1. Genetics I (prokaryotes) IT Carlow Bioinformatics September 2006

2. Biochemistry How biology works Mechanisms

3. Genetics How things are inherited Why you are like your parents but also different Where genes, pathways, wings, flippers come from How things develop from zygote But it’s all molecular biology nowadays

4. Genetics The interesting stuff “Nothing in biology makes sense except in the light of evolution” Dobzhansky “Nothing in bioinformatics makes sense except in the light of evolution” Higgs & Attwood Evolution = change in gene frequency over time What is gene? What is frequency? What is change? What is time? What is life?

5. Genome size and differences SpeciesGenome size BPGenome size genes Human3,000,000,00025,000 Yeast16,000,0006,500 E.coli4,000,0004,000 Gene = 1000bp = 300AA All descended from LUCA How?

6. DNA Double helix –10Å radius (1 or better 1.2nm) –34Å for single turn –3.4Å for single base (0.34nm) –10 bp per turn E.coli 4Mb how many Å 3 /nm 3 of DNA? Size of E.coli? About 1x2  m Thinking exercise: % E.coli vol is DNA?

7. Mutation DNA damage from UV light, coal-tar Replicative failure (DNApol is good but..) Humans 2.5 *10 -8 /bp/cell div E.coli 1*10 -7 /bp/div Humans/Chimps 1% diff but 35m diffs You have 10 14 cells now from start of 1

8. Bases Purines R big Purines Are biG Pyrimidines Y CUT tinY A CT G

9. Base pairs Weak Strong Tm!

10. Mutation 2 E.coli has mutations Humans have somatic and germline mutations Point mutation –missense transition R – R, Y – Y, C – T, G – A transversion R – Y A-T C-G C-A –nonsense  TGA, TAG, TAA –Non-coding Splice, 5’ 3’, Intron

11. Mutation 3 Insertions and deletions –One bp is sometimes called “point” –Frameshift –ATGCCCTGCAATGAC –ATGCCCCTGCAATGAC Ooops

12. Methylation of C

13. Mutations 4 Chromosomal rearrangement –Inversion –Translocation Chromosome copy –Aneuploidy (Down’s) –Polyploidy (tetraploid) –Whole genome duplication WGD Mutational hotspots Repeats GCGCGCGCGC slip = microsatellites

14. Genetic code The “Universal” Genetic Code. Phe UUU Ser UCU Tyr UAU Cys UGU UUC UCC UAC UGC Leu UUA UCA ter UAA ter UGA UUG UCG ter UAG Trp UGG Leu CUU Pro CCU His CAU Arg CGU CUC CCC CAC CGC CUA CCA Gln CAA CGA CUG CCG CAG CGG Ile AUU Thr ACU Asn AAU Ser AGU AUC ACC AAC AGC AUA ACA Lys AAA Arg AGA Met AUG ACG AAG AGG Val GUU Ala GCU Asp GAU Gly GGU GUC GCC GAC GGC GUA GCA Glu GAA GGA GUG GCG GAG GGG

15. Willie Taylor’s AAs

16. Mutations 5 Synonymous usually 3 rd base Non-synonymous –Conservative AAA – AGA Lys - Arg –Radical AAA – UAU Lys - Tyr CpG methylation  mutational hotspot CpG islands 5’ mamm housekeeping genes

17. Mutations Quiz Exon Intron 5’ 3’ A T CGU Which mutations AUTCG are most likely to be baaaad?

18. Mutations & evolution Most bacteria have a characteristic mutational bias. This will give a species specific G+C ratio –E.coli 50% –B.subtilis 40% –Extreme Mycoplasma, Micrococcus Many bacteria have strand bias because the Okazaki enzymes have a different bias Hi GC and Lo GC gram positive.

19. Quiz “answers” LocationRate (subst/site/year*10 -9 ) 5’2.36 Synon4.65 NonSyn0.88 Intron3.7 3’4.46  4.85 Synon Not neutral? (Pseudogene)

20. Substitution A mutation that’s been sieved by selection Selection is a population/probability term Probability that a mutation will a) survive? b) become polymorphism? c) replace existing? Depends on population size

21. Bacterial genes/genomes E.coli about 4000 genes, 4 Mbases Tightly packed, usually no overlap –Viruses ++ tightly packed, overlapping genes Origin of replication –Usually near dnaA DNA polymerase –Binds and copies –Needs gyrase, helicase etc. –5’-3’ strand = read through –3’-5’ strand read in chunks: Okazaki fragments

22. Operons Jacob and Monod (and Lwoff) Lac operon lacZ lacY lacA induced and transcribed together lacI adjacent but separate transcript MolBiol? Measure mRNA levels,  -gal Evol? Co-transcription for better control zyaopi

23. Odd operons Easy explanation when only E. coli and B. subtilis available But M. jannaschii (first archaea sequenced) –Linked, cotranscribed but biochemically mad Fallout from genome sequencing tRNA complement informs expression

24. Bioinformatic consequences RNA polymerase needs binding site Promoter site upstream from transcrip start -35 -10 TTGACANNNNNNNNNNNNNNNNNTATATT Site directed mutagenesis can parse the info Remember lacZ,Y,A cotranscribed Then 3’ trailer after last stop codon Try to think of 3-D picture

25. Gene structure Upstream control regions Start codon Open Reading Frame (ORF) Stop codon UGA UAG UAA 3’ downstream So gene prediction is “easy”

26. Consequences This view of how the process works –Colours our view of sequences Central dogma: –DNA makes RNA makes PROTEIN makes everything else RNA makes DNA means inheritance of acquired characteristics (Lamarck). Leads to a particular definition of “gene”

27. Translation Transcription gives you mRNA Translation gives you protein In bacteria transcrp transl simultaneous Ribosome – complex (cottageloaf) of two subunits 50S and 30S = 70S 30S 21 proteins rpsX and 16S RNA 50S 34 proteins rplX and 23S+5S RNA Needs tRNA, mRNA Ribosome binding site RBS upstream from ATG

28. Summary What we know about the genetics can help us identify genes bioinformatically –DNA signatures (RBS, Promoter) –Start - ORF - stop pattern –Consistent codon usage Have we predicted a real gene? –Is it present as mRNA?