Oryza Arjan van Zeijl Claire Lessa Alvim Kamei Robert van Loo Ruud Heshof BIF

Goal Generate a platform to analyze gene expression of Saccharomyces cerevisiae using RNAseq data. Compare high expressed genes vs. low expressed genes on exon-intron length, GC-content, codon-usage.

MustTopHat, Cufflink ShouldExon-Intron length, GC content CouldGO-annotation, Codon-usage, Palindromes WouldChemostat analysis, Cytoscape MoSCoW

RNAseq data Trimmed Untrimmed TopHat Cufflinks Exon – Intron length GC content Palindrome Codon-usage Pipeline NCBI data GO-terms Validation Sequence retrieval

RNAseq data Selected Top100 genes per 20% batches of total genes 0-20%20-40%40-60%60-80%80-100% 100 genes Data output Perc 1Perc 2Perc 3Perc 4Perc 5 FPKM-value

NCBI data LOCUS NP_ aa linear PLN 25-FEB-2013 DEFINITION ribosomal 40S subunit protein S30B [Saccharomyces cerevisiae S288c]. ACCESSION NP_ VERSION NP_ GI: DBSOURCE REFSEQ: accession NM_ KEYWORDS. SOURCE Saccharomyces cerevisiae S288c ORGANISM Saccharomyces cerevisiae S288c Eukaryota; Fungi; Dikarya; Ascomycota; Saccharomycotina; Saccharomycetes; Saccharomycetales; Saccharomycetaceae; Saccharomyces....

Exon - Intron length ID SHORT EXON INTRON FPKM CDS GC_CDS L_PALIN GC_PALIN YOR182C RPS30B Ribosomal 40S subunit protein S30B

GC content Claire Does more GC means more mRNA?

GC content & CDS length

Comparative genome analysis suggests characteristics of yeast inverted repeats that are important for transcriptional activity (2011) Humphrey-Dixon EL, Sharp R, Schuckers M, Lock R. Genome 54(11): Palindrome IR: at least 6 bp long, spacers maximum 10 bp Conservation: IR must be identical, spacer not

Palindrome Comparative analysis in 4 Saccharomyces genomes: S. cereviseae S. paradoxus S. mikatae S. bayanus IR in S. cereviseae Conserved in the 4 species Crossed the top 100 gene lists with the palindrome list to create 3 hash tables using the gene ID as keys: %gene_palin; %gene_palinseq; %GC_palin ;

Palindrome length

Percentiles 1

GC Palindrome & CDS

Codon usage Previous studies indicated more extreme codon usage preference in highly expressed genes (Sharp, 1986; Plotkin, 2011) Codon usage bias was shown to correlate with tRNA abundance (Sharp, 1986) Non-optimal codons might slow down translation, to allow correct protein folding (Pechmann, 2013) HOT TOPIC: 2 papers in Nature this week  Non-optimal codon usage is important for circadian clock rhythms

Codon usage MEASURE: Relative Synonymous Codon Usage (RSCU) Took mean RSCU over genes in top 100 for each class Problem annotation: CDS not always dividable by three

Codon usage

No.GOBPIDPvalueOddsRatio ExpCoun tCountSizeTerm 1GO: E cytoplasmic translation 2GO: E biosynthetic process 3GO: E cellular protein metabolic process 4GO: E gene expression 5GO: E cellular macromolecule biosynthetic process 6GO: E rRNA export from nucleus 7GO: E cellular component biogenesis at cellular level 8GO: E cellular metabolic process 9GO: E maturation of SSU-rRNA from tricistronic rRNA transcript (SSU- rRNA, 5.8S rRNA, LSU-rRNA) 10GO: E ribosomal small subunit biogenesis 11GO: E primary metabolic process 12GO: E RNA transport 13GO: E nuclear export 14GO: E RNA localization 15GO: E nucleobase-containing compound transport 16GO: E hexose catabolic process 17GO: E organelle assembly 18GO: E ribosomal small subunit assembly 19GO: E rRNA processing 20GO: E nuclear transport 21GO: E regulation of translational fidelity 22GO: E gluconeogenesis 23GO: E glycolysis 24GO: E monosaccharide biosynthetic process 25GO: E ncRNA metabolic process 26GO: E regulation of translation 27GO: E translational elongation 28GO: ribonucleoprotein complex subunit organization 29GO: carbohydrate catabolic process Long list top 100 Basically two processes, components, functions Ribosome and translation related Glycolysis/gluconeogenesis related Zoom in on part of the table GO term enrichment

No.GOBPIDPvalueOddsRatioExpCountCountSizeTerm 1GO: E cytoplasmic translation 2GO: E biosynthetic process 3GO: E cellular protein metabolic process 8GO: E cellular metabolic process 11GO: E primary metabolic process 16GO: E hexose catabolic process 22GO: E gluconeogenesis 23GO: E glycolysis 24GO: E monosaccharide biosynthetic process Top 100 GO-terms

Blast2GO

GO terms top 100

KEGG pathways

Technical validation use 4 paired end RNA-seq reads Create multiple copies (total 200, each 25 %) Run pipeline: 5 hits found! (one maps on two homologous gene on two chromosomes) FPKM values not equal (large length differences), so this is right Validation

Conclusion -High expressed genes have a high chance to contain introns. -There is a correlation between palindrome length and gene expression. -There is a preference for codon usage in highly expressed genes. -Highly expressed genes are richer in GC content and are shorter -Large differences exist in GC, intron/exon, palindromes and in GO terms between the top 100 and the rest

Questions