Supplementary Material for: Increasing Genotype-Phenotype Model Determinism: Application to Bivariate Reading/Language Traits and Epistatic Interactions in Language-Impaired Families
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https://figshare.com/articles/dataset/Supplementary_Material_for_Increasing_Genotype-Phenotype_Model_Determinism_Application_to_Bivariate_Reading_Language_Traits_and_Epistatic_Interactions_in_Language-Impaired_Families/5121409
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While advances in network and pathway analysis have flourished in the era of genome-wide association analysis, understanding the genetic mechanism of individual loci on phenotypes is still readily accomplished using genetic modeling approaches. Here, we demonstrate two novel genotype-phenotype models implemented in a flexible genetic modeling platform. The examples come from analysis of families with specific language impairment (SLI), a failure to develop normal language without explanatory factors such as low IQ or inadequate environment. In previous genome-wide studies, we observed strong evidence for linkage to 13q21 with a reading phenotype in language-impaired families. First, we elucidate the genetic architecture of reading impairment and quantitative language variation in our samples using a bivariate analysis of reading impairment in affected individuals jointly with language quantitative phenotypes in unaffected individuals. This analysis largely recapitulates the baseline analysis using the categorical trait data (posterior probability of linkage (PPL) = 80%), indicating that our reading impairment phenotype captured poor readers who also have low language ability. Second, we performed epistasis analysis using a functional coding variant in the brain-derived neurotrophic factor (BDNF) gene previously associated with reduced performance on working memory tasks. Modeling epistasis doubled the evidence on 13q21 and raised the PPL to 99.9%, indicating that BDNF and 13q21 susceptibility alleles are jointly part of the genetic architecture of SLI. These analyses provide possible mechanistic insights for further cognitive neuroscience studies based on the models developed herein.
尽管在全基因组关联分析(Genome-Wide Association Analysis)时代,网络与通路分析领域已取得蓬勃发展,但借助遗传建模方法解析单个基因座对表型的遗传作用机制,依然是较为便捷可行的研究手段。本文介绍了在灵活遗传建模平台中实现的两种新型基因型-表型模型。相关案例源自对特定语言障碍(Specific Language Impairment, SLI)家族的分析——特定语言障碍指在排除低智商、不良环境等明确解释因素后,仍无法发育出正常语言能力的病症。在既往全基因组研究中,我们曾在语言障碍家族中观察到阅读表型与13q21区域存在显著连锁证据。其一,我们通过对受累个体的阅读障碍表型与非受累个体的语言数量性状开展联合双变量分析,阐明了本研究队列中阅读障碍与数量化语言变异的遗传结构。该分析基本复现了使用分类性状数据进行的基线分析结果(连锁后验概率(Posterior Probability of Linkage, PPL)=80%),提示本研究的阅读障碍表型涵盖了同时伴随语言能力低下的阅读困难人群。其二,我们利用此前被证实与工作记忆任务表现降低相关的脑源性神经营养因子(Brain-Derived Neurotrophic Factor, BDNF)基因功能编码变异开展上位性分析。上位性建模使13q21区域的连锁证据提升一倍,将连锁后验概率提升至99.9%,表明BDNF与13q21易感等位基因共同参与了特定语言障碍的遗传结构构成。本研究基于构建的模型,为后续认知神经科学相关研究提供了潜在的机制性研究视角。
创建时间:
2017-06-20



