Translatome and transcriptome analysis of TMA20 (MCT-1) and TMA64 (eIF2D) knockout yeast strains

• Main Authors: Desislava S. Makeeva, Andrey S. Lando, Aleksandra Anisimova, Artyom A. Egorov, Maria D. Logacheva, Alexey A. Penin, Dmitry E. Andreev, Pavel G. Sinitcyn, Ilya M. Terenin, Ivan N. Shatsky, Ivan V. Kulakovskiy, Sergey E. Dmitriev
• Format: Article
• Language: English
• Published: Elsevier 2019-04-01
• Series: Data in Brief
• Online Access: http://www.sciencedirect.com/science/article/pii/S2352340919300502

TMA20 (MCT-1), TMA22 (DENR) and TMA64 (eIF2D) are eukaryotic translation factors involved in ribosome recycling and re-initiation. They operate with P-site bound tRNA in post-termination or (re-)initiation translation complexes, thus participating in the removal of 40S ribosomal subunit from mRNA stop codons after termination and controlling translation re-initiation on mRNAs with upstream open reading frames (uORFs), as well as de novo initiation on some specific mRNAs. Here we report ribosomal profiling data of S.cerevisiae strains with individual deletions of TMA20, TMA64 or both TMA20 and TMA64 genes. We provide RNA-Seq and Ribo-Seq data from yeast strains grown in the rich YPD or minimal SD medium. We illustrate our data by plotting differential distribution of ribosomal-bound mRNA fragments throughout uORFs in 5′-untranslated region (5′ UTR) of GCN4 mRNA and on mRNA transcripts encoded in MAT locus in the mutant and wild-type strains, thus providing a basis for investigation of the role of these factors in the stress response, mating and sporulation. We also document a shift of transcription start site of the APC4 gene which occurs when the neighboring TMA64 gene is replaced by the standard G418-resistance cassette used for the creation of the Yeast Deletion Library. This shift results in dramatic deregulation of the APC4 gene expression, as revealed by our Ribo-Seq data, which can be probably used to explain strong genetic interactions of TMA64 with genes involved in the cell cycle and mitotic checkpoints. Raw RNA-Seq and Ribo-Seq data as well as all gene counts are available in NCBI Gene Expression Omnibus (GEO) repository under GEO accession GSE122039 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE122039).