![Comparative Genomics Tools
• Similarity search programs
– BLAST2 (Basic Local Alignment Search Tool)
– FASTA
– MUMmer (Maximal Unique Match)
(Comparisons and analyses at both Nucleic acid and
protein level)
• Other alignment programs
– DBA [DNA Block Aligner] (Jareborg et al)
– blastz (Schwartz et al.)
– BLAT/AVID,
– WABA [Wobble Aware Bulk Aligner]
– DIALIGN [Diagonal ALIGNment] (Morgenstern et al.)
– SSAHA [Sequence Search and Alignment by
Hashing Algorithm] S S Jena](https://image.slidesharecdn.com/comparativegenomicssid2003format-150525185240-lva1-app6892/75/Comparative-genomics-sid-2003-format-25-2048.jpg)
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Comparative genomics @ sid 2003 format
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- 4. Human Genome Projectdecided to use smaller genomes as warm-up for human genome. Resulted in sequencing: Many bacteria Model organism genomes Yeast, C. elegans, Arabidopsis, Drosophila Crop plants – Rice Comparison of these genome sequences provided basis for field of “Comparative Genomics” S S Jena
- 5. What is comparativegenomics? Analyzing & comparing genetic material from different species to study evolution, gene function, and inherited disease. To understand the uniqueness between different species. S S Jena
- 6. Comparative genomics priorto obtaining full genome sequence Genome size •Compared DNA content among species. (DAPI staining- FACS) Single copy and repetitive DNA •Used hybridization kinetics. (Cot curve) •Found amount of repetitive DNA differed greatly among species. S S Jena
- 7. What is compared? Genelocation Gene structure Exon number Exon lengths Intron lengths Sequence similarity Gene characteristics Splice sites Codon usage Conserved synteny S S Jena
- 8. What can homologytell us? 1. Identity of genes: - The identity of the gene in another organism - The identity of nearby genes - The function of the gene (if annotated) 2. Suggestions of how the gene might be causing disease 3. Infer ancestral relationships 4. Discover principles of evolution S S Jena
- 9. Negative selection: Theremoval of deleterious mutations from a population; also referred to as purifying selection. Positive selection: The retention of mutations that benefit an organism; also referred to as Darwinian selection. Homologs: Features (including DNA and protein sequences) in species being compared that are similar because they are ancestrally related. S S Jena
- 10. Orthologs and Paralogs •While comparing sequence from different genomes, we must distinguish between two types of closely related sequences: Orthologs are genes found in two species that had a common ancestor. Paralogs are genes found in the same species that were created through gene duplication events. S S Jena
- 11. A A’ A’’ B’ B B” A & BOrthologs A’ & A’’ B’ & B’’ Paralogs Orthologs and Paralogs S S Jena
- 12. Example Early globin gene Alpha chain Beta chain Frog alpha Human alpha Human Beta Frog beta First duplication event Second duplication event 0 12 3 t Orthologs Paralogs Orthologs H o m o l o g s S S Jena
- 13. Synteny Regions of twogenomes that show considerable similarity in terms of sequence and conservation of the order of genes. Genes that are in the same relative position on two different chromosomes. Closely related species generally have similar order of genes on chromosomes. Synteny can be used to identify genes in one species based on map-position in another. S S Jena
- 14. Synteny among cropgenomes: rice, maize and wheat Maize: evolved from tetraploid ancestor
- 15. THE ORIGIN ANDEVOLUTION OF MODEL ORGANISMS Hedges SB (2002) Nature Reviews Genetics 3: 838 -849. The colored blocks represent synteny blocks S S Jena
- 16. Synteny of Mouseand Human genome When sequence from mouse and human genomes compared, regions of remarkable synteny were found. Genes are in almost identical order for long stretches along the chromosome. Human Chr 14 Mouse Chr 14 S S Jena
- 17. Synteny of Mouse& Human genome Almost entirely syntenic S S Jena
- 18. The one toone linear correspondence between the order of codons in a coding sequence and the order of amino acids in the protein encoded. A linear map of mutation sites within a gene corresponds to the linear location of amino acid substitutions within the polypeptide encoded by that gene. Comparative genome analyses demonstrated that gene orders among related plant species remained largely conserved over millions of years of evolution. Colinearity S S Jena
- 19. Comparative genomics exploitsboth similarities and differences in the proteins, RNA and regulatory regions of different organisms to infer how selection has acted upon these elements. Those elements that are responsible for similarities between different species should be conserved through time (stable selection), while those elements responsible for differences among species should be divergent (positive selection). S S JenaS S Jena
- 20. The DNA sequencesencoding the proteins and RNAs responsible for functions that were conserved from the last common ancestor should be preserved in contemporary genome sequences. Likewise, the DNA sequences controlling the expression of genes that are regulated similarly in two related species should also be conserved. Conversely, sequences that encode (or control the expression of) proteins and RNAs responsible for differences between species will themselves be divergent. Principle cont. S S JenaS S Jena
- 21. Evolution and sequenceconservation If no constraints on DNA sequence, Random mutations will occur. Over tens of millions of years these random mutations will make two related sequences Different. e.g. Non-coding DNA that does not have a regulatory function tends to diverge much more rapidly than protein coding DNA. S S JenaS S Jena
- 22. Function and sequenceconservation However: if there are constraints, e.g. oDNA codes for protein oor transcription factor binds DNA oReplication origin Then there will be sequence similarity when related sequences compared Basic rule when comparing two related sequences: Sequence conservation = functional importance
- 23. Why do weannotate genomes? • If we find the gene in a model organism (like the rat), then we need to know what the homolog is in humans. • If we find the gene in a model organism, we need to know if it’s doing the same thing in humans. • If we DON’T know what gene is implicated in a disease, we can annotate ALL the genes in a region and find candidates for further study S S JenaS S Jena
- 24. Comparison of genomicsequences from different species can help to identify: oGene structure oGene function oRegulatory sequences oInteractions between gene products S S JenaS S Jena
- 25. Comparative Genomics Tools •Similarity search programs – BLAST2 (Basic Local Alignment Search Tool) – FASTA – MUMmer (Maximal Unique Match) (Comparisons and analyses at both Nucleic acid and protein level) • Other alignment programs – DBA [DNA Block Aligner] (Jareborg et al) – blastz (Schwartz et al.) – BLAT/AVID, – WABA [Wobble Aware Bulk Aligner] – DIALIGN [Diagonal ALIGNment] (Morgenstern et al.) – SSAHA [Sequence Search and Alignment by Hashing Algorithm] S S Jena
- 26. Comparative Genomics Tools •Comparative gene prediction programs – Twinscan – Doublescan – SGP-1 • Regulatory region prediction – Consite • Visualization/ Sequence analysis programs – Dot plot (e.g. Dotter) – PIP maker (Percent Identity Plot) – Alfresco – VISTA (VISualization Tools for Alignments) – ACT (Artemis comparison tool) S S Jena
- 27. General Databases Usefulfor Comparative Genomics • Locus Link/RefSeq: http://www.ncbi.nih.gov/LocusLink/ • PEDANT-Protein Extraction Description ANalysis Tool http://pedant.gsf.de • COGs - Cluster of Orthologous Groups (of proteins) http://www.ncbi.nih.gov/COG/ • KEGG- Kyoto Encyclopedia of Genes and Genomes http://www.genome.ad.jp/kegg/ • MBGD - Microbial Genome Database http://mbgd.genome.ad.jp/ • GOLD - Genome OnLine Database http://wit.integratedgenomics.com/GOLD/ • TIGR – The Institute of Genome Research Comparative genomics of Parasites S S Jena
- 28. Alignment ofDNA sequences is the core process in comparative genomics. An alignment is a mapping of the nucleotides in one sequence onto the nucleotides in the other sequence, with gaps introduced into one or the other sequence to increase the number of positions with matching nucleotides. Several powerful alignment algorithms have been developed to align two or more sequences. COMPARATIVE GENOMICS -COMPARATIVE GENOMICS - PROCESSPROCESS S S Jena
- 29. • The mostfrequently performed type of sequence comparison is the sequence similarity search. • Sequence comparisons that implicate function are widely used: – To determine if newly sequenced cDNA or genomic region encodes gene of known function. – Search for similar sequence in other species (or in same species) Sequence similarity searchSequence similarity search S S Jena
- 30. • Search databasesof DNA sequences • Use computer algorithms to align sequences – Don’t require perfect matches between sequences – Allow for insertions, deletions and base changes • Most commonly used algorithms: – BLAST – FAST-A Homology searches S S Jena
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- 32. Pairwise genome comparisonof protein homologs (symmetrical best hits) http://www.ncbi.nlm.nih.gov/sutils/geneplot.cgi S S Jena
- 33. Genome databases • Genomesat NCBI, EBI, TIGR
- 34. NCBI comparative maps SS Jena
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- 37. Gramene (http://www.gramene.org)is a comparative genome mapping database for grasses and a community resource for rice (Oryza sativa). It combines a semi-automatically generated database of cereal genomic and expressed sequence tag sequences, genetic maps, map relations, and publications, with a curated database of rice mutants (genes and alleles), molecular markers, and proteins. Gramene curators read and extract detailed information from published sources, summarize that information in a structured format, and establish links to related objects both inside and outside the database. S S Jena
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- 40. • Rice – wholegenome sequence • Other crop grasses – Maize – Sorghum – Millet – Sugarcane – Wheat – Oats – Barley Gramene scope Synteny in Gramene
- 41. Genome analysesGenome analyses •Variation in – Genome size – GC content – Codon usage – Amino acid composition – Genome organization • Single circular chromosomes • Linear chromosome + extra chromosomal elements E. coli: 4.6Mbp M. pneumoniae: 0.81Mbp B. subtilis: 4.20Mbp B. burgdorferi: 29% M. tuberculosis: 68% G, A, P, R: GC rich I, F, Y, M, D: AT rich S S Jena
- 42. CG: Comparisons betweengenomes • The stains of the same species • The closely related species • The distantly related species – List of Orthologs – Evolution of individual genes – Evolution of organisms S S Jena
- 43. Comparison of thecoding regions • Begins with the gene identification algorithm: Infer what portions of the genomic sequence actively code for genes. • There are four basic approaches. 4 basic categories of gene identification programs Category Algorithm 1. Based on direct evidence of transcription EST_GENOME sim4 2. Based on homology with known genes PROCRUSTES 3. Statistical or ab-initio approaches Genscan FGENES GeneMark Glimmer 4. Using genome comparison TwinScan Rosetta S S Jena
- 44. ‘Trait-to-gene’ approach A bioinformaticsapproach to identify genes involved in adaptive traits is called “Trait-to-gene”. Assumption: New genes will be created to perform tasks required for an adaptive response. Underlying reasoning: organisms that share a particular trait will share related genes. Also used to identify two different genes that serve the same function in different organisms. S S Jena
- 45. Relating traits togenes To compare genes among species the Trait-to- gene approach uses “COG database”. (Eugene Koonin) It is a method for identifying likely orthologues when making whole genome comparisons among multiple species. S S Jena
- 46. Important observations withregard to Gene Order • Order is highly conserved in closely related species but gets changed by rearrangements. • With more evolutionary distance, no correspondence between the gene order of orthologous genes. • Group of genes having similar biochemical function tend to remain localized. S S Jena
- 47. Finding regulatory regionsFindingregulatory regions Called phylogentic footprinting (analogous with DNAase footprinting) Functionally important regions are mutated less. These cis-regulatory motifs can be determined by: – Finding common motifs in orthologous sequences – Aligning orthologous sequences first, then indentifying common regions Previously known motifs might help S S Jena
- 48. Regulatory region prediction Consite: –Detection of TFBS conserved in corresponding genomic sequences from different species S S Jena
- 49. Visualization Dot plot: A graphicaldot plot program for detailed comparison of two sequences Soft wares for dot-plot: DNA strider Dotlet Dotter Dottup S S JenaS S JenaS S Jena
- 50. Dot plot – TheX axis represents the first sequence (PHO5), – The Y axis represents the second sequence (PHO3) – A dot is plotted for each match between two residues of the sequences. – Diagonal lines reveal regions of identity between the two sequences. A dot plot is a simple graphical representation of identical residues between two sequences. S S JenaS S JenaS S Jena
- 51. Hypothetical whole genomemap dot plots S S JenaS S Jena
- 52. Whole genome mapdot plots of E. coli vs B. subtilis and E. coli vs S. typhimurium Random distribution Diagonal patternS S JenaS S Jena
- 53. Sequence logo A veryuseful representation of the conservation patterns is the so-called sequence logo. This shows the conserved residues as larger characters, where the total height of a column is proportional to how conserved that position is. S S JenaS S Jena
- 54. Applications ofApplications of comparativegenomicscomparative genomics 1. Gene prediction 2. Regulatory region prediction 3. Interaction mapping S S Jena
- 55. When comparinggenomes of different species – Genes normally have same exon/intron structure (Neutral theory of evolution) Look for ORFs that are conserved in both genomes Frequently permits accurate identification of genes – Fugu/human comparison: found >1000 genes that had been missed by annotation – Mouse/human comparison indicates only 30,000 genes in genome How genome comparisons help? S S Jena
- 56. The comparisonof fruit fly genome with the human genome discovered that about 60 percent of genes are conserved between fly and human. Virtually all (99%) of the protein-coding genes in humans align with homologs in mouse, and over 80% are clear 1:1 orthologs. In most cases, the intron-exon structures are highly conserved. The finding that the three wheat genomes have a highly similar gene content and order was the first demonstration of colinearity in the grasses and a pivotal finding in the development of comparative genomics. How genome comparisons help? Cont. S S Jena
- 57. Comparison of thehuman and mouse spermidine synthase genes revealed an additional intron in the human gene that is not found in the mouse homologue. Sequence comparison example Human Mouse 5,500 bp S S Jena
- 58. Relationships among theGenomes of Rice, Foxtail Millet, and Pearl Millet
- 59. CG helps genomeannotationsCG helps genome annotations In prokaryotes, finding genes is relatively easy based on open reading frames (ORFs) In eukaryotes, we have to look for ORFs, exons, introns, splice sites, polyA sites Difficulties: • Predicted exons sometimes do not exist • Pseudogenes • Alternative splicing Merit: In different species, the genes normally have similar exon-intron structure S S Jena
- 60. Finding regulatory sequencesFindingregulatory sequencesFinding regulatory sequencesFinding regulatory sequences Regulatory sequences are difficult to identify using computer programs. Problems are: Most enhancer sequences have yet to be identified They are usually short: 6-10 basepairs Those that are known are usually degenerate • They can differ in one or more basepairs • Still bind the cognate transcription factor S S Jena
- 61. Comparisons to identifyregulatory elements Comparisons of genomes of different species can identify cis-regulatory elements. (Neutral theory of evolution) Change in intergenic regions and introns are usually more rapid than in coding regions Nevertheless, regulatory elements tend to be conserved (because these seq. bind TFs) Conserved intergenic sequences identified by aligning genomic regions of orthologs are called “phylogenetic footprint.” (analogous with DNAase footprinting).
- 62. Interaction mapping Aremarkable use of comparative genomics is to identify interacting proteins. Protein-protein interactions are critical for cellular functions like Transfer of information in a genetic pathway Scaffolding to tether other proteins Enzymatic reactions (multi-subunit enzymes) Large molecular machines such as motors S S Jena
- 63. Rosetta Stone Interactionproteins are encoded by single gene in some species, whereas in other species same proteins are encoded in two genes. Systematic search through sequenced genomes for these relationships should identify proteins that interact. This method is called “Rosetta Stone” approach S S Jena
- 64. Rosetta Stone example Equivalent of yeast protein topoisomerase II, in E. coli is encoded by two genes: gyrase A and gyrase B. Suggests that gyrase B and gyrase A interact in E. coli S S Jena
- 65. 1. Identification andmapping of Leucine-rich repeat resistance gene analogs in Bermuda grass 31 Bermuda grass (Cynodon spp.) disease resistance gene analogs (BRGA) were cloned and sequenced from diploid, triploid, tetraploid and hexaploid bermuda grass using degenerate primers to target Nucleotide Binding site (NBS) of the NBS-Leucine Rich Repeat (LRR) resistance family. (Harris et al., (2010) J.Amer.Soc.135:74-82) S S Jena
- 66. 2. Synteny betweenthe centromeric regions of wheat and rice Recently discovered that rice centromeres contain genes. This helps in studying centromere homologies between wheat and rice chromosomes by mapping rice centromeric regions on to wheat aneuploid stocks Genome wide comparison of wheat ESTs that were mapped to centromeric regions against rice genome sequences revealed high conservation and one to one correspondence of centromeric regions between wheat and rice chromosome pairs W1-R5, W2-R7, W3-R1, W5-R12, W6-R2 and W7-R8 (Qi et al., (2009) Genetics 183:1235-1247) S S Jena
- 67. 3. Sequencing andcomparative analysis of conserved syntenic segment (CSS) in the solanaceae Wang et.al. reported generation and analysis of sequences for unduplicated conserved syntenic segment (CSS) in genomes of five members of solanaceae. This analysis indicates 30 million years of plant evolution in absence of polyploidization. The sequenced segments of the potato, tomato, pepper, eggplant, and petunia genomes are shown alongside corresponding regions of the Arabidopsis (At) genome. (Wang et al., (2008) Genetics 180:391-408) S S Jena
- 68. Conserved syntenic segment(CSS) in five species of Solanaceae
- 69. 4. Comparative physicalmapping of Rice Comparative physical mapping between Oryza sativa (AA Genome type) and Oryza punctata (BB Genome type) was constructed by aligning physical map of O. punctata on to O. punctata genome sequence. The level of conservation of each genome between two species was determined. The alignment suggests more divergence of intergenic and repeat regions in comparison to gene rich regions. Genome of O. punctata was 8% larger than O. sativa with individual chr. differences of 1.5 to 16.5%. (Kim et al., (2007) Genetics:379-390) S S Jena
- 70. Alignment view ofthe comparative physical map of O. punctata (BB genome type) and O. sativa (AA genome type) using SyMap
- 71. What is differencebetween man and ape? Man and chimpanzee have a genome wide similarity of greater than 95%. What accounts for differences in species?. Recent study suggests that it is due to specific gene expression differences. – Striking differences found only in brain S S Jena
- 72. Human/ape gene expressioncomparisons Blood tissue Brain tissueLiver tissue S S Jena
- 73. CASE STUDYCASE STUDYCASESTUDYCASE STUDY S S Jena
- 74. Objective of theresearchObjective of the research Classification and phylogenic analysis of phytohormone related genes, from metabolism enzymes to receptors and signaling components, in different species. S S Jena
- 75. Abstract of theworkAbstract of the work Genetic and molecular studies in the model organism Arabidopsis thaliana have revealed the individual pathways of various plant hormone responses. Selected 479 genes that were convincingly associated with various hormone actions. By using these 479 genes as queries, a genome-wide search for their orthologues in several species (microorganisms, plants and animals) was performed. Meanwhile, a comparative analysis was conducted to evaluate their evolutionary relationship. S S Jena
- 76. Result and discussionResultand discussion Phylogenetic tree generated by orthologue genes, using orthologue gene similarity as compared to A. thaliana hormone related genes Protein sequence phylogenetic tree S S Jena
- 77. Distribution of orthologuesin function category of hormone related genes in different species Distribution of orthologues in function category of hormone related genes in different species The height of each bar showing in different color represents the percentage of orthologue genes in AHRG of selected plants as compared to that of A. thaliana. Blue - orthologues belonging to hormone metabolism related genes; Purple - orthologues belonging to hormone transport genes; light yellow – orthologues belonging to genes related to signal transduction. S S Jena
- 78. Comparison of thecopy numbers of AHRG orthologues in cereals – Rice, S. bicolor, P. trichocarpa, and A. thaliana. Different colors represent ratios that are calculated by the number of orthologue genes in selected species versus the number of AHRG in A. thaliana. S S Jena
- 79. ConclusionConclusion The metabolisms andfunctions of plant hormones are generally more sophisticated and diversified in higher plant species. In particular, several phytohormone receptors and key signaling components were not present in lower plants or animals. Meanwhile, as the genome complexity increases, the orthologue genes tend to have more copies and probably gain more diverse functions. S S Jena
- 80. CASE STUDY- 2CASESTUDY- 2 S S Jena
- 81. Plant disease resistance(R) loci frequently lack synteny between related species of cereals and crucifers but appear to be positionally well conserved in the Solanaceae. In this report, a local RGA approach is adopted using genomic information from the model Solanaceous plant tomato to isolate R3a, a potato gene that confers race-specific resistance to the late blight pathogen Phytophthora infestans. Abstract of the researchAbstract of the research S S Jena
- 82. The genomic regionsharboring the R3 late blight resistance locus in potato and the I2 Fusarium wilt resistance locus in tomato are colinear (Huang et al., 2004). Identified a cluster of I2 gene analogues (I2GAs) in potato. This potato I2GA cluster positionally corresponds to the SL8D cluster of the I2 complex locus in tomato and was therefore named the St-I2 cluster. Results and discussionResults and discussion S S Jena
- 83. R3a candidates were identifiedusing a local resistance gene analogue (RGA) approach The syntenic relationships of R gene clusters are highlighted using gray rectangles. To identify I2GAs physically close to R3a, an association analysis on bacterial artificial chromosome (BAC) pools was conducted. ResultsResults cont.cont. Comparative genetic maps of the I2 complex locus in tomato and the R3 complex locus in potato.
- 84. ResultsResults cont.cont. In vitroinoculation of the primary transformants of R3a. Massive sporulation (S) and localized hypersensitive reactions (HR) are observed on compatible and incompatible interactions, respectively. S S Jena
- 85. In this study,genomic information from tomato was used to isolate the potato late blight resistance gene R3a from an ancient locus involved in plant innate immunity in the Solanaceae. Comparative analyses of the R3 complex locus with the corresponding I2 complex locus in tomato suggest that this is an ancient locus involved in plant innate immunity against oomycetes and fungal pathogens. However, the R3 complex locus has evolved after divergence from tomato and the locus has experienced a significant expansion in potato without disruption of the flanking colinearity. ConclusionConclusion S S Jena
- 86. LIMITATIONS OF CGLIMITATIONSOF CGLIMITATIONS OF CGLIMITATIONS OF CG Homologous genes are relatively well preserved while noncoding regions tend to show varying degrees of conservation. Cross species comparative genomics is influenced by the evolutionary distance of the compared species. Genetic drift- how can we tell what differences are really selection and important to organism function and not a result of genetic drift. Computationally intensive- large amount of data that are being compared, still coming up with the tools to process and compare genomes. In order for the comparisons to statistically relevant many more genomes will need to be sequenced.S S Jena
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- 88. The goal ofcomparative genomics Due to our current ability to annotate genomes we can precisely place a list of genes on the chromosome, resulting in something similar to a set of lights of uniform color and intensity. We will be able to tell what each gene does and when and where it is expressed. S S Jena
- 89. Issues for thefuture • Faster/better algorithms for aligning vertebrate genomes • Multiple alignments – Comparing several species can give clues to which regulatory sequences are of a basic nature, and which are lineage specific • Cataloguing of comparative data • Better visualisation – Whole syntenic region <> nucleotide level – Multiple genome sequences S S Jena
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Editor's Notes
- #5 The origins of the field of Comparative Genomics can be found in the strategy used by the Human Genome Project to start sequencing smaller genomes to gain experience prior to tackling the large and complex human genome. This resulted in the sequencing of several bacterial genomes as well as the genomes of some of the most widely studied model organisms including (in chronological order of sequence completion): brewers yeast, S. cerevisiae; the nematode, C. elegans; the model plant, Arabidopsis thaliana; and the fruitfly, Drosophila melanogaster. As each genome sequence was completed, it was compared to those already in the databases and the study of the comparison of genomes came to be known as “Comparative Genomics”.
- #7 Prior to the availability of fully-sequenced genomes and the acquisition of the name Comparative Genomics, genome-wide comparisons had been performed. These included determining relative genome size by comparing the DNA content of different species. One way of determining DNA content was to incubate cells with a DNA-binding dye such as DAPI and then analyze the fluorescence found in individual nuclei using a fluorescence activated cell sorter (FACS). Another parameter that could be roughly determined prior to sequencing was the relative abundance of single copy versus repetitive DNA in the genome. Genomic DNA was randomly sheared and denatured. It was then allowed to reanneal and the amount of double-stranded DNA was determined at successive time intervals. Because repetitive DNA finds a complementary strand more rapidly than single-copy DNA, the proportion of double-stranded DNA detected at early times was considered to be roughly equal to the amount of repetitive DNA in the genome. Graphs of the proportion of double stranded DNA versus time were called Cot curves. This use of hybridization kinetics was refined to identify highly repetitive DNA (the DNA that most rapidly reannealed), middle repetitive DNA (more slowly reannealing DNA) and single copy DNA (the slowest to reanneal).
- #11 There is a trap that is easy to fall into when comparing two genomic sequences. For a comparison of two genes to be meaningful one must know the evolutionary relationship between them. The genes can be either orthologs or paralogs. Othologs are genes found in two species that had a common ancestor prior to the divergence of the two species. Paralogs are genes found in the same species that were created through gene duplication events. The problem arises when one compares genes from two species that are similar in sequence but are not orthologs. These genes may have different structure, function and expression patterns in the two species.
- #12 This slides depicts the relationship between orthologs and paralogs. A species indicated by the green line evolves from a species represented by the red line. In the green species, gene A evolves from gene B in the red species. After the two species have diverged, gene duplication events take place in both species. In the green species these events produce A’ and A’’, while in the red species they produce B’ and B’’. A and B are the most closely related to the ancestral gene while A’, A’’, B’ and B’’ are more distantly related and have taken on new functions. Thus it is reasonable to compare A and B but not A’ with B’ or with B’’ nor should one compare B with A’ or A’’. The important question to ask is are two genes related by a speciation event as is the case for orthologs, or by a gene duplication event, as is the case for paralogs.
- #14 Prior to the availability of sequenced genomes, genetic and physical maps of different species were compared. When a similar order of genes was found on the chromosomes of two different species it was called “synteny.” Sometimes, duplications of chromosomal segments leads to syntenic regions within the genome of the same species. In general, it has been found that closely related species have fairly similar gene order on their chromosomes, leading to large syntenic regions. An important practical application of synteny is to identify a gene that has been genetically mapped in a species that has a very large genome. If the gene is mapped between two known genes then synteny would suggest that the gene of interest is likely to lie between the same two genes in a species with a smaller genome.
- #15 One of the most dramatic examples of synteny between species whose genomes vary greatly in size is found in the crop plants, rice, maize (corn) and wheat. In this figure the chromosomes of each species are arranged in a circle. Rice has the smallest genome and is in the middle in red. Maize has a duplicated genome which is indicated by the two sets of yellow chromosomes. Wheat has a considerably larger genome than maize and is on the outside. The location of genes that control traits such as height or seed shattering are indicated on the chromosomes of the different species. Now that the rice genome is fully sequenced, wheat and maize breeders can use synteny to identify genes involved in these and other traits for which they have a genetic map position.
- #17 Once genomes of related species are fully sequenced, then the precise order of genes can be compared. For Mouse and Human there are stretches of remarkable synteny like the one shown on this slide between a portion of Human chromosome 14 and mouse chromosome 12. The blue lines linking the two chromosomal regions indicate genes that are found on both chromosomes. Note that the size of the intergenic regions varies considerably, but the order of genes is nearly identical.
- #18 Comparison of Mouse and Human sequences across the whole genome revealed a hodge-podge of chromosomal translocations as shown on this slide. At the bottom of the image are the 23 human chromosomes each with a different color code. Above them are the 20 mouse chromosomes showing the regions that are syntenic to a particular human chromosome through use of the human chromosome’s color. Some mouse chromosomes like the X chromosome are almost entirely syntenic to their human counterpart. Others have syntenic regions from many human chromosomes, like mouse chromosome 2 which has syntenic regions from at least seven human chromosomes.
- #22 Most uses of DNA sequence comparison are based on the observation that conservation of DNA sequence is usually for a reason. The idea is that if there are no constraints on the DNA sequence then mutations will occur randomly. The accumulation of these random mutations means that over tens of millions of years of evolutionary time, two sequences that started out the same will become so different as to be unrecognizable. An example is non-coding DNA that does not have a regulatory function tends to diverge much more rapidly than protein coding DNA.
- #23 However, if there are constraints on the DNA such as coding for a protein or binding a transcription factor, then that portion of the DNA sequence will not randomly drift, but will remain relatively similar in sequence over the millions of years that two species evolve independently. Thus, the basic rule when comparing two related sequences is that sequence conservation indicates that there is functional importance. We will discuss how this rule has been used to identify various features of DNA sequence. It is important to point out that sequence conservation will also exist when the two related genomes are so closely related that insufficient time has passed to allow for sequence divergence.
- #25 Once DNA sequence is known for two genomes, comparisons between them can be used for many purposes including determining gene structure (e.g. exon/intron boundaries), specifying gene function (by similarity to a gene encoding a protein of known function) and identifying regulatory sequences (such as promoters and enhancers). Comparisons of DNA sequences have even been used to determine which gene products are likely to interact with each other.
- #30 By far the most frequently performed type of sequence comparison is the sequence similarity search. This is frequently called a homology search, although strictly speaking, homology refers to similarity due to a common origin and sequence similarity can also arise through convergent evolution. Whenever DNA is freshly sequenced the question naturally arises, “Does it encode something that is similar to a protein (or RNA) of known function?” To answer this question, researchers search for similar sequences in other species, or in the same species.
- #31 To find out if there are any sequences that are similar to a newly acquired sequence requires searching the databases of DNA and protein sequences. This process is described in detail in the Bioinformatics chapter. Briefly, there are computer algorithms that attempt to find the best alignment between the search sequence and all the sequences in the databases. Because the sequences in other species are likely to have undergone some changes the computer programs don’t require perfect matches between the sequences. They allow for some base or amino acid changes as well as small insertions and deletions. The most commonly used program is BLAST because it performs a thorough search in a relatively small amount of time. Another program known as FAST-A is able to detect matching segments over longer stretches of sequence but takes much longer to perform a thorough search of the databases.
- #45 A bioinformatics approach to identify genes involved in adaptive traits is called “Trait-to-gene”. This method is based on the assumption that in some cases at least, new genes will be created to perform tasks required for an adaptive response. Its underlying reasoning is that organisms that share a particular trait will share related genes. This method can also be used to identify two different genes that serve the same function in different organisms.
- #46 To compare genes among species the Trait-to-gene approach uses a database developed by Eugene Koonin’s group of orthologues known as the “COG database”. COG stands for “Cluster of Orthologous Group” and it is a method for identifying likely orthologues when making whole genome comparisons among multiple species. When all species share a COG then there is little that can be learned except that it is likely to play an important role in a basic housekeeping function. However, as is illustrated in this slide, if all the species that share a particular trait have a gene that is a member of a particular COG, and species that don’t share the trait also don’t have the COG, then this is evidence that the gene may play an important role in the particular adaptive trait.
- #52 Perfectly congruent maps produce a single diagonal set of dots. Maps that differ by simple chromosomal rearrangements show recognizable patterns corresponding to those rearrangements.
- #53 Whole genome map dot plots show essentially random distributions of homologous genes when the maps of E. coli and B. subtilis are compared. However, a similar plot of E. coli and S. typhimurium shows an obvious diagonal and gives some evidence of the well known inversion in the 30-40 minute region (Sanderson and Hall, 1970; Riley and Krawiec, 1987).
- #56 When genomes of more than one species are compared, due to the neutral theory of evolution coding regions tend to be conserved as well as exon/intron structures. Thus, it becomes fairly straightforward to look for ORFs that are conserved in both genomes and found in similar positions relative to surrounding ORFs. Cross-genome comparisons have been shown to be an effective means of accurately annotating genes as well as identifying new genes. For example, in the comparison of the Fugu genome with the human genome, over 1000 putative genes were discovered that had been missed by the annotation programs. Comparison of the mouse genome with the human genome indicates that there are only about 30,000 genes in both genomes. This is consistent with the predictions made from the draft human sequence but runs contrary to earlier pre-genome predictions that set the number of genes as closer to 100,000.
- #58 When the human spermidine synthase gene involved in the synthesis of polyamines was compared with the homologous gene in the mouse genome it was found that there is an additional intron in the human gene which interrupts the fifth exon in the mouse gene. This is an example of a comparison that highlights how gene structure can change as species evolve.
- #61 Identifying regulatory sequences in fully sequenced genomes is very challenging for computer programs. There are several issues that compound the problem. The first is that relatively few transcription factor binding sites have been characterized by biochemical or genetic experiments. Thus, many have yet to be identified. Second, most enhancer and repressor cis-elements are short, between 6 and 10 basepairs. Third, and perhaps most problematic, is the fact that most cis-elements are degenerate, meaning that two sites can differ in one or more basepairs but still bind the same transcription factor. The combination of these characteristics means that it is very difficult to write a computer program that can reliably identify cis-elements in eukaryotic genomes.
- #62 The neutral theory of evolution can greatly aid in the search for cis-regulatory elements. Because these sequences bind transcription factors they are constrained from random mutations. Thus sequence conservation in intergenic regions and introns can be used to help identify cis-regulatory elements. To detect conserved intergenic sequences usually involves aligning the genomic regions of orthologues from two or more species. The conserved sequences identified by this type of alignment are called “phylogenetic footprints.”
- #63 A remarkable use of comparative genomics has been to identify proteins that are likely to interact with each other. Protein-protein interactions are critical for various types of cellular functions including: the transfer of information in a genetic pathway, providing a scaffold to tether other proteins, multi-subunit enzymes and large molecular machines such as dynein which works as a molecular motor.
- #64 Normally, one would think that it would be necessary to work with proteins to be able to detect interacting partners. However, with remarkable insight, the group of Christos Ouzounis realized that proteins that interact in one species can be encoded by a single gene in another species. They used these criteria to systematically search through the sequenced genomes to identify genes encoding proteins that are likely to interact with each other. They called their method the “Rosetta Stone” approach.
- #65 An example of the Rosetta Stone approach is the finding that when the genome of the yeast S. cereviseae was compared with the bacterium E. coli it was noted that the equivalent of the yeast protein, topoisomerase II is encoded in two genes in E. coli: gyrase A and gyrase B. This is taken as evidence that gyrase A and gyrase B probably interact in E. coli.
- #72 Of particular concern to some people is the very small difference at the genome level between humans and apes. Based on hybridization between the two genomes there appeared to be a 98.4% similarity, but more recent analysis of sequence comparisons suggests that it is closer to 95%, which is still highly similar. This raises the question,”If the genomes are so similar what accounts for the important differences between the species such as language, the ability to walk upright, etc.?” Pioneering work by Svante Pääbo’s group has begun to address this question. The initial data suggest that there are striking differences in gene expression patterns in the brain, but not in other organs.
- #73 In their 2002 study, Pääbo’s group used microarrays of 12,000 human genes to analyze expression patterns in rhesus monkeys, chimpanzees, and humans. The results showed little difference in the results from liver or blood among the three primates. However, when tissue from the brain was used, it showed a 5.5 fold difference between humans and chimpanzees. The difference was calculated by using the absolute change in gene expression in all 12,000 genes and then doing the interspecies comparison. This study suggests that the most dramatic differences between humans and chimpanzees, namely the disparity in cognitive abilities, might be explained by a difference in gene expression in the brain.
- #89 Our current ability to annotate genomes results in a list of genes for which we still know very little about either their function or regulation. We can precisely place them on the chromosome resulting in something similar to a set of lights of uniform color and intensity. With the approaches of comparative genomics it is hoped that we will be able to soon gain enough knowledge so that we will be able to tell what each gene does and when and where it is expressed. The genome will then resemble a multi-colored set of lights for which we know both their purpose and exactly how they are controlled.