小柯机器人

美国麻省理工学院和哈佛大学布罗德研究所Elise B. Robinson和Daniel J. Weiner研究组合作提出，自闭症常见和罕见遗传影响在染色体16p上的统计和功能一致性。该研究于2022年10月24日发表于国际一流学术期刊《自然—遗传学》杂志上。

在目前的研究中，他们证明了从基因组的一个非常大的区域研究生物学机制的可行性，并利用这一策略来研究遗传对自闭症的影响。使用一种新的统计方法，他们确定了16号染色体的33-Mb p臂(16p)是对自闭症影响最大的常见多基因区域。该区域还包括与自闭症相关的16p11.2拷贝数变体。RNA测序数据分析显示，16p内常见的多基因影响和16p11.2缺失均与16p内平均基因表达的降低相关。罕见缺失和扩散性共同变异的转录效应在个体基因水平上是相关的，Hi-C数据分析揭示了染色质交互模式，这可能解释了这种转录一致性。

这些结果反映了一种从遗传关联数据中研究生物学机制的新方法，并表明常见和罕见的基因对自闭症的影响在16p区域的一致性。

研究人员表示，将遗传关联转化为机制的经典范式包括，迭代地将个体关联映射到它们作用的近端基因。

附：英文原文

Title: Statistical and functional convergence of common and rare genetic influences on autism at chromosome 16p

Author: Weiner, Daniel J., Ling, Emi, Erdin, Serkan, Tai, Derek J. C., Yadav, Rachita, Grove, Jakob, Fu, Jack M., Nadig, Ajay, Carey, Caitlin E., Baya, Nikolas, Bybjerg-Grauholm, Jonas, Berretta, Sabina, Macosko, Evan Z., Sebat, Jonathan, OConnor, Luke J., Hougaard, David M., Brglum, Anders D., Talkowski, Michael E., McCarroll, Steven A., Robinson, Elise B.

Issue&Volume: 2022-10-24

Abstract: The canonical paradigm for converting genetic association to mechanism involves iteratively mapping individual associations to the proximal genes through which they act. In contrast, in the present study we demonstrate the feasibility of extracting biological insights from a very large region of the genome and leverage this strategy to study the genetic influences on autism. Using a new statistical approach, we identified the 33-Mb p-arm of chromosome 16 (16p) as harboring the greatest excess of autism’s common polygenic influences. The region also includes the mechanistically cryptic and autism-associated 16p11.2 copy number variant. Analysis of RNA-sequencing data revealed that both the common polygenic influences within 16p and the 16p11.2 deletion were associated with decreased average gene expression across 16p. The transcriptional effects of the rare deletion and diffuse common variation were correlated at the level of individual genes and analysis of Hi-C data revealed patterns of chromatin contact that may explain this transcriptional convergence. These results reflect a new approach for extracting biological insight from genetic association data and suggest convergence of common and rare genetic influences on autism at 16p.

DOI: 10.1038/s41588-022-01203-y

Source: https://www.nature.com/articles/s41588-022-01203-y

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