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Organization and Structure of Genomes (contd) • Genome size – i.e. total number of DNA bp – Varies widely - WHY? • C- paradox – i.e., what is the source of the differences? • Do the number of genes required vary so much? – (how many “phyla” are represented at the right?) BioSci D145 lecture 1 page 1 ©copyright Bruce Blumberg 2004. All rights reserved Phylum Chordata Phylum Arthropoda Organization and Structure of Genomes (contd) • How to measure genome complexity? – Hybridization kinetics – Shear and melt DNA – Allow to hybridize and measure ds vs ss by spectrophotometry • Cot½ - measures genome size and complexity – Larger value – longer to hybridize • Smaller k – Longer to hybridize – more unique sequences, larger genome – Much of what we knew about genome size and complexity comes from these studies BioSci D145 lecture 1 page 2 ©copyright Bruce Blumberg 2004. All rights reserved Organization and Structure of Genomes (contd) • Assumptions – Cot½ measures rate of association of sequences – Simple curves at right suggest simple composition • No repetitive sequences • (graphed inverse to book) • What would a more complex genome look like? – Would it be just shifted further to the right? – Or ? BioSci D145 lecture 1 page 3 ©copyright Bruce Blumberg 2004. All rights reserved Organization and Structure of Genomes (contd) • Measure eukaryotic DNA – Multiple components – Can calculate more than 1 Cot½ value – Either means starting material is not pure (i.e., multiple types of DNA) – Or means different frequency classes of DNA • Highly repetitive • Moderately repetitive • Unique – Very big surprise BioSci D145 lecture 1 page 4 ©copyright Bruce Blumberg 2004. All rights reserved Organization and Structure of Genomes (contd) • What does it mean? Genetic complexity is not directly proportional to genome size! • Increase in C is not always accompanied by proportional increase in number of genes – Note incorrect numbers in chart • Drosophila – ~14,000 • human – Controversial – ~30-50K BioSci D145 lecture 1 page 5 ©copyright Bruce Blumberg 2004. All rights reserved Organization and Structure of Genomes (contd) • What can we learn by hybridizing RNA back to the genomic DNA? – Label RNA and hybridize with excess DNA – measure formation of hybrids over time – Rot½ analysis shows that RNA does not hybridize with highly repetitive DNA – What does this mean? • Most of mRNA is transcribed from non-repetitive DNA • Moderately repetitive DNA is transcribed • Highly repetitive DNA is probably not transcribed into mRNA – Key argument why genome sequencers do not bother with “difficult” regions of repetitive DNA BioSci D145 lecture 1 page 6 ©copyright Bruce Blumberg 2004. All rights reserved Organization and Structure of Genomes (contd) • Gene content is proportional to single copy DNA – Amount of non-repetitive DNA has a maximum,total genome size does not – What is all the extra DNA, i.e., what is it good for? • • • • • Repetitive DNA Telomeres Centromeres Transposons Junk of all sorts – Where did all this junk come from and why is it still around? • DNA replication is very accurate • Selective advantage? • OR BioSci D145 lecture 1 page 7 ©copyright Bruce Blumberg 2004. All rights reserved Organization and Structure of Genomes (contd) • What is this highly repetitive DNA? • Selfish DNA? – Parasitic sequences that exist solely to replicate themselves? • Or evolutionary relics? – Produced by recombination, duplication, unequal crossing over • Probably both – Transposons exemplify “selfish DNA” • Akin to viruses? – Crossing over and other forms of recombination lead to large scale duplications BioSci D145 lecture 1 page 8 ©copyright Bruce Blumberg 2004. All rights reserved Transcription of Prokaryotic vs Eukaryotic genomes • Prokaryotic genes are expressed in linear order on chromosome – mRNA corresponds directly to gDNA • Most eukaryotic genes are interrupted by non-coding sequences – Introns (Gilbert 1978) – These are spliced out after transcription and prior to transport out of nucleus – Posttranscriptional processing in an important feature of eukaryotic gene regulation • Why do eukaryotes have introns? – What are they good for? BioSci D145 lecture 1 page 9 ©copyright Bruce Blumberg 2004. All rights reserved Introns and splicing • Alternative splicing can generate protein diversity – Many forms of alternative splicing seen – Some genes have numerous alternatively spliced forms • Dozens are not uncommon, e.g., cytochrome P450s BioSci D145 lecture 1 page 10 ©copyright Bruce Blumberg 2004. All rights reserved Introns and splicing • Alternative splicing can generate protein diversity (contd) – Others show sexual dimorphisms • Sex-determining genes • Classic chicken/egg paradox – how do you determine sex if sex determines which splicing occurs and spliced form determines sex? BioSci D145 lecture 1 page 11 ©copyright Bruce Blumberg 2004. All rights reserved Origins of intron/exon organization • Introns and exons tend to be short but can vary considerably – “Higher” organisms tend to have longer lengths in both – First introns tend to be much larger than others – WHY? • Often contain regulatory elements – Enhancers – Alternative promoters – etc BioSci D145 lecture 1 page 12 ©copyright Bruce Blumberg 2004. All rights reserved Origins of intron/exon organization • Exon number tends to increase with increasing organismal complexity – Possible reasons? • Longer time to accumulate introns? • Genomes are more recombinogenic due to repeated sequences? • Selection for increased protein complexity – Gene number does not correlate with complexity – Ergo, it must come from somewhere BioSci D145 lecture 1 page 13 ©copyright Bruce Blumberg 2004. All rights reserved Origins of intron/exon organization • When did introns arise – Introns early – Walter Gilbert • There from the beginning, lost in bacteria and many simpler organisms – Introns late – Cavalier-Smith, Ford Doolittle, Russell Doolittle • Introns acquired over time as a result of transposable elements, aberrant splicing, etc • If introns benefit protein evolution – why would they be lost? – Which is it? • Introns late (at the moment) BioSci D145 lecture 1 page 14 ©copyright Bruce Blumberg 2004. All rights reserved Evolution of gene clusters • Many genes occur as multigene families (e.g., actin, tubulin, globins, Hox) – Inference is that they evolved from a common ancestor – Families can be • clustered - nearby on chromosomes (α-globins, HoxA) • Dispersed – on various chromosomes (actin, tubulin) • Both – related clusters on different chromosomes (α,β-globins, HoxA,B,C,D) – Members of clusters may show stage or tissue-specific expression • Implies means for coregulation as well as individual regulation BioSci D145 lecture 1 page 15 ©copyright Bruce Blumberg 2004. All rights reserved Evolution of gene clusters (contd) • multigene families (contd) – Gene number tends to increase with evolutionary complexity • Globin genes increase in number from primitive fish to humans – Clusters evolve by duplication and divergence BioSci D145 lecture 1 page 16 ©copyright Bruce Blumberg 2004. All rights reserved Evolution of gene clusters (contd) • History of gene families can be traced by comparing sequences – Molecular clock model holds that rate of change within a group is relatively constant • Not totally accurate – check rat genome sequence paper – Distance between related sequences combined with clock leads to inference about when duplication took place BioSci D145 lecture 1 page 17 ©copyright Bruce Blumberg 2004. All rights reserved