Скачать презентацию GGAGATTCTGGGCCACTTTGGTTCCCCATGAGCCAAGACGGCACTTCTAATTTGCATTCCCTACCGGAGTCCCTGTAGCCTGGCTTTCAGCTGGTGCCCAAAGTGACAAATGTATCTGCAATGACAAAGGTACCC TGGAAGGGCTCGCCCTCTGCGGAATTTCAGTTCATGCAGGCCTTGGTGCTTCCACATCTGTCCAAGGGCCTTTCAAATGTGACTTTTAACTCTGTGGATTTGCCCGGTTGTCACATTCTGAGCAGCCACAACCTACTGC ATCCCATGTAGAAGTGACCTGATTTTTTCCTGCTTTTCAAGGCTGTATGTTTACATTTGCCTCCAATCATTCCTATGGGAATTCCTTGGGAGTCTAACTTGGAGATTTTGTTTCTTCTGCCTTTGCTCCTGGGGGCT TAATCACTTCTGTGCCTCTGGTTATCTGTGGCACATTTGTCATTAGTCAACCGGAGACTCGGGGTCTGAGTGGAGGGTATGTCCCCCTCCAGTGATGGTTTCTGTTGGCTTCCCAGGGTGAGGATGACTCATGACCA CTTGCAAGTGGTTTTTGTGTCTGGGGTTTATGATCACACAGTCATACACGTTCTAACTCCAGACTGTTGAGAAAGCCTCTGGGTAAGGGAATTCCTGGGAAACACACTGTTTTCATGCATCCTCTGGAAGATGAGGCCT GAAGTTACCAGGGTCTCTGTTTGCTGATGATCCACATTTTCTAGCCCACTCTGCTTCTCTGACACCTTTAGTCTTGAGGATCCATGNTCTGTGAAGGAATCCAAGCTCTCATTTCGCACTCACCTTGGCCCTGGCTC TGTCTCCAGGACCTCTTCTACTACAAAATCCTAAAGCTCTGGGAGCTGGGTGTCAACCTGTGCCCGAGGAAATCATACAGTTACTGTGGACTTTCCAGTTTGCTGTCTTCTAGTATTCCATTGTAGCTCTTGGGTATTTTCCC ATCCACCCCAAGATCCAGCTGGAAATCAGTGAACACACTTGATGGGAGTTTTCCTGCATGTGCTCTGGGCATTGACAGTAGAAGGGTGTTCAGAATGTCTGCTGTGCCCTCATGGAGGAAGAGNGCTCAGTGTACATGCTCTG Скачать презентацию GGAGATTCTGGGCCACTTTGGTTCCCCATGAGCCAAGACGGCACTTCTAATTTGCATTCCCTACCGGAGTCCCTGTAGCCTGGCTTTCAGCTGGTGCCCAAAGTGACAAATGTATCTGCAATGACAAAGGTACCC TGGAAGGGCTCGCCCTCTGCGGAATTTCAGTTCATGCAGGCCTTGGTGCTTCCACATCTGTCCAAGGGCCTTTCAAATGTGACTTTTAACTCTGTGGATTTGCCCGGTTGTCACATTCTGAGCAGCCACAACCTACTGC ATCCCATGTAGAAGTGACCTGATTTTTTCCTGCTTTTCAAGGCTGTATGTTTACATTTGCCTCCAATCATTCCTATGGGAATTCCTTGGGAGTCTAACTTGGAGATTTTGTTTCTTCTGCCTTTGCTCCTGGGGGCT TAATCACTTCTGTGCCTCTGGTTATCTGTGGCACATTTGTCATTAGTCAACCGGAGACTCGGGGTCTGAGTGGAGGGTATGTCCCCCTCCAGTGATGGTTTCTGTTGGCTTCCCAGGGTGAGGATGACTCATGACCA CTTGCAAGTGGTTTTTGTGTCTGGGGTTTATGATCACACAGTCATACACGTTCTAACTCCAGACTGTTGAGAAAGCCTCTGGGTAAGGGAATTCCTGGGAAACACACTGTTTTCATGCATCCTCTGGAAGATGAGGCCT GAAGTTACCAGGGTCTCTGTTTGCTGATGATCCACATTTTCTAGCCCACTCTGCTTCTCTGACACCTTTAGTCTTGAGGATCCATGNTCTGTGAAGGAATCCAAGCTCTCATTTCGCACTCACCTTGGCCCTGGCTC TGTCTCCAGGACCTCTTCTACTACAAAATCCTAAAGCTCTGGGAGCTGGGTGTCAACCTGTGCCCGAGGAAATCATACAGTTACTGTGGACTTTCCAGTTTGCTGTCTTCTAGTATTCCATTGTAGCTCTTGGGTATTTTCCC ATCCACCCCAAGATCCAGCTGGAAATCAGTGAACACACTTGATGGGAGTTTTCCTGCATGTGCTCTGGGCATTGACAGTAGAAGGGTGTTCAGAATGTCTGCTGTGCCCTCATGGAGGAAGAGNGCTCAGTGTACATGCTCTG

ea48b43cc2fc1d13447942dc2cb29bea.ppt

  • Количество слайдов: 76

GGAGATTCTGGGCCACTTTGGTTCCCCATGAGCCAAGACGGCACTTCTAATTTGCATTCCCTACCGGAGTCCCTGTAGCCTGGCTTTCAGCTGGTGCCCAAAGTGACAAATGTATCTGCAATGACAAAGGTACCC TGGAAGGGCTCGCCCTCTGCGGAATTTCAGTTCATGCAGGCCTTGGTGCTTCCACATCTGTCCAAGGGCCTTTCAAATGTGACTTTTAACTCTGTGGATTTGCCCGGTTGTCACATTCTGAGCAGCCACAACCTACTGC ATCCCATGTAGAAGTGACCTGATTTTTTCCTGCTTTTCAAGGCTGTATGTTTACATTTGCCTCCAATCATTCCTATGGGAATTCCTTGGGAGTCTAACTTGGAGATTTTGTTTCTTCTGCCTTTGCTCCTGGGGGCT TAATCACTTCTGTGCCTCTGGTTATCTGTGGCACATTTGTCATTAGTCAACCGGAGACTCGGGGTCTGAGTGGAGGGTATGTCCCCCTCCAGTGATGGTTTCTGTTGGCTTCCCAGGGTGAGGATGACTCATGACCA CTTGCAAGTGGTTTTTGTGTCTGGGGTTTATGATCACACAGTCATACACGTTCTAACTCCAGACTGTTGAGAAAGCCTCTGGGTAAGGGAATTCCTGGGAAACACACTGTTTTCATGCATCCTCTGGAAGATGAGGCCT GAAGTTACCAGGGTCTCTGTTTGCTGATGATCCACATTTTCTAGCCCACTCTGCTTCTCTGACACCTTTAGTCTTGAGGATCCATGNTCTGTGAAGGAATCCAAGCTCTCATTTCGCACTCACCTTGGCCCTGGCTC TGTCTCCAGGACCTCTTCTACTACAAAATCCTAAAGCTCTGGGAGCTGGGTGTCAACCTGTGCCCGAGGAAATCATACAGTTACTGTGGACTTTCCAGTTTGCTGTCTTCTAGTATTCCATTGTAGCTCTTGGGTATTTTCCC ATCCACCCCAAGATCCAGCTGGAAATCAGTGAACACACTTGATGGGAGTTTTCCTGCATGTGCTCTGGGCATTGACAGTAGAAGGGTGTTCAGAATGTCTGCTGTGCCCTCATGGAGGAAGAGNGCTCAGTGTACATGCTCTG GGTCAGTAGGTGCCCTTGAGCCCAGCTTTGGGAGCAATGTTGGATGAGTGAAGGAGGGATCCAGGGCAAAGCAGGCACGACAGAGTGGAGACGGCGCTGCTGGCTCTCAGGGGAATGGGCATGGAGTGGGTAGGAGATCCACC TAAGGAGGCTGGCTGGACGAGTCAGGAGCCCCTTCCAAGGGTGGACACTGACAGGCCCCCAGTCTTGGTCTCCTGCATGCCAGAGGTACCAGCCCATCTTTTTTCCTAAACTTGATGACCTAGGGGCATGTTG AATCTCAGCCTCGCCCACTGGCGCTGGACTTGGTACACAGGGTGGGGCAAAGTGGGTACTGGATCCTGATCATCCCTGGGGTGTGGCTTCTTGCTGCACAGTCAGCTTCTAGTTCTGTAGCCCCAGCTGCTCCTGCG GTGGAGCTACACATCAGGCTCTGACCCCCTCCAGGTGGGGCCTTCGCGTGAGGGGAGTCAGCACGCATCAGCAGCTGGGCCCAGGGAGTTGCCCCACTGAGCACTGCGGGCTGACCTGCTCCCAACCAGGGAGATGGAG CTTCCCCCTTGAGTCGGGCTGCTGAAGGGGGGTAGGGGATGGAAACAGTGCGTTTGCAGGAGTAAGGGTGCAGTTGGGTCCCTGCGAGAAAATGTCTCAGTTGTGGCAACTGATTGGTGACCTGGGGGGCGTTTCTGAGCCCA CAGTGCTGGCATCAGGACTCAGGTGTGAGGTGCCCCAGACCCTCCCCTTGCCAGTAATTAGCTGATGGCTCGGTGATGCCCAGGGTGAAGACTTGATTTTGGGAGTTCTCTCGTAATGACACTGAGGATGCCTT GGAGATTCTGGGCCACTTTGGTTCCCCATGAGCCAAGACGGCACTTCTAATTTGCATTCCCTACCGGAGTCCCTGTAGCCTGGCTTTCAGCTGGTGCCCAAAGTGACAAATGTATCTGCAATGACAAAGGTACCC TGGAAGGGCTCGCCCTCTGCGGAATTTCAGTTCATGCAGGCCTTGGTGCTTCCACATCTGTCCAAGGGCCTTTCAAATGTGACTTTTAACTCTGTGGATTTGCCCGGTTGTCACATTCTGAGCAGCCACAACCTACTGC ATCCCATGTAGAAGTGACCTGATTTTTTCCTGCTTTTCAAGGCTGTATGTTTACATTTGCCTCCAATCATTCCTATGGGAATTCCTTGGGAGTCTAACTTGGAGATTTTGTTTCTTCTGCCTTTGCTCCTGGGGGCT TAATCACTTCTGTGCCTCTGGTTATCTGTGGCACATTTGTCATTAGTCAACCGGAGACTCGGGGTCTGAGTGGAGGGTATGTCCCCCTCCAGTGATGGTTTCTGTTGGCTTCCCAGGGTGAGGATGACTCATGACCA CTTGCAAGTGGTTTTTGTGTCTGGGGTTTATGATCACACAGTCATACACGTTCTAACTCCAGACTGTTGAGAAAGCCTCTGGGTAAGGGAATTCCTGGGAAACACACTGTTTTCATGCATCCTCTGGAAGATGAGGCCT GAAGTTACCAGGGTCTCTGTTTGCTGATGATCCACATTTTCTAGCCCACTCTGCTTCTCTGACACCTTTAGTCTTGAGGATCCATGNTCTGTGAAGGAATCCAAGCTCTCATTTCGCACTCACCTTGGCCCTGGCTC TGTCTCCAGGACCTCTTCTACTACAAAATCCTAAAGCTCTGGGAGCTGGGTGTCAACCTGTGCCCGAGGAAATCATACAGTTACTGTGGACTTTCCAGTTTGCTGTCTTCTAGTATTCCATTGTAGCTCTTGGGTATTTTCCC ATCCACCCCAAGATCCAGCTGGAAATCAGTGAACACACTTGATGGGAGTTTTCCTGCATGTGCTCTGGGCATTGACAGTAGAAGGGTGTTCAGAATGTCTGCTGTGCCCTCATGGAGGAAGAGNGCTCAGTGTACATGCTCTG GGTCAGTAGGTGCCCTTGAGCCCAGCTTTGGGAGCAATGTTGGATGAGTGAAGGAGGGATCCAGGGCAAAGCAGGCACGACAGAGTGGAGACGGCGCTGCTGGCTCTCAGGGGAATGGGCATGGAGTGGGTAGGAGATCCACC TAAGGAGGCTGGCTGGACGAGTCAGGAGCCCCTTCCAAGGGTGGACACTGACAGGCCCCCAGTCTTGGTCTCCTGCATGCCAGAGGTACCAGCCCATCTTTTTTCCTAAACTTGATGACCTAGGGGCATGTTG AATCTCAGCCTCGCCCACTGGCGCTGGACTTGGTACACAGGGTGGGGCAAAGTGGGTACTGGATCCTGATCATCCCTGGGGTGTGGCTTCTTGCTGCACAGTCAGCTTCTAGTTCTGTAGCCCCAGCTGCTCCTGCG GTGGAGCTACACATCAGGCTCTGACCCCCTCCAGGTGGGGCCTTCGCGTGAGGGGAGTCAGCACGCATCAGCAGCTGGGCCCAGGGAGTTGCCCCACTGAGCACTGCGGGCTGACCTGCTCCCAACCAGGGAGATGGAG CTTCCCCCTTGAGTCGGGCTGCTGAAGGGGGGTAGGGGATGGAAACAGTGCGTTTGCAGGAGTAAGGGTGCAGTTGGGTCCCTGCGAGAAAATGTCTCAGTTGTGGCAACTGATTGGTGACCTGGGGGGCGTTTCTGAGCCCA CAGTGCTGGCATCAGGACTCAGGTGTGAGGTGCCCCAGACCCTCCCCTTGCCAGTAATTAGCTGATGGCTCGGTGATGCCCAGGGTGAAGACTTGATTTTGGGAGTTCTCTCGTAATGACACTGAGGATGCCTT CAAGTTGGGCTTCTGGCATGTTCTGCCCTCGCTCCCCTTCTGTAGTCACCTTGGCCCTCGTGTTGCTGAGCTGTGGGAGCGGGAAGCGCGTCAGTGGGCGGAGTATTTGAG AACATTTCACAAGCCGCTGTTGAGGTTCAGAATCAACCAGCAGATACAGAAACATATTTCGGAGCGTGGGGACCCTTGGGTGAGCTGCCACATGAAGCAGCCCCAGGACCTCCCTGGCTCAAGGAGTGACAGCGAGTTTGTCT GAGGTGAGGGCACAGGCCTGGCGAAGCCTCGTGTGTGGGTGAGACCTGCCCGACCCCAGTGCCTTACCCGAGGAGCTACTGGCCCAGTGGGGGAGGCATTCAGGTGGGCAGAGTCAGGGAGACTCATGAGGCCGTTGAGGCCA GGGGCATAGAGCTGGCCAAGGAGCCATGGCTCACTAACGTGTTGTATGGGGCTCCTTCAGGTCCAGGCTCCTGCGTGAAGTGATGCTCCTCTTTGCCTTACTCCTAGCCATGGAGCTCCCATTGGTGGCAGCCAGTGC CACCATCGCGCTCAGTGTAAGTATCATTCCCTCTCACTGTCCTGGAGAGGACGAGAATTCCACCTGGAGATTCTGGGCCACTTTGGTTCCCCATGAGCCAAGACGGCACTTCTAATTTGCATTCCCTACCGGAGTCCCTGTCT GTAGCCTGGCTTTCAGCTGGTGCCCAAAGTGACAAATGTATCTGCAATGACAAAGGTACCCTGGAAGGGCTCGCCCTCTGCGGAATTTCAGTTCATGCAGGCCTTGGTGCTTCCACATCTGTCCAAGGGCCTTTCAAAT GTGACTTTTAACTCTGTGGATTTGCCCGGTTGTCACATTCTGAGCAGCCACAACCTACTGCATCCCATGTAGAAGTGACCTGATTTTTTCCTGCTTTTCAAGGCTGTATGTTTACATTTGCCTCCAATCATTC CTATGGGAATTCCTTGGGAGTCTAACTTGGAGATTTTGTTTCTTCTGCCTTTGCTCCTGGGGGCTTAATCACTTCTGTGCCTCTGGTTATCTGTGGCACATTTGTCATTAGTCAACCGGAGACTCGGGGTCTGAGTG GAGGGTATGTCCCCCTCCAGTGATGGTTTCTGTTGGCTTCCCAGGGTGAGGATGACTCATGACCACTTGCAAGTGGTTTTTGTGTCTGGGGTTTATGATCACACAGTCATACACGTTCTAACTCCAGACTGTTGAGAAA GCCTCTGGGTAAGGGAATTCCTGGGAAACACACTGTTTTCATGCATCCTCTGGAAGATGAGGCCTGAAGTTACCAGGGTCTCTGTTTGCTGATGATCCACATTTTCTAGCCCACTCTGCTTCTCTGACACCTTTAGT CTTGAGGATCCATGNTCTGTGAAGGAATCCAAGCTCTCATTTCGCACTCACCTTGGCCCTGGCTCTGTCTCCAGGACCTCTTCTACTACAAAATCCTAAAGCTCTGGGAGCTGGGTGTCAACCTGTGCCCGAGGAAATCATAC AGTTACTGTGGACTTTCCAGTTTGCTGTCTTCTAGTATTCCATTGTAGCTCTTGGGTATTTTCCCATCCACCCCAAGATCCAGCTGGAAATCAGTGAACACACTTGATGGGAGTTTTCCTGCATGTGCTCTGGGCATTGACAG TAGAAGGGTGTTCAGAATGTCTGCTGTGCCCTCATGGAGGAAGAGNGCTCAGTGTACATGCTCTGGGTCAGTAGGTGCCCTTGAGCCCAGCTTTGGGAGCAATGTTGGATGAGTGAAGGAGGGATCCAGGGCAAAGCAGGCAC GACAGAGTGGAGACGGCGCTGCTGGCTCTCAGGGGAATGGGCATGGAGTGGGTAGGAGATCCACCTAAGGAGGCTGGCTGGACGAGTCAGGAGCCCCTTCCAAGGGTGGACACTGACAGGCCCCCAGTCTTGGTCTCCT GCATGCCAGAGGTACCAGCCCATCTTTTTTCCTAAACTTGATGACCTAGGGGCATGTTGAATCTCAGCCTCGCCCACTGGCGCTGGACTTGGTACACAGGGTGGGGCAAAGTGGGTACTGGATCCTGATCATCCCTA TCCCTGGGGTGTGGCTTCTTGCTGCACAGTCAGCTTCTAGTTCTGTAGCCCCAGCTGCTCCTGCGGTGGAGCTACACATCAGGCTCTGACCCCCTCCAGGTGGGGCCTTCGCGTGAGGGGAGTCAGCACGCATCAGCAG CTGGGCCCAGGGAGTTGCCCCACTGAGCACTGCGGGCTGACCTGCTCCCAACCAGGGAGATGGAGCTTCCCCCTTGAGTCGGGCTGCTGAAGGGGGGTAGGGGATGGAAACAGTGCGTTTGCAGGAGTAAGGGTGCAGTTGGG TCCCTGCGAGAAAATGTCTCAGTTGTGGCAACTGATTGGTGACCTGGGGGGCGTTTCTGAGCCCACAGTGCTGGCATCAGGACTCAGGTGTGAGGTGCCCCAGACCCTCCCCTTGCCAGTAATTAGCTGATGGCTCGGTGATG CCCAGGGTGAAGACTTGATTTTGGGAGTTCTCTCGTAATGACACTGAGGATGCCTTCAAGTTGGGCTTCTGGCATGTTCTGCCCTCGCTCCCCTTCTGTAGTCACCTTGGCCCTCGTGTTGCTGAGCTGTGTGT GGGAGCGGGAAGCGCGTCAGTGGGCGGAGTATTTGAGAACATTTCACAAGCCGCTGTTGAGGTTCAGAATCAACCAGCAGATACAGAAACATATTTCGGAGCGTGGGGACCCTTG GGTGAGCTGCCACATGAAGCAGCCCCAGGACCTCCCTGGCTCAAGGAGTGACAGCGAGTTTGTCTGAGGGCACAGGCCTGGCGAAGCCTCGTGTGTGGGTGAGACCTGCCCGACCCCAGTGCCTTACCCGAGGAGCTA CTGGCCCAGTGGGGGAGGCATTCAGGTGGGCAGAGTCAGGGAGACTCATGAGGCCGTTGAGGCCAGGGGCATAGAGCTGGCCAAGGAGCCATGGCTCACTAACGTGTTGTATGGGGCTCCTTCAGGTCCAGGCTCCTG CGTGAAGTGATGCTCCTCTTTGCCTTACTCCTAGCCATGGAGCTCCCATTGGTGGCAGCCAGTGCCACCATCGCGCTCAGTGTAAGTATCATTCCCTCTCACTGTCCTGGAGAGGACGAGAATTCCACCTGCCAGTGCCTTAC CCGAGGAGCTACTGGCCCAGTGGGGGAGGCATTCAGGTGGGCAGAGTCAGGGAGACTCATGAGGCCGTTGAGGCCAGGGGCATAGAGCTGGCCAAGGAGCCATGGCTCACTAACGTGTTGTATGGGGCTCCTTCAGGT CCAGGCTCCTGCGTGAAGTGATGCTCCTCTTTGCCTTACTCCTAGCCATGGAGCTCCCATTGGTGGCAGCCAGTGCCACCATCGCGCTCAGTGTAAGTATCATTCCCTCTCACTGTCCTGGAGAGGACGAGAATTCCACCTGG AGATTCTGGGCCACTTTGGTTCCCCATGAGCCAAGACGGCACTTCTAATTTGCATTCCCTACCGGAGTCCCTGTAGCCTGGCTTTCAGCTGGTGCCCAAAGTGACAAATGTATCTGCAATGACAAAGGTACCCTG GAAGGGCTCGCCCTCTGCGGAATTTCAGTTCATGCAGGCCTTGGTGCTTCCACATCTGTCCAAGGGCCTTTCAAATGTGACTTTTAACTCTGTGGATTTGCCCGGTTGTCACATTCTGAGCAGCCACAACCTACTGCAT CCCATGTAGAAGTGACCTGATTTTTTCCTGCTTTTCAAGGCTGTATGTTTACATTTGCCTCCAATCATTCCTATGGGAATTCCTTGGGAGTCTAACTTGGAGATTTTGTTTCTTCTGCCTTTGCTCCTGGGGGCTTA ATCACTTCTGTGCCTCTGGTTATCTGTGGCACATTTGTCATTAGTCAACCGGAGACTCGGGGTCTGAGTGGAGGGTATGTCCCCCTCCAGTGATGGTTTCTGTTGGCTTCCCAGGGTGAGGATGACTCATGACCACT TGCAAGTGGTTTTTGTGTCTGGGGTTTATGATCACACAGTCATACACGTTCTAACTCCAGACTGTTGAGAAAGCCTCTGGGTAAGGGAATTCCTGGGAAACACACTGTTTTCATGCATCCTCTGGAAGATGAGGCCTGA AGTTACCAGGGTCTCTGTTTGCTGATGATCCACATTTTCTAGCCCACTCTGCTTCTCTGACACCTTTAGTCTTGAGGATCCATGNTCTGTGAAGGAATCCAAGCTCTCATTTCGCACTCACCTTGGCCCTGGCTCTG TCTCCAGGACCTCTTCTACTACAAAATCCTAAAGCTCTGGGAGCTGGGTGTCAACCTGTGCCCGAGGAAATCATACAGTTACTGTGGACTTTCCAGTTTGCTGTCTTCTAGTATTCCATTGTAGCTCTTGGGTATTTTCCCAT CCACCCCAAGATCCAGCTGGAAATCAGTGAACACACTTGATGGGAGTTTTCCTGCATGTGCTCTGGGCATTGACAGTAGAAGGGTGTTCAGAATGTCTGCTGTGCCCTCATGGAGGAAGAGNGCTCAGTGTACATGCTCTGGG TCAGTAGGTGCCCTTGAGCCCAGCTTTGGGAGCAATGTTGGATGAGTGAAGGAGGGATCCAGGGCAAAGCAGGCACGACAGAGTGGAGACGGCGCTGCTGGCTCTCAGGGGAATGGGCATGGAGTGGGTAGGAGATCCACCTA AGGAGGCTGGCTGGACGAGTCAGGAGCCCCTTCCAAGGGTGGACACTGACAGGCCCCCAGTCTTGGTCTCCTGCATGCCAGAGGTACCAGCCCATCTTTTTTCCTAAACTTGATGACCTAGGGGCATGTTGAA GTGACTTTTAACTCTGTGGATTTGCCCGGTTGTCACATTCTGAGCAGCCACAACCTACTGCATCCCATGTAGAAGTGACCTGATTTTTTCCTGCTTTTCAAGGCTGTATGTTTACATTTGCCTCCAATCATTC CTATGGGAATTCCTTGGGAGTCTAACTTGGAGATTTTGTTTCTTCTGCCTTTGCTCCTGGGGGCTTAATCACTTCTGTGCCTCTGGTTATCTGTGGCACATTTGTCATTAGTCAACCGGAGACTCGGGGTCTGAGTG GAGGGTATGTCCCCCTCCAGTGATGGTTTCTGTTGGCTTCCCAGGGTGAGGATGACTCATGACCACTTGCAAGTGGTTTTTGTGTCTGGGGTTTATGATCACACAGTCATACACGTTCTAACTCCAGACTGTTGAGAAA GCCTCTGGGTAAGGGAATTCCTGGGAAACACACTGTTTTCATGCATCCTCTGGAAGATGAGGCCTGAAGTTACCAGGGTCTCTGTTTGCTGATGATCCACATTTTCTAGCCCACTCTGCTTCTCTGACACCTTTAGT CTTGAGGATCCATGNTCTGTGAAGGAATCCAAGCTCTCATTTCGCACTCACCTTGGCCCTGGCTCTGTCTCCAGGACCTCTTCTACTACAAAATCCTAAAGCTCTGGGAGCTGGGTGTCAACCTGTGCCCGAGGAAATCATAC AGTTACTGTGGACTTTCCAGTTTGCTGTCTTCTAGTATTCCATTGTAGCTCTTGGGTATTTTCCCATCCACCCCAAGATCCAGCTGGAAATCAGTGAACACACTTGATGGGAGTTTTCCTGCATGTGCTCTGGGCATTGACAG The British Columbia Cancer Agency Genome Sciences Centre: Platforms for collaborative genomic analyses.

The Genome Sciences Centre. . . • Mandate: to become a world-class Genome Centre. The Genome Sciences Centre. . . • Mandate: to become a world-class Genome Centre. • Department of the British Columbia Cancer Agency Research Centre. • Located on the third floor of the Vancouver Cancer Clinic. • Moved into current lab space Dec. 13, 1999. • 12, 000 sf interim space divided into Structural Genomics and bioinformatics (10, 500 sf) and Functional Genomics (1, 500 sf). • Renovation, start-up and some operating funds provided by the BC Cancer Foundation. Major projects are grant funded. • Focus initially is on large-scale high-throughput mapping, sequencing and bioinformatics projects.

Staff Staff

Vision Vision

Advantages Centre Location Genomics Emphasis & Expertise Large. Scale Genomics Clinical Context Clinical Trials Advantages Centre Location Genomics Emphasis & Expertise Large. Scale Genomics Clinical Context Clinical Trials Regional Mandate Sanger Centre Cancer Genomics Project United Kingdom Sequencing genes in tumour DNA √ √ Baylor College of Medicine Human Genome Sequencing Center Texas Genome mapping and sequencing √ MD Anderson Cancer Center Texas No large-scale genomics emphasis √ √ Memorial Sloan Kettering Cancer Centre New York No large-scale genomics emphasis √ √ Dana Farber Cancer Institute Boston No large-scale genomics emphasis √ √ Cancer Genome Anatomy Project, NCBI Multiinvestigator consortium Gene expression analysis by SAGE √ √ Ontario Cancer Institute Toronto Gene expression analysis by microarray √ √ Cross Cancer Institute Edmonton No large-scale genomics emphasis √ √ Genome Sciences Centre, BC Cancer Agency Vancouver Cancer genomics and genetics, genome mapping and sequencing, bioinformatics, genotyping, gene expression profiling by SAGE and microarrays √ √

BCCA Collaborations BCCA Collaborations

Funding $79 Million in Competitive Grant Funding, 1999 to Present Funding $79 Million in Competitive Grant Funding, 1999 to Present

Technologies ¨Bioinformatics ¨DNA sequencing ¨Expression profiling ¨Whole Genome Shotgun ¨SNP discovery ¨BAC fingerprint mapping Technologies ¨Bioinformatics ¨DNA sequencing ¨Expression profiling ¨Whole Genome Shotgun ¨SNP discovery ¨BAC fingerprint mapping ¨Genotyping ¨Affymetrix arrays ¨Protein profiling

Capacity Capacity

Funding opportunities Funding opportunities

Publications Publications

Scientific staff Scientific staff

Projections Projections

Training B. Sc. Biochemistry (University of Ottawa) B. Sc. (Hon. ) Physics-Math (University of Training B. Sc. Biochemistry (University of Ottawa) B. Sc. (Hon. ) Physics-Math (University of Ottawa) M. Sc. Physics (UBC) Genome Sciences Centre 1999 -2001 System Administrator computing infrastructure; mapping/sequencing data processing pipeline; data mining and visualizations; maintenance and design of extranet/intranet 2001 -2002 Bioinformatics Coordinator management and coordination of bioinformatics activities Martin Krzywinski 2002 - Scientist, Bioinformatics development of GSC BAC rearray technology; application of fingerprint maps to sequence validation; mapping analysis toolsets

Research Themes @ whole-genome BAC rearrays > generation of comprehensive BAC clone sets covering Research Themes @ whole-genome BAC rearrays > generation of comprehensive BAC clone sets covering the entire genome for human and mouse using fingerprint maps and sequence information + rearrays targetted for CGH/FISH application + 50 kb resolution @ informatics > application of multiple-enzyme fingerprints to validate Release 3 sequence assembly of Drosophila melanogaster > distributed fingerprint map search service > use of fingerprint technology to study rearranged DNA from tumour tissue @ computing > development of web-based utilities and computer cluster tools > automation, data representation and visualization

Whole Genome BAC Rearrays - Human and Mouse @ set of 30, 000 bacterial Whole Genome BAC Rearrays - Human and Mouse @ set of 30, 000 bacterial artificial chromosome clones (~150 kb) > optimized for size and overlap @ 99%+ coverage of genome (sequence assembly and fingerprint map) @ identity of clones validated with fingerprinting @ 50 kb average resolution - any position in the genome is represented by 1 -2 clones Figure. Chromosome 10 as a graph. Clones are selected from the fingerprint map, and sequence data is used to characterize and fill gaps in coverage. Figure. Coverage of the human genome by the 32, 000 BAC clone human rearray set. Blue areas represent 100% coverage.

Martin Krzywinski fingerprint map contigs detected genome position of BAC clones Figure top. Excerpt Martin Krzywinski fingerprint map contigs detected genome position of BAC clones Figure top. Excerpt of mouse chromosome 5 (122 -132 Mb) showing fingerprint map contigs and clone layout Figure left. Distribution of clone covers in the mouse rearray. 50% of covers are smaller than 50 kb. inferred Figure. Clone position in the fingerprint map is used to ensure genomic coverage where sequence information is not yet available. Figure. Controlled overlap produces small clone covers, smallest regions that can be detected by CGH/FISH experiments.

Validation of Drosophila Release 3 Sequence Assembly @ tiling set BACs from Drosophila sequence Validation of Drosophila Release 3 Sequence Assembly @ tiling set BACs from Drosophila sequence assembly fingerprinted with 5 enzymes > 1000 clones, 120 Mb of euchromatic sequence @ in-silico digests of BAC sequence compared to experimental fingerprints @ fingerprint size resolution ~ 1 % @ independent way of assessing correctness of difficult repeat-rich assembly regions Figure. (top) Outline of verification process, showing a putative 3 enzyme digest method (right) detection of correct and incorrect sequence assembly

Application of Fingerprinting to Study of Translocations in Cancer @ study origin of DNA Application of Fingerprinting to Study of Translocations in Cancer @ study origin of DNA of BACs derived from cancer tissue > no sequence information except BAC ends @ similarity matrix of fingerprint used to locate similarity regions in the genomic sequence @ in-silico digest of sequence reveals potential translocation 200 kb BAC from tumour tissue Figure. Putative BAC derived from three distinct genomic regions. Figure. Block diagnonal elements reveal regions in the fingerprint map which closely match areas of the cancer BAC.

Training B. Sc. Biochemistry (Bristol) M. Sc. Genetics (SFU) Ph. D. Bioinformatics (Sanger Institute) Training B. Sc. Biochemistry (Bristol) M. Sc. Genetics (SFU) Ph. D. Bioinformatics (Sanger Institute) Genome Sciences Centre 1999 -2001 System Administrator computing infrastructure; mapping/sequencing data processing pipeline; data mining and visualizations; maintenance and design of extranet/intranet 2001 -2002 Bioinformatics Coordinator management and coordination of bioinformatics activities Steven Jones 2002 - Scientist, Bioinformatics development of GSC BAC rearray technology; application of fingerprint maps to sequence validation; mapping analysis toolsets

Research Themes @ Bioinformatic analysis of Gene Expression in Cancer @ Laboratory Information Management. Research Themes @ Bioinformatic analysis of Gene Expression in Cancer @ Laboratory Information Management. @ Computational analysis of gene regulatory elements @ Software development to support physical mapping @ Bioinformatic support for other projects including gene expression in early mouse and C. elegans development, forestry and salmonid genomics, the Mammalian Gene Collection Program (NCI – USA).

Discovery. Space: A Platform for analysis and annotation of (differentially expressed) genes. Discovery. Space Discovery. Space: A Platform for analysis and annotation of (differentially expressed) genes. Discovery. Space integrates functional information, pathway, disease, model organism and literature information for gene expression analysis.

Sockeye Genome Viewer For visualization and detection of gene regulatory elements Conserved DNA sequences Sockeye Genome Viewer For visualization and detection of gene regulatory elements Conserved DNA sequences between human and other mammals are indicated

Sockeye Cont. . Detected polymorphic variances between individuals are shown here as spikes Sockeye Cont. . Detected polymorphic variances between individuals are shown here as spikes

i. CE – Internet Contig Explorer Online access for Physical Map Data Physical maps i. CE – Internet Contig Explorer Online access for Physical Map Data Physical maps available online for: Human Mouse Rat Bovine C. neoformans

Jaswinder Khattra - Background • BSc Biology (1994), SFU • Fisheries & Oceans Canada Jaswinder Khattra - Background • BSc Biology (1994), SFU • Fisheries & Oceans Canada (1995 -2001). West Vancouver Lab, Molecular Biology Program. Research Technician. - Molecular Parasitology: Diagnostic PCR and phylogenetic analysis of pathogens relevant to wild and cultured aquatic species. - Salmon genetics: characterization of GH-transgene insertions in Sockeye genomes. • Genome Sciences Centre (2001)

Jaswinder Khattra - Activities • Gene Expression Laboratory, Coordinator: - Serial Analysis of Gene Jaswinder Khattra - Activities • Gene Expression Laboratory, Coordinator: - Serial Analysis of Gene Expression (SAGE) – C. elegans longevity studies and expression profiles of developmental stages, cells and tissues; mouse atlas of expression; human tumor cells subject to transient hypoxia; human and mouse ES cell lines. - Affymetric Gene. Chip platform – high-density oligonucleotide DNA chips for genome-wide expression analysis and genotyping. - Mammalian Gene Collection, directed approach. - Genomic shotgun library construction – Rhodococcus RHA 1, Cryptococcus neoformans WM 276 - RNA: isolation and analysis at the picogram level (10’s of cells) - Technology development: application of SAGE and Gene. Chip protocols at nanogram levels of total RNA (100’s of cells).

SAGE schematic SAGE schematic

Gene. Chip Expression Analysis Overview 1. 2. 3. 4. 5. 6. RNA isolation and Gene. Chip Expression Analysis Overview 1. 2. 3. 4. 5. 6. RNA isolation and analysis – Day 1 Eukaryotic labeling chemistry – Day 2 Hybridization – Days 3 & 4 Washing & Staining on Fluidics station – Days 4 & 5 Scanning – Days 4 & 5 Raw data processing & analysis - Microarray Suite v 5. 0, Net. Affx, Gene. Spring.

MGC library-specific transcript size and abundance variation NIH-MGC 72 (melanoma) Hs_952 Hs_674 FR Rev MGC library-specific transcript size and abundance variation NIH-MGC 72 (melanoma) Hs_952 Hs_674 FR Rev For Neg 12 kb - 11 4. 0 kb - 2. 0 kb 1. 6 kb - NIH-MGC 85 (lymphoma) 3. 9 2. 0 1. 8 1. 4 1. 0 kb - 1% agarose, 1 x TAE 5% of PCR product loaded For = p. CMV-Sport 6 vector primer (SP 6 variant) Rev = gene-specific reverse primer Hs_952 = SLC 10 A 1, solute carrier family 10 (predicted 1. 8 kb) Hs_674 = IL 12 B, interleukin 12 B (predicted 2. 3 kb)

Rhodococcus RHA 1 whole genome shotgun library Rhodococcus RHA 1 whole genome shotgun library

Agilent Bioanalyzer RNA Picochip: 115 pg/u. L total RNA 25 nt marker Agilent Bioanalyzer RNA Picochip: 115 pg/u. L total RNA 25 nt marker

Rob Holt • Ph. D. in molecular neuropharmacology from University of Alberta. • Postdoctoral Rob Holt • Ph. D. in molecular neuropharmacology from University of Alberta. • Postdoctoral work in molecular mechanisms of adaptive evolution in primates. State University of New York, Albany. • Founding member of Celera Genomics. • managed design and scale up of sequencing platform. • a senior author on Celera’s Drosophila, human and mouse genome publications. • lead scientist for whole genome analysis of the malaria mosquito A. gambiae. • Joined GSC as Sr. Scientist and Head of Sequencing in Nov ‘ 02

Current Research Interests • Whole genome sequencing and analysis • Technology development • Vector Current Research Interests • Whole genome sequencing and analysis • Technology development • Vector systems and library construction • Molecular cloning • Laboratory automation • Comparative sequencing and analysis of genomic regions implicated in complex disease.

Classification of Human Proteins Classification of Human Proteins

Human Genome Duplications Human Genome Duplications

 • Mouse gene content and order is highly conserved with blocks of human • Mouse gene content and order is highly conserved with blocks of human chromosomes 3, 8, 12, 16, 21 and 22. • Of 731 predicted mouse. Chr 16 genes… 509 1: 1 orthologs 44 paralogs 144 other chromosomes 14 unique to mouse

Anopheles gambiae • Principal vector of the malaria parasite plasmodium falciparum • 300 -900 Anopheles gambiae • Principal vector of the malaria parasite plasmodium falciparum • 300 -900 million clinical attacks of malaria per year • 1 -3 millions deaths, primarily African children • Historically, greatest advances against malaria have come from mosquito control

Regulation of global gene expression by flood feeding (EST analysis). Regulation of global gene expression by flood feeding (EST analysis).

Long term goals of Anopheles genomics • Define molecular markers to detect and monitor Long term goals of Anopheles genomics • Define molecular markers to detect and monitor the spread of insecticide resistance. • Discover new insecticides and increase the efficacy of current vector-targeted control efforts. • Understanding and subverting the strong preference of A. gambiae for HUMAN BLOOD. • Perhaps creating and releasing genetically altered mosquitoes that are resistant to Plasmodium.

 • • • • BSc. Biochemistry and Math, SFU MSc. Medical Biophysics, U • • • • BSc. Biochemistry and Math, SFU MSc. Medical Biophysics, U of T Tony Pawson, oncogene structure / function Ph. D. Medical Genetics, UBC Paul Goodfellow, MEN 2 PDF Pathology, U of W Ray Monnat, Werner syndrome Sequana Therapeutics / Axys Pharmaceuticals Asthma program co-leader, physical mapping Xenon Genetics, Inc. : Director of Human Genetics ABCA 1 mutated in Tangier disease and Familial HDL Deficiency Genome Sciences Centre Cancer Genetics

Cancer Genetics Group: Current Focus • Genetic susceptibility to cancer • Pharmacogenetics • Technology: Cancer Genetics Group: Current Focus • Genetic susceptibility to cancer • Pharmacogenetics • Technology: • • SNP / Variant Discovery SNP / Variant Genotyping

Genetic Susceptibility to Cancer • Why do certain individuals develop particular cancers? • Germline Genetic Susceptibility to Cancer • Why do certain individuals develop particular cancers? • Germline factors (not somatic / tumour changes) • Basis for future screening / surveillance programs to limit cancer incidence and reduce mortality; ‘personalized medicine’ • Genetic association studies (case / control) • Collaborations with Cancer Control Research (interactions with lifestyle / environmental factors) • Current focus: Non-Hodgkin Lymphoma* *Collaboration with John Spinelli

Pharmacogenetics • Genetic factors contributing to (adverse) drug response • Variation in drug metabolism Pharmacogenetics • Genetic factors contributing to (adverse) drug response • Variation in drug metabolism genes • Basis for future screening / surveillance programs to limit side effects of drug treatments; ‘personalized medicine’ • Genetic association studies (case / control) • Size of trial / sample numbers are key • Current focus: Drug-induced hepatotoxicity in latent tuberculosis infection (collaboration with the BC Centres for Disease Control)

SNP Discovery 1 2 Template aliquotting: Robbins Hydra 3 PCR Set-up: Packard Multiprobe II SNP Discovery 1 2 Template aliquotting: Robbins Hydra 3 PCR Set-up: Packard Multiprobe II liquid handler PCR and cycle sequencing: MJ Tetrads 5 PCR products Cycle Sequencing 4 6 Sequencing: ABI 3700 s Purification of PCR Products: Agencourt

Data Analysis in SNP Discovery Data Analysis in SNP Discovery

E-cadherin Mutations in Gastric Cancer* Exon 5 splice mutation (IVS 5 +1 G to E-cadherin Mutations in Gastric Cancer* Exon 5 splice mutation (IVS 5 +1 G to A) Exon 9 deletion (1212 del. C) *Collaboration with David Huntsman Exon 12 insertion (1779 ins. C) Exon 9 SNP (W 409 R)

SNP Genotyping 1 2 PCR Set-up: Packard Multiprobe II liquid handler Template aliquotting: Robbins SNP Genotyping 1 2 PCR Set-up: Packard Multiprobe II liquid handler Template aliquotting: Robbins Hydra 4 3 Read Taq. Man Genotypes: ABI 7900 PCR and cycle sequencing: MJ Tetrads

Supplemental Slides Supplemental Slides

Genomics and the Future of Cancer Care B Cancer Patients Gene expression profiling Somatic Genomics and the Future of Cancer Care B Cancer Patients Gene expression profiling Somatic mutation detection Pharmacogenomics A cancer patient visits a BC Cancer Agency clinic Early detection and Characterization of lesion Gene expression profiling Somatic mutation detection Pharmacogenomics Customized Treatment + Clinical Care A Increased Surveillance: Healthy individuals each provide a blood sample for testing at a clinic General Population Legend No appreciable cancer susceptibility Susceptible to developing a cancer Diagnosed with cancer Susceptibility Testing: Genotyping Genetic analysis Proteomics: New Tumour Markers Frequent screening: Blood-based tests Mammography Colonoscopy Cervical screening

High-Throughput Pipelines at the GSC 1. Whole genome fingerprinting mouse rat cow 2. Bioinformatics High-Throughput Pipelines at the GSC 1. Whole genome fingerprinting mouse rat cow 2. Bioinformatics sequence analysis comparative genomics 3. Sequencing genomic sequencing SAGE SNP discovery 4. Genotyping

Summary of Projects Active: NHL Susceptibility (Brooks-Wilson and Spinelli) NHL Inter. Lymph (Brooks-Wilson and Summary of Projects Active: NHL Susceptibility (Brooks-Wilson and Spinelli) NHL Inter. Lymph (Brooks-Wilson and Spinelli) Gastric Cancer (with David Huntsman, Genome BC) Pediatric Cancer (with Poul Sorensen) Proposed: NHL Gene / Environment (Spinelli and Brooks-Wilson) NHL Genome Scan (Brooks-Wilson, Spinelli, Sequenom) Breast Cancer (C. Bajdik, K. Aronson) Prostate Cancer (R. Gallagher) Aging (Marra, Brooks-Wilson et. al. ) Planned: Many others!

Inherited Vs. Somatic Genetic Variation Constitutional Genetic Variation • Susceptibility • Resistance Somatic Mutation Inherited Vs. Somatic Genetic Variation Constitutional Genetic Variation • Susceptibility • Resistance Somatic Mutation • • Point mutations LOH events Epigenetic changes Tumor evolution

Background • B. Sc. from SFU: biochemistry major, biology minor. • M. Sc. from Background • B. Sc. from SFU: biochemistry major, biology minor. • M. Sc. from SFU: C. elegans genetics. • 1997 -1999: Genome Sequencing Center, St. Louis. Involved in generation of large-insert clone fingerprints and their use in physical map construction. Worked on the C. briggsae, A. thaliana and human genomes. • 1999: Joined the Genome Sciences Centre, BC Cancer Agency. Currently, head of the Mapping group.

Mapping Group Activities Fingerprinting: • BAC/fosmid clone-based genome maps • Sequence assembly verification • Mapping Group Activities Fingerprinting: • BAC/fosmid clone-based genome maps • Sequence assembly verification • BAC arrays for CGH experiments Development of related software • Automated restriction fragment identification • Automated tools for refinement of fingerprint assemblies • Automated clone selection for sequencing • Web-based fingerprint map viewer

Definition of a Fingerprint Map A fingerprint map is a set of fingerprints (restriction Definition of a Fingerprint Map A fingerprint map is a set of fingerprints (restriction digests of BACs or other large-insert clones) assembled into “contigs”. The contigs are clusters of related clones representing the genomic regions from which the clones were derived.

Building a Fingerprint Map • 384 -well glycerol stock • Inoculation/Growth • Harvest cells Building a Fingerprint Map • 384 -well glycerol stock • Inoculation/Growth • Harvest cells • Purify DNA • Cleave DNA • A. G. E. • Fragment I. D. • Add Markers • Stringent assembly

Fingerprinting Gels marker lanes 29, 950 bp 540 bp Digested BAC DNA is electrophoresed Fingerprinting Gels marker lanes 29, 950 bp 540 bp Digested BAC DNA is electrophoresed on 1. 2% agarose gels for 8 hours at 3 V/cm. Each gel contains 96 sample and 25 marker lanes. Two gels are run in tandem on each eletrophoresis unit. Gels are then stained in SYBR Green and the image is collected on a Molecular Dynamics Fluorimager 595.

GSC Genome Mapping Activities Organism No. fingerprint s 305, 768 No. contigs (>2) 266 GSC Genome Mapping Activities Organism No. fingerprint s 305, 768 No. contigs (>2) 266 ~ 2. 6 GB Complete (18 X) WUSTL GSC Whitehead Inst. NHGRI 2, 642 2, 612 2, 630 20 (20) 20 (19) 17(17) 16 MB Complete (16 X) Jim Kronstad, UBC 2, 032 51 (50) ~ 20 MB Complete (9 X) Jim Kronstad, UBC 736 7 (7) 4. 9 MB Complete (15 X) WUSTL GSC Rod Wing, Clemson Rattus norvegicus 185, 292 11, 262 (9, 982) ~ 2. 7 GB Complete (10 X) Bos taurus 294, 652 10, 116 (8, 498) ~ 3 GB Complete (16 X) WUSTL GSC Baylor HGC NHGRI USDA S. Moore, Uof. A ASRA 4, 561 78 (75) 34 MB Complete (12 X) Peter Myler, SBRI 46, 024 5, 950 (4, 338) ~500 MB Complete (9 X) Carl Douglas / Brian Ellis, UBC Salmo salar 135, 800 7, 943 (6185) ~3 GB? ? In progress W. Davidson, SFU Ben Koop, SFU Stickleback N/A (78, 000) N/A ~700 MB? ? In progress Richard Myers David Kingsley Mus musculus Genome Size Status (coverage) (C 57 BL/6) C. neoformans JEC 21 C. neoformans H 99 C. neoformans WM 276 Ustilago hordeii S. typhimurium (Holstein, Hereford, Angus) Leishmania major Poplar Collaborator

Software Development Band. Leader* • Automated detection and sizing of restriction fragments • 97% Software Development Band. Leader* • Automated detection and sizing of restriction fragments • 97% overall accuracy in fragment identification • 98% accuracy in multiplet identification • Has been used for the analysis of over 1 million fingerprints D. Fuhrmann et al. , Genome Research (in press)

i. CE: Internet Contig Explorer* http: //ice. bcgsc. ca *C. Fjell et al. – i. CE: Internet Contig Explorer* http: //ice. bcgsc. ca *C. Fjell et al. – Genome Research (in press)

S. Gorski Background 1999 - current NCIC Research Fellow; lead Programmed Cell Death (PCD) S. Gorski Background 1999 - current NCIC Research Fellow; lead Programmed Cell Death (PCD) research team at the Genome Sciences Centre 1994 -1999 Ph. D. , Washington University School of Medicine, Division of Biology and Biomedical Sciences. PCD in Drosophila retinal development. 1991 -1992 M. Sc. , University of British Columbia, Department of Medical Genetics. Human genetic linkage analysis. 1990 B. Sc. Honors in Biology, Simon Fraser University

PCD Group Research Activities/Interests • Cloning and characterization of inxs and echinus, two genes PCD Group Research Activities/Interests • Cloning and characterization of inxs and echinus, two genes involved in apoptotic cell death in the Drosophila retina • Identification of the genes necessary and sufficient for autophagic cell death in Drosophila and mammals • Role of autophagic cell death in cancer and investigation of therapeutic potential of autophagic cell death for cancer

inxs is required for PCD in the Drosophila retina. wild-type inxs. B 94/inxs. P inxs is required for PCD in the Drosophila retina. wild-type inxs. B 94/inxs. P 2 * * * *

inxs candidate region Do you want? inxs candidate region Do you want?

A SAGE Approach to Discovery of Genes Involved in Autophagic Cell Death. Sharon M. A SAGE Approach to Discovery of Genes Involved in Autophagic Cell Death. Sharon M. Gorski, Suganthi Chittaranjan, Erin D. Pleasance, J. D. Freeman, Carrie L. Anderson, Richard J. Varhol, Shaun M. Coughlin, Scott D. Zuyderduyn, Steven J. M. Jones, & Marco A. Marra Current Biology, in press. CATGACCAAGTTCG CATGACCACTGAAA CATGACCCACGAGC CATGACCTGCACGC CATGACGAGATCGG CATGACGAGCTTTT CATGACGAGGACTA CATGACGATGGCGG CATGACGCGATCCA CATGACTATCTAAA CATGACTGCGTTAG CATGACTTACGATT CATGACTTTGTTAA CATGAGAAATAAAA CATGAGAACAACTA CATGAGAAGATAAA

Drosophila salivary gland PCD • autophagic • stage-specific • synchronous (Jiang et al. , Drosophila salivary gland PCD • autophagic • stage-specific • synchronous (Jiang et al. , 1997) • known cell death genes are regulated transcriptionally RT-PCR analysis Reverse transcription hr (APF, 18°C) diap 2 rpr hid - + - + -+ - + 16 18 20 22 23 24

SAGE Identifies Genes Associated Previously With Salivary Gland Death BFTZ-F 1 BR-C E 74 SAGE Identifies Genes Associated Previously With Salivary Gland Death BFTZ-F 1 BR-C E 74 E 93 rpr hid ark dronc crq Ec. R/USP E 75 iap 2 Cell Death

1244 genes are expressed differentially (p <. 05) prior to salivary gland PCD 512 1244 genes are expressed differentially (p <. 05) prior to salivary gland PCD 512 genes have associated biological annotations (Flybase Gene Ontology) R. Varhol, S. Zuyderduyn 732 genes have unknown functions 377 of these were unpredicted

Autophagic cell death and cancer Examples • spontaneous regression of human neuroblastoma • tamoxifen-treated Autophagic cell death and cancer Examples • spontaneous regression of human neuroblastoma • tamoxifen-treated mammary carcinoma cells (MCF-7) • bcl-2 antisense treatment of human leukemic HL 60 cells Questions • Can tumor cells resistant to apoptosis (e. g. apoptosis-inducing therapies) be induced to die instead by autophagic cell death? • Are tumors, e. g. . groups of cells, more sensitive to removal by autophagic cell death mechanisms than by other mechanisms?

Marco Marra Marco Marra

Head, Proteomics Head, Proteomics

Head, Clinical Collaborations Head, Clinical Collaborations

Genome Sciences Centre Asano, Jennifer Astakhov, Vadim Astakhova, Tamara Astell, Caroline Barber, Sarah Bilenky, Genome Sciences Centre Asano, Jennifer Astakhov, Vadim Astakhova, Tamara Astell, Caroline Barber, Sarah Bilenky, Mikhail Bosdet, Ian Brooks-Wilson, Angela Brown-John, Mabel Butterfield, Yaron Chan, Andy Chan, Susanna Chand, Steve Cherkasov, Artem Chittaranjan, Suganthi Chiu, Readman Cloutier, Alison Coughlin, Shaun Fehr, Lesa Fjell, Chris Flibotte, Stephane Freeman, Doug Girn, Noreen Gorski, Sharon Griffith, Obi Guin, Ranabir Holt, Robert Hou, Claire Hsiao, Letticia Huang, Peter Hume, Lynn Jang, Carrie Jeyes, Jennifer Jones, Steven Khattra, Jaswinder Kirkpatrick, Robert Kronstad, Jim Krzywinski, Martin Leach, Stephen Lee, Soo Sen Lee, Darlene Leung, Derek Li, Bernard Liu, Jerry Ma, Kevin Marra, Marco Masson, Amara Mathewson, Carrie Mayo, Michael Mayo, Mark Mc. Donald, Helen Mc. Kay, Sheldon Messervier, Steve Montgomery, Stephen Moran, Josh Olson, Teika Ouellette, Francis Oveisi, Mehrdad Pandoh, Pawan Pleasance, Erin Prabhu, Anna-Liisa Rak, Marcin Robertson, Gordon Rusaw, Shawn Ruzanov, Peter Saeedi, Parvaneh Schein, Jacquie Schnerch, Angelique Schoeffel, Kirk Shin, Heesun Sleumer, Monica Smailus, Duane Spence, Lorraine Stewart, Noah Stott, Jeff Teague, Kevin Tsai, Miranda Varabei, Dmitry Vardy, Jill Varhol, Richard Vatcher, Greg Warren, Rene Wye, Natasja Yang, George Zuyderduyn, Scott