Identification and analysis of differentially expressed genes in

Identification and analysis of differentially expressed genes in Saccharomyces cerevisiae. Group Populus: Petra van Berkel Casper Gerritsen Astri Herlino Brian Lavrijssen

Dataset of S. cerevisiae �Data generated by Nookaew et al (2012) �Two conditions: �Glucose excess (Batch) & Glucose limited (Chemostat) � 3 Biological replicates per condition �RNA-seq data: � 12 Files � 3 Sets of Paired-end reads per condition �Pipeline for differential gene expression analysis

Top. Hat – Cufflinks analysis �Protocols based on Trapnell et al (2012) � 75% of reads mapped �Plots based on Cuffdiff gene expression output

Cuffdiff output • 5800 genes with FPKM values • Q-value threshold based on Nookaew et al (2012) Data Summary Significant differentially expressed FPKM > 0 and value_2 > 0 log 2(fold change) > 1 log 2(fold change) < -1 log 2(fold change) > 3 log 2(fold change) > -2 Q-value < 0. 05 2560 2554 735 510 177 44 Q-value < 1 e-5 1293 1292 516 410 151 33

Validation of Top. Hat - Cufflinks �Validation of selection �Using Excel �Literature study �Boer et al (2003) � Influence of C, N, P and S limitation � Microarray analysis � > 68 out of 151 significantly upregulated � > 9 out of 33 significantly downregulated �More or less same genes found in other papers

Expression network up Up regulated genes mrnet method in R Number of Nodes = 57 Number of Edges = 1560

Expression network down Down regulated genes mrnet method in R Number of Nodes = 33 Number of Edges = 513

GO Terms and GO Enrichment R version 2. 15. 0 (2012 -03 -30) �Packages: �bioma. Rt: Ensembl gene 69, S. cerevisiae EF 3 �org. Sc. sgd. db �GOstats �Rgraphviz �GO enrichment: � 8419 genes in the universe (org. Sc. sgd. PMID 2 ORF) �Threshold: p-value < 10 -4

GO Terms �Down regulated 32 genes 29 genes with 208 GO terms (3 genes are not annotated) Gene GO ID Description HXT 3 GO: 0006810, GO: 0016021, Low affinity glucose transporter GO: 0005215, GO: 0055085 HXT 4 GO: 0006810, GO: 0055085, GO: 0022891, High-affinity glucose transporter GO: 0005215, GO: 0022857 �Up regulated 133 genes 113 genes with 855 GO terms (20 genes are not annotated) Gene GO ID Description - Protein of unknown function involved in energy metabolism under respiratory conditions - Protein required for survival at high temperature during stationary phase RGI 2 SPG 4 JEN 1 GO: 0097079, GO: 0015355, GO: 0022857, Monocarboxylate/proton symporter GO: 0016021, GO: 0034219 of the plasma membrane

GO Enrichment �Down regulated �Biological process: not found �Up regulated GOBPID Pvalue Odds. Ratio Exp. Count Size Term GO: 0055114 2. 02 E-10 4. 98 7. 66 29 415 oxidation-reduction process monocarboxylic acid catabolic 23 process generation of precursor 221 metabolites and energy GO: 0072329 2. 41 E-10 33. 95 0. 46 9 GO: 0006091 1. 70 E-09 6. 00 4. 40 21 GO: 0006099 3. 75 E-09 22. 61 0. 60 9 30 tricarboxylic acid cycle GO: 0009109 3. 75 E-09 22. 61 0. 60 9 30 coenzyme catabolic process

Biological process of up regulated genes

�Validation: Yeast genome database �Problem: �Not well annotated because the bioma. Rt was not updated to Ensembl gene 70, S. cerevisiae EF 4

Top 100 �gffread: make the transcripts fasta file �Determine the top 100 highest and lowest expressed genes for the two conditions �R: order cuffdiff output on FPKM value (4 files) �Take out the genes with FPKM = 0

Top 100 �Top genes: �G 3 P dehydrogenase, �F 16 P aldolase, �Ribosomal subunit protein �Bottom genes: �dubious transcript, �retro transposon, �etc. .

GC-content & transcript length �Determine GC-content and transcript length �Import top 100 genes files �For each file check the genes in top 100 file in transcripts. fa and count GC content and the transcript length

GC-content & transcript length �Highly expressed in batch: � Length: 515. 19 GC: 0. 43 �Lowly expressed in batch: � Length: 831. 46 GC: 0. 41 �Highly expressed in chemostat: � Length: 556. 65 GC: 0. 43 �Lowly expressed in chemostat: � Length: 727. 29 GC: 0. 41

GC-content & transcript length �Short sequence length! �mainly in highly expressed genes, gives unrealistic view of codon usage and intron length �These are often ribosomal subunit proteins

Intron length Genes. gtf as input Create an indexfile Look for the interesting genes Print them to an outputfile Calculate average file mean intron length introns_hi 1. out 429. 455 introns_hi 2. out 440. 125 introns_low 1. out 60. 6667 introns_low 2. out 43. 5

Codon usage �Method (perl script): � Input are top high and low expressed genes � Build gene ID list and codons list and retrieve sequences � Count codon usage and calculate RSCU and average RSCU

Conclusion �The up and down regulated genes are involved in carbon metabolism �Highly expressed genes are involved in carbon metabolism or are ribosomal subunit proteins