* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download Using mouse genetics to understand human disease
Transposable element wikipedia , lookup
Ridge (biology) wikipedia , lookup
Gene desert wikipedia , lookup
Therapeutic gene modulation wikipedia , lookup
Biology and consumer behaviour wikipedia , lookup
Mitochondrial DNA wikipedia , lookup
Human genetic variation wikipedia , lookup
Whole genome sequencing wikipedia , lookup
Gene expression profiling wikipedia , lookup
Epigenetics of neurodegenerative diseases wikipedia , lookup
Oncogenomics wikipedia , lookup
Y chromosome wikipedia , lookup
Epigenetics of human development wikipedia , lookup
Neocentromere wikipedia , lookup
Epigenetics of diabetes Type 2 wikipedia , lookup
Genetic engineering wikipedia , lookup
Gene expression programming wikipedia , lookup
Epigenetics in learning and memory wikipedia , lookup
Non-coding DNA wikipedia , lookup
X-inactivation wikipedia , lookup
Genomic library wikipedia , lookup
Pathogenomics wikipedia , lookup
Genomic imprinting wikipedia , lookup
Helitron (biology) wikipedia , lookup
Nutriepigenomics wikipedia , lookup
Artificial gene synthesis wikipedia , lookup
Human genome wikipedia , lookup
Minimal genome wikipedia , lookup
Human Genome Project wikipedia , lookup
Microevolution wikipedia , lookup
Genome editing wikipedia , lookup
Designer baby wikipedia , lookup
Genome (book) wikipedia , lookup
Public health genomics wikipedia , lookup
Site-specific recombinase technology wikipedia , lookup
Quantitative trait locus wikipedia , lookup
Using mouse genetics to understand human disease Mark Daly Whitehead/Pfizer Computational Biology Fellow What we do • Genetics: the study of the inheritance of biological phenotype – Mendel recognized discrete units of inheritance – Theories rediscovered and disputed ca. 1900 – Experiments on mouse coat color proved Mendel correct and generalizable to mammals – We now recognize this inheritance as being carried by variation in DNA Why mice? • Mammals, much better biological model • Easy to breed, feed, and house • Can acclimatize to human touch • Most important: we can experiment in many ways not possible in humans What do they want with me? Mice are close to humans Kerstin Lindblad-Toh Whitehead/MIT Center for Genome Research Mouse sequence reveals great similarity with the human genome Extremely high conservation: 560,000 “anchors” Mouse-Human Comparison both genomes 2.5-3 billion bp long > 99% of genes have homologs > 95% of genome “syntenic” Genomes are rearranged copies of each other Roughly 50% of bases change in the evolutionary time from mouse to human Mouse sequence reveals great similarity with the human genome Extremely high conservation: 560,000 “anchors” Anchors (hundreds of bases with >90% identity) represent areas of evolutionary selection… …but only 30-40% of the highly conserved segments correspond to exons of genes!!! What we can do • Directed matings • Inbred lines and crosses • • • • Knockouts Transgenics Mutagenesis Nuclear transfer • Control exposure to pathogens, drugs, diet, etc. YIKES!!! Example: diabetes related mice available from The Jackson Labs • • • • • • • Type I diabetes (3) Type II diabetes (3) Hyperglycemic (27) Hyperinsulinemic (25) Hypoglycemic (1) Hypoinsulinemic (5) Insulin resistant (30) • Impaired insulin processing (7) • Impaired wound healing (13) Inbreeding • Repeated brothersister mating leads to completely homozygous genome – no variation! Experimental Crosses • Breed two distinct inbred lines • Offspring (F1) are all genetically identical – they each have one copy of each chromosome from each parent • Further crosses involving F1 lead to mice with unique combinations of the two original strains Experimental Cross Experimental Cross: backcross • F1 bred back to one of the parents • Backcross (F1 x RED) offspring: 50% red-red 50% red-blue Experimental Cross: F2 intercross • One F1 bred to another F1 • F2 intercross (F1xF1) offspring: 25% red-red 50% red-blue 25% blue-blue F2 Trait mapping F2 100 200 300 Trait mapping Blue trees = tall, Red trees = short In the F2 generation, short trees tend to carry “red” chromosomes where the height genes are located, taller trees tend to carry “blue” chromosomes QTL mapping use statistical methods to find these regions How do we distinguish chromosomes from different strains? • Polymorphic DNA markers such as Single Nucleotide Polymorphisms (SNPs) can be used to distinguish the parental origin of offspring chromosomes ATTCGACGTATTGGCACTTACAGG ATTCGATGTATTGGCACTTACAGG SNP Example: susceptibility to Tb % survival 100 • C3H mice extremely susceptible to Tb • B6 mice resistant B6 50 C3H 0 0 100 200 Days post infection 300 • F1, F2 show intermediate levels of susceptibility One gene location already known B6 % survival 100 C3H 50 C3H.B6-sst1 0 0 50 100 Survival Time 150 200 • Previous work identified chromosome 1 as carrying a major susceptibility factor • Congenic C3H animals carrying a B6 chromosome 1 segment were bred Congenic and consomic mice • Derived strains of mice in which the homozygous genome of one mouse strain has a chromosome or part of a chromosome substituted from another strain C3H Chr 1 Chr 2 Chr 3 Chr 4 Etc. B6 C3H.B6_chr1 Tb mapping cross F2 intercross: C3H.B6sst1 x x B6 C3H.B6-sst1 - MTBsusceptible, carrying B6 chr 1 resistance F1 B6 - MTB-resistant Trait – survival following MTB infection n = 368 … F2 Results: 3 new gene locations identified! Gene identified on chromosome 12 100 100 bh % survival % survival bb hh 50 Mice engineered to be missing a critical component of the immune system Days after infection located in this region are C57Bl/6J B.likewise more susceptible, C. B6-Igh6 validating that particular gene as involved in Tb susceptibility 0 0 0 100 200 days post infection A. 50 Chi square 18.99 df 2 P value P<0.0001 300 0 25 50 75 100 125 150 100 % survival At the end of chr 12 – mice inheriting two C3H copies survive significantly longer than those with one or two B6-IL12-/B6 copies 50 0 0 25 50 75 100 125 150 Days after infection Chi square 30.02 Chi square 20.17 df 2 df 1 P value P<0.0001 P value P<0.0001 BALB/cBJ BALB/c-mMT-/- Mouse History • Modern “house mice” emerged from Asia into the fertile crescent as agriculture was born Mouse history Recent mouse history Fancy mouse breeding - Asia, Europe (last few centuries) Retired schoolteacher Abbie Lathrop collects and breeds these mice Granby, MA – 1900 Castle, Little and others form most commonly used inbred strains from Lathrop stock (1908 on) W.E. Castle C.C. Little Mouse history Mouse history • Asian musculus and European domesticus mice dominate the world but have evolved separately over ~ 1 Million years • Mixing in Abbie Lathrop’s schoolhouse created all our commonly used mice from these two distinct founder groups Genetic Background of the inbred lab mice musc C3H DBA domest domest domest cast musc musc domest { C57BL/6 domest musc Avg segment size ~ 2 Mb <1 SNP/10 kb { { Comparing two inbred strains – frequency of differences in 50 kb segments ~40 SNP/10 kb Finding the genes responsible for biomedical phenotypes 20 Mb C3H (susceptible) B6 (resistant) Traditionally: positional cloning is painful (e.g., generating thousands of mice for fine mapping, breeding congenics) – As a result, countless significant QTLs have been identified in mapping crosses but only a small handful have thusfar resulted in identification of which gene is responsible – the critical information that will advance research into prevention and treatment! Using DNA patterns to find genes 20 Mb C3H (susc.) B6 (res.) Critical Region Using DNA patterns to find genes 20 Mb C3H (susc.) B6 (res.) DBA (susc.) Critical Region Example: mapping of albinism Critical region First genomic region mapped 129S1 T A * C C C * C G G T A C G A G G G AKR A G T T T A A T G G T A C G A G G G A_J A G T T T A A T G G T A C G A G G G BALB_c T A * C C C G C G G T A C G A G G G C3H A G T T T A A T G G T A C G A G G G C57B6 A G T T T A A T C T A G T A C C C A CBA A G T T T A A T C T A G T A C C C A DBA2 A G T T T A A T C T A G T A C C C A FVB A G T T T A A T C T A G T A C C C A I A G T T T A A T G G T A C G A G G G NOD A G T T T A A T G G T A C G A G G G NZB * A C C C C * C C T * G T A C C C A SJL A G T T T A A T C T A G T A C C C A SWR A G T T T A A T C T A G T A C C C A Chr 4 (Mb) 35.7 37.6 37.9 39.4 Future Genetic Studies Mapping Expression Pathways Model Systems Thanks to (Whitehead Institute) Claire Wade Andrew Kirby (MIT Genome Center) EJ Kulbokas Mike Zody Eric Lander Kerstin Lindblad-Toh Funding: Whitehead Institute Pfizer, Inc. National Human Genome Research Institute