Dataset Information

Mapping autism risk loci using genetic linkage and chromosomal rearrangements.

ABSTRACT: Autism spectrum disorders (ASDs) are common, heritable neurodevelopmental conditions. The genetic architecture of ASDs is complex, requiring large samples to overcome heterogeneity. Here we broaden coverage and sample size relative to other studies of ASDs by using Affymetrix 10K SNP arrays and 1,181 [corrected] families with at least two affected individuals, performing the largest linkage scan to date while also analyzing copy number variation in these families. Linkage and copy number variation analyses implicate chromosome 11p12-p13 and neurexins, respectively, among other candidate loci. Neurexins team with previously implicated neuroligins for glutamatergic synaptogenesis, highlighting glutamate-related genes as promising candidates for contributing to ASDs.

SUBMITTER: Autism Genome Project Consortium

PROVIDER: S-EPMC4867008 | biostudies-literature | 2007 Mar

REPOSITORIES: biostudies-literature

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Mapping autism risk loci using genetic linkage and chromosomal rearrangements.

Szatmari Peter P Paterson Andrew D AD Zwaigenbaum Lonnie L Roberts Wendy W Brian Jessica J Liu Xiao-Qing XQ Vincent John B JB Skaug Jennifer L JL Thompson Ann P AP Senman Lili L Feuk Lars L Qian Cheng C Bryson Susan E SE Jones Marshall B MB Marshall Christian R CR Scherer Stephen W SW Vieland Veronica J VJ Bartlett Christopher C Mangin La Vonne LV Goedken Rhinda R Segre Alberto A Pericak-Vance Margaret A MA Cuccaro Michael L ML Gilbert John R JR Wright Harry H HH Abramson Ruth K RK Betancur Catalina C Bourgeron Thomas T Gillberg Christopher C Leboyer Marion M Buxbaum Joseph D JD Davis Kenneth L KL Hollander Eric E Silverman Jeremy M JM Hallmayer Joachim J Lotspeich Linda L Sutcliffe James S JS Haines Jonathan L JL Folstein Susan E SE Piven Joseph J Wassink Thomas H TH Sheffield Val V Geschwind Daniel H DH Bucan Maja M Brown W Ted WT Cantor Rita M RM Constantino John N JN Gilliam T Conrad TC Herbert Martha M Lajonchere Clara C Ledbetter David H DH Lese-Martin Christa C Miller Janet J Nelson Stan S Samango-Sprouse Carol A CA Spence Sarah S State Matthew M Tanzi Rudolph E RE Coon Hilary H Dawson Geraldine G Devlin Bernie B Estes Annette A Flodman Pamela P Klei Lambertus L McMahon William M WM Minshew Nancy N Munson Jeff J Korvatska Elena E Rodier Patricia M PM Schellenberg Gerard D GD Smith Moyra M Spence M Anne MA Stodgell Chris C Tepper Ping Guo PG Wijsman Ellen M EM Yu Chang-En CE Rogé Bernadette B Mantoulan Carine C Wittemeyer Kerstin K Poustka Annemarie A Felder Bärbel B Klauck Sabine M SM Schuster Claudia C Poustka Fritz F Bölte Sven S Feineis-Matthews Sabine S Herbrecht Evelyn E Schmötzer Gabi G Tsiantis John J Papanikolaou Katerina K Maestrini Elena E Bacchelli Elena E Blasi Francesca F Carone Simona S Toma Claudio C Van Engeland Herman H de Jonge Maretha M Kemner Chantal C Koop Frederieke F Langemeijer Marjolein M Hijmans Channa C Staal Wouter G WG Baird Gillian G Bolton Patrick F PF Rutter Michael L ML Weisblatt Emma E Green Jonathan J Green Jonathan J Aldred Catherine C Wilkinson Julie-Anne JA Pickles Andrew A Le Couteur Ann A Berney Tom T McConachie Helen H Bailey Anthony J AJ Francis Kostas K Honeyman Gemma G Hutchinson Aislinn A Parr Jeremy R JR Wallace Simon S Monaco Anthony P AP Barnby Gabrielle G Kobayashi Kazuhiro K Lamb Janine A JA Sousa Ines I Sykes Nuala N Cook Edwin H EH Guter Stephen J SJ Leventhal Bennett L BL Salt Jeff J Lord Catherine C Corsello Christina C Hus Vanessa V Weeks Daniel E DE Volkmar Fred F Tauber Maïté M Fombonne Eric E Shih Andy A Meyer Kacie J KJ

Nature genetics 20070218 3

Autism spectrum disorders (ASDs) are common, heritable neurodevelopmental conditions. The genetic architecture of ASDs is complex, requiring large samples to overcome heterogeneity. Here we broaden coverage and sample size relative to other studies of ASDs by using Affymetrix 10K SNP arrays and 1,181 [corrected] families with at least two affected individuals, performing the largest linkage scan to date while also analyzing copy number variation in these families. Linkage and copy number variati ...[more]

PMID: 17322880

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Project description:Using behavioral and genetic information from the Autism Genetics Resource Exchange (AGRE) data set we developed phenotypes and investigated linkage and association for individuals with and without Autism Spectrum Disorders (ASD) who exhibit expressive language behaviors consistent with a motor speech disorder. Speech and language variables from Autism Diagnostic Interview-Revised (ADI-R) were used to develop a motor speech phenotype associated with non-verbal or unintelligible verbal behaviors (NVMSD:ALL) and a related phenotype restricted to individuals without significant comprehension difficulties (NVMSD:C). Using Affymetrix 5.0 data, the PPL framework was employed to assess the strength of evidence for or against trait-marker linkage and linkage disequilibrium (LD) across the genome. Ingenuity Pathway Analysis (IPA) was then utilized to identify potential genes for further investigation. We identified several linkage peaks based on two related language-speech phenotypes consistent with a potential motor speech disorder: chromosomes 1q24.2, 3q25.31, 4q22.3, 5p12, 5q33.1, 17p12, 17q11.2, and 17q22 for NVMSD:ALL and 4p15.2 and 21q22.2 for NVMSD:C. While no compelling evidence of association was obtained under those peaks, we identified several potential genes of interest using IPA. CONCLUSION: Several linkage peaks were identified based on two motor speech phenotypes. In the absence of evidence of association under these peaks, we suggest genes for further investigation based on their biological functions. Given that autism spectrum disorders are complex with a wide range of behaviors and a large number of underlying genes, these speech phenotypes may belong to a group of several that should be considered when developing narrow, well-defined, phenotypes in the attempt to reduce genetic heterogeneity. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11689-010-9063-2) contains supplementary material, which is available to authorized users.

Project description:ObjectiveComplex chromosome rearrangements (CCR) are rare structural abnormalities involving at least three breakpoints, categorized into three types based on their structure: type A (three-way rearrangements), type B (double two-way translocations), and type C (exceptional CCR). However, thus far, limited data exists on preimplantation genetic testing for chromosomal structural rearrangements (PGT-SR) in CCR carriers. This study aims to evaluate the clinical outcomes and influencing factors of PGT-SR in couples with CCR.MethodsFifteen couples with unique CCR recruited from 793 couples following PGT-SR between January 2017 and May 2023. In addition, a total of 54 CCR cases, 39 previously reported as well as 15 newly added, were included in the analysis of factors associate with normal/balanced embryos.ResultsA total of 100 blastocysts were biopsied and analyzed in 15 CCR couples after 17 PGT-SR cycles, with 16.0% being euploid, 78.0% aneuploid and 6.0% mosaic. 11 normal/balanced embryos and one mosaic embryo were transferred, resulting in eight live births. Furthermore, based on the combined data from 54 CCR carriers, the proportion of normal/balanced embryos was 10.8%, with a significant decrease observed among female carriers compared to male heterozygotes (6.5% vs. 15.5%, p = 0.002). Type B exhibited the lowest rate of euploid embryos at only 6.7%, followed by type A at 11.6% and type C at 14.0%, although the differences were not significant (p = 0.182). After completing the multivariate generalized estimating equation (GEE) analysis, type B (p = 0.014) and female carrier (p = 0.002) were identified as independent risk factors for fewer euploid embryos.ConclusionThe occurrence of balanced CCR in patients with reproductive abnormalities may be more frequent than we expected. Despite the proportion of normal/balanced embryos being significantly low, which can be influenced by CCR type and carrier's sex, PGT-SR may improve the reproductive outcomes among CCR cases. These findings can optimize the clinical management and genetic counseling of CCR carriers seeking assisted reproductive technology (ART).

Project description:The aim of this study was to analyze the genomic homology between cattle (Bos taurus) and buffaloes (Bubalus bubalis) and to propose a rearrangement of the buffalo genome through linkage disequilibrium analyses of buffalo SNP markers referenced in the cattle genome assembly and also compare it to the buffalo genome assembly. A panel of bovine SNPs (single nucleotide polymorphisms) was used for hierarchical, non-hierarchical and admixture cluster analyses. Thus, the linkage disequilibrium information between markers of a specific panel of buffalo was used to infer chromosomal rearrangement. Haplotype diversity and imputation accuracy of the submetacentric chromosomes were also analyzed. The genomic homology between the species enabled us to use the bovine genome assembly to recreate a buffalo genomic reference by rearranging the submetacentric chromosomes. The centromere of the submetacentric chromosomes exhibited high linkage disequilibrium and low haplotype diversity. It allowed hypothesizing about chromosome evolution. It indicated that buffalo submetacentric chromosomes are a centric fusion of ancestral acrocentric chromosomes. The chronology of fusions was also suggested. Moreover, a linear regression between buffalo and cattle rearranged assembly and the imputation accuracy indicated that the rearrangement of the chromosomes was adequate. When using the bovine reference genome assembly, the rearrangement of the buffalo submetacentric chromosomes could be done by SNP BTA (chromosome of Bos taurus) calculations: shorter BTA (shorter arm of buffalo chromosome) was given as [(shorter BTA length - SNP position in shorter BTA)] and larger BTA length as [shorter BTA length + (larger BTA length - SNP position in larger BTA)]. Finally, the proposed linkage disequilibrium-based method can be applied to elucidate other chromosomal rearrangement events in other species with the possibility of better understanding the evolutionary relationship between their genomes.

Dataset Information

Mapping autism risk loci using genetic linkage and chromosomal rearrangements.

Publications

Mapping autism risk loci using genetic linkage and chromosomal rearrangements.

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