Presentation is loading. Please wait.

Presentation is loading. Please wait.

Genomics I: The Transcriptome RNA Expression Analysis Determining genomewide RNA expression levels.

Similar presentations

Presentation on theme: "Genomics I: The Transcriptome RNA Expression Analysis Determining genomewide RNA expression levels."— Presentation transcript:

1 Genomics I: The Transcriptome RNA Expression Analysis Determining genomewide RNA expression levels

2 Genome-wide expression analysis Goal: to measure RNA levels of all genes in genome RNA levels vary with the following: –Cell type –Developmental stage –External stimuli Time and location of expression provide useful information as to gene function

3 Genome-wide expression analysis methods Microarrays –Hybridization based RNA-seq –Direct sequencing of cDNAs

4 Microarray Hybridization Measurements of RNA abundance by microarrays based on hybridization –Between complementary strands of RNA and DNA –Or two complementary DNA strands Similar in principle to RNA blot (Northern blot)

5 Microarray Analysis of Transcription

6 Animation

7 Basics of microarrays DNA attached to solid support –Glass, plastic, or nylon RNA is labeled –Usually indirectly Bound DNA is the probe –Labeled RNA is the “target”

8 Microarray hybridization Usually comparative –Ratio between two samples Examples –Tumor vs. normal tissue –Drug treatment vs. no treatment –Embryo vs. adult mRNA cDNA DNA microarray samples

9 Two major types of microarrays cDNA arrays- PCR product corresponding to a portion of a cDNA is immobilized on the slide oligonucleotide arrays- oligonucleotide complementary to transcript is synthesized on slide or immobilized on the slide

10 How microarrays are made: spotted microarrays DNA mechanically placed on glass slide Need to deliver nanoliter to picoliter volumes –Too small for normal pipetting devices Robot “prints,” or “spots,” DNA in specific places

11 How microarrays are made: Affymetrix GeneChips Oligonucleotides synthesized on silicon chip –One base at a time Uses process of photolithography –Developed for printing computer circuits

12 Affymetrix GeneChips Oligonucleotides –Usually 20–25 bases in length –10–20 different oligonucleotides for each gene Oligonucleotides for each gene selected by computer program to be the following: –Unique in genome –Nonoverlapping Composition based on design rules Empirically derived

13 Comparison of microarray hybridization Spotted microarrays –Competitive hybridization Two labeled cDNAs hybridized to same slide Affymetrix GeneChips –One labeled RNA population per chip –Comparison made between hybridization intensities of same oligonucleotides on different chips

14 Target labeling: fluorescent cDNA cDNA made using reverse transcriptase Fluorescently labeled nucleotides added Labeled nucleotides incorporated into cDNA

15 Spotted-microarray hybridization Control and experimental cDNA labeled –One sample labeled with Cy3 –Other sample labeled with Cy5 Both samples hybridized together to microarray Relative intensity determined using confocal laser scanner

16 Results given as ratios Images use colors: Cy3 = Green Cy5 = red Yellow –Yellow is equal intensity or no change in expression Analysis of hybridization

17 Example of spotted microarray cDNA of RNA from irradiated cells (red) Compare with untreated cells (green) Most genes have little change (yellow) Gene CDKN1A: red = increase in expression Gene Myc: green = decrease in expression CDKNIA MYC -Flash animation -YouTube video

18 Analysis of cell-cycle regulation Yeast cells stopped at different stages of cell cycle –G1, S, G2, and M RNA extracted from each stage Control RNA from unsynchronized culture

19 Results of yeast cell-cycle analysis 800 genes identified whose expression changes during cell cycle Grouped by peak expression M/G1, G1, S, G2, and M Four different treatments used to synchronize cells –All gave similar results Results from Spellman et al., 1998; Cho et al., 1998

20 Cluster Analysis: Cell-cycle regulated genes Each gene is a line on the longitudinal axis Treatments in different panels Cell-cycle stages are color coded at top Vertical axis groups genes by stage in which expression peaks Brown and Botstein, 1999 Alphacdc15cdc28Elu M/G1 G1 S G2 M

21 Affymetrix GeneChip experiment RNA from different types of brain tumors extracted Extracted RNA hybridized to GeneChips containing approximately 6,800 human genes Identified gene expression profiles specific to each type of tumor

22 Profiling tumors Image portrays gene expression profiles showing differences between different tumors Tumors: MD (medulloblastoma) Mglio (malignant glioma) Rhab (rhabdoid) PNET (primitive neuroectodermal tumor) Ncer: normal cerebella

23 Cancer diagnosis by microarray Gene expression differences for medulloblastoma correlated with response to chemotherapy Those who failed to respond had a different profile from survivors Can use this approach to determine treatment 60 different samples

24 RNA- seq High throughput sequencing of cDNAs from biological samples Determine abundance of mRNA by representation in sequencing reads May detect variants (alternative splicing, specific alleles, etc.)


26 DNA Sequencing Cost per Genome

Download ppt "Genomics I: The Transcriptome RNA Expression Analysis Determining genomewide RNA expression levels."

Similar presentations

Ads by Google