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Berkeley MCELLBI 140 - Natural var in expression 2

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Office hours Wednesday 3-4pm 304A Stanley Hall Review session 5pm Thursday, Dec. 11 GPB100Coding sequence array“RNA-seq”Expression effects of cancerDiagnosis via transcriptional profileSlide 6PowerPoint PresentationSlide 8Slide 9Slide 10Slide 11Slide 12Slide 13Slide 14Slide 15Slide 16Slide 17Slide 18Slide 19Slide 20Slide 21Slide 22Can we map expression traits first, disease afterward?Slide 24Slide 25Slide 26Slide 27Slide 28Slide 29A new brand of genetic variationTranslationSlide 32PSI+ yeast read through STOPsSlide 34Slide 35Weird genetics of read-throughSlide 37Slide 38Cytoplasmic aggregates of Sup35Slide 40Hard to make aggregate, easy to joinProtein inheritanceSlide 43PSI+ begets more PSI+Nucleating prions in mad cow diseaseIs PSI+ the yeast analog of mad cow or Alzheimer’s?If bad, would be lostSlide 48PSI+ phenotypesSlide 50Slide 51Slide 52Slide 53Slide 54Slide 55The clincherSlide 57Slide 58Slide 59Slide 60Aggregation = more read-throughSlide 62PSI+ allows epigenetic change in protein sequence.Genetic effects?Slide 65Slide 66Slide 67Slide 68Slide 69Slide 70Cryptic variation: DNA sequence differences between individuals that are usually not expressedOffice hoursWednesday 3-4pm304A Stanley HallReview session5pm Thursday, Dec. 11GPB100Coding sequence arrayFig. 1.13“RNA-seq”AAAAAAAAAAAAAAA counts seq maps genome pos orient 26982 TCGTTCACTTGTATTGG U0 sbaySum.fsa 3002121 R 25885 TCTCTACTGGTGGTGGT U0 chr03.fsa 138912 F 17851 GACAAACTGTCGCTGTC R0 15715 TCTCTACCGGTGGTGGT U0 sbaySum.fsa 11182634 F 14963 TCGTTCACTTGTAATGG U0 chr04.fsa 1489376 R … 610 TTGAAGCTACCACCAAC R0 607 TGTCCTTATCTATGTGT U0 sbaySum.fsa 8491512 R 602 CGTACTTTTTTAATTGT U1 chr11.fsa 145622 F 602 ATCATTGTTCCAGAAAT R0 601 TTATCAGAGGTGCTGGT U0 chr14.fsa 694435 R 600 CAAAGACCTCATTTAAT U0 sbaySum.fsa 4671591 R 599 AGGAGGGTATATATGCT U0 chr14.fsa 575509 R …Solexa sequencingExpression effects of cancerQuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.Diagnosis via transcriptional profileQuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.transcriptspatient samplesDiagnosis via transcriptional profileQuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.QuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.Linkage mapping of mRNA levels“Black 6” mouse x “DBA” mouse111 F2 progenyMicroarrayeach F2 liver…Genotypeeach F2Looking for linkage (coinheritance) between marker and mRNA level.Marker is linked to polymorphism in expression regulation cascadeORFTFTFGkinaseTFGGLocally acting polymorphismsQuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.Polymorphism responsible for mRNA difference is at the locus of the gene itself~25% of varying mRNAs are caused by locally acting polymorphismNonlocal polymorphismsQuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.Nonlocal polymorphismsOne polymorphism in a key regulator can affect a regulon: 100’s of related mRNAs.Clinical applications“Black 6” mouse x “DBA” mouse111 F2 progenyMicroarrayeach F2 liver…Genotypeeach F2Measure fat pad each F2QuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.QuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.QuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.Clinical applicationsQuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.Clinical applicationsQuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.Colored curves = fat mass at different body locationsClinical applicationsFinding polymorphism responsible for difference in macroscopic phenotype is hardClinical applicationsFinding polymorphism responsible for difference in macroscopic phenotype is hardIf mRNAs change too, can learn mechanism from known function of encoded proteinsClinical applicationsClinical applicationsClinical applicationsQuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.Clinical applicationsQuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.Counts allele 1/allele 2, casesCounts allele 1/allele 2, controls= 1.5Clinical applicationsClinical applicationsMarker predicts quantitative expression level = associationCan we map expression traits first, disease afterward?QuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.Linkage of human transcriptsLinkage of human transcriptsQuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.Association of human transcriptsQuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.Association of human transcriptsQuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.linkage (families)assoc (unrelated)Association in multiple populationsQuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.Han Chinese and JapaneseEuropean-Americans in UtahAssociation in multiple populationsQuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.A new brand of genetic variationFig. 8.25TranslationFig. 8.25TranslationPSI+ yeast read through STOPsPSI+ yeast read through STOPsPSI+ yeast read through STOPs40-150 bpWeird genetics of read-throughHaploid PSI+Haploid psi-Diploid PSI+Weird genetics of read-throughHaploid PSI+Haploid psi-Diploid PSI+sporulateHaploid PSI+ Haploid PSI+Haploid PSI+ Haploid PSI+…Weird genetics of read-throughHaploid PSI+Haploid psi-Diploid PSI+sporulateHaploid PSI+ Haploid PSI+Haploid PSI+ Haploid PSI+But why wouldn’t it get diluted over many divisions?Cytoplasmic aggregates of Sup35How would this explain the results?Cytoplasmic aggregates of Sup35Hard to make aggregate, easy to joinQuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.Protein inheritanceProtein inheritanceOriginal from PSI+ nucleates in all progenyPSI+ begets more PSI+Not due to dominant genetics in the usual way.Nucleating prions in mad cow diseaseIs PSI+ the yeast analog of mad cow or Alzheimer’s?If bad, would be lostQuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this


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Berkeley MCELLBI 140 - Natural var in expression 2

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