Functional convergence of histone methyltransferases EHMT1 and KMT2C involved in intellectual disability and autism spectrum disorder

Kleefstra syndrome, caused by haploinsufficiency of euchromatin histone methyltransferase 1 (EHMT1), is characterized by intellectual disability (ID), autism spectrum disorder (ASD), characteristic facial dysmorphisms, and other variable clinical features. In addition to EHMT1 mutations, de novo variants were reported in four additional genes (MBD5, SMARCB1, NR1I3, and KMT2C), in single individuals with clinical characteristics overlapping Kleefstra syndrome. Here, we present a novel cohort of five patients with de novo loss of function mutations affecting the histone methyltransferase KMT2C. Our clinical data delineates the KMT2C phenotypic spectrum and reinforces the phenotypic overlap with Kleefstra syndrome and other related ID disorders. To elucidate the common molecular basis of the neuropathology associated with mutations in KMT2C and EHMT1, we characterized the role of the Drosophila KMT2C ortholog, trithorax related (trr), in the nervous system. Similar to the Drosophila EHMT1 ortholog, G9a, trr is required in the mushroom body for short term memory. Trr ChIP-seq identified 3371 binding sites, mainly in the promoter of genes involved in neuronal processes. Transcriptional profiling of pan-neuronal trr knockdown and G9a null mutant fly heads identified 613 and 1123 misregulated genes, respectively. These gene sets show a significant overlap and are associated with nearly identical gene ontology enrichments. The majority of the observed biological convergence is derived from predicted indirect target genes. However, trr and G9a also have common direct targets, including the Drosophila ortholog of Arc (Arc1), a key regulator of synaptic plasticity. Our data highlight the clinical and molecular convergence between the KMT2 and EHMT protein families, which may contribute to a molecular network underlying a larger group of ID/ASD-related disorders

Summary of molecular and clinical features of individuals with <i>KMT2C</i> mutations.

<p>Summary of molecular and clinical features of individuals with <i>KMT2C</i> mutations.</p

Trr is required in the mushroom body for short term memory.

<p>Fluorescent confocal images of control (A-D) and trr knockdown (E-H) adult male brains. UAS-mCD8::GFP calyx (A, E) shows the expression domain of the <i>R14H06-Gal4</i> driver in the mushroom body and is marked by yellow dashed lines and an asterisk. The scale bar represents 10 μm. DAPI (B, F) is shown to identify nuclei and note the low nuclear density in the peduncle, which is indicated with a P. Trr (C, G) is labeled by immunohistochemistry using an anti-trr antibody. The overlay of DAPI and trr signal (D, H) shows a reduction of trr in the target cells (blue and red channels). (I-J) Confocal projections showing the main axonal lobes of the mushroom body that are labeled by <i>UAS-mDC8</i>::<i>GFP</i> through expression with the <i>R14H06-Gal4</i> driver in control flies (I) and trr knockdown flies (J). The scale bar represents 10 μm. (K) Standard boxplots representing the courtship indexes (CIs) resulting from courtship conditioning in control and trr knockdown flies. + indicates the mean. The mean CI for naïve and trained flies was compared using the Mann-Whitney test. (L) Learning Indexes (LI) for controls and trr knockdown flies derived from the CIs. Trr knockdown males have a significantly reduced LI (randomization test, 10,000 bootstrap replicates).</p

Trr localizes to promoters of neuronal genes in <i>Drosophila</i> heads and shows a significant overlap with G9a targets.

<p>(A) Pie-chart representing the location of trr binding sites in annotated genomic features as specified by HOMER software. (B) Fold enrichment of trr binding sites in annotated genomic features compared to an equivalent group of random genomic positions. (C) Average trr occupancy (black) of all transcription start sites (tss) relative to the –1kb region compared to the average read depth in the input control (grey). (D) Gene ontology enrichment analysis of genes with a trr binding site near the tss. Shown here are the top 10 enriched terms. (E) Venn diagram showing the overlap between predicted trr target genes identified here, and predicted G9a targets that were previously published [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006864#pgen.1006864.ref018" target="_blank">18</a>]. The overlap of 1047 genes is larger than expected by random chance, based on a hypergeometric test (p-value = 1.9*10⁻³⁷ and 1.35 times enriched). (F) Top 10 enriched GO terms for biological processes identified for the 1047 overlapping predicted targets for G9a and trr. For D and F, enrichment is indicated by black bars (lower x-axis), and the –log10 transformation of p-values is indicated by grey bars (upper x-axis).</p

Differentially expressed genes in <i>trr</i> and <i>G9a</i> mutants show a strong biological overlap.

<p>(A,C) Scatter plots showing Log2 fold changes plotted against the Log2 normalized expression. Significantly up and down regulated genes (p-adj < 0.05, FC > 1.5) are represented by red and blue dots respectively in the G9a (A) and trr (C) mutant. Enriched GO terms are shown for differentially expressed genes in trr (B) and G9a (D) mutant heads. (E) Venn Diagram showing the overlap of differential expressed genes between the two mutant conditions. The overlap of 119 is significantly more than expected by random chance, based on a hypergeometric test (p-value = 6.4*10⁻²³ and 2.7 times enriched). (F) GO term enrichment of the 119 overlapping genes. (B,D,F) Enriched GO terms were identified using the Panther software (GO-slim setting). The –log10 transformation of p-values is indicated by black bars (lower x-axis). Grey bars (upper x-axis) indicate enrichment. GO terms that overlap between the different datasets in panels B,D, and F, are indicated in bold.</p

Patients and identified <i>KMT2C</i> mutations.

<p>(A) Schematic view of the KMT2C protein with reported domains (purple: AT hook DNA binding domain; dark blue: zinc finger domain; yellow: cysteine rich; orange: High mobility group (HMG); dark red: Ring finger; light blue: "FY-rich" domain; dark green: SET and Post-SET domains) and identified frameshift mutations (open lollipops), nonsense mutations (closed lollipops) and deletion. Scale bar represents amino acid position. (B) Frontal and lateral photographs of individual 1 at age 29 years, individual 2 at age 31 years, and individual 3 at age 15 years. Though there are variable facial features, dysmorphisms consistent with Kleeftra syndrome are observed, including flattened midface (individual 1 and 4), prominent eyebrows (individuals 1 and 3), everted lower lip (individual 4), and thick ear helices (individuals 1 and 3). Photographs of individual 4 and 5 are not shown.</p

Gene discovery for Mendelian conditions via social networking: de novo variants in KDM1A cause developmental delay and distinctive facial features

PURPOSE: The pace of Mendelian gene discovery is slowed by the "n-of-1 problem"-the difficulty of establishing the causality of a putatively pathogenic variant in a single person or family. Identification of an unrelated person with an overlapping phenotype and suspected pathogenic variant in the same gene can overcome this barrier, but it is often impeded by lack of a convenient or widely available way to share data on candidate variants/genes among families, clinicians, and researchers. METHODS: Social networking among families, clinicians, and researchers was used to identify three children with variants of unknown significance in KDM1A and similar phenotypes. RESULTS: De novo variants in KDM1A underlie a new syndrome characterized by developmental delay and distinctive facial features. CONCLUSION: Social networking is a potentially powerful strategy to discover genes for rare Mendelian conditions, particularly those with nonspecific phenotypic features. To facilitate the efforts of families to share phenotypic and genomic information with each other, clinicians, and researchers, we developed the Repository for Mendelian Genomics Family Portal (RMD-FP; http://uwcmg.org/#/family). Design and development of MyGene2 (http://www.mygene2.org), a Web-based tool that enables families, clinicians, and researchers to search for gene matches based on analysis of phenotype and exome data deposited into the RMD-FP, is under way

Clinical spectrum of STX1B-related epileptic disorders.

OBJECTIVE: The aim of this study was to expand the spectrum of epilepsy syndromes related to STX1B, encoding the presynaptic protein syntaxin-1B, and establish genotype-phenotype correlations by identifying further disease-related variants. METHODS: We used next-generation sequencing in the framework of research projects and diagnostic testing. Clinical data and EEGs were reviewed, including already published cases. To estimate the pathogenicity of the variants, we used established and newly developed in silico prediction tools. RESULTS: We describe 17 new variants in STX1B, which are distributed across the whole gene. We discerned 4 different phenotypic groups across the newly identified and previously published patients (49 patients in 23 families): (1) 6 sporadic patients or families (31 affected individuals) with febrile and afebrile seizures with a benign course, generally good drug response, normal development, and without permanent neurologic deficits; (2) 2 patients with genetic generalized epilepsy without febrile seizures and cognitive deficits; (3) 13 patients or families with intractable seizures, developmental regression after seizure onset and additional neuropsychiatric symptoms; (4) 2 patients with focal epilepsy. More often, we found loss-of-function mutations in benign syndromes, whereas missense variants in the SNARE motif of syntaxin-1B were associated with more severe phenotypes. CONCLUSION: These data expand the genetic and phenotypic spectrum of STX1B-related epilepsies to a diverse range of epilepsies that span the International League Against Epilepsy classification. Variants in STX1B are protean and contribute to many different epilepsy phenotypes, similar to SCN1A, the most important gene associated with fever-associated epilepsies

Data from: Clinical spectrum of STX1B-related epileptic disorders

Objective: The aim of this study was to expand the spectrum of epilepsy syndromes related to STX1B, encoding the presynaptic protein syntaxin-1B, and establish genotype-phenotype correlations by identifying further disease-related variants. Methods: We used next generation sequencing in the framework of research projects and diagnostic testing. Clinical data and EEGs were reviewed, including already published cases. To estimate the pathogenicity of the variants, we used established and newly developed in silico prediction tools. Results: We describe 15 new variants in STX1B which are distributed across the whole gene. We discerned four different phenotypic groups across the newly identified and previously published patients (49 patients in 23 families): 1) Six sporadic patients or families (31 affected individuals) with febrile and afebrile seizures with a benign course, generally good drug response, normal development and without permanent neurological deficits; 2) two patients with genetic generalized epilepsy without febrile seizures and cognitive deficits; 3) 13 patients or families with intractable seizures, developmental regression after seizure onset and additional neuropsychiatric symptoms; 4) two patients with focal epilepsy. More often we found loss-of-function mutations in benign syndromes, whereas missense variants in the SNARE motif of syntaxin-1B were associated with more severe phenotypes. Conclusion: These data expand the genetic and phenotypic spectrum of STX1B-related epilepsies to a diverse range of epilepsies that span the ILAE classification. Variants in STX1B are protean and contribute to many different epilepsy phenotypes, similar to SCN1A, the most important gene associated with fever-associated epilepsies