1. Vince Buonaccorsi Associate Professor of Biology Juniata College

2. NextGen Sequencing Technologies 454 Sequencing (Roche) SOLiD Sequencing (ABI)

3. Throughput 400-600 million high-quality, filter-passed bases per run* 1 billion bases per day Run Time10 hours Read Length Modal length = 500 bases, Average length = 400 bases DataTrace data accepted by NCBI since 2005 http://www.454.com/products-solutions/system-features.asp

4. http://www.454.com

5. DNA Isolation: 1.Typical DNA extraction. 2.Nebulization: mechanical DNA shearing. http://www.roche-applied- science.com/publications/multimedia/genome_sequencer/flx_multimedia/wbt.htm

17. http://www.dnastar.com/media/flowgramlarge.jpg

20. http://en.wikipedia.org/wiki/File:Phred_Score.svg Q20 = -10 x log 10 (0.01) Q30 = -10 x log 10 (0.001) Quality Scores

21. Overview of Next Gen Sequencing Medini et al. 2008. Microbiology in the post-genomic era. Nature Reviews Microbiology 6:419-430

22. http://www3.appliedbiosystems.com/AB_Home/applicationstechnologies/SOLiDSyste mSequencing/OverviewofSOLiDSequencingChemistry/index.htm

25. Summary of Capabilities ~ 10k per full run 454½ to 1 Million reads of 400bp ea = 200 to 400 Mb, 10hrs http://www.454.com/products-solutions/system-features.asp SOLiD½ Billion reads of 50 to 100bp ea= 25 to 50 Gb for 3 to 10 days http://www3.appliedbiosystems.com/AB_Home/applicationstechnologies/SOLiDSystemSequencing/overviewofsolidsystem/index.htm

26. http://www.nature.com/nmeth/journal/v6/n11s/pdf/nmeth.f.268.pdf

27.  Workshops/Tutorials to Learn Freeware  Metagenomic analysis using Galaxy  Vender Assisted Analysis  CHIP-seq analysis using Soft Genetics  Miscellaneous Web Programs/ListServes  SEQanswers (http://seqanswers.com)

28. http://www.openhelix.com/

29. Metagenomic Analysis Of Windshield Splatter

30. http://main.g2.bx.psu.edu/

31. Pond et a. Genome Res. (2009) 19: 2144-2153 Taylor et al. (2007) Current Protocols in Bioinformatics 10.5.1-10.5.25

35.  Soft Genetics: http://www.softgenetics.com/NextGENe.html Soft Genetics: http://www.softgenetics.com/NextGENe.html  “The NextGENe Condensation Tool™, solves the 3 critical problems”  Reads too short  High Error Rates  Overwhelming Data Volume

37.  For many applications, the data can be analyzed in four major steps:  1. Convert sample file format.  2. Condense sequence reads (polish data)  Low frequency instrument errors  Elongating the read lengths  Optional reduction of number of reads to increase analysis speed  3. Align or assemble reads.  4. View and export results.

41.  Symposium on Life Science Education, NC State, May 2009  http://statgen.ncsu.edu/slse http://statgen.ncsu.edu/slse  DOE adopt a genome, Cheryl Kerfeld  http://www.jgi.doe.gov/education/genomeannotation.html http://www.jgi.doe.gov/education/genomeannotation.html  Bioinformatics Lab, Malcolm Campbell  http://www.bio.davidson.edu/courses/Bio343/LabMethods_2009.html http://www.bio.davidson.edu/courses/Bio343/LabMethods_2009.html  DNA Learning Center Gene Annotation labs, Bruce Nash  http://www.dnalc.org/websites/dynamic.html http://www.dnalc.org/websites/dynamic.html

42. http://www.jgi.doe.gov/education/adoptagenome/index.html

43. http://www.jgi.doe.gov/education/assembly/teacher.html

44. Application: de Novo Whole Genome Sequencing of Complex Genomes 454 for deNovo sequencing of large genomes, connect over repeats The GS FLX Titanium Series Paired End Protocol

45. http://www.jgi.doe.gov/education/assembly/quality.html

47. Apollo gene annotation of a genome region in Sebastes influenced by natural selection

48. UCSC Genome Browser http://genome.ucsc.eduhttp://genome.ucsc.edu) From Genes to Genomes in Non-Model Species

49.  Learning Objectives  Understand capabilities of emerging tools used in genetic analysis  Verbal fluency in basic principles and practices of genetics  Understand how geneticists study evolution at a variety of time scales  Independent mastery and creative thought in one area of genetics via writing research proposal  Assessment  Demonstrate understanding of material through two midterms (30%)  Presentations, case studies (25%)  Write a research proposal (45%)  http://www.juniata.edu/faculty/buonaccorsi/

50.  http://www.pacificbiosciences.com/ http://www.pacificbiosciences.com/  80,000 reads * 20,000 bp per read = 1.6GB for $100 in 10hrs start-finish

52. SNP detection against reference

53.  Cofactor Genomics  http://www.cofactorgenomics.com/home/about/cofactor-gives-back/ http://www.cofactorgenomics.com/home/about/cofactor-gives-back/  NSF REU: student internships  http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=5517&from=fund http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=5517&from=fund  NSF CCLI 200k-250k  http://www.nsf.gov/pubs/2009/nsf09529/nsf09529.html http://www.nsf.gov/pubs/2009/nsf09529/nsf09529.html  Projects that:  Build on the current understanding of how people learn  Have the potential to transform undergraduate STEM education  Research Coordination Networks in Biological Sciences (RCN)  http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=11691&org=BIO http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=11691&org=BIO  Other: Innovative approach to a well-defined, important problem

54.  A guide to web resources http://bib.oxfordjournals.org/cgi/reprint/8/1/6

55.  From 32000 ESTs  Polymorphic Metabolic EST-SSRs  Download ESTs http://www.ncbi.nlm.nih.gov/nucest  Find msats http://tandem.bu.edu/trf/trf.html  Consolidate http://egassembler.hgc.jp/http://egassembler.hgc.jp/  http://toolkit.tuebingen.mpg.de/blastclust http://toolkit.tuebingen.mpg.de/blastclust  Identify using blastx http://blast.ncbi.nlm.nih.gov/Blast.cgiblastx  ID Metabolic process http://www.uniprot.org/help/uniprotkbshttp://www.uniprot.org/help/uniprotkbs  Insert introns http://genome.ucsc.edu  Design primers http://probes.pw.usda.gov/batchprimer3/  Scan polymorphisms wet lab

60. Applications deNovo Genomic Sequencing Deep Sequencing for SNPs Ancient DNA RNA-Seq Chip-Seq Metagenomics

61. 100- base reads and up to 40 Gb of data per sequencing run

62. Applications deNovo Genomic Sequencing Deep Sequencing for SNPs RNA-Seq Chip-Seq Metagenomics

63. https://products.appliedbiosystems.com/ab/en/US/adirect/ab?cmd=catNavigate2&catID=604416&tab=DetailInfo

65. http://www.illumina.com/technology/sequencing_technology.ilmn

69. 454 Technology Medini et al. 2008. Microbiology in the post-genomic era. Nature Reviews Microbiology 6:419-430

71.  http://www.hsls.pitt.edu/guides/genetics/obrc/

76. Jonathan Rothberg Rothberg Institute of Childhood Diseases 454