Copy number variation in fetal alcohol spectrum disorder.

Fetal alcohol spectrum disorder (FASD) is characterized by a combination of neurological, developmental, and congenital defects that may occur as a consequence of prenatal alcohol exposure. Earlier reports showed that large chromosomal anomalies may link to FASD. Here, we examined the prevalence and types of copy number variations (CNVs) in FASD cases previously diagnosed by a multidisciplinary FASD team in sites across Canada. We genotyped 95 children with FASD and 87 age-matched, typically developing controls on the Illumina Human Omni2.5 SNP (single nucleotide polymorphisms) array platform. We compared their CNVs with those of 10 851 population controls to identify rare CNVs (<0.1% frequency), which may include large unbalanced chromosomal abnormalities, that might be relevant to FASD. In 12/95 (13%) of the FASD cases, rare CNVs were found that impact potentially clinically relevant developmental genes, including the CACNA1H involved in epilepsy and autism, the 3q29 deletion disorder, and others. Our results show that a subset of children diagnosed with FASD have chromosomal deletions and duplications that may co-occur or explain the neurodevelopmental impairments in a diagnosed cohort of FASD individuals. Children suspected to have FASD with or without sentinel facial features of fetal alcohol syndrome and neurodevelopmental delays should potentially be evaluated by a clinical geneticist and possibly have genetic investigations as appropriate to exclude other etiologies.

Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects.

Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (odds ratio (OR) = 1.11, P = 5.7 × 10-15), which persisted after excluding loci implicated in previous studies (OR = 1.07, P = 1.7 × 10-6). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 × 10-11) and neurobehavioral phenotypes in mouse (OR = 1.18, P = 7.3 × 10-5). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by nonallelic homologous recombination.

The accuracy of several multiple sequence alignment programs for proteins.

BACKGROUND: There have been many algorithms and software programs implemented for the inference of multiple sequence alignments of protein and DNA sequences. The "true" alignment is usually unknown due to the incomplete knowledge of the evolutionary history of the sequences, making it difficult to gauge the relative accuracy of the programs. RESULTS: We tested nine of the most often used protein alignment programs and compared their results using sequences generated with the simulation software Simprot which creates known alignments under realistic and controlled evolutionary scenarios. We have simulated more than 30,000 alignment sets using various evolutionary histories in order to define strengths and weaknesses of each program tested. We found that alignment accuracy is extremely dependent on the number of insertions and deletions in the sequences, and that indel size has a weaker effect. We also considered benchmark alignments from the latest version of BAliBASE and the results relative to BAliBASE- and Simprot-generated data sets were consistent in most cases. CONCLUSION: Our results indicate that employing Simprot's simulated sequences allows the creation of a more flexible and broader range of alignment classes than the usual methods for alignment accuracy assessment. Simprot also allows for a quick and efficient analysis of a wider range of possible evolutionary histories that might not be present in currently available alignment sets. Among the nine programs tested, the iterative approach available in Mafft (L-INS-i) and ProbCons were consistently the most accurate, with Mafft being the faster of the two.