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Weiszmann, R.

Publications and source records attributed to Weiszmann, R..

2 recordsLinked to original sources

An important class of intron retention events in human erythroblasts is regulated by cryptic exons proposed to function as splicing decoys

During terminal erythropoiesis, the splicing machinery in differentiating erythroblasts executes a robust intron retention (IR) program that impacts expression of hundreds of genes. We studied IR mechanisms in the SF3B1 splicing factor gene, which expresses ~50% of its transcripts in late erythroblasts as a nuclear isoform that retains intron 4. RNA-seq analysis of nonsense-mediated decay (NMD)-inhibited cells revealed previously undescribed splice junctions, rare or not detected in normal cells, that connect constitutive exons 4 and 5 to highly conserved cryptic cassette exons within the intron. Minigene splicing reporter assays showed that these cassettes promote IR. Genome-wide analysis of splice junction reads demonstrated that cryptic noncoding cassettes are much more common in large (>1kb) retained introns than they are in small retained introns or in non-retained introns. Functional assays showed that heterologous cassettes can promote retention of intron 4 in the SF3B1 splicing reporter. Although many of these cryptic exons were spliced inefficiently, they exhibited substantial binding of U2AF1 and U2AF2 adjacent to their splice acceptor sites. We propose that these exons function as decoys that engage the intron-terminal splice sites, blocking cross-intron interactions required for excision. Developmental regulation of decoy function underlies a major component of the erythroblast IR program.

molecular biology

Exploiting regulatory heterogeneity to systematically identify enhancers with high accuracy

Identifying functional enhancers elements in metazoan systems is a major challenge. For example, large-scale validation of enhancers predicted by ENCODE reveal false positive rates of at least 70%. Here we use the pregrastrula patterning network of Drosophila melanogaster to demonstrate that loss in accuracy in held out data results from heterogeneity of functional signatures in enhancer elements. We show that two classes of enhancer are active during early Drosophila embryogenesis and that by focusing on a single, relatively homogeneous class of elements, over 98% prediction accuracy can be achieved in a balanced, completely held-out test set. The class of well predicted elements is composed predominantly of enhancers driving multi-stage, segmentation patterns, which we designate segmentation driving enhancers (SDE). Prediction is driven by the DNA occupancy of early developmental transcription factors, with almost no additional power derived from histone modifications. We further show that improved accuracy is not a property of a particular prediction method: after conditioning on the SDE set, naive Bayes and logistic regression perform as well as more sophisticated tools. Applying this method to a genome-wide scan, we predict 1,640 SDEs that cover 1.6% of the genome, 916 of which are novel. An analysis of 32 novel SDEs using wholemount embryonic imaging of stably integrated reporter constructs chosen throughout our prediction rank-list showed >90% drove expression patterns. We achieved 86.7% precision on a genome-wide scan, with an estimated recall of at least 98%, indicating high accuracy and completeness in annotating this class of functional elements.\n\nSignificance StatementWe demonstrate a high accuracy method for predicting enhancers genome wide with > 85% precision as validated by transgenic reporter assays in Drosophila embryos. This is the first time such accuracy has been achieved in a metazoan system, allowing us to predict with high-confidence 1640 enhancers, 916 of which are novel. The predicted enhancers are demarcated by heterogeneous collections of epigenetic marks; many strong enhancers are free from classical indicators of activity, including H3K27ac, but are bound by key transcription factors. H3K27ac, often used as a one-dimensional predictor of enhancer activity, is an uninformative parameter in our data.

genomics