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Computational efforts to identify functional elements within genomes leverage comparative sequence information by looking for regions that exhibit evidence of selective constraint. One way of detecting constrained elements is to follow a bottom-up approach by computing constraint scores for individual positions of a multiple alignment and then defining constrained elements as segments of contiguous, highly scoring nucleotide positions. Here we present GERP++, a new tool that uses maximum likelihood evolutionary rate estimation for position-specific scoring and, in contrast to previous bottom-up methods, a novel dynamic programming approach to subsequently define constrained elements. GERP++ evaluates a richer set of candidate element breakpoints and ranks them based on statistical significance, eliminating the need for biased heuristic extension techniques. Using GERP++ we identify over 1.3 million constrained elements spanning over 7% of the human genome. We predict a higher fraction than earlier estimates largely due to the annotation of longer constrained elements, which improves one to one correspondence between predicted elements with known functional sequences. GERP++ is an efficient and effective tool to provide both nucleotide- and element-level constraint scores within deep multiple sequence alignments.

Deletions at chromosome 2p25.3 are associated with a syndrome consisting of intellectual disability and obesity. The smallest region of overlap for deletions at 2p25.3 contains PXDN and MYT1L. MYT1L is expressed only within the brain in humans. We hypothesized that single nucleotide variants (SNVs) in MYT1L would cause a phenotype resembling deletion at 2p25.3. To examine this we sought MYT1L SNVs in exome sequencing data from 4, 296 parent-child trios. Further variants were identified through a genematcher-facilitated collaboration. We report 9 patients with MYT1L SNVs (4 loss of function and 5 missense). The phenotype of SNV carriers overlapped with that of 2p25.3 deletion carriers. To identify the transcriptomic consequences of MYT1L loss of function we used CRISPR-Cas9 to create a knockout cell line. Gene Ontology analysis in knockout cells demonstrated altered expression of genes that regulate gene expression and that are localized to the nucleus. These differentially expressed genes were enriched for OMIM disease ontology terms \"mental retardation\". To study the developmental effects of MYT1L loss of function we created a zebrafish knockdown using morpholinos. Knockdown zebrafish manifested loss of oxytocin expression in the preoptic neuroendocrine area. This study demonstrates that MYT1L variants are associated with syndromic obesity in humans. The mechanism is related to dysregulated expression of neurodevelopmental genes and altered development of the neuroendocrine hypothalamus.

Two groups describe approaches for synthesizing and assaying the function of thousands of variants of mammalian DNA regulatory elements. Melnikov et al . use their results to engineer short optimized regulatory elements in human cells, whereas Patwardhan et al . study enhancers hundreds of bases long in mice. The functional consequences of genetic variation in mammalian regulatory elements are poorly understood. We report the in vivo dissection of three mammalian enhancers at single-nucleotide resolution through a massively parallel reporter assay. For each enhancer, we synthesized a library of >100,000 mutant haplotypes with 2–3% divergence from the wild-type sequence. Each haplotype was linked to a unique sequence tag embedded within a transcriptional cassette. We introduced each enhancer library into mouse liver and measured the relative activities of individual haplotypes en masse by sequencing the transcribed tags. Linear regression analysis yielded highly reproducible estimates of the effect of every possible single-nucleotide change on enhancer activity. The functional consequence of most mutations was modest, with ∼22% affecting activity by >1.2-fold and ∼3% by >2-fold. Several, but not all, positions with higher effects showed evidence for purifying selection, or co-localized with known liver-associated transcription factor binding sites, demonstrating the value of empirical high-resolution functional analysis.

Background Developmental disabilities have diverse genetic causes that must be identified to facilitate precise diagnoses. We describe genomic data from 371 affected individuals, 309 of which were sequenced as proband-parent trios. Methods Whole-exome sequences (WES) were generated for 365 individuals (127 affected) and whole-genome sequences (WGS) were generated for 612 individuals (244 affected). Results Pathogenic or likely pathogenic variants were found in 100 individuals (27%), with variants of uncertain significance in an additional 42 (11.3%). We found that a family history of neurological disease, especially the presence of an affected first-degree relative, reduces the pathogenic/likely pathogenic variant identification rate, reflecting both the disease relevance and ease of interpretation of de novo variants. We also found that improvements to genetic knowledge facilitated interpretation changes in many cases. Through systematic reanalyses, we have thus far reclassified 15 variants, with 11.3% of families who initially were found to harbor a VUS and 4.7% of families with a negative result eventually found to harbor a pathogenic or likely pathogenic variant. To further such progress, the data described here are being shared through ClinVar, GeneMatcher, and dbGaP. Conclusions Our data strongly support the value of large-scale sequencing, especially WGS within proband-parent trios, as both an effective first-choice diagnostic tool and means to advance clinical and research progress related to pediatric neurological disease.

Evan Eichler and colleagues analyze copy number variation in 15,767 children with intellectual disability, developmental delay, congenital birth defects and/or other related phenotypes. They identify 59 likely pathogenic CNV regions, including 14 new candidate regions, and estimate that ~14% of disorders in this sample collection are caused by large CNVs. To understand the genetic heterogeneity underlying developmental delay, we compared copy number variants (CNVs) in 15,767 children with intellectual disability and various congenital defects (cases) to CNVs in 8,329 unaffected adult controls. We estimate that ∼14.2% of disease in these children is caused by CNVs >400 kb. We observed a greater enrichment of CNVs in individuals with craniofacial anomalies and cardiovascular defects compared to those with epilepsy or autism. We identified 59 pathogenic CNVs, including 14 new or previously weakly supported candidates, refined the critical interval for several genomic disorders, such as the 17q21.31 microdeletion syndrome, and identified 940 candidate dosage-sensitive genes. We also developed methods to opportunistically discover small, disruptive CNVs within the large and growing diagnostic array datasets. This evolving CNV morbidity map, combined with exome and genome sequencing, will be critical for deciphering the genetic basis of developmental delay, intellectual disability and autism spectrum disorders.

Jay Shendure and colleagues report exome sequencing of ten individuals with Kabuki syndrome. They identify mutations in MLL2 , encoding a Trithorax-group histone methyltransferase, as causal for this rare autosomal dominant malformation disorder. We demonstrate the successful application of exome sequencing 1 , 2 , 3 to discover a gene for an autosomal dominant disorder, Kabuki syndrome (OMIM%147920). We subjected the exomes of ten unrelated probands to massively parallel sequencing. After filtering against existing SNP databases, there was no compelling candidate gene containing previously unknown variants in all affected individuals. Less stringent filtering criteria allowed for the presence of modest genetic heterogeneity or missing data but also identified multiple candidate genes. However, genotypic and phenotypic stratification highlighted MLL2 , which encodes a Trithorax-group histone methyltransferase 4 : seven probands had newly identified nonsense or frameshift mutations in this gene. Follow-up Sanger sequencing detected MLL2 mutations in two of the three remaining individuals with Kabuki syndrome (cases) and in 26 of 43 additional cases. In families where parental DNA was available, the mutation was confirmed to be de novo ( n = 12) or transmitted ( n = 2) in concordance with phenotype. Our results strongly suggest that mutations in MLL2 are a major cause of Kabuki syndrome.

Dravet syndrome (DS) is a developmental and epileptic encephalopathy that results from mutations in the Na v 1.1 sodium channel encoded by SCN1A . Most known DS-causing mutations are in coding regions of SCN1A , but we recently identified several disease-associated SCN1A mutations in intron 20 that are within or near to a cryptic and evolutionarily conserved “poison” exon, 20N, whose inclusion is predicted to lead to transcript degradation. However, it is not clear how these intron 20 variants alter SCN1A expression or DS pathophysiology in an organismal context, nor is it clear how exon 20N is regulated in a tissue-specific and developmental context. We address those questions here by generating an animal model of our index case, NM_006920.4(SCN1A):c.3969+2451G>C, using gene editing to create the orthologous mutation in laboratory mice. Scn1a heterozygous knock-in (+/ KI ) mice exhibited an ~50% reduction in brain Scn1a mRNA and Na v 1.1 protein levels, together with characteristics observed in other DS mouse models, including premature mortality, seizures, and hyperactivity. In brain tissue from adult Scn1a +/+ animals, quantitative RT-PCR assays indicated that ~1% of Scn1a mRNA included exon 20N, while brain tissue from Scn1a +/KI mice exhibited an ~5-fold increase in the extent of exon 20N inclusion. We investigated the extent of exon 20N inclusion in brain during normal fetal development in RNA-seq data and discovered that levels of inclusion were ~70% at E14.5, declining progressively to ~10% postnatally. A similar pattern exists for the homologous sodium channel Na v 1.6, encoded by Scn8a . For both genes, there is an inverse relationship between the level of functional transcript and the extent of poison exon inclusion. Taken together, our findings suggest that poison exon usage by Scn1a and Scn8a is a strategy to regulate channel expression during normal brain development, and that mutations recapitulating a fetal-like pattern of splicing cause reduced channel expression and epileptic encephalopathy.

Comprehensive descriptions of large insertion/deletion or segmental duplication polymorphisms (SDs) in the human genome have recently been generated. These annotations, known collectively as structural or copy-number variants (CNVs), include thousands of discrete genomic regions and span hundreds of millions of nucleotides. Here we review the genomic distribution of CNVs, which is strongly correlated with gene, repeat and segmental duplication content. We explore the evolutionary mechanisms giving rise to this nonrandom distribution, considering the available data on both human polymorphisms and the fixed changes that differentiate humans from other species. It is likely that mutational biases, selective effects and interactions between these forces all contribute substantially to the spectrum of human copy-number variation. Although defining these variants with nucleotide-level precision remains a largely unmet but critical challenge, our understanding of their potential medical impact and evolutionary importance is rapidly emerging.

Evan Eichler and colleagues present an analysis of how well current commercial SNP platforms accurately capture copy number variants (CNVs). Although they were able accurately predict from Illumina Human 1M genotype data many sites identified in their recent study assessing CNVs in nine human individuals with a fosmid paired-end sequence approach, they find that commonly used platforms offer limited coverage for a large fraction of CNVs. SNP genotyping has emerged as a technology to incorporate copy number variants (CNVs) into genetic analyses of human traits. However, the extent to which SNP platforms accurately capture CNVs remains unclear. Using independent, sequence-based CNV maps, we find that commonly used SNP platforms have limited or no probe coverage for a large fraction of CNVs. Despite this, in 9 samples we inferred 368 CNVs using Illumina SNP genotyping data and experimentally validated over two-thirds of these. We also developed a method (SNP-Conditional Mixture Modeling, SCIMM) to robustly genotype deletions using as few as two SNP probes. We find that HapMap SNPs are strongly correlated with 82% of common deletions, but the newest SNP platforms effectively tag about 50%. We conclude that currently available genome-wide SNP assays can capture CNVs accurately, but improvements in array designs, particularly in duplicated sequences, are necessary to facilitate more comprehensive analyses of genomic variation.