide scan for genes experiencing positive selection and identified a novel class of adaptively evolving genes involved in the conversion of epithelial cells in skin, hair, and nails to keratin. Interestingly, the genes we identify under positive selection also exhibit significantly increased allele frequency differences among human populations, suggesting that they play a role in both recent and long-term adaptation. We also identify several genes that have been lost on specific primate lineages, which illustrate the broad utility of this data set for other evolutionary analyses. These results demonstrate the power of second-generation sequencing in comparative genomics and greatly expand the repertoire of available primate coding sequences.

Detecting coevolution in mammalian sperm-egg fusion proteins.

Interactions between sperm and egg proteins can occur physically between gamete surface-binding proteins, and genetically between gamete proteins that work in complementary pathways in which they may not physically interact. Physically interacting sperm-egg proteins have been functionally identified in only a few species, and none have been verified within mammals. Candidate genes on both the sperm and egg surfaces exist, but gene deletion studies do not support functional interactions between these sperm-egg proteins; interacting sperm-egg proteins thus remain elusive. Cooperative gamete proteins undergo rapid evolution, and it is predicted that these sperm-egg proteins will also have correlated evolutionary rates due to compensatory changes on both the sperm and egg. To explore potential physical and genetic interactions in sperm-egg proteins, we sequenced four candidate genes from diverse primate species, and used regression and likelihood methods to test for signatures of coevolution between sperm-egg gene pairs. With both methods, we found that the egg protein CD9 coevolves with the sperm protein IZUMO1, suggesting a physical or genetic interaction occurs between them. With regression analysis, we found that CD9 and CRISP2 have correlated rates of evolution, and with likelihood analysis, that CD9 and CRISP1 have correlated rates. This suggests that the different tests may reflect different levels of interaction, be it physical or genetic. Coevolution tests thus provide an exploratory method for detecting potentially interacting sperm-egg protein pairs.

Risk of meningomyelocele mediated by the common 22q11.2 deletion.

Meningomyelocele is one of the most severe forms of neural tube defects (NTDs) and the most frequent structural birth defect of the central nervous system. We assembled the Spina Bifida Sequencing Consortium to identify causes. Exome and genome sequencing of 715 parent-offspring trios identified six patients with chromosomal 22q11.2 deletions, suggesting a 23-fold increased risk compared with the general population. Furthermore, analysis of a separate 22q11.2 deletion cohort suggested a 12- to 15-fold increased NTD risk of meningomyelocele. The loss of Crkl, one of several neural tube-expressed genes within the minimal deletion interval, was sufficient to replicate NTDs in mice, where both penetrance and expressivity were exacerbated by maternal folate deficiency. Thus, the common 22q11.2 deletion confers substantial meningomyelocele risk, which is partially alleviated by folate supplementation.

Ensuring fair, safe, and interpretable artificial intelligence-based prediction tools in a real-world oncological setting.

BACKGROUND: Cancer patients often experience treatment-related symptoms which, if uncontrolled, may require emergency department admission. We developed models identifying breast or genitourinary cancer patients at the risk of attending emergency department (ED) within 30-days and demonstrated the development, validation, and proactive approach to in-production monitoring of an artificial intelligence-based predictive model during a 3-month simulated deployment at a cancer hospital in the United States. METHODS: We used routinely-collected electronic health record data to develop our predictive models. We evaluated models including a variational autoencoder k-nearest neighbors algorithm (VAE-kNN) and model behaviors with a sample containing 84,138 observations from 28,369 patients. We assessed the model during a 77-day production period exposure to live data using a proactively monitoring process with predefined metrics. RESULTS: Performance of the VAE-kNN algorithm is exceptional (Area under the receiver-operating characteristics, AUC = 0.80) and remains stable across demographic and disease groups over the production period (AUC 0.74-0.82). We can detect issues in data feeds using our monitoring process to create immediate insights into future model performance. CONCLUSIONS: Our algorithm demonstrates exceptional performance at predicting risk of 30-day ED visits. We confirm that model outputs are equitable and stable over time using a proactive monitoring approach.

Patients with cancer often need to visit the hospital emergency department (ED), for example due to treatment side effects. Predicting these visits might help us to better manage the treatment of patients who are at risk. Here, we develop a computer-based tool to identify patients with cancer who are at risk of an unplanned ED visit within 30 days. We use health record data from over 28,000 patients who had visited a single cancer hospital in the US to create and test the model. The model performed well and was consistent across different demographic and disease groups. We monitor model behavior over time and show that it is stable. The approach we take to monitoring model performance may be a particularly useful contribution toward implementing similar predictive models in the clinic and checking that they are performing as intended.

Control-independent mosaic single nucleotide variant detection with DeepMosaic.

Mosaic variants (MVs) reflect mutagenic processes during embryonic development and environmental exposure, accumulate with aging and underlie diseases such as cancer and autism. The detection of noncancer MVs has been computationally challenging due to the sparse representation of nonclonally expanded MVs. Here we present DeepMosaic, combining an image-based visualization module for single nucleotide MVs and a convolutional neural network-based classification module for control-independent MV detection. DeepMosaic was trained on 180,000 simulated or experimentally assessed MVs, and was benchmarked on 619,740 simulated MVs and 530 independent biologically tested MVs from 16 genomes and 181 exomes. DeepMosaic achieved higher accuracy compared with existing methods on biological data, with a sensitivity of 0.78, specificity of 0.83 and positive predictive value of 0.96 on noncancer whole-genome sequencing data, as well as doubling the validation rate over previous best-practice methods on noncancer whole-exome sequencing data (0.43 versus 0.18). DeepMosaic represents an accurate MV classifier for noncancer samples that can be implemented as an alternative or complement to existing methods.

Comprehensive multi-omic profiling of somatic mutations in malformations of cortical development.

Malformations of cortical development (MCD) are neurological conditions involving focal disruptions of cortical architecture and cellular organization that arise during embryogenesis, largely from somatic mosaic mutations, and cause intractable epilepsy. Identifying the genetic causes of MCD has been a challenge, as mutations remain at low allelic fractions in brain tissue resected to treat condition-related epilepsy. Here we report a genetic landscape from 283 brain resections, identifying 69 mutated genes through intensive profiling of somatic mutations, combining whole-exome and targeted-amplicon sequencing with functional validation including in utero electroporation of mice and single-nucleus RNA sequencing. Genotype-phenotype correlation analysis elucidated specific MCD gene sets associated with distinct pathophysiological and clinical phenotypes. The unique single-cell level spatiotemporal expression patterns of mutated genes in control and patient brains indicate critical roles in excitatory neurogenic pools during brain development and in promoting neuronal hyperexcitability after birth.

Clinician-centric diagnosis of rare genetic diseases: performance of a gene pertinence metric in decision support for clinicians.

BACKGROUND: In diagnosis of rare genetic diseases we face a decision as to the degree to which the sequencing lab offers one or more diagnoses based on clinical input provided by the clinician, or the clinician reaches a diagnosis based on the complete set of variants provided by the lab. We tested a software approach to assist the clinician in making the diagnosis based on clinical findings and an annotated genomic variant table, using cases already solved using less automated processes. RESULTS: For the 81 cases studied (involving 216 individuals), 70 had genetic abnormalities with phenotypes previously described in the literature, and 11 were not described in the literature at the time of analysis ("discovery genes"). These included cases beyond a trio, including ones with different variants in the same gene. In 100% of cases the abnormality was recognized. Of the 70, the abnormality was ranked #1 in 94% of cases, with an average rank 1.1 for all cases. Large CNVs could be analyzed in an integrated analysis, performed in 24 of the cases. The process is rapid enough to allow for periodic reanalysis of unsolved cases. CONCLUSIONS: A clinician-friendly environment for clinical correlation can be provided to clinicians who are best positioned to have the clinical information needed for this interpretation.

Molecular diagnosis in recessive pediatric neurogenetic disease can help reduce disease recurrence in families.

BACKGROUND: The causes for thousands of individually rare recessive diseases have been discovered since the adoption of next generation sequencing (NGS). Following the molecular diagnosis in older children in a family, parents could use this information to opt for fetal genotyping in subsequent pregnancies, which could inform decisions about elective termination of pregnancy. The use of NGS diagnostic sequencing in families has not been demonstrated to yield benefit in subsequent pregnancies to reduce recurrence. Here we evaluated whether genetic diagnosis in older children in families supports reduction in recurrence of recessive neurogenetic disease. METHODS: Retrospective study involving families with a child with a recessive pediatric brain disease (rPBD) that underwent NGS-based molecular diagnosis. Prenatal molecular testing was offered to couples in which a molecular diagnosis was made, to help couples seeking to prevent recurrence. With this information, families made decisions about elective termination. Pregnancies that were carried to term were assessed for the health of child and mother, and compared with historic recurrence risk of recessive disease. RESULTS: Between 2010 and 2016, 1172 families presented with a child a likely rPBD, 526 families received a molecular diagnosis, 91 families returned to the clinic with 101 subsequent pregnancies, and 84 opted for fetal genotyping. Sixty tested negative for recurrence for the biallelic mutation in the fetus, and all, except for one spontaneous abortion, carried to term, and were unaffected at follow-up. Of 24 that genotyped positive for the biallelic mutation, 16 were electively terminated, and 8 were carried to term and showed features of disease similar to that of the older affected sibling(s). Among the 101 pregnancies, disease recurrence in living offspring deviated from the expected 25% to the observed 12% ([95% CI 0·04 to 0·20], p = 0·011). CONCLUSIONS: Molecular diagnosis in an older child, coupled with prenatal fetal genotyping in subsequent pregnancies and genetic counselling, allows families to make informed decisions to reduce recessive neurogenetic disease recurrence.

mTOR pathway somatic variants and the molecular pathogenesis of hemimegalencephaly.

OBJECTIVES: Recently, defects in the protein kinase mTOR (mammalian target of rapamycin) and its associated pathway have been correlated with hemimegalencephaly (HME). mTOR acts as a central regulator of important physiological cellular functions such as growth and proliferation, metabolism, autophagy, death, and survival. This study was aimed at identifying specific variants in mTOR signaling pathway genes in patients diagnosed with HME. METHODS: Using amplicon and whole exome sequencing (WES) of resected brain and paired blood samples from five HME patients, we were able to identify pathogenic mosaic variants in the mTOR pathway genes MTOR, PIK3CA, and DEPDC5. RESULTS: These results strengthen the hypothesis that somatic variants in PI3K-Akt-mTOR pathway genes contribute to HME. We also describe one patient presenting with a pathogenic variant on DEPDC5 gene, which reinforces the role of DEPDC5 on cortical structural changes due to mTORC1 hyperactivation. These findings also provide insights into when in brain development these variants occurred. An early developmental variant is expected to affect a larger number of cells and to result in a larger malformation, whereas the same variant occurring later in development would cause a minor malformation. SIGNIFICANCE: In the future, numerous somatic variants in known or new genes will undoubtedly be revealed in resected brain samples, making it possible to draw correlations between genotypes and phenotypes and allow for a genetic clinical diagnosis that may help to predict a given patient's outcome.

Autism risk in offspring can be assessed through quantification of male sperm mosaicism.

De novo mutations arising on the paternal chromosome make the largest known contribution to autism risk, and correlate with paternal age at the time of conception. The recurrence risk for autism spectrum disorders is substantial, leading many families to decline future pregnancies, but the potential impact of assessing parental gonadal mosaicism has not been considered. We measured sperm mosaicism using deep-whole-genome sequencing, for variants both present in an offspring and evident only in father's sperm, and identified single-nucleotide, structural and short tandem-repeat variants. We found that mosaicism quantification can stratify autism spectrum disorders recurrence risk due to de novo mutations into a vast majority with near 0% recurrence and a small fraction with a substantially higher and quantifiable risk, and we identify novel mosaic variants at risk for transmission to a future offspring. This suggests, therefore, that genetic counseling would benefit from the addition of sperm mosaicism assessment.

Direct multiplexed measurement of gene expression with color-coded probe pairs.

We describe a technology, the NanoString nCounter gene expression system, which captures and counts individual mRNA transcripts. Advantages over existing platforms include direct measurement of mRNA expression levels without enzymatic reactions or bias, sensitivity coupled with high multiplex capability, and digital readout. Experiments performed on 509 human genes yielded a replicate correlation coefficient of 0.999, a detection limit between 0.1 fM and 0.5 fM, and a linear dynamic range of over 500-fold. Comparison of the NanoString nCounter gene expression system with microarrays and TaqMan PCR demonstrated that the nCounter system is more sensitive than microarrays and similar in sensitivity to real-time PCR. Finally, a comparison of transcript levels for 21 genes across seven samples measured by the nCounter system and SYBR Green real-time PCR demonstrated similar patterns of gene expression at all transcript levels.