Chapter 14 Genomes and Genomics

Sequencing DNA dideoxy (Sanger) method ddGTP ddATP ddTTP ddCTP 5’TAATGTACG TAATGTAC TAATGTA TAATGT TAATG TAAT TAA TA T Fred Sanger, Nobel prize 1980

Sequencing DNA dideoxy (Sanger) method Leroy Hood, Caltech Fluorescence based sequencing Norm Dovici – Capillary electrophoresis

Sequencing DNA dideoxy (Sanger) method

Sequencing DNA Dideoxy (Sanger) method and now several next generation sequencing (NGS) methods Watch the video: https://www.youtube.com/watch?v=jFCD8Q6qSTM

Genomics era: High-throughput DNA sequencing  The first high-throughput genomics technology was automated DNA sequencing in the early 1990.  TIGR (The Institute for Genomics Research) 1995 – first whole genome sequence, H. influenza  Baker’s yeast, Saccharomyces cerevisiae (15 million bp), was the first eukaryotic genome to be sequenced.  In September 1999, Celera Genomics completed the sequencing of the Drosophila genome.

Genomics: Completed genomes as 2016  Currently the genomes of over 4,000 eukaryotes and 91,000 prokaryotes are sequenced. https://www.ncbi.nlm.nih.gov/genome/browse/ This generates large amounts of information to be handled by individual computers.

Cloning/libraries BAC, YAC and ESTs BAC = bacterial artificial chromosome 150 kb, replicate in E.coli YAC = yeast artificial chromosome 150 kb -1.5 Mb, replicate in yeast

Assembling contigs

Ordered-clone Sequencing Clones ordered by restriction enzyme sites

Annotation ORF – open reading frame EST- Expressed sequence tag Based on mRNA Comparative genomics

The trend of data growth 21st century is a century of biotechnology: Genomics: New sequence information is being produced at increasing rates. (The contents of GenBank double every year) Microarray: Global expression analysis: RNA levels of every gene in the genome analyzed in parallel. Proteomics:Global protein analysis generates by large mass spectra libraries. Metabolomics:Global metabolite analysis: 25,000 secondary metabolites characterized Glycomics:Global sugar metabolism analysis

How to handle the large amount of information? Drew Sheneman, New Jersey--The Newark Star Ledger Answer: bioinformatics and Internet

Bioinformatics history In1960s: the birth of bioinformatics IBM 7090 computer The 1960s marked the beginning of bioinformatics. Prior to the advent of high-level computer languages in 1957, programmers needed a detailed knowledge of a computer’s design and were forced to use languages that were unintuitive to humans. High-level computer languages allowed computer scientists to spend more time designing complex algorithms and less time worrying about the technical details of the particular computer model they were using. By the 1960s, mainframe computers like the one pictured in the slide were becoming common at universities and research institutions, giving academics unprecedented access to computers. (As useful as these computers were, they filled entire rooms and had processing power far below that of consumer-grade personal computers today!) Margaret Oakley Dayhoff and colleagues took advantage of these developments and the accumulation of protein sequence data to create some of the first bioinformatics applications. For example, Dayhoff wrote the first computer program to automate sequence assembly, enabling a task that previously took human workers months to be accomplished in minutes. She and her colleagues also published (in paper form) the first protein sequence database and performed many groundbreaking studies regarding phylogeny and scoring sequence comparisons. For these reasons, she is considered one of the great pioneers of computational biology and bioinformatics. Margaret Oakley Dayhoff created: The first protein database The first program for sequence assembly There is a need for computers and algorithms that allow: Access, processing, storing, sharing, retrieving, visualizing, annotating…

DNA (nucleotide sequences) databases They are big databases and searching either one should produce similar results because they exchange information routinely. -GenBank (NCBI): www.ncbi.nlm.nih.gov -Arabidopsis: (TAIR) www.arabidopsis.org Specialized databases:Tissues, species… -ESTs (Expressed Sequence Tags) ~at NCBI ~at TIGR - ...many more!

Comparative genomics BLAST – basic local alignment and search tool (http://www.ncbi.nlm.nih.gov/) Homologs orthologs paralogs

Question cDNA sequences Protein sequences Genomic DNA sequences You are a researcher who has tentatively identified a human homolog of a yeast gene. You determine the DNA sequence of cDNAs of both your yeast gene and the human gene and decide to compare the gene sequences, as well as the predicted protein sequence of each, using alignment software. You would expect the greatest sequence identity from comparisons of the: cDNA sequences Protein sequences Genomic DNA sequences Both (a) and (b) will give you equivalent sequence similarity All will give equivalent sequence similarity

What is a microarray?

Types of Arrays Expression Arrays Tiling arrays cDNA Genome Affymetrix (GeneChip®) Agilent Tiling arrays

Overview of Microarrays

Transcription Profiling of a mutant WT

A “good” microarray plate Red = only in treatment Green = only in normal Yellow = found in both Black = found in neither

those turned on, those turned off Results 100’s of genes identified, those turned on, those turned off

Expression map red = up regulated green= down regulated

Question Microarray technology directly involves: PCR DNA sequencing Hybridization RFLP detection None of the above

Protein – protein interactions ChIP (chomatin immunoprecipitation) Yeast two hybrid Bi Molecular Fluorescence Complementation (BMFC)

ChIP and ChIP- chip

Yeast two hybrid

Bi Molecular Fluorescence Complementation (BMFC) Citovsky et al., 2006

Reverse genetics Gene knockouts RNAi Overexpression Altered expression

Summary DNA Sequencing and the rise of genomics Annotation of genome sequence Comparative genomics Functional genomics Protein-protein interactions ESTs Reverse genetics