Barcoded RNA-seq libraries were sequenced as 150-bp paired-end reads using the Illumina HiSeq 4000 platform. Reads were mapped to the reference genome (GRCh37/hg19) using TopHat2 (51) with a GENCODE GTF file supplied as gene model annotations. HTSeq (52) was used to quantitate the abundance of transcripts for each gene. DESeq2 (53) was used to perform normalization and regularized log transformations on read counts. PCA was conducted with regularized log-transformed data. Hierarchical clustering was performed over samples with replicates. Euclidean distance and complete linkage were used as a clustering metric and method, respectively. Lists of genes with differential transcript abundance between enhancer KO and WT samples were obtained on the basis of the following criteria: (i) Benjamini-Hochberg adjusted P < 0.1 and (ii) fold change of transcript abundance (enhancer KO versus WT) >1.5 for up-regulation or <1 or 1.5 for down-regulation. Differentially expressed genes were subjected to functional classification analysis with DAVID (Database for Annotation, Visualization and Integrated Discovery) version 6.8 (54, 55). We applied Gene Cluster 3.0 ( software to perform clustering analysis on the gene expression data. Genes were centered by means across samples, and hierarchical clustering was performed over genes and samples. The similarity metric of Euclidean distance and the clustering method of complete linkage were used. Clustering results were examined and visualized in Java TreeView (

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