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Transcription of coregulated genes occurs in the context of long-range chromosomal contacts that form multigene complexes. Such contacts and transcription are lost in knockout studies of transcription factors and structural chromatin proteins. To ask whether chromosomal contacts are required for cotranscription in multigene complexes, we devised a strategy using TALENs to cleave and disrupt gene loops in a well-characterized multigene complex. Monitoring this disruption using RNA FISH and immunofluorescence microscopy revealed that perturbing the site of contact had a direct effect on transcription of other interacting genes. Unexpectedly, this effect on cotranscription was hierarchical, with dominant and subordinate members of the multigene complex engaged in both intra-and interchromosomal contact. This observation reveals the profound influence of these chromosomal contacts on the transcription of coregulated genes in a multigene complex.

Long noncoding RNAs (lncRNAs) constitute the majority of transcripts in the mammalian genomes, and yet, their functions remain largely unknown. As part of the FANTOM6 project, we systematically knocked down the expression of 285 lncRNAs in human dermal fibroblasts and quantified cellular growth, morphological changes, and transcriptomic responses using Capped Analysis of Gene Expression (CAGE). Antisense oligonucleotides targeting the same lncRNAs exhibited global concordance, and the molecular phenotype, measured by CAGE, recapitulated the observed cellular phenotypes while providing additional insights on the affected genes and pathways. Here, we disseminate the largest-todate lncRNA knockdown data set with molecular phenotyping (over 1000 CAGE deep-sequencing libraries) for further exploration and highlight functional roles for ZNF213-AS1 and lnc-KHDC3L-2.

Single-cell transcriptomic profiling is a powerful tool to explore cellular heterogeneity. However, most of these methods focus on the 3′-end of polyadenylated transcripts and provide only a partial view of the transcriptome. We introduce C1 CAGE, a method for the detection of transcript 5′-ends with an original sample multiplexing strategy in the C1TM microfluidic system. We first quantifiy the performance of C1 CAGE and find it as accurate and sensitive as other methods in the C1 system. We then use it to profile promoter and enhancer activities in the cellular response to TGF-β of lung cancer cells and discover subpopulations of cells differing in their response. We also describe enhancer RNA dynamics revealing transcriptional bursts in subsets of cells with transcripts arising from either strand in a mutually exclusive manner, validated using single molecule fluorescence in situ hybridization.

26Single-cell transcriptomic profiling is a powerful tool to explore cellular heterogeneity. However, 27 most of these methods focus on the 3'-end of polyadenylated transcripts and provide only a 28 partial view of the transcriptome. We introduce C1 CAGE, a method for the detection of 29 transcript 5'-ends with an original sample multiplexing strategy in the C1 TM microfluidic system. 30We first quantified the performance of C1 CAGE and found it as accurate and sensitive as other 31 methods in C1 system. We then used it to profile promoter and enhancer activities in the cellular 32 response to TGF-β of lung cancer cells and discovered subpopulations of cells differing in their 33 response. We also describe enhancer RNA dynamics revealing transcriptional bursts in subsets 34 of cells with transcripts arising from either strand within a single-cell in a mutually exclusive 35 manner, which was validated using single molecule fluorescence in-situ hybridization. 37Single-cell transcriptomic profiling can be used to uncover the dynamics of cellular states and 38 gene regulatory networks within a cell population (Trapnell, 2015; Wagner, Regev and Yosef, 39 2016). Most available single-cell methods capture the 3'-end of transcripts and are unable to 40 identify where transcription initiates. Instead, capturing the 5'-end of transcripts allows the 41 identification of transcription start sites (TSS) and thus the inference of the activities of their 42 regulatory elements. Cap analysis gene expression (CAGE), which captures the 5'-end of 43 transcripts, is a powerful tool to identify TSS at single nucleotide resolution (Shiraki et al., 2003; 44 Carninci et al., 2006). Using this technique, the FANTOM consortium has built an atlas of TSS 45 across major human cell-types and tissues (Forrest et al., 2014), analysis of which has led to the 46 identification of promoters as well as enhancers in the human genome (Andersson et al., 2014; 47 Hon et al., 2017). Enhancers have been implicated in a variety of biological processes (Lam et 48 al., 2014; Li, Notani and Rosenfeld, 2016), including the initial activation of responses to 49 stimuli (Arner et al., 2015) and chromatin remodeling for transcriptional activation (Mousavi et al., 50 2013). In addition, over 60% of the fine-mapped causal noncoding variants in autoimmune 51 disease lay within immune-cell enhancers (Farh et al., 2015), suggesting the relevance of 52 enhancers in pathogenesis of complex diseases. Enhancers have been identified by the 53 presence of balanced bidirectional transcription producing enhancer RNAs (eRNAs), which are 54 generally short, unstable and non-polyadenylated (non-polyA) (Andersson et al., 2014). Single 55 molecule fluorescence in situ hybridization (smFISH) studies have suggested that eRNAs are 56 induced with similar kinetics to their target mRNAs but that co-expression at individual alleles 57 was infrequent (Rahman et al., 2016). However, the majority of enhancer studies have been 58 conducted using bulk populations of cells...