dataset for 5′ UTR cis-regulatory logic governs ribosome engagement on canonical and noncoding RNAs

Unexpected Translational Features in mRNA and ncRNA 5' UTR: Comprehensive Explanation and ApplicationTable of contentsANALYSIS PART IPrepare dependenciesSource data and preprocessCodesANALYSIS PART IISource dataCodesModelPrepare dependenciesSource dataCodesThe trained modelsCitationsANALYSIS PART IPrepare dependenciessoftwareThis project requires Python version >= 3.9, uses cd-hit 4.8.1 and RNAfold 2.6.4, bedtools 2.31.0.python librarypip install -r requirements.txtSource data and preprocessDatabaseurlEnsembl ncRNAftp.ensembl.org/pub/release-112/fasta/homo_sapiens/ncrna/Smprothttp://bigdata.ibp.ac.cn/SmProt/download.htmSPENCERhttps://spencer.renlab.org/#/downloadmRNA MANEftp.ncbi.nlm.nih.gov/refseq/MANE/MANE_human/release_1.3/FANTOMhttps://fantom.gsc.riken.jp/5/suppl/Hon_et_al_2016/data/assembly/lv1_raw/GENCODEhttps://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_46/gencode.v46.transcripts.fa.gzAHIGH(annotation)ars.els-cdn.com/content/image/1-s2.0-S1097276522006062-mmc3.xlsCodesRun data_preprocess.ipynb to generate transcripts and ORF annotation files for MANE mRNA and ncRNA_ribo from Smprot, SPENCER, and predicted ORFs of ncRNA.We also provide the above files associated with ncRNA_ribo in ribo_rawfiles.zip.Run data_produce.ipynb to generate 50nt downstream start codon, 5' UTR, ORF sequence files of mRNA, ncRNA_ribo, ncRNA.Calculate features and plot.3.1 RNA folding energy: RNAfold < mRNA/ribo/ncRNA_d50.fasta > res_mRNA/ribo/ncRNA_d50.3.2 Other features include edit distance, uStart, uORF, last uORF distance, pair kozak distances, fickett score and hexamer score are in Cal_features.ipynb.ANALYSIS PART IISource dataDataurlAHIGH(expression)ars.els-cdn.com/content/image/1-s2.0-S1097276522006062-mmc4.xlsxPhast scorehgdownload.cse.ucsc.edu/goldenpath/hg38/database/phastConsElements30way.txt.gzCodesRun plot.ipynb to analysis translational features of mRNA with long 5' UTR grouped by translational efficiency.Run ConservedEle.ipynb to intersect 5' UTR with conserved elements within genome, and compare the distribution of mRNA with long 5' UTR grouped by TE.MODELPrepare dependenciessoftwareThis project requires Python version >= 3.9, uses RNAfold 2.6.4.python librarypip install -r requirements.txtSource dataDataurl5'UTR sequences and annotations from Caogithub.com/zzz2010/5UTR_Optimizer/tree/master/dataCodesDownload the sequence file and annotation files.mkdir data output wget github.com/zzz2010/5UTR_Optimizer/blob/master/data/gencode_v17_5utr_15bpcds.fa ./data wget github.com/zzz2010/5UTR_Optimizer/blob/master/data/df_counts_and_len.TE_sorted.HEK_Andrev2015.with_annot.txt ./data wget github.com/zzz2010/5UTR_Optimizer/blob/master/data/df_counts_and_len.TE_sorted.Muscle.with_annot.txt ./data wget github.com/zzz2010/5UTR_Optimizer/blob/master/data/df_counts_and_len.TE_sorted.Muscle.with_annot.txt ./data Prepare features of all sequences(except conserved elements) and database for querying conserved elements.python FeatureExtraction_final.py data/gencode_v17_5utr_15bpcds.fa output/ Run plusCE_database.ipynb.Train model and output spearman ρ.python plusCE.py --data data --annot df_counts_and_len.TE_sorted.Muscle.with_annot.txt --feature output --rna 5 --ribo 0.1 --querydb DB The trained modelscell lineurlHEKzenodo.org/records/13289680/files/rf_model_HEK.pkl?download=1Musclehttps://zenodo.org/records/13289680/files/rf_model_Muscle.pkl?download=1pc3https://zenodo.org/records/13289680/files/rf_model_pc3.pkl?download=1CitationsLi Y, Zhou H, Chen X, Zheng Y, Kang Q, Hao D, Zhang L, Song T, Luo H, Hao Y, et al: SmProt: A Reliable Repository with Comprehensive Annotation of Small Proteins Identified from Ribosome Profiling.

Genomics Proteomics Bioinformatics 2021, 19:602-610. dx.doi.org/10.1016/j.gpb.2021.09.002.Luo X, Huang Y, Li H, Luo Y, Zuo Z, Ren J, Xie Y: SPENCER: a comprehensive database for small peptides encoded by noncoding RNAs in cancer patients. Nucleic Acids Res 2022, 50:D1373-D1381. dx.doi.org/10.1093/nar/gkab822.Chothani SP, Adami E, Widjaja AA, Langley SR, Viswanathan S, Pua CJ, Zhihao NT, Harmston N, D'Agostino G, Whiffin N, et al: A high-resolution map of human RNA translation.