Bioinformatics Techniques 051 123
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This 53 page Class Notes was uploaded by Russel Osinski V on Friday October 23, 2015. The Class Notes belongs to 051 123 at University of Iowa taught by Terry Braun in Fall. Since its upload, it has received 48 views. For similar materials see /class/228029/051-123-university-of-iowa in Biomedical Engineering at University of Iowa.
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Date Created: 10/23/15
Discovering Genomics Proteomics amp Bioinformatics second edition by A Malcolm Campbell and Laurie J Heyer Chapter 1 What s Wrong With My Child 0 Begins as hypothetical dialogue as if you are a clinician seeing a patient 0 One of your patients is a 6yo boy BB digestive problems child is unresponsive to questions stomach ache for several months unable to stand or walk on his own Chapter 1 histology the microscopic study of thinly sliced tissuescells a Control Muscle Biopsy b Paiienl s Muscle Biopsy v V Figure 11 Genotyping 0 Collect blood and genotype family RFLPs 0 Another patient and family girl GG GG39s phenotype some similar symptoms Cannot walk enlarged calves poor re exes in limbs no intellectual de cits 3 healthy brothers Z theiCGa HHHHHHHU 2 dHlEJCGa HHHHHHHU HHHHHHHU 3 DHFEiCGA 2 dHfEJCGA 3 3 DHFEJCGA 2 dhfeJCGa IIIIIIII 2 dhfeJCGa 2 IIIIIIII dhfeJCGa 2 dhfeJCGa IIIIIIII HHHHHHHU 3 iCGA DHFE 2 dHFEiCGA 2 2 dhfeJCGa theJCGA 3 thEiCGa markers may be very near genes even Within introns markers genes HIIIIIID 2 theJCGA Easy to mistakenly equate genes with markers I do it Figure 12 The disease recessive BB39s disease is recessive on X chrm Perform karyotype Why is GG affected she has TWO copies of X chromosome Markers suggest that she only has one copy of the disease haplotype or bad copy of defective gene near markers Figure 13a c X derm s der 6 Sqler e M emer gt p 21 M Xp21 1 w gt I q 21 qu1 I Xp21 FIgure13d e 2 u m x quer 639 Mosaics GG Wild type X chrm appears to be replicating later than mutant approx 55 out of 56 times X inactivation 1 time out of 56 the Wild type X chromosome is expressing genes Why Sequence Them 0 Let39s assume we know how to sequence them more on that later Tahle11 39 for BB 1 MLWWEEVEDC YEREDVQKKT FTKWWIAQFS KFGKQHIENL FSDLQDGRRL LDLREGLTGQ s BE s mnthev 1 MLWWEEVEDC YEREDVQKKT FTKVWAQFS KFGKQHIENL FsDLQDGRRL LDL EGLTGQ so 1 mwwmvmc YEREDVQKKT FTKWWIAQFS GKQHIENL FSDLQDGRRL LDLLEGLTGQ 60 Ge 1 MLWWEEVEDC YEREDVQKKT FTKVNNAQFS KFGKQHIENL FSDLQDGRRL LDLLEGLTGQ so 1 rmv wEEx EDC YEREDVQKKT F MIAQFS KFGKQHIENL FSDLQDGRRL LDLREGLTGQ 60 86 s muthev 1 MLW39 EDC YEREDVQKKT FTmNNAQFS KFGKQHIENL FSDLQDGRRL LDLLEGLTGQ so 1 mwwEEv EDc YEREDVQKKT FrmmIAQFs KFGKQHIENL FSDLQDGRRL LDLLEGLTGQ so GG slathev 1 ILNWEEVEDC YEREDVQKKT FTKWVNAQFS KFGKQHIENL FSDLQDGRRL LDLLEGLTGQ so Tab e 1 1 How can GG have an quotRquot if neither mother or father has it Duchenne39s muscular dystrophy DMD mRNA is gt 14000 gene is 1 million nts How is this possible 14000 1000000 Back in the day 500 bp by hand per day Impossible Gene later became known as quotdystrophinquot Gene names and aliases are still a big problem May actually be more misleading A novel gene may be named because it quotlooksquot like another gene may have alternative splicing The function thought to be associated With original gene may be wrong etc 14 0 quotchaperonin likequot 40 years of research in lt 20 slides Presents as nice linear and logical sequence of events Papers and case studies are often presented like this but the reality is that there were many failed experiments and hypotheses People came and went real science is almost never this linear Writing grants Teaching and faculty meetings Meetings and conferences Training students staff scientists secretaries etc Writing papers Experiments experiments experiments Math Minute 11 E values and BLAST we39ll come back to BLAST later BLAST basic local alignment search tool BLAST in this case BLASTp for quotproteinquot takes as input one protein sequence query and compares it to a database of multiple proteins sequences subjects A signi cant hit between query and subject is measured by E value expect value the E value is the value you39d expect from a hit in two sequences by chance two extremes 0 if your database is so large you have all possible combinations of sequences then you are VERY likely to nd the sequence you are looking for but this E value will be very low le good or signi cant since there are so many sequences 0 if your database is very small then a quothitquot will not be as signi cant and rarely will you nd a match As E value gets closer to 0 the hit becomes more signi cant A quotbit score Squot is a measure of the similarity between Q and S Big bit score corresponds to small e value Essence of BLAST and BLAT is to quothashquot What39s next 0 Need an animal model 0 Why 0 Mutant mice mdx develops DMD lD39ed by biologists and isolated mouse labs to this day watch for and cultivate spontaneous phenotypes J ax lab had mouse before the gene no guarantee it s the same gene may actually try therapies gene found With anti body 0 dystrophin localized to surface of cell in skeletal muscles 0 in neurons explains mental retardation 0 no dystrophin in mdx mice 0 explains Why its recessive loss of function remember mom had one good copy and one bad copy Utrophin 0 Looks very similar to dystrophin based on sequence similarity 0 expressed in fetal tissues regenerating muscle and other tissues during development ubiquitous small caliber muscles like eye movement An gens quot quotT Antigen 4 Anhgmhmdng fmgmrnl Antibody For more information Wikipedia quotpolyclonal antibodyquot or quotmonoclonal antibodyquot 19 lmrnuno uorescent labeling of dystrophing and utrophin localizes protein to cell membrane and neurons W data not shown Figure 15 Function of dystrophin 0 Jim Ervasti and Kevin Campbell 0 Identi ed proteinscomplexes associated With dystrophin 21 dystrophin predicted to form quotcoiled coilquot motif a X ray diffraction crystallography Figure 16 Now thought that this structure links cytoskeleton cells to skeleton bones muscles tendons too Sarcospan Out Plasma membrane Figure 1 7 23 Systems biology reductionism to synthesis Inside I Sarcoglycan Outside 05 cell complex I ll elbystr pl39 n lt gt Dyfgi glzian lt gtlt gt Bone H Syntrophin complex Plasma membrane Figure 18 DMD Muscle Deterioration How does mutation cause disease How does single missense cause children to develop disease Why children and not infants Why do the muscles gradually deteriorate 25 DMD 54 L gt R at amino acid position 54 leucine has been Changed to arginine Is this a big Change Hypothesis 26 Hypothesis 0 Hypothesis muscle contracts and damages the cell membrane because cell is anchored to the bone but not to the cytoskeleton rigid structure of the cell 0 Infants don39t move around as much so damage doesn39t occur 0 Explains muscle deterioration but What about neurons 27 DMD neuronal penetrance mental symptoms of DMD has low penetrance not everyone With the mutation gets the symptom 0 suggested that maybe neuronal cells fail to attach to each other or other interfaces 0 not really sure 28 More patients 0 mother 0 son YY 4 yo 0 daughter DD 12 yo 29 Mother VV DD Unlikely that both children would inherit 4 disease alleles Why 786 9quot 5 f quot i r I 536 I Figure19 i 30 Mutated beta sarcoglycan Misforming of complex Figure 110 Only 3 mutations found in sarcospan in 50 families and it did not cause the disease Exon3 682 G gtA WTWT WTPOLY POLYPOLY GGGTGT GGGTNT GGGT T o u a Figure 111 NHg SGSPN complnx I I nSG 756 956 356 NH2 5 COOH coon coon Samspan drab COOH 155 756 355 ass N 23 coo cow Truncated sarcoglycan a E In E 4W COOH a Figure 112 Table 12 The dystrophin complex proteins chromosomal location and associated LGMD classifications Disease Chromosomal Location Protein Autosomai Dominant type 1 A 5q31 myotilin 1B 1q212 amin NC 10 3p52 caveoiin S 1D 7Q unknown Autosomai Recessive type 2 2A 15q15721 caipain 3 2B 2p13 dysferlin 20 13q12 y sarcogiycan 2D 17q12 oc sarcoglycan 2E 4012 B sarcogiycan 2F 5q31 6sarcoglycan 2G 7011712 teiethonin 2H 9q317341 TRIMSZ 2 19q13 FKRP Source Modified from Betta et at 1999 Hanan Jouria of Neumagca Sciences 206 375 Tame 2 Ta ble 1 2 BBS 0 Chiang AP Beck J S Yen HJ Tayeh MK Scheetz TE SWiderski RE Nishimura DY Braun TA Kim KY Huang J Elbedour K Carmi R Slusarski DC Casavant TL Stone EM Shef eld VC Homozygosity mapping With SNP arrays identi es TRIM32 an E3 ubiquitin ligase as a Bardet Biedl syndrome gene BBS11 Proc Natl Acad Sci U S A 2006 Apr 18103166287 92 Epub 2006 Apr 10 PMID 16606853 PubMed indexed for MEDLINE 35 Search for all mutations in calpain 5 2 o o o o o HAOZOA 3 M 188 SXSQHHSHE HHHHHHHH HHHHHHHHHHHF Exons 1 2 3 4 5 6 7 8 9 10 1112 13 1415161718192021222324 x lnrframe deletion A Frameshi deletion v Insertion B Complex mumion ngre 1183 36 2 misseuse mmau39uns missense 1 null mmauan VH V V 3 3 z z W a a Ml H o 10 2a 30 4a 50 so 7 Age Onset lyezvs old Mean me dura nn before Onset lyezvs c d Mean me dura nn before Mea 39 3 I055 ofwa king abiliw Mean39 19 I055 ofwa king abiliw Rang 74o 19 yeavs Range 5737 2n yeavs Sxandard devlztian 609 Sxandard devlztian EA 1 2 mm mma nns a E 5 emu lyezvs em Mean me dura nn before Mean39 11 loss ofwahdng abmw Range 25719 16 yeavs smuzm deviatio 45 Figure 118bd 37 End chapter 1 0 Although the rest of the material is extremely interesting and I encourage you to read if interested it gets somewhat speculative So you Will not be responsible for this material 38 Emacehmw muacaHmzr Puuum mu USPWuhan 1Jva 4 a m Mynsmrb ndmw Wm Exuaca mzv Figure 113 Extracellular lmracellular Spemln Fraclin PDZVZL39 Myosin mick filamem Actin thin filamem 39m lENH ZASPqpherl 2le PDZJLim i lALPl 1 licapTeleihonin Figure 113a 40 ngure113b 41 Sarcoglvcan complex SFVAminlt gt D f rr g 4 Lamlnln 4 Bone ycan ex Caveolin Symrophin V 9 Complex Plasma membrane Figure 113c Figure 114 ECM Plasma membrane mm W ZVUNE Figure 115 Figure 116 Figure 1 1 7 Figure 118 Exams COOODDDlt v X 0 COD4X 2 3 QIOOOOOQQP A 4 O O I O 4 a ox u ud u 978910 Y A OCCOOOOOOD x A A a o 0 A2 0 HA 0A a VOAOWV a AIA39HOH9HD H12 13 101515 713 92n2 222224 n mm mm Mfssense mute un 9 nrheme mam x mmquot samemmmm mam A mem de e an 7 human 1 mm mmmum M M n a w hug 25 m Sumrd mmn sns Imam Meln u n m dwman before m mm mm 2 Mn mm M m sy n m urumn tumors m mm mm B ump exmuta un WWW Wu mmmun E w w v a E w u M n w hug 571 summmmn an n m Au Mun m Harman before mum mm vquot 47 m as 2 0 A00 0x00 0 HA2A 3 am n a 3m nan HZHBHAHjHGH EHH H HH HHHHHHH HHHP x Q lnrframe deletion A Frameshi deletion v Insertion 9 10 1112 13 141516 1718192021 222324 B Complex mumion ngre 1 1 8a 48 2 misseuse mmau39uns missense 1 null mmauan VH V V 3 3 z z W a a Ml H o 10 2a 30 4a 50 so 7 Age Onset lyezvs old Mean me dura nn before Onset lyezvs c d Mean me dura nn before Mea 39 3 I055 ofwa king abiliw Mean39 19 I055 ofwa king abiliw Rang 74o 19 yeavs Range 5737 2n yeavs Sxandard devlztian 609 Sxandard devlztian EA 1 2 mm mma nns a E 5 emu lyezvs em Mean me dura nn before Mean39 11 loss ofwahdng abmw Range 25719 16 yeavs smuzm deviatio 45 Figure 118bd 49 gm 9quot e Figure 119 Skeletal muscle adbnl O f 3 LO 5 m iv o Figure 121 Figure 122 fmol cGMP per mg wet weight adbn l39 was
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