Neuropsychiatric phenotypes have long been known to be influenced by heritable risk factors, directly confirmed by the past decade of genetic studies that have revealed specific genetic variants enriched in disease cohorts. However, the initial hope that a small set of genes would be responsible for a given disorder proved false. The more complex reality is that a given disorder may be influenced by myriad small-effect noncoding variants and/or by rare but severe coding variants, many de novo. Noncoding genomic sequences-for which molecular functions cannot usually be inferred-harbor a large portion of these variants, creating a substantial barrier to understanding higher-order molecular and biological systems of disease. Fortunately, novel genetic technologies-scalable oligonucleotide synthesis, RNA sequencing, and CRISPR (clustered regularly interspaced short palindromic repeats)-have opened novel avenues to experimentally identify biologically significant variants en masse. Massively parallel reporter assays (MPRAs) are an especially versatile technique resulting from such innovations. MPRAs are powerful molecular genetics tools that can be used to screen thousands of untranscribed or untranslated sequences and their variants for functional effects in a single experiment. This approach, though underutilized in psychiatric genetics, has several useful features for the field. We review methods for assaying putatively functional genetic variants and regions, emphasizing MPRAs and the opportunities they hold for dissection of psychiatric polygenicity. We discuss literature applying functional assays in neurogenetics, highlighting strengths, caveats, and design considerations-especially regarding disease-relevant variables (cell type, neurodevelopment, and sex), and we ultimately propose applications of MPRA to both computational and experimental neurogenetics of polygenic disease risk.

中文翻译：

---

大规模并行报告分析：定义跨生物背景的功能性精神病遗传变异。

长期以来，人们都知道神经精神表型受到遗传危险因素的影响，过去十年的遗传学研究直接证实了这一点，这些研究揭示了疾病群体中丰富的特定遗传变异。然而，最初认为一小部分基因会导致某种特定疾病的希望被证明是错误的。更复杂的现实是，某种疾病可能会受到无数小效应非编码变异和/或罕见但严重的编码变异的影响，其中许多是从头开始的。非编码基因组序列（通常无法推断其分子功能）包含大部分这些变异，为理解疾病的高级分子和生物系统造成了巨大障碍。幸运的是，新的遗传技术——可扩展的寡核苷酸合成、RNA测序和CRISPR（成簇的规则间隔的短回文重复序列）——已经为通过实验识别大量具有生物学意义的变异开辟了新的途径。大规模并行报告分析 (MPRA) 是此类创新带来的一种特别通用的技术。MPRA 是强大的分子遗传学工具，可用于在单个实验中筛选数千个未转录或未翻译的序列及其变体的功能效果。这种方法虽然在精神遗传学中没有得到充分利用，但对该领域有几个有用的特征。我们回顾了分析假定的功能性遗传变异和区域的方法，强调 MPRA 及其为剖析精神病多基因性提供的机会。我们讨论了在神经遗传学中应用功能测定的文献，强调了优点、注意事项和设计注意事项，特别是关于疾病相关变量（细胞类型、神经发育和性别），我们最终提出将 MPRA 应用到多基因疾病的计算和实验神经遗传学中风险。