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Autism spectrum disorder (ASD) is a constellation of neurodevelopmental disorders with high phenotypic and genetic heterogeneity, complicating the discovery of causative genes. Through a forward genetics approach selecting for defective vocalization in mice, we identified Kdm5a as a candidate ASD gene. To validate our discovery, we generated a Kdm5a knockout mouse model (Kdm5a-/-) and confirmed that inactivating Kdm5a disrupts vocalization. In addition, Kdm5a-/- mice displayed repetitive behaviors, sociability deficits, cognitive dysfunction, and abnormal dendritic morphogenesis. Loss of KDM5A also resulted in dysregulation of the hippocampal transcriptome. To determine if KDM5A mutations cause ASD in humans, we screened whole exome sequencing and microarray data from a clinical cohort. We identified pathogenic KDM5A variants in nine patients with ASD and lack of speech. Our findings illustrate the power and efficacy of forward genetics in identifying ASD genes and highlight the importance of KDM5A in normal brain development and function.

Background NGLY1-CDDG is a congenital disorder of deglycosylation caused by a defective peptide:N-glycanase (PNG). To date, all but one of the reported patients have been diagnosed through whole-exome or whole-genome sequencing, as no biochemical marker was available to identify this disease in patients. Recently, a potential urinary biomarker was reported, but the data presented suggest that this marker may be excreted intermittently. Methods In this study, we performed untargeted direct-infusion high-resolution mass spectrometry metabolomics in seven dried blood spots (DBS) from four recently diagnosed NGLY1-CDDG patients, to test for small-molecule biomarkers, in order to identify a potential diagnostic marker. Results were compared to 125 DBS of healthy controls and to 238 DBS of patients with other diseases. Results We identified aspartylglycosamine as the only significantly increased compound with a median Z-score of 4.8 (range: 3.8–8.5) in DBS of NGLY1-CDDG patients, compared to a median Z-score of −0.1 (range: −2.1–4.0) in DBS of healthy controls and patients with other diseases. Discussion The increase of aspartylglycosamine can be explained by lack of function of PNG. PNG catalyzes the cleavage of the proximal N-acetylglucosamine residue of an N-glycan from the asparagine residue of a protein, a step in the degradation of misfolded glycoproteins. PNG deficiency results in a single N-acetylglucosamine residue left attached to the asparagine residue which results in free aspartylglycosamine when the glycoprotein is degraded. Thus, we here identified aspartylglycosamine as the first potential small-molecule biomarker in DBS for NGLY1-CDDG, making a biochemical diagnosis for NGLY1-CDDG potentially feasible.

BackgroundMammalian X and Y chromosomes share a common evolutionary origin and retain regions of high sequence similarity. Similar sequence content can confound the mapping of short next-generation sequencing reads to a reference genome. It is therefore possible that the presence of both sex chromosomes in a reference genome can cause technical artifacts in genomic data and affect downstream analyses and applications. Understanding this problem is critical for medical genomics and population genomic inference.ResultsHere, we characterize how sequence homology can affect analyses on the sex chromosomes and present XYalign, a new tool that (1) facilitates the inference of sex chromosome complement from next-generation sequencing data; (2) corrects erroneous read mapping on the sex chromosomes; and (3) tabulates and visualizes important metrics for quality control such as mapping quality, sequencing depth, and allele balance. We find that sequence homology affects read mapping on the sex chromosomes and this has downstream effects on variant calling. However, we show that XYalign can correct mismapping, resulting in more accurate variant calling. We also show how metrics output by XYalign can be used to identify XX and XY individuals across diverse sequencing experiments, including low- and high-coverage whole-genome sequencing, and exome sequencing. Finally, we discuss how the flexibility of the XYalign framework can be leveraged for other uses including the identification of aneuploidy on the autosomes. XYalign is available open source under the GNU General Public License (version 3).ConclusionsSex chromsome sequence homology causes the mismapping of short reads, which in turn affects downstream analyses. XYalign provides a reproducible framework to correct mismapping and improve variant calling on the sex chromsomes.

Mammalian X and Y chromosomes share a common evolutionary origin and retain regions of high sequence similarity. This sequence homology can cause the mismapping of short sequencing reads derived from the sex chromosomes and affect variant calling and other downstream analyses. Understanding and correcting this problem is critical for medical genomics and population genomic inference. Here, we characterize how sequence homology can affect analyses on the sex chromosomes and present XYalign, a new tool that: (1) facilitates the inference of sex chromosome complement from next-generation sequencing data; (2) corrects erroneous read mapping on the sex chromosomes; and (3) tabulates and visualizes important metrics for quality control such as mapping quality, sequencing depth, and allele balance. We show how these metrics can be used to identify XX and XY individuals across diverse sequencing experiments, including low and high coverage whole genome sequencing, and exome sequencing. We also show that XYalign corrects mismapped reads on the sex chromosomes, resulting in more accurate variant calling. Finally, we discuss how the flexibility of the XYalign framework can be leveraged for other use cases including the identification of aneuploidy on the autosomes. XYalign is available open source under the GNU General Public License (version 3).

Background Intellectual Disability (ID) is among the most common global disorders, yet etiology is unknown in ~30% of patients despite clinical assessment. Whole genome sequencing (WGS) is able to interrogate the entire genome, providing potential to diagnose idiopathic patients. Methods We conducted WGS on eight children with idiopathic ID and brain structural defects, and their normal parents; carrying out an extensive data analyses, using standard and discovery approaches. Results We verified de novo pathogenic single nucleotide variants (SNV) in ARID1B c.1595delG and PHF6 c.820C > T, potentially causative de novo two base indels in SQSTM1 c.115_116delinsTA and UPF1 c.1576_1577delinsA, and de novo SNVs in CACNB3 c.1289G > A, and SPRY4 c.508 T > A, of uncertain significance. We report results from a large secondary control study of 2081 exomes probing the pathogenicity of the above genes. We analyzed structural variation by four different algorithms including de novo genome assembly. We confirmed a likely contributory 165 kb de novo heterozygous 1q43 microdeletion missed by clinical microarray. The de novo assembly resulted in unmasking hidden genome instability that was missed by standard re-alignment based algorithms. We also interrogated regulatory sequence variation for known and hypothesized ID genes and present useful strategies for WGS data analyses for non-coding variation. Conclusion This study provides an extensive analysis of WGS in the context of ID, providing genetic and structural insights into ID and yielding diagnoses. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-3671-0) contains supplementary material, which is available to authorized users.