1. Chapter 14 Genomes and Genomics

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

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

4. Sequencing DNA dideoxy (Sanger) method

5. Sequencing DNA Dideoxy (Sanger) method and now several next generation sequencing (NGS) methods
Watch the video:

6. 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.

7. Genomics: Completed genomes as 2016
 Currently the genomes of over 4,000 eukaryotes and 91,000 prokaryotes are sequenced.
This generates large amounts of information to be handled by individual
computers.

8. 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

9. Assembling
contigs

10. Ordered-clone Sequencing
Clones ordered by
restriction enzyme sites

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

12. 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

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

14. 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…

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

16. Comparative genomics BLAST – basic local alignment and search tool(
Homologs
orthologs
paralogs

17. 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

18. What is a microarray?

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

20. Overview of Microarrays

21. Transcription Profiling of a mutantWT

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

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

24. Expression map
red = up regulated
green= down regulated

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

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

27. ChIP and ChIP- chip

28. Yeast two hybrid

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

30. Reverse genetics
Gene knockouts
RNAi
Overexpression
Altered expression

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