Chromatin-based mechanisms to coordinate convergent overlapping transcription

In eukaryotic genomes, transcription units of genes often overlap with other protein-coding and/or noncoding transcription units1,2. In such intertwined genomes, coordinated transcription of nearby or overlapping genes would be important to ensure integrity of genome function; however, the mechanisms underlying this coordination are largely unknown3-6. Here, we show in Arabidopsis thaliana that genes with convergent orientation of transcription are major sources of overlapping bidirectional transcripts and that these bidirectionally transcribed genes are regulated by a putative LSD1 family histone demethylase, FLD7,8. Our genome-wide chromatin profiling revealed that FLD downregulated histone H3K4me1 in regions with convergent overlapping transcription. FLD localizes to actively transcribed genes where it colocalizes with elongating RNA polymerase II phosphorylated at Ser-2 or Ser-5 sites. Genome-wide transcription analyses suggest that FLD-mediated H3K4me1 removal negatively regulates bidirectional transcription by retaining the elongating transcription machinery. Furthermore, this effect of FLD on transcription dynamics is mediated by DNA topoisomerase I. Our study has revealed chromatin-based mechanisms to cope with overlapping bidirectional transcription, likely by modulating DNA topology. This global mechanism to cope with bidirectional transcription could be co-opted for specific epigenetic processes, such as cellular memory of responses to environment9.

Dissecting chronic myeloid leukaemia overlapping transcriptome with TIF-Seq2

ABSTRACTEukaryotic transcriptomes are complex involving thousands of overlapping transcripts. The interleaved nature of the transcriptome limits our ability to identify regulatory regions and, in some cases, can lead to misinterpretation of gene expression. To improve the understanding of the overlapping transcriptome, we have developed an optimized method, TIF-Seq2, able to sequence simultaneously the 5’ and 3’ ends of individual RNA molecules at single-nucleotide resolution. We investigated the transcriptome of a well characterized human cell line (K562) and identify thousands of unannotated transcript isoforms. By focusing on transcripts which are challenging to be investigated with RNA-seq, we accurately defined boundaries of lowly expressed unannotated and read-though transcripts putatively encoding fusion genes. We validated our results by targeted long-read sequencing and standard RNA-Seq for chronic myeloid leukaemia patient samples. Taking the advantage of TIF-Seq2, we explore transcription regulation among the overlapping units and investigate their crosstalk. We show that most overlapping upstream transcripts use poly(A) sites within the first 2 kb of the downstream transcription unit. Our work shows that, by paring the 5’ and 3’ end of each RNA, TIF-Seq2 can improve the annotation of complex genomes, facilitates accurate assignment of promoters to genes and easily identify transcriptionally fused genes.Key pointsStudy of TSS-PAS co-occurrence allows dissecting complex overlapping transcription units.Partially overlapping transcription units in human commonly use PAS within the first 2Kb.TIF-Seq2 facilitates the identification of lowly expressed and transcriptionally fused genes.

Landscape of Overlapping Gene Expression in the Equine Placenta

Increasing evidence suggests that overlapping genes are much more common in eukaryotic genomes than previously thought. These different-strand overlapping genes are potential sense–antisense (SAS) pairs, which might have regulatory effects on each other. In the present study, we identified the SAS loci in the equine genome using previously generated stranded, paired-end RNA sequencing data from the equine chorioallantois. We identified a total of 1261 overlapping loci. The ratio of the number of overlapping regions to chromosomal length was numerically higher on chromosome 11 followed by chromosomes 13 and 12. These results show that overlapping transcription is distributed throughout the equine genome, but that distributions differ for each chromosome. Next, we evaluated the expression patterns of SAS pairs during the course of gestation. The sense and antisense genes showed an overall positive correlation between the sense and antisense pairs. We further provide a list of SAS pairs with both positive and negative correlation in their expression patterns throughout gestation. This study characterizes the landscape of sense and antisense gene expression in the placenta for the first time and provides a resource that will enable researchers to elucidate the mechanisms of sense/antisense regulation during pregnancy.