Functional Genomics Research Stream. Research Meeting: November 15, 2011 Developments in the Field of Functional Genomics

Transcription

1 Functional Genomics Research Stream Research Meeting: November 15, 2011 Developments in the Field of Functional Genomics

2 Are you excited about your FRI research and interested in telling others about your work? Would you like to visit your high school and let your former teachers know what you ve been doing at UT? The goal of the FRI Ambassador Program is to promote the Freshman Research Initiative in high schools throughout Texas, informing teachers and students about the unique opportunities the program provides. Ambassador Training Meetings: November 4 h 1pm WEL November 9 th 5pm WEL For more information, Contact Research Educator: Anne Tibbetts a.tibbs@mail.utexas.edu And YOU the FRI students are the best representatives! If this sounds interesting to you, please attend an ambassador information meeting, either Friday, November 4 th (1pm) or Wednesday, November 9 th (5pm).

3 One-on-one meetings Discuss progress thus far Discuss future opportunities Please schedule with me (by ) Office hours are good, or any other time 9am - 5pm Except W 9-10, 12-1; Th

4 Final Reports Post on Results Central - Important When: Friday, December 2PM Professionalism, quality... General introduction... Conclusions, reflections... Clear section titles (bold)... Name, Date, Research Stream...

5 Final Reports Present research for entire semester Combine previous reports - make corrections Take your time - count hours

6 Next Week! Life Technologies Demonstration Drs. Diana Batten and Charmaine San Jose - SOLiD Total RNA-Seq Kit During regular class time in this room May go past 4:20 a bit Here to answer questions as well

7 SOLiD Total RNA-Seq Kit Protocol

8 CHAPTER 2 Prepare Whole Transcriptome Libraries Fragment the whole transcriptome RNA µg poly(a) RNA or ng rrna-depleted total RNA Fragment the RNA (page 14) Clean up the RNA (page 15) Fragmented RNA Assess the yield and size distribution of the fragmented RNA (page 16) Construct the amplified whole transcriptome library Hybridize and ligate the RNA (page 18) + NNNNN B NNNNN NNNNN B NNNNN Perform reverse transcription (page 19) Purify the cdna (page 20) Size select the cdna (page 21) cdna 5 PCR Primer Amplify the cdna (page 25)

9 Fragment the RNA (page 14) Clean up the RNA (page 15) Fragmented RNA Assess the yield and size distribution of the fragmented RNA (page 16) Construct the amplified whole transcriptome library Hybridize and ligate the RNA (page 18) + NNNNN B NNNNN NNNNN B NNNNN Perform reverse transcription (page 19) Purify the cdna (page 20) Size select the cdna (page 21) cdna 5 PCR Primer Amplify the cdna (page 25) Purify the amplified DNA (page 27) P1 sequence RNA sequence (Barcode) optional internal adaptor (IA) 3 PCR Primer barcode (BC) P2 sequence Assess the yield and size distribution of the amplified DNA (page 28) Proceed with SOLiD System templated bead preparation Refer to the Applied Biosystems SOLiD 4 System Templated Bead Preparation Guide (PN ) P1 IA BC P2

10 Size select the cdna Run the gel until the leading dye front is 1 cm below the middle of the gel 8. Illuminate the stained gel, then excise the gel containing nt cdna: Note: Be careful not to include extra gel that does not contain any cdna. a. Using a clean razor blade, make horizontal cuts to excise the gel containing nt cdna. IMPORTANT! Table 1 Expected lengths of the insert and PCR according to excised cdna length Excised cdna length (nt) Insert length (bp) PCR product length (bp) 50 ~0 ~ ~50 ~ ~100 ~ ~150 ~ ~200 ~300 Make the horizontal cuts first to obtain the desired insert length

11 5 PCR Primer (Barcode) optional 3 PCR Primer P1 sequence internal adaptor (IA) P2 sequence RNA sequence barcode (BC)

12 Hallmarks of Cancer

13 The Roads to Aneuploidy

14 Tumor Transcriptome Sequencing Reveals Allelic Expression Imbalances Associated with Copy Number Alterations Brian B. Tuch 1., Rebecca R. Laborde 2., Xing Xu 1, Jian Gu 3, Christina B. Chung 1, Cinna K. Monighetti 1, Sarah J. Stanley 1, Kerry D. Olsen 4, Jan L. Kasperbauer 4, Eric J. Moore 4, Adam J. Broomer 1, Ruoying Tan 1, Pius M. Brzoska 1, Matthew W. Muller 1, Asim S. Siddiqui 1, Yan W. Asmann 5, Yongming Sun 1, Scott Kuersten 3, Melissa A. Barker 1, Francisco M. De La Vega 1 *, David I. Smith 2 * 1 Life Technologies Inc., Foster City, California, United States of America, 2 Division of Experimental Pathology, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, United States of America, 3 Life Technologies Inc., Austin, Texas, United States of America, 4 Department of Otorhinolaryngology, Mayo Clinic, Rochester, Minnesota, United States of America, 5 Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, United States of America Abstract Due to growing throughput and shrinking cost, massively parallel sequencing is rapidly becoming an attractive alternative to microarrays for the genome-wide study of gene expression and copy number alterations in primary tumors. The sequencing of transcripts (RNA-Seq) should offer several advantages over microarray-based methods, including the ability to detect somatic mutations and accurately measure allele-specific expression. To investigate these advantages we have applied a novel, strand-specific RNA-Seq method to tumors and matched normal tissue from three patients with oral squamous cell carcinomas. Additionally, to better understand the genomic determinants of the gene expression changes observed, we have sequenced the tumor and normal genomes of one of these patients. We demonstrate here that our RNA- Seq method accurately measures allelic imbalance and that measurement on the genome-wide scale yields novel insights into cancer etiology. As expected, the set of genes differentially expressed in the tumors is enriched for cell adhesion and differentiation functions, but, unexpectedly, the set of allelically imbalanced genes is also enriched for these same cancerrelated functions. By comparing the transcriptomic perturbations observed in one patient to his underlying normal and tumor genomes, we find that allelic imbalance in the tumor is associated with copy number mutations and that copy number mutations are, in turn, strongly associated with changes in transcript abundance. These results support a model in which allele-specific deletions and duplications drive allele-specific changes in gene expression in the developing tumor. Citation: Tuch BB, Laborde RR, Xu X, Gu J, Chung CB, et al. (2010) Tumor Transcriptome Sequencing Reveals Allelic Expression Imbalances Associated with Copy Number Alterations. PLoS ONE 5(2): e9317. doi: /journal.pone

15 Cancer Cells Identity Shared Among Three Patients

16 RNA-Seq of Four Differentially Expressed Loci

17 Tumor Cells Display Allelic Imbalance

18 Allelic Imbalance Correlated with Genomic Expansion RNA-Seq of Oral Carcinomas

19 differentially expressed mirnas, as shown in the volcano plots below. Differential Expression of mirnas Normal vs. A Cancer Cells in the Thyroid B of all expressed mirna probes in the 8 groups of thyroid samples, as indicated above P

20 B sh sa RT tr