Verna Vu & Timothy Abreo

Study the transcriptome of transgenic mice vs wild type δC-doublecortin-like kinase (Dclk1) Transgenic mice express a constitutively active splice variant of doublecortin-like kinase 1 (Dclk1) gene. Goals: Study the transcriptome of wild type vs transgenic mice Compare microarray with DGE http://pubs.niaaa.nih.gov/publications/arh284/images/swart1.gif http://www.lintoninst.co.uk/Portals/0/productimages/276_0adeb.jpg δC-DCLK-short mice spend less time, move less in the open arms of the elevated plus maze→ δC-DCLK-short mice display a more anxious behavioral phenotype. http://www.lintoninst.co.uk http://pubs.niaaa.nih.gov/

Microarray Problems: 5 different microarray high back ground measures only relative abundances of transcripts only predefined sequences can be detected transcripts expressed at low levels can’t be detected 5 different microarray Affymetrix Agilent Illumina Applied Biosystems Home spotted http://dnachips-microarrays.wikispaces.com/file/view/flowchart.gif/143884121/flowchart.gif dnachips-microarrays.wikispaces.com/

Quantitative PCR analysis Cycle Based Sybr Green: Binds to all ds PCR products Gold standard: used to validate Problems Can’t Multiplex Many cycles to detect low frequency RNA transcripts, can be lost in background noise Can’t use on all transcripts real time PCR gold standard. can’t qPCR all genes but used to validate in this study a lot of work http://www.thermoscientificbio.com

Helpful Nomenclature Canonical sequence: sequences that reflects the most common choice of base at each position Noncanonical sequence: tags in the genome that map to any known exon either strand Transcripts per million: t.p.m.

Origins of Digital Gene Expression (DGE): SAGE Problems: Laborious Sequencing steps 100 k canonical tags would take up to a year Considerable financial investment needed http://www.sagenet.org/images/Sagenv1b.gif www.sagenet.org/

Digital Gene Expression (DGE) tag profiling Procedure 1st and 2nd strand cDNA synthesis using oligo-dT beads to capture polyadenylated RNA While still on beads, NlaIII was used to digest the DNA, makes cDNA fragment with 3’ most CATG GEX adapter 1 is ligated to the free 5’ end MmeI then cuts 17bp downstream of CATG site Gex adapter 2 ligate to free 3’ end PCR conducted using primers complementary to adapters, then sent for deep sequencing using Solexa/Illumina Whole Genome Sequencer NO CLONING First purify RNA, make cDNA, digest with first restriction enzyme, ligate first adapter to 3’ end, digest with other enzyme and ligate 5’ adapter

ENSEMBL transcripts To enable comparison, all canonical sequence tags and microarray probe sequences were put in FASTA format and then aligned to the ENSEMBL transcript database. Same samples used for DGE and microarray. http://en.wikipedia.org/wiki/FASTA_format http://en.wikipedia.org

Alternative Polyadenylation Transcripts with different 3’ ends that are separated by at least one restriction site can be differentiated with DGE 47% of detected ENSEMBL transcripts were discovered by more than one tag, most likely a result of alternative polyadenylation in 3’UTR 29% estimated previously based on EST sequences http://www.nature.com/nrg/journal/v14/n7/images_article/nrg3482-f2.jpg http://www.nature.com

Antisense Transcription Found evidence of bidirectional transcription in 51% of gene clusters when considering canonical and non-canonical tags of abundance >2 t.p.m. Antisense transcripts were expressed at high levels, although sense transcripts were still most abundant http://www.nature.com/nrg/journal/v14/n12/images/nrg3594-i1.jpg Importance: there could be gene transcripts in the opposite direction that we don’t know the function antisense tags that are found were not due to reverse transcriptase artifacts http://www.nature.com

Differentially Expressed Genes Sequencing of pooled samples caused problems; blood contamination in one sample Used Bayesian statistics to attempt to exclude genes that were not truly differentially expressed abundance of transcripts found to be highly expressed in blood

Biological Implications Used Gene Ontology consortium and DGE data to identify differentially regulated gene sets Most affected pathway: Disturbances of microtubule guided transport of SNARE containing synaptic vesicles due to changes in gene expression CaMK pathway was the second most affected pathway, possibly via feedback mechanisms involved in behavioral pathways in brain http://eferrari.blogs.lincoln.ac.uk/files/2013/02/SNAREs.png http://eferrari.blogs.lincoln.ac.uk

Dynamic Range The ratio between the largest and smallest possible values of a changeable quantity 3 to 4 orders of magnitude Lowest frequency but most consistently detected was 2 t.p.m. (0.3 copies per cell) limit of chips at lower range. due to noise. low signal linear portion of sigmoidal curve =DR

Comparison to SAGE and Microarray The effect of sequencing depth on detection of differentially expressed genes Simulated SAGE: randomly took 1/60 of DGE reads. Detected a decrease in 15 fold from 3179 to 200 reads Simulated SAGE: lowest: 91 t.p.m. DGE: average: >2 t.p.m. median: 4 t.p.m lowest: 0.8 t.pm. Microarray platforms median: 106 t.p.m Affymetrix had the most transcripts in common with DGE 11 different probes per transcript

Validation with qPCR 29 significant genes from DGE, 33 from microarray 43/62 showed some sort of variation between the wt and transgenic same direction only 5 were considered to be significant by both platforms To test for accuracy log 2 ratio: expression level of transgenic/wild type

Reproducibility The correlation between the normalized number of counts from the summed individual samples in their laboratory and the pool analyzed in the other laboratory were 0.98 wild-type 0.96 transgenic To test for precision Technique allows collaboration with other labs. False discovery rate was 8.5% determined the distribution of the differences between independent replicate measurements of log ratios between wild-type and transgenic samples

Why use DGE over Microarrays? unbiased view of the transcriptome detects high levels of differential polyadenylation and antisense transcription data are more precise & accurate than microarray data data analysis requires a lower number of preprocessing  facilitates interlaboratory comparisons high interlaboratory comparability of DGE data, probably due to the avoidance of hybridization processes (notoriously difficult to standardize) more sensitive in the detection of low-abundant transcripts and of small changes in gene expression. Absence of background signal and saturation effects unbiased view of the transcriptome detects high levels of differential polyadenylation and antisense transcription (undetectable with standard microarrays) data are more precise & accurate than microarray data data analysis requires a lower number of preprocessing steps (like background correction and normalization), which facilitates interlaboratory comparisons high interlaboratory comparability of DGE data, probably due to the avoidance of hybridization processes, which are notoriously difficult to standardize more sensitive in the detection of low-abundant transcripts and of small changes in gene expression. Absence of background signal and saturation effects (major causes of ratio compression on microarrays)

Implications: Enhancements in sequencing depth to improve accuracy in particular for low abundant transcripts Improvements in sensitivity, resolution, interlaboratory consistency Boost field of expression profiling Basic research and comparative genomics fields will benefit from major improvement of data portability Once held back by extensive and lengthy standardization issues

What the Future has in Store Deep sequencing→ robustness, comparability and richness of expression profiling data. Will boost collaborative, comparative and integrative genomics studies RNAseq http://static1.squarespace.com/static/526da5e4e4b039ceb7da1058/t/5317ed02e4b05fcac6a8d60b/1394076931330/human-dna.jpg static1.squarespace.com/

Questions? Criticism? http://www.clipartbest.com http://www.clipartbest.com/cliparts/jcx/pgp/jcxpgpnKi.png http://www.clipartbest.com