Monge Molly, Giovanetti Simone M, Ravishankar Apoorva, Sadhu Meru J
Center for Genomics and Data Science Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.
G3 (Bethesda). 2025 Jul 14. doi: 10.1093/g3journal/jkaf146.
Many biological experiments involve studying the differences caused by genetic modifications, including genotypes composed of modifications at more than 1 locus. However, as the genotypes increase in number and complexity, it becomes a major challenge to independently generate and track the necessary number of biological replicate samples. A major development in genetic studies of large numbers of genotypes has been the use of barcode tracking. Inspired by such high-throughput studies, we developed a barcode-based method to track large numbers of independent replicates of a small number of combinatorial genotypes in a pooled format, enabling robust detection of subtle phenotypic differences. To construct a plasmid library of combinatorial genotypes, we utilized a nested serial cloning process to combine gene variants of interest that have associated DNA barcodes. The final plasmids each contain variants of multiple genes of interest, and a combined barcode that specifies the genotype of all the genes while also encoding a random sequence for tracking individual replicates. Sequencing of the pool of barcodes by next-generation sequencing allows the whole population to be studied in a single flask, enabling a high degree of replication even for complex genotypes. Using this approach, we tested the functionality of combinations of yeast, human, and null orthologs of the nucleotide excision repair factor I (NEF-1) complex and found that yeast cells expressing all 3 yeast NEF-1 subunits had superior growth in DNA-damaging conditions. We also assessed the sensitivity of our method by simulating downsampling of barcodes across different degrees of phenotypic differentiation. Our results demonstrate the utility of NICR (nested identification combined with replication) barcodes for high-throughput combinatorial genetic screens and provide a scalable framework for exploring complex genotype-phenotype relationships.
许多生物学实验都涉及研究基因修饰所导致的差异，包括由多个位点修饰组成的基因型。然而，随着基因型数量和复杂性的增加，独立生成并追踪必要数量的生物学重复样本成为一项重大挑战。在对大量基因型进行基因研究方面的一项重大进展是使用条形码追踪技术。受此类高通量研究的启发，我们开发了一种基于条形码的方法，以汇集的形式追踪少量组合基因型的大量独立重复样本，从而能够可靠地检测细微的表型差异。为构建组合基因型的质粒文库，我们利用嵌套的连续克隆过程来组合带有相关DNA条形码的感兴趣的基因变体。最终的质粒各自包含多个感兴趣基因的变体，以及一个组合条形码，该条形码既指定了所有基因的基因型，同时还编码一个用于追踪单个重复样本的随机序列。通过下一代测序对条形码池进行测序，使得能够在单个培养瓶中研究整个群体，即使对于复杂的基因型也能实现高度的重复。使用这种方法，我们测试了核苷酸切除修复因子I（NEF-1）复合物的酵母、人类和无功能直系同源物组合的功能，发现表达所有3个酵母NEF-1亚基的酵母细胞在DNA损伤条件下具有更好的生长能力。我们还通过模拟在不同程度表型分化情况下对条形码的下采样来评估我们方法的灵敏度。我们的结果证明了NICR（嵌套鉴定与重复相结合）条形码在高通量组合遗传筛选中的实用性，并为探索复杂的基因型-表型关系提供了一个可扩展的框架。
