the For next few weeks:
Genome projects
Chapter 4
DNA fingerprinting
Chapter 10
Cloning and genetically modified organisms
Chapter 21, Strachan (will be handed out)
Ethical considerations of human genetics
Genome, Matt Ridley
Grad student presentations
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Genome projects
E. coli - 4.6 Mb - 1997 S. cerevisiae - 12 Mb - 1996 - ~6,000 genes C. elegans - 100 Mb - 1998 - 20,000 genes D. melanogaster - 165 Mb - 2000 - 13,000 genes Arabidopsis - 2001 Fugu (pufferfish) - 400 Mb Mouse - 3000 Mb Human - 3000 Mb - 2001 - 65,000- 80,000 genes estimated
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History of genome project
First formal proposal to sequence genome in 1985 1990 - Human genome project (HGP) initiated in US with 15 year plan for completing genome Human Genome Organization (HUGO) founded to coordinate international efforts 1998 - Celera Genomics announced their 3 year plan to sequence genome TIGR (The Institute for Genomic Research)
Developed technology to characterize and annotate ESTs
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Genome project timeline
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Goals of project
Genetic map Physical map Develop DNA sequence technology Gene identification Technology development Sequencing model organism DNA
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Strategies for project
IHGSC
Hierarchical shotgun sequencing
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BAC assembly
BAC clones were digested with HindIII and the resulting fragments gave each BAC a unique fingerprint These were used to determine clone overlaps and assemble BACs into contigs Selected minimally overlapping set of clones Each clone was then shotgun sequenced after being broken into small ~2kb fragments Pair ends- sequence each clone from both ends
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Strategies for project
Celera
To practice, sequenced entire Drosophila genome in 1 year Whose DNA did they use?
5 people- 2 men, 3 women; 1 African-American, 1 AsianChinese, 1 Hispanic-Mexican, 2 Caucasians
Whole-genome shotgun sequencing
Sequence random bits of genome and assemble at the end Library construction
Made 3 plasmid libraries from each donor- with inserts of different sizes- 2 kb, 10 kb, 50 kb Goal is to get ~500 bp sequence data from both ends of each clone
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Celera genome assembly
Used 2 approaches
Computational combining of their data with sequence from GenGank- whole genome assembly
Took their random data and combined it with the data from the IHGP which had been "disassembled" and used their algorithms to assemble everything
Clustering of all fragments to regions based on mapping info, called compartmentalized assembly process
Used STS maps to orient their contigs
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Celera method
Screener
Marks all microsatellites with less than 6 bp repeats, and screens out all known repeat elements (Alu, Line, rRNA)
Overlapper
Works with all marked regions Looks for end to end overlaps of at least 40 bp and assembles contigs
Scaffolder
Uses mate-pair info to link contigs together into scaffolds
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Whole genome shotgun sequencing
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Sequencing techniques
Sanger dideoxy method Perform 4 parallel reactions, one example is shown here Dideoxy nucleotides block further chain extension
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4 colour sequencing
Greatly improved ability to obtain large amounts of sequence Need only one lane/gel Use either fluor. labelled primers or chain terminating analogs
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Genome Gaps coverage
in sequence
Some easy to fix with PCR, others more difficult
Genome size
Estimate 3200 Mb Euchromatin estimate 2.9 Gb Total amount of finished sequence is ~1 Gb
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Genome browsers
http://genome.ucsc.edu http://www.ensembl.org
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Gene content of the human genome
Only about 30,000-40,000 protein-coding genes! But, the genes are more complex than in lower organisms
Transcriptional control Alternative splicing
Average of 2.6 transcripts/gene 70% of alternative splices affect coding region of gene, rather than just changing UTR Alternative splicing in last exon seen 20% of time.
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Titling arrays to identify and define exons
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Testing whether predicted exons are expressed as mRNA
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The proteome
Full set of proteins encoded by genome More complex than invertebrates
Mainly b/c vertebrates have arranged pre-existing protein motifs into more domains structures Also some vertebrate-specific protein domains and motifs Domain architecture
Linear arrangement of domains within a protein Can be created by shuffling, adding or deleting domains
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Genomic landscape features
GC content
Found dramatic variation in CG content from 41% genome wide average Regions of high CG (50-60%) next to those with lower CG content (30-40%) Find strong correlation between CG content and gene density Correlation with G-banding
98% of clones mapping to darkest G bandsare in regions of low GC content (~37%) 80% of clones mapping to lightest G bbands have a higher GC content (~45%)
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Genomic landscape features
CpG islands
Density correlates well with gene density Some chromosomes have many more islands, chr. 19 has 43 per 1 Mb sequence Y chr. Has only 2.9 per 1 Mb Average is 10.5 islands per Mb
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Repeat content
Account for at least 50% of genome Of this 45% of genome is from trans...