Lu Xiaona, Ni Pengyu, Suarez-Meade Paola, Ma Yu, Forrest Emily Niemitz, Wang Guilin, Wang Yi, Quiñones-Hinojosa Alfredo, Gerstein Mark, Jiang Yong-Hui
Department of Genetics, Yale University School of Medicine New Haven, CT, 06520 USA.
Biomedical Informatics & Data Science, Yale University School of Medicine New Haven, CT, 06520 USA.
bioRxiv. 2024 Mar 19:2024.03.18.585480. doi: 10.1101/2024.03.18.585480.
Precision of transcription is critical because transcriptional dysregulation is disease causing. Traditional methods of transcriptional profiling are inadequate to elucidate the full spectrum of the transcriptome, particularly for longer and less abundant mRNAs. is one of the most common autism causative genes. Twenty-four mutant animal lines have been developed for autism modeling. However, their preclinical validity has been questioned due to incomplete transcript structure. We applied an integrative approach combining cDNA-capture and long-read sequencing to profile the transcriptome in human and mice. We unexpectedly discovered an extremely complex transcriptome. Specific transcripts were altered in mutant mice and postmortem brains tissues from individuals with ASD. The enhanced transcriptome significantly improved the detection rate for potential deleterious variants from genomics studies of neuropsychiatric disorders. Our findings suggest the stochastic transcription of genome associated with family genes.
转录的精确性至关重要,因为转录失调会引发疾病。传统的转录谱分析方法不足以阐明转录组的全貌,尤其是对于较长且丰度较低的mRNA。[基因名称]是最常见的自闭症致病基因之一。已经开发了24种[基因名称]突变动物模型用于自闭症建模。然而,由于[基因名称]转录结构不完整,它们的临床前有效性受到质疑。我们应用了一种结合cDNA捕获和长读长测序的综合方法来分析人类和小鼠的[基因名称]转录组。我们意外地发现了一个极其复杂的[基因名称]转录组。特定的[基因名称]转录本在[基因名称]突变小鼠和自闭症谱系障碍(ASD)个体的死后脑组织中发生了改变。增强的[基因名称]转录组显著提高了神经精神疾病基因组学研究中潜在有害变异的检测率。我们的研究结果表明与[基因家族名称]基因相关的基因组的随机转录。