The Genes, the Whole Genes, and Nothing But the Genes Jim KentUniversity of California Santa Cruz
Ben Franklin - Childhood HeroHi Voltage Experiments
A Man of High Values
Early to bedEarly to rise
Rock Collection
Shell Collection
Bottlecap Collection
Bug Collection
Jim Kent - Genome Scientist not to be confused with Richard Stallman
Modern Bug Collectionif (a = b)
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Naive Biological QuestionsIs an ant an individual?Do dolphins talk with each other?How come newts and worms can regenerate so much better than we can?How does a plant grow from a seed, an animal from an egg?
Regeneration by NatureAmong vertebrates only amphibians can regenerate limbs.The process involves dedifferentiation, repatterning, and growth.Not likely well be able to engineer this soon.Simpler regenerations though may be tractable and medically quite important.
From Egg to Adult in 3x109 BasesA single cell, the fertilized egg, eventually differentiates into the ~300 different types of cells that make up an adult body.With a few exceptions all of these cells contain the full human genome, but express only a subset of the genes.Gene expression patterns are determined largely by the cell type, and vice versa.
From Totempotency to SenilityHuman cells become more and more specialized during developmentAn egg can become anything. (Initially most of it will become placenta).Liver cells only become liver cells.A neuron cant even reproduce.
DNAmRNAtranscriptionfactorssplicingfactorsstructuralproteinsEnzymesstructuralsugarsstructurallipidsReceptorssignalingmoleculesEnvironment& other cellscreationregulationPrimary Flows of Information and Substance in Cell
An Extreme Case of DedifferentiationThe cloning of Dolly the sheep showed that a differentiated genome could be reset.An egg is huge compared to a normal cell. Putting a normal cell into an egg as Wilmut et al did, swamps out the normal cell transcription factor and receptors with egg transcription factors and receptors.Cloning success rate sometimes improved by passing a nucleus through multiple eggs.
Human Diseases Involving a Small Population of CellsParkinsons - from the death of dopamine producing neurons in the substantia negra. Macular degeneration - a leading cause of blindness in the elderly.Type I Diabetes - from the death of insulin-producing cells in the pancreas.
Pancreas Differentiation PathwayFrom Huang Tsai, J Biomed Sci 2000:7:27-34 and Jensen et al, Diabetes 2000:49 163-176
Cell Type DeterminantsCell type of parent cell.Interactions with other cells.Interactions with the extracellular environment.
Flexibility of Stem CellsIn many cases stem cells are flexible enough that putting them into a particular tissue will cause them to differentiate into the type of cells that make up that tissue.At low levels bone transplanted bone marrow (blood stem cells) develops into neuron in stroke victims!Making this happen at high enough levels to be useful will likely require some engineering.
DNAmRNAtranscriptionfactorssplicingfactorsstructuralproteinsEnzymesstructuralsugarsstructurallipidsReceptorssignalingmoleculesenvironmentother cellscreationregulationPrimary Flows of Information and Substance in Cell
To Understand the Body NeedThe genomeA comprehensive list of genesGene expression dataProtein localization in cellProtein/protein and protein/DNA interaction information. Ways to store, display and query masses of data so human investigators can focus on relevant bits.Many talented and hardworking human investigators.
The GenesIdentifying genes is a prerequisite for a great deal of other research.Expression microarraysIn situ mRNA hybridizationProducing proteins for cellular localization experimentsEtc.
The Whole GenesThe full gene including the 5 and 3 UTRs are critical forAvoiding misleading fragmentation/fusion artifacts.Understanding mRNA targeting and stabilityFinding transcription factor binding sitesUnderstanding the regulatory networks that drive and maintain cell differentiation.
Nothing But the GenesExperimental analysis is expensive.Unreal genes can mislead:Analysis of multiple alignments to look for active sites etc.Protein classification systems and phylogeniesOne bogus gene can lead to another as much annotation is done via homology.
Methods of Identifying GenesmRNA/cDNA sequencingMicroarrays covering entire genomeGenetics in model organismsCross species protein homologyCross species genomic homologyHMM and other purely computational genefinding.
cDNA SequencingExtract RNA from cells.Use reverse transcriptase and a poly-U primer to convert to RNA starting at poly-A tail.Insert cDNA into vectors that grow in E. coliSequence a read from one or both sides of insert using primers on vectorIf EST looks to be new sequence full cDNA.Artifacts and limitations are possible at each stage!
Common cDNA Problems & SolutionsFor rarely expressed genes little RNA is available.Normalize libraries. Use embryonic and exotic tissues as mRNA source.Splicing is not instantanious, can get retained introns.Spin out nuclei and just use cytoplasmic mRNAAlign to genome and look for splicingReverse transcriptase falls off before its finishedPreferentially taking larger cDNAs.G-cap selected libraries (Sugano)Normalizing only on 5 ends (Soares)
More cDNA Problems & SolutionsReverse transcriptase has a high error rate and is prone to small deletions.Compare cDNA to genomic DNASequence multiple cDNA clonesAt a low level cell seems to tolerate a certain degree of nonsense transcription and splicing. Normalizing increases concentration of these as well as of rare genes.Ignore everything thats not coding (ouch)???
cDNA Status & Summary~10,000 cDNA sequence have been accumulated over years by various labs working on gene families and pathways.Riken project has ~33,000 unique cDNAs in mouse. ~11,000 of these seem to have retained introns. ~3,000 are noncoding antisense. ~70% include initial ATGMammalian Gene Collection (MGC) has ~15,000 human cDNAs with initial ATGs. Having to resort to exotic libraries and RT-PCR to get more.Human refSeq has ~18,000 human cDNAs.
Whole Genome MicroarraysPerlegen and Affymetrix are making microarrays that cover entire non-RepeatMasker masked genome. Results on chromosome 21 and 22 published.Based on 25-mers.Rarely expressed genes may not stand out above background.Have to cope with cross-hybridization issues, GC content, etc.Advantages - no homology required, can sense lower concentrations of mRNA than random EST sequencing.
Cross-hybridization at WorkZoomed in on right side:
Genetics in Model OrganismsZap hapless yeast, worms, flies, and mice Inbreed offspring and look for twisted ones.Advantages:Works at DNA level, so expression level doesnt matterYou get hints of function right away.Can look for gene interactions simply by breeding mutants.Disadvantages:Finding which DNA is mutated can take a long time.Essential genes can be hard to find - all you see is reduced fertility in the inbreeding stage.Genes only needed in certain environments and duplicated genes may be missed in screens.
Cross Species Genome ComparisonsMutations occur more or less randomly across genome butMutations in functional areas tend to be weeded out by selectionIn comparing DNA across species, the functional areas are more conserved than the nonfunctional areas in general
Of Fish and Mice and Men
Comparative Genomics at BMP10
Conservation of Gene Features Conservation pattern across 3165 mappings of human RefSeq mRNAs to the genome. A program sampled 200 evenly spaced bases across 500 bases upstream of transcription, the 5 UTR, the first coding exon, introns, middle coding exons, introns, the 3 UTR and 500 bases after polyadenylatoin. There are peaks of conservation at the transition from one region to another.
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0.6954
0.7014
0.7082
0.7234
0.7407
0.7604
0.7904
0.9193
0.9123
0.8887
0.8756
0.8752
0.8712
0.871
0.8706
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0.8701
0.8696
0.8649
0.8672
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0.866
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0.8626
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0.862
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0.8653
0.8688
0.866
0.8656
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0.8682
0.8653
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0.8617
0.8625
0.8635
0.8616
0.865
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0.8667
0.8612
0.8604
0.8623
0.8615
0.8621
0.8599
0.8622
0.8622
0.862
0.8612
0.8631
0.8604
0.8608
0.8622
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0.8621
0.8617
0.8639
0.8619
0.8614
0.8634
0.8632
0.8612
0.8603
0.8621
0.8598
0.8584
0.8582
0.8618
0.8616
0.8658
0.8627
0.8626
0.8613
0.8597
0.8612
0.8651
0.8606
0.8592
0.8609
0.8625
0.8644
0.8633
0.8605
0.8626
0.8615
0.861
0.8599
0.86
0.8576
0.8619
0.8622
0.8602
0.8591
0.8586
0.8552
0.8596
0.8624
0.8598
0.8578
0.8582
0.8582
0.8592
0.8592
0.8599
0.8594
0.8594
0.8614
0.8626
0.8556
0.8613
0.8583
0.8571
0.8583
0.8588
0.8576
0.8605
0.8629
0.8615
0.8593
0.8579
0.8563
0.8564
0.8572
0.8608
0.8606
0.863
0.8599
0.8607
0.8581
0.8609
0.8603
0.857
0.8571
0.8595
0.8618
0.8611
0.8606
0.8593
0.8617
0.8563
0.8557
0.859
0.86
0.8603
0.8583
0.8607
0.8623
0.865
0.8626
0.8626
0.8599
0.8603
0.8593
0.8604
0.8582
0.8568
0.8614
0.8629
0.8603
0.8628
0.8625
0.8619
0.861
0.8614
0.8571
0.8628
0.8636
0.8593
0.8613
0.8641
0.8647
0.8636
0.8626
0.8653
0.8638
0.8637
0.8635
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0.8641
0.8668
0.8699
0.8723
0.8731
0.8759
0.8816
0.8952
0.9059
0.9199
0.9377
0.9877
0.7938
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0.7367
0.7166
0.7084
0.7004
0.6938
0.6936
0.6959
0.6921
0.6875
0.6855
0.6801
0.6773
0.6758
0.6741
0.6733
0.6746
0.6784
0.6731
0.6747
0.6759
0.6771
0.6757
0.6751
0.6773
0.6785
0.6763
0.6704
0.6763
0.6745
0.6762
0.6743
0.6791
0.6778
0.6756
0.6794
0.6765
0.
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