De novo and rare inherited copy-number variations in the hemiplegic form of cerebral palsy.

PurposeHemiplegia is a subtype of cerebral palsy (CP) in which one side of the body is affected. Our earlier study of unselected children with CP demonstrated de novo and clinically relevant rare inherited genomic copy-number variations (CNVs) in 9.6% of participants. Here, we examined the prevalence and types of CNVs specifically in hemiplegic CP.MethodsWe genotyped 97 unrelated probands with hemiplegic CP and their parents. We compared their CNVs to those of 10,851 population controls, in order to identify rare CNVs (<0.1% frequency) that might be relevant to CP. We also sequenced exomes of "CNV-positive" trios.ResultsWe detected de novo CNVs and/or sex chromosome abnormalities in 7/97 (7.2%) of probands, impacting important developmental genes such as GRIK2, LAMA1, DMD, PTPRM, and DIP2C. In 18/97 individuals (18.6%), rare inherited CNVs were found, affecting loci associated with known genomic disorders (17p12, 22q11.21) or involving genes linked to neurodevelopmental disorders.ConclusionWe found an increased rate of de novo CNVs in the hemiplegic CP subtype (7.2%) compared to controls (1%). This result is similar to that for an unselected CP group. Combined with rare inherited CNVs, the genomic data impacts the understanding of the potential etiology of hemiplegic CP in 23/97 (23.7%) of participants.

Functional impact of global rare copy number variation in autism spectrum disorders.

The autism spectrum disorders (ASDs) are a group of conditions characterized by impairments in reciprocal social interaction and communication, and the presence of restricted and repetitive behaviours. Individuals with an ASD vary greatly in cognitive development, which can range from above average to intellectual disability. Although ASDs are known to be highly heritable ( approximately 90%), the underlying genetic determinants are still largely unknown. Here we analysed the genome-wide characteristics of rare (<1% frequency) copy number variation in ASD using dense genotyping arrays. When comparing 996 ASD individuals of European ancestry to 1,287 matched controls, cases were found to carry a higher global burden of rare, genic copy number variants (CNVs) (1.19 fold, P = 0.012), especially so for loci previously implicated in either ASD and/or intellectual disability (1.69 fold, P = 3.4 x 10(-4)). Among the CNVs there were numerous de novo and inherited events, sometimes in combination in a given family, implicating many novel ASD genes such as SHANK2, SYNGAP1, DLGAP2 and the X-linked DDX53-PTCHD1 locus. We also discovered an enrichment of CNVs disrupting functional gene sets involved in cellular proliferation, projection and motility, and GTPase/Ras signalling. Our results reveal many new genetic and functional targets in ASD that may lead to final connected pathways.

A genome-wide scan for common alleles affecting risk for autism.

Although autism spectrum disorders (ASDs) have a substantial genetic basis, most of the known genetic risk has been traced to rare variants, principally copy number variants (CNVs). To identify common risk variation, the Autism Genome Project (AGP) Consortium genotyped 1558 rigorously defined ASD families for 1 million single-nucleotide polymorphisms (SNPs) and analyzed these SNP genotypes for association with ASD. In one of four primary association analyses, the association signal for marker rs4141463, located within MACROD2, crossed the genome-wide association significance threshold of P < 5 × 10(-8). When a smaller replication sample was analyzed, the risk allele at rs4141463 was again over-transmitted; yet, consistent with the winner's curse, its effect size in the replication sample was much smaller; and, for the combined samples, the association signal barely fell below the P < 5 × 10(-8) threshold. Exploratory analyses of phenotypic subtypes yielded no significant associations after correction for multiple testing. They did, however, yield strong signals within several genes, KIAA0564, PLD5, POU6F2, ST8SIA2 and TAF1C.

The Centre for Modeling Human Disease Gene Trap resource.

Gene trap mutagenesis of mouse embryonic stem cells generates random loss-of-function mutations, which can be identified by a sequence tag and can often report the endogenous expression of the mutated gene. The Centre for Modeling Human Disease is performing expression- and sequence-based screens of gene trap insertions to generate new mouse mutations as a resource for the scientific community. The gene trap insertions are screened using multiplexed in vitro differentiation and induction assays, and sequence tags are generated to complement expression profiles. Researchers may search for insertions in genes expressed in target cell lineages, under specific in vitro conditions, or based upon sequence identity via an online searchable database (http://www.cmhd.ca/sub/genetrap.asp). The clones are available as a resource to researchers worldwide to help to functionally annotate the mammalian genome and will serve as a source to test candidate loci identified by phenotype-driven mutagenesis screens.

Transcriptome-wide characterization of the endogenous miR-34A-p53 tumor suppressor network.

microRNA-34A is a critical component of the p53 network and expression of miR- 34A is down-regulated by promoter hypermethylation or focal deletions in numerous human cancers. Although miR-34A deregulation may be an important driver in cancer, the endogenous role of this microRNA in cellular homeostasis is not well characterized. To address this knowledge gap, we aimed to determine the transcriptional landscape of the miR-34A-p53 axis in non-transformed cells. Using primary skin-derived fibroblast cell lines from patients who developed childhood cancers, and who harbor either germline TP53 mutations or are TP53 wild type, we sought to characterize the transcriptional response to miR-34A modulation. Through transcriptome-wide RNA-Sequencing, we show for the first time that in human non- transformed cells harboring TP53 mutations, miR-34A functions in a noncanonical manner to influence noncoding RNA networks, including RNA components of the minor (U12) spliceosome, as well as TP53-dependent and independent epigenetic pathways. miR- 34A-regulated transcripts include known cell cycle mediators and abrogation of miR-34A leads to a TP53-dependent increase in the fraction of cells in G2/M. Collectively, these results provide a framework for understanding the endogenous role of the miR-34A signaling axis and identify novel transcripts and pathways regulated by the essential miR-34A-p53 tumor suppressor network.

Gene and miRNA expression profiles in autism spectrum disorders.

Accumulating data indicate that there is significant genetic heterogeneity underlying the etiology in individuals diagnosed with autism spectrum disorder (ASD). Some rare and highly-penetrant gene variants and copy number variation (CNV) regions including NLGN3, NLGN4, NRXN1, SHANK2, SHANK3, PTCHD1, 1q21.1, maternally-inherited duplication of 15q11-q13, 16p11.2, amongst others, have been identified to be involved in ASD. Genome-wide association studies have identified other apparently low risk loci and in some other cases, ASD arises as a co-morbid phenotype with other medical genetic conditions (e.g. fragile X). The progress studying the genetics of ASD has largely been accomplished using genomic analyses of germline-derived DNA. Here, we used gene and miRNA expression profiling using cell-line derived total RNA to evaluate possible transcripts and networks of molecules involved in ASD. Our analysis identified several novel dysregulated genes and miRNAs in ASD compared with controls, including HEY1, SOX9, miR-486 and miR-181b. All of these are involved in nervous system development and function and some others, for example, are involved in NOTCH signaling networks (e.g. HEY1). Further, we found significant enrichment in molecules associated with neurological disorders such as Rett syndrome and those associated with nervous system development and function including long-term potentiation. Our data will provide a valuable resource for discovery purposes and for comparison to other gene expression-based, genome-wide DNA studies and other functional data.