The translational landscape of the splicing factor SRSF1 and its role in mitosis

Author:

Maslon Magdalena M1,Heras Sara R12,Bellora Nicolas3,Eyras Eduardo34,Cáceres Javier F1

Affiliation:

1. MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom

2. GENYO, Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government, Granada, Spain

3. Computational Genomics Group, Universitat Pompeu Fabra, Barcelona, Spain

4. Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain

Abstract

The shuttling serine/arginine rich (SR) protein SRSF1 (previously known as SF2/ASF) is a splicing regulator that also activates translation in the cytoplasm. In order to dissect the gene network that is translationally regulated by SRSF1, we performed a high-throughput deep sequencing analysis of polysomal fractions in cells overexpressing SRSF1. We identified approximately 1500 mRNAs that are translational targets of SRSF1. These include mRNAs encoding proteins involved in cell cycle regulation, such as spindle, kinetochore, and M phase proteins, which are essential for accurate chromosome segregation. Indeed, we show that translational activity of SRSF1 is required for normal mitotic progression. Furthermore, we found that mRNAs that display alternative splicing changes upon SRSF1 overexpression are also its translational targets, strongly suggesting that SRSF1 couples pre-mRNA splicing and translation. These data provide insights on the complex role of SRSF1 in the control of gene expression at multiple levels and its implications in cancer.

Funder

MRC Core Funding

Wellcome Trust Senior Investigator Award

Marie Curie

Consolider RNAReg

Ministerio de Economia y Competitividad

Sandra Ibarra Foundation

Medical Research Council

Wellcome Trust

Ministerio de Economía y Competitividad

Publisher

eLife Sciences Publications, Ltd

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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4. The RNA-binding landscapes of two SR proteins reveal unique functions and binding to diverse RNA classes;Änkö;Genome Biology,2012

5. Fitting a mixture model by expectation maximization to discover motifs in biopolymers;Bailey;Proceedings/International Conference on Intelligent Systems for Molecular Biology; ISMB,1994

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