High-throughput genome engineering

高通量基因组工程

• 批准号: 10023084
• 负责人: Meru Sadhu
• 金额: $ 77.33万
• 依托单位: NATIONAL HUMAN GENOME RESEARCH INSTITUTE
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10023084
• 关键词: Biology; CRISPR/Cas technology; Cells; Clustered Regularly Interspaced Short Palindromic Repeats; DNA; Family; Frequencies; Genes; Genetic; Genetic Variation; Genetic study; Genome engineering; Genomics; Genotype; Goals; Guide RNA; Height; Heritability; Human; Individual; Learning; Link; Masks; Medicine; Methods; Mutation; Oligonucleotides; Outcome; Phenotype; Plasmids; Quantitative Trait Loci; Reporting; Systems Biology; Testing; Variant; Work; Yeast Model System; Yeasts; design; follower of religion Jewish; genetic information; genetic variant; genome wide association study; human study; interest; novel; rare variant; repaired; yeast genome

A major goal in genetics is to use genetic information to predict phenotype, which could have enormous impact in medicine and in our general understanding of biology. We are contributing towards this goal by using high-throughput genome engineering methods to generate and study thousands of genetic variants. This will allow us to understand the consequences of the specific variants we study, and also learn about the general principles underlying variant consequences for extension to the even broader space of untested variants. To accomplish high-throughput genome engineering, we use large-scale parallelized oligonucleotide synthesis to generate pools of thousands of unique yeast plasmids, each of which carries a guide RNA (gRNA) gene and a paired repair template encoding a specific mutation of interest. Following directed DNA cleavage by Cas9 using the gRNA, the repair template introduces the mutation in the yeast genome. The edited pool of yeast cells is then subjected to selection for a phenotype of interest. The abundances of the unique plasmids in the selected pool thus reports on the effect each genetic variant had on the phenotype under study. We are also developing new high-throughput genome engineering approaches. These include advancements to CRISPR technology, by expanding the space of genetic outcomes that CRISPR can target, as well as novel applications of high-throughput editing, such as careful deployment of CRISPR-directed deletions. In the past year, we contributed to a study of the genetics of human height in Jewish families. This study was designed to test the hypothesis that despite the majority of heritability in human height coming from common genetic variants, rare variants nonetheless might often have large phenotypic consequences, with this overall contribution to heritability being masked by such variants' rarity. By specifically looking at the genetics of height within families, rare variants will segregate at the same frequency as common variants, and thus quantitative trait loci (QTLs) uncovered in these families could have larger effect sizes than seen through genome-wide association studies on unrelated individuals. Indeed, this study found evidence of large-effect QTLs segregating in the families under study, supporting the initial hypothesis.

遗传学的一个主要目标是利用遗传信息来预测表型，这可能对医学和我们对生物学的一般理解产生巨大影响。我们正在通过使用高通量基因组工程方法来产生和研究数千种遗传变异来实现这一目标。这将使我们能够理解我们所研究的特定变体的后果，并了解变体后果的一般原则，以便扩展到更广阔的未经测试的变体空间。 为了实现高通量基因组工程，我们使用大规模并行寡核苷酸合成来生成数千个独特酵母质粒的池，每个质粒都携带一个指导RNA（gRNA）基因和一个编码特定突变的配对修复模板。在使用gRNA通过Cas9进行定向DNA切割后，修复模板在酵母基因组中引入突变。然后对编辑的酵母细胞池进行目标表型的选择。因此，所选池中独特质粒的丰度报告了每种遗传变异对所研究表型的影响。 我们还在开发新的高通量基因组工程方法。这些包括CRISPR技术的进步，通过扩大CRISPR可以靶向的遗传结果的空间，以及高通量编辑的新应用，例如CRISPR定向缺失的精心部署。 在过去的一年里，我们对犹太家庭中人类身高的遗传学研究做出了贡献。这项研究的目的是检验这样一个假设，即尽管人类身高的大部分遗传力来自常见的遗传变异，但罕见的变异往往会产生很大的表型后果，这种对遗传力的总体贡献被这种变异的罕见性所掩盖。通过专门研究家系内的身高遗传学，罕见变异将以与常见变异相同的频率分离，因此在这些家系中发现的数量性状基因座（QTL）可能比通过对无关个体的全基因组关联研究所看到的效应更大。事实上，这项研究发现的证据，大效应QTL分离的家庭正在研究中，支持最初的假设。