1. Outline of Talk Protein Genes Protein Genes SNPs SNPs Haplotypes Haplotypes Finding a Disease Locus Finding a Disease Locus

2. Size of the Genomes bacteria yeast round worm fruit fly flowering plant

3. The Human Genome

4. What the letters stand for DNA has four chemical subunits, called nucleotide bases abbreviated A, C, G, T. GATTACA http:// en.wikipedia.org/wiki/Nucleotide

5. Whats in the Genome? Chromosomes – 23 pairs Chromosomes – 23 pairs – Genes Protein genes RNA genes MicroRNA genes – Repeats Tandem repeats Inverted repeats Transposons Segmental duplications – Regulatory regions Promoters Transcription factor binding sites

6. Protein Genes A protein gene contains the genetic code for a protein. The production of protein involves transcription (copying DNA to RNA) and translation (using RNA code to produce a protein). http://www.slic2.wsu.edu:82/hurlbert/micro101/images/TransTranscrip.gif

7. http://nobelprize.org/medicine/educational/dna/a/transla tion/polysome_em.html http://users.rcn.com/jkimball.ma.ultranet/BiologyPages/M/Mille r_Beatty3.jpg Transcription Translation

8. Finding Protein Genes Before the sequencing of genomes, protein genes were found experimentally. Now, new genes are predicted computationally using a gene model.

9. Finding Protein Genes Before the sequencing of genomes, protein genes were found experimentally. Now, new genes are predicted computationally using a gene model.

10. Finding Protein Genes Before the sequencing of genomes, protein genes were found experimentally. Now, new genes are predicted computationally using a gene model.

11. Finding Protein Genes Before the sequencing of genomes, protein genes were found experimentally. Now, new genes are predicted computationally using a gene model.

12. Finding Protein Genes Before the sequencing of genomes, protein genes were found experimentally. Now, new genes are predicted computationally using a gene model.

13. Building a Gene Model Gene models for prediction are based on the structure of genes in DNA and their messenger RNAs (mRNAs). This includes exons, introns, promoters, and the polyadenylation signal. http://xray.bmc.uu.se/Courses/Bke2/Exercises/Exercise_answers/pre_mRNA_processing.gif

14. Exons In this example, EXONS are uppercase and introns are lowercase. Exons contain the code for a protein, introns interrupt the exons. Before translation, introns are removed from the messenger RNA. DNA: …ACTGCTACAGtctattgaGAACAACATAGtcacgaacttaacgtgca GTTTAACAGCACGtctcgaagggca… RNA (before removal of introns): …ACUGCUACAGucuauugaGAACAACAUAGucacgaacuuaacg ugcaGUUUAACAGCACGucucgaagggca… RNA (after removal of introns): …ACUGCUACAGGAACAACAUAGGUUUAACAGCACG…

15. The sequence of an exon contains codons. Each codon is a triplet of nucleotides which codes for a single amino acid. Amino acids are the building blocks of a protein. Finding Exons http://en.wikipedia.org/wiki/Genetic_code

16. Genetic Code. Each codon specifies one of twenty amino acids. Three codons are stop codons, which specify the end of translation. http://www.emc.maricopa.edu/faculty/farabee/BIOBK/code.gif

17. An open reading frame (ORF), is a sequence of codons that does not contain a stop codon. Open Reading Frame (ORF) http://en.wikipedia.org/wiki/Genetic_code alaninethreonine glutamic acid leucinearginineserineSTOP!

18. Sequence: acggacucuagccuaaugugacgacugacauagguaaauucgcuc Even though this sequence contains stop codons, they are not present in all reading frames. frame +1 acg gac ucu agc cua aug uga cga cug aca uag gua aau ucg cuc frame +2 a cgg acu cua gcc uaa ugu gac gac uga cau agg uaa auu cgc uc frame +3 ac gga cuc uag ccu aau gug acg acu gac aua ggu aaa uuc gcu c Very short ORFs are unlikely. Finding Exons

19. Finding Introns Introns usually start at a G – T boundary and end at an A – G boundary.

20. Sequence:acggacucuagccuaaugugacgacugacauagguaaauucgcuc A gene can contain open reading frames connected across stop codons by an intron frame +1 acg gac ucu agc cua aug uga cga cug aca uag gua aau ucg cuc frame +3 ac gga cuc uag ccu aau gug acg acu gac aua ggu aaa uuc gcu c Finding Exons

21. How many genes are there? Estimates pre 2000: 100,000 based on estimates of required number of genes to account for human complexity pre 2000: 100,000 based on estimates of required number of genes to account for human complexity 2001: 30,000 – 40,000 based on first draft of human genome 2001: 30,000 – 40,000 based on first draft of human genome 2003: 23,000 – 24,500 based on gene prediction computer programs 2003: 23,000 – 24,500 based on gene prediction computer programs Why so low? alternate splicing of exons alternate splicing of exons complex regulatory mechanisms complex regulatory mechanisms inability to predict genes which are unlike those seen before inability to predict genes which are unlike those seen before http://www.ornl.gov/sci/techresources/Human_Genome/faq/genenumber.shtml

22. RNA Genes RNA genes do not code for proteins. Instead, the RNA molecule itself is functional in the cell. Examples include: 1.Ribosomal RNA – these molecules form the major component of the protein building machinery 2.Transfer RNA – work with ribosomal RNA to insert correct amino acids into growing proteins 3.MicroRNA – a newly discovered class of RNA which helps regulate gene expression.

23. Ribosome http://www.ncbi.nl m.nih.gov/Class/N AWBIS/Modules/R NA/images/fig_rna 12.jpg

24. http://nobelprize.org/medicine/educational/dna/a/transla tion/polysome_em.html http://users.rcn.com/jkimball.ma.ultranet/BiologyPages/M/Mille r_Beatty3.jpg Transcription Translation

25. RNA Genes MicroRNAs are short and show little or no conservation of sequence. Unlike protein genes, RNA genes do not contain codons or open reading frames. But, they do contain inverted repeats.

26. Inverted Repeats (IRs) RNA G A C U U G A U C A A G U C G A C U U G A U C A A G U C complemented reversed Two patterns, one the reverse complement of the other

27. IR Nomenclature Left arm Right arm Spacer RNA G A C U U G A U C A A G U C G A C U U G A U C A A G U C

28. Stem-Loop Structure CAGUUCAGGUCAAGUC Spacer Left arm Right arm Structure forms by pairing of complementary bases

29. MicroRNA MicroRNAs come from a precursor that contains a stem-loop. http://www.ma.uni-heidelberg.de/apps/zmf/argonaute/interface/mirna.jpeg

30. Detection of Approximate Inverted Repeats Human Chr. 3 ~173,291,101 AAGACTTGAA CAACTTTTAA ACATAAGATC AATTATTTCA AGTAGATTCC CTTTTTCATT CACAATCACA TTCTCACAGA CACAGTCCCA GTTTCTACCT GACTGAGATG CAGTAAGGAA TCTGATTATA ACACTCATTG ATTATAACAC TCATTGAATT TATGGATTCC TTACTGCATC TCATTCAGGT AGAAAAAGGG ACTGTGTCTG TGAGAATGTG ATTGTGAATG AAAAAGATGG AATATGTGTA TTTTTGAGTG TCTATGGAAG AGCTTCTGAC AAGAGAGAGG AAGATTAGGT AAAATGAAAT ATCGCCGTCG GCATTTCCCC CTACGT AAGACTTGAA CAACTTTTAA ACATAAGATC AATTATTTCA AGTAGATTCC CTTTTTCATT CACAATCACA TTCTCACAGA CACAGTCCCA GTTTCTACCT GACTGAGATG CAGTAAGGAA TCTGATTATA ACACTCATTG ATTATAACAC TCATTGAATT TATGGATTCC TTACTGCATC TCATTCAGGT AGAAAAAGGG ACTGTGTCTG TGAGAATGTG ATTGTGAATG AAAAAGATGG AATATGTGTA TTTTTGAGTG TCTATGGAAG AGCTTCTGAC AAGAGAGAGG AAGATTAGGT AAAATGAAAT ATCGCCGTCG GCATTTCCCC CTACGT

31. Detection of Approximate Inverted Repeats Human Chr. 3 ~173,291,101 AAGACTTGAA CAACTTTTAA ACATAAGATC AATTATTTCA AGTAGATTCC CTTTTTCATT CACAATCACA TTCTCACAGA CACAGTCCCA GTTTCTACCT GACTGAGATG CAGTAAGGAA TCTGATTATA ACACTCATTG ATTATAACAC TCATTGAATT TATGGATTCC TTACTGCATC TCATTCAGGT AGAAAAAGGG ACTGTGTCTG TGAGAATGTG ATTGTGAATG AAAAAGATGG AATATGTGTA TTTTTGAGTG TCTATGGAAG AGCTTCTGAC AAGAGAGAGG AAGATTAGGT AAAATGAAAT ATCGCCGTCG GCATTTCCCC CTACGT AAGACTTGAA CAACTTTTAA ACATAAGATC AATTATTTCA AGTAGATTCC CTTTTTCATT CACAATCACA TTCTCACAGA CACAGTCCCA GTTTCTACCT GACTGAGATG CAGTAAGGAA TCTGATTATA ACACTCATTG ATTATAACAC TCATTGAATT TATGGATTCC TTACTGCATC TCATTCAGGT AGAAAAAGGG ACTGTGTCTG TGAGAATGTG ATTGTGAATG AAAAAGATGG AATATGTGTA TTTTTGAGTG TCTATGGAAG AGCTTCTGAC AAGAGAGAGG AAGATTAGGT AAAATGAAAT ATCGCCGTCG GCATTTCCCC CTACGT Arms are 72 nt long, spacer is 42bp long

32. The Problem: Find the Inverted Repeat Human Chr. 3 ~173,291,101 AAGACTTGAA CAACTTTTAA ACATAAGATC AATTATTTCA AGTAGATTCC ATGG AATATGTGTA TTTTTGAGTG TCTATGGAAG AGCTTCTGAC AAGAGAGAGG AAGATTAGGT AAAATGAAAT ATCGCCGTCG GCATTTCCCC CTACGT AAGACTTGAA CAACTTTTAA ACATAAGATC AATTATTTCA AGTAGATTCC CTTTTTCATT CACAATCACA TTCTCACAGA CACAGTCCCA GTTTCTACCT GACTGAGATG CAGTAAGGAA TCTGATTATA ACACTCATTG ATTATAACAC TCATTGAATT TATGGATTCC TTACTGCATC TCATTCAGGT AGAAAAAGGG ACTGTGTCTG TGAGAATGTG ATTGTGAATG AAAAAGATGG AATATGTGTA TTTTTGAGTG TCTATGGAAG AGCTTCTGAC AAGAGAGAGG AAGATTAGGT AAAATGAAAT ATCGCCGTCG GCATTTCCCC CTACGT

33. Single Nucleotide Polymorphisms (SNPs) A SNP is a single position in the genome (a locus) that is not the same in all people. Some people have one type of nucleotide and other people have a different nucleotide. Differences in the population at a single locus are called polymorphisms and the individual types are called alleles. SNPs are found experimentally acattcct acgttatt SNPs

34. Haplotypes A haplotype is a collection of SNP alleles on a single chromosome in an individual. Shown are SNPS on two chromosomes in each individual. acgttcatacattcattcgttcatacagatatacattcct acattcct atagtccaacagtcca tcattcatacattcaa

35. Haplotypes A haplotype is a collection of SNP alleles on a single chromosome in an individual. Homozygous (same alleles) acgttcatacattcattcgttcatacagatatacattcct acattcct atagtccaacagtcca tcattcatacattcaa

36. Haplotypes A haplotype is a collection of SNP alleles on a single chromosome in an individual. Heterozygous (different alleles) acgttcatacattcattcgttcatacagatatacattcct acattcct atagtccaacagtcca tcattcatacattcaa

37. Haplotypes A haplotype is a collection of SNP alleles on a single chromosome in an individual. Rare alleles acgttcatacattcattcgttcatacagatatacattcct acattcct atagtccaacagacca tcattcatacattcaa

38. Haplotypes A haplotype is a collection of SNP alleles on a single chromosome in an individual. Strong linkage (usually occur together) acgttcatacattcattcgttcatacagatatacattcct acattcct atagtccaacagtcca tcattcatacattcaa

39. Linkage Analysis SNPs and haplotypes are used to identify regions of the genome that cause disease. The technique is called linkage analysis and evidence of a connection is called linkage disequilibrium (LD). acattcat`atagtcca acagatattcattcat momdad acagtcc aaccaaggttcccca`a`aaccaaggttcccca`a`acagacat child recombination and inheritance

40. Linkage Analysis SNPs and haplotypes are used to identify regions of the genome that cause disease. The technique is called linkage analysis and evidence of a connection is called linkage disequilibrium (LD). acattcat`atagtcca acagatattcattcat momdad acagtcc aaccaaggttcccca`a`aaccaaggttcccca`a`acagacat child recombination in the mothers chromosomes

41. Linkage Analysis SNPs and haplotypes are used to identify regions of the genome that cause disease. The technique is called linkage analysis and evidence of a connection is called linkage disequilibrium (LD). acattcat`atagtcca acagatattcattcat momdad acagtcc aaccaaggttcccca`a`aaccaaggttcccca`a`acagacat child recombination in the fathers chromosomes

42. Linkage Analysis SNPs and haplotypes are used to identify regions of the genome that cause disease. The technique is called linkage analysis and evidence of a connection is called linkage disequilibrium (LD). acattcat`atagtcca acagatattcattcat momdad acagtcc aaccaaggttcccca`a`aaccaaggttcccca`a`acagacat child two to three crossovers per chromosome per generation

43. Linkage Analysis Key point: Alleles that are physically close together tend to be inherited together because the chance of a crossover between them is small. They exhibit strong linkage. acattcat`atagtcca acagatattcattcat momdad acagtcc aaccaaggttcccca`a`aaccaaggttcccca`a`acagacat child

44. Finding an Unknown Disease Locus The location on the genome of many diseases is unknown. SNPs and haplotypes are being used to search for disease loci using linkage analysis. acattcat`atagtcca acagatattcattcat mom dad has disease acagtcc aaccaaggttcccca`a`aaccaaggttcccca`a`acagacat child has disease

45. Linkage Analysis – Dominant Model Assume the disease is caused by a dominant allele, meaning one copy is enough to cause the disease. acattcat`atagtcca acagatattcattcat mom dad has disease acagtcc aaccaaggttcccca`a`aaccaaggttcccca`a`acagacat child has disease SNP alleles in father that are not in mother

46. Linkage Analysis – Dominant Model Assume the disease is caused by a dominant allele, meaning one copy is enough to cause the disease. acattcat`atagtcca acagatattcattcat mom dad has disease acagtcc aaccaaggttcccca`a`aaccaaggttcccca`a`acagacat child has disease SNP allele in child, inherited from father with disease

47. Linkage Analysis – Dominant Model Assume the disease is caused by a dominant allele, meaning one copy is enough to cause the disease. acattcat`atagtcca acagatattcattcat mom dad has disease acagtcc aaccaaggttcccca`a`aaccaaggttcccca`a`acagacat child has disease SNP allele and disease are linked indicating possible disease locus.

48. Linkage Analysis – Recessive Model Assume the disease is caused by a recessive allele, meaning two copies are required to cause the disease. acattcatatagtcca acagatattcattcat mom dad has disease acagtcc aaccaaggttcccca`a`aaccaaggttcccca`a`acagacat child has disease homozygous SNP alleles in father that are heterozygous in mother

49. Linkage Analysis – Recessive Model Assume the disease is caused by a recessive allele, meaning two copies are required to cause the disease. acattcat`atagtcca acagatattcattcat mom dad has disease acagtcc aaccaaggttcccca`a`aaccaaggttcccca`a`acagacat child has disease homozygous SNP allele in child, identical to fathers

50. Linkage Analysis – Recessive Model Assume the disease is caused by a recessive allele, meaning two copies are required to cause the disease. acattcat`atagtcca acagatattcattcat mom dad has disease acagtcc aaccaaggttcccca`a`aaccaaggttcccca`a`acagacat child has disease SNP allele and disease are linked indicating possible disease locus.

52. BMI = weight/height 2 in kg/m 2, BMI > 25 overweight, BMI > 30 obese

53. Other Differences – Microdeletions A microdeletion is the loss of a small piece of DNA, perhaps as small as 1000 bases. These pieces can contain genes, parts of genes or regulatory regions. acattcct atgttt gcgcat acactcct microdeletions

54. Other Differences – Microdeletions A microdeletion is the loss of a small piece of DNA, perhaps as small as 1000 bases. These pieces can contain genes, parts of genes or regulatory regions. acattcct atgttt gcgcat acactcct heterozygous

55. Other Differences – Microdeletions A microdeletion is the loss of a small piece of DNA, perhaps as small as 1000 bases. These pieces can contain genes, parts of genes or regulatory regions. acattcct atgttt gcgcat acactcct homozygous

56. Other Differences – Microdeletions A microdeletion is the loss of a small piece of DNA, perhaps as small as 1000 bases. These pieces can contain genes, parts of genes or regulatory regions. acattcct atgttt gcgcat acactcct miscalled homozygous

57. Apparent Inheritance Inconsistency SNPs and haplotypes are used to identify regions of the genome that cause disease. The technique is called linkage analysis and evidence of a connection is called linkage disequilibrium (LD). ataagaaccccac acatccacccctccac momdad ccca ccccccaac`c`ccccccaac`c`acatccac child

58. Apparent Inheritance Inconsistency SNPs and haplotypes are used to identify regions of the genome that cause disease. The technique is called linkage analysis and evidence of a connection is called linkage disequilibrium (LD). ataagaaccccac acatccacccctccac momdad ccca ccccccaac`c`ccccccaac`c`acatccac child a a + t t a t by Mendelian inheritance

59. Apparent Inheritance Inconsistency SNPs and haplotypes are used to identify regions of the genome that cause disease. The technique is called linkage analysis and evidence of a connection is called linkage disequilibrium (LD). ataagaaccccac acatccacccctccac momdad ccca ccccccaac`c`ccccccaac`c`acatccac child cluster of inconsistencies suggests a microdeletion.

60. Microdeletions Hundreds of microdeletion haplotypes have been discovered recently. They may be a major contributor to human differences and disease.

61. Resources UCSC Human Genome Browser http://genome.ucsc.edu/cgi-bin/hgGateway National Center for Biotechnology Information (NCBI) http://www.ncbi.nlm.nih.gov/ PubMed http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed