Institute for Quantitative and Computational Biosciences, UCLA, Los Angeles, CA, USA.
Departments of Integrative Biology and Physiology and Chemistry and Biochemistry, UCLA, Los Angeles, CA, USA.
Sci Rep. 2020 Nov 25;10(1):20566. doi: 10.1038/s41598-020-77638-2.
Gene expression variability, differences in the number of mRNA per cell across a population of cells, is ubiquitous across diverse organisms with broad impacts on cellular phenotypes. The role of chromatin in regulating average gene expression has been extensively studied. However, what aspects of the chromatin contribute to gene expression variability is still underexplored. Here we addressed this problem by leveraging chromatin diversity and using a systematic investigation of randomly integrated expression reporters to identify what aspects of chromatin microenvironment contribute to gene expression variability. Using DNA barcoding and split-pool decoding, we created a large library of isogenic reporter clones and identified reporter integration sites in a massive and parallel manner. By mapping our measurements of reporter expression at different genomic loci with multiple epigenetic profiles including the enrichment of transcription factors and the distance to different chromatin states, we identified new factors that impact the regulation of gene expression distributions.
基因表达的可变性，即在细胞群体中每个细胞的 mRNA 数量的差异，在不同的生物体中普遍存在，对细胞表型有广泛的影响。染色质在调节平均基因表达方面的作用已被广泛研究。然而，染色质的哪些方面导致了基因表达的可变性，这仍然是一个未被充分探索的问题。在这里，我们通过利用染色质多样性，并通过对随机整合的表达报告基因的系统研究，来解决这个问题，以确定染色质微环境的哪些方面导致了基因表达的可变性。我们使用 DNA 条形码和分裂池解码技术，创建了一个大型的同源报告基因克隆文库，并以大规模和并行的方式识别报告基因的整合位点。通过将我们在不同基因组位置的报告基因表达测量与包括转录因子富集和与不同染色质状态的距离在内的多种表观遗传特征进行映射，我们确定了影响基因表达分布调控的新因素。
