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Belle marquise , vos beaux yeux me font mourir d'amour . Vos yeux beaux d'amour me font , belle marquise , mourir . Me font vos beaux yeux mourir , belle marquise , d'amour . Genome Rearrangements. Anne Bergeron, Comparative Genomics Laboratory Université du Québec à Montréal.
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Belle marquise, vosbeauxyeuxme fontmourird'amour. Vosyeuxbeauxd'amour me font, belle marquise,mourir. Me font vosbeauxyeux mourir, belle marquise,d'amour. Genome Rearrangements Anne Bergeron, Comparative Genomics Laboratory Université du Québec à Montréal
1. General introduction to genome rearrangements Examples of rearranged genomes 2. Measures of distance Rearrangement operations The Hannenhalli-Pevzner distance equation 3. A unifying view of genome rearrangements The Double-Cut-and-Join operation The adjacency graph and the distance equation
1. General introduction to genome rearrangements Examples of rearranged genomes 2. Measures of distance Rearrangement operations The Hannenhalli-Pevzner distance equation 3. A unifying view of genome rearrangements The Double-Cut-and-Join operation The adjacency graph and the distance equation
Example of rearranged genomes : Mitochondrial Genomes Homo sapiens Bombyx mori Mitochondria are small, oval shaped organelles surrounded by two highly specialized membranes. Animal mitochondrial genomes are normally circular, ~16 kB in length, and encode: 13 proteins 22 tRNAs and 2 rRNAs.
Example of rearranged genomes : Mitochondrial Genomes Here is an alignment of the cytochrome c oxidase I of, respectively, Homo sapiens and Bombyx mori. RWLFSTNHKDIGTLYLLFGAWAGVLGTALSLLIRAELGQPGNLLGNDHIYNVIVTAHAFVMIFFMVMPIMIGGFGNWLVPLMIGAPDMAFPRMNNM KWIYSTNHKDIGTLYFIFGIWSGMIGTSLSLLIRAELGNPGSLIGDDQIYNTIVTAHAFIMIFFMVMPIMIGGFGNWLVPLMLGAPDMAFPRMNNM :*::***********::** *:*::**:**********:**.*:*:*:***.*******:**********************:************* SFWLLPPSLLLLLASAMVEAGAGTGWTVYPPLAGNYSHPGASVDLTIFSLHLAGVSSILGAINFITTIINMKPPAMTQYQTPLFVWSVLITAVLLLLSLP SFWLLPPSLMLLISSSIVENGAGTGWTVYPPLSSNIAHSGSSVDLAIFSLHLAGISSIMGAINFITTMINMRLNNMSFDQLPLFVWAVGITAFLLLLSLP *********:**::*::** ************:.* :*.*:****:********:***:********:***: *: * *****:* ***.******* VLAAGITMLLTDRNLNTTFFDPAGGGDPILYQHLFWFFGHPEVYILILPGFGMISHIVTYYSGKKEPFGYMGMVWAMMSIGFLGFIVWAHHMFTVGMDVD VLAGAITMLLTDRNLNTSFFDPAGGGDPILYQHLFWFFGHPEVYILILPGFGMISHIISQESGKKETFGCLGMIYAMLAIGLLGFIVWAHHMFTVGMDID ***..************:***************************************:: *****.** :**::**::**:****************:* TRAYFTSATMIIAIPTGVKVFSWLATLHGSNMKWSAAVLWALGFIFLFTVGGLTGIVLANSSLDIVLHDTYYVVAHFHYVLSMGAVFAIMGGFIHWFPLF TRAYFTSATMIIAVPTGIKIFSWLATMHGTQINYNPNILWSLGFVFLFTVGGLTGVILANSSIDITLHDTYYVVAHFHYVLSMGAVFAIIGGFINWYPLF *************:***:*:******:**:::::.. :**:***:**********::*****:**.***********************:****:*:*** SGYTLDQTYAKIHFTIMFIGVNLTFFPQHFLGLSGMPRRYSDYPDAYTTWNILSSVGSFISLTAVMLMIFMIWEAFASKRKVLMVEEPSMNLE TGLSLNSYMLKIQFFTMFIGVNMTFFPQHFLGLAGMPRRYSDYPDSYISWNMISSLGSYISLLSVMMMLIIIWESMINQRINLFSLNLPSSIE :* :*:. **:* ******:**********:***********:* :**::**:**:*** :**:*:::***:: .:* *: : . .:* RWLFSTNHKDIGTLYLLFGAWAGVLGTALSLLIRAELGQPGNLLGNDHIYNVIVTAHAFVMIFFMVMPIMIGGFGNWLVPLMIGAPDMAFPRMNNM KWIYSTNHKDIGTLYFIFGIWSGMIGTSLSLLIRAELGNPGSLIGDDQIYNTIVTAHAFIMIFFMVMPIMIGGFGNWLVPLMLGAPDMAFPRMNNM :X::XXXXXXXXXXX::XXX:X::XX:XXXXXXXXXX:XX.X:X:X:XXX.XXXXXXX:XXXXXXXXXXXXXXXXXXXXXX:XXXXXXXXXXXXX SFWLLPPSLLLLLASAMVEAGAGTGWTVYPPLAGNYSHPGASVDLTIFSLHLAGVSSILGAINFITTIINMKPPAMTQYQTPLFVWSVLITAVLLLLSLP SFWLLPPSLMLLISSSIVENGAGTGWTVYPPLSSNIAHSGSSVDLAIFSLHLAGISSIMGAINFITTMINMRLNNMSFDQLPLFVWAVGITAFLLLLSLP XXXXXXXXX:XX::X::XXXXXXXXXXXXXX:.X :X.X:XXXX:XXXXXXXX:XXX:XXXXXXXX:XXX: X: XXXXXX:XXXX.XXXXXXX VLAAGITMLLTDRNLNTTFFDPAGGGDPILYQHLFWFFGHPEVYILILPGFGMISHIVTYYSGKKEPFGYMGMVWAMMSIGFLGFIVWAHHMFTVGMDVD VLAGAITMLLTDRNLNTSFFDPAGGGDPILYQHLFWFFGHPEVYILILPGFGMISHIISQESGKKETFGCLGMIYAMLAIGLLGFIVWAHHMFTVGMDID XXX..XXXXXXXXXXXX:XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX:: XXXXX.XX :XX::XX::XX:XXXXXXXXXXXXXXXX:X TRAYFTSATMIIAIPTGVKVFSWLATLHGSNMKWSAAVLWALGFIFLFTVGGLTGIVLANSSLDIVLHDTYYVVAHFHYVLSMGAVFAIMGGFIHWFPLF TRAYFTSATMIIAVPTGIKIFSWLATMHGTQINYNPNILWSLGFVFLFTVGGLTGVILANSSIDITLHDTYYVVAHFHYVLSMGAVFAIIGGFINWYPLF XXXXXXXXXXXXX:XXX:X:XXXXXX:XX:::::.. :XX:XXX:XXXXXXXXXX::XXXXX:XX.XXXXXXXXXXXXXXXXXXXXXXX:XXXX:X:XXX SGYTLDQTYAKIHFTIMFIGVNLTFFPQHFLGLSGMPRRYSDYPDAYTTWNILSSVGSFISLTAVMLMIFMIWEAFASKRKVLMVEEPSMNLE TGLSLNSYMLKIQFFTMFIGVNMTFFPQHFLGLAGMPRRYSDYPDSYISWNMISSLGSYISLLSVMMMLIIIWESMINQRINLFSLNLPSSIE :X :X:. XX:XXXXXXX:XXXXXXXXXX:XXXXXXXXXXX:X :XX::XX:XX:XXX :XX:X:::XXX:: .:XX: : . .:X 73% identity over more than 500 amino acids.
Example of rearranged genomes : Mitochondrial Genomes The 37 genes of animal mitochondria are highly conserved. But the order of the genes differs from species to species. Charles Darwin, 1809 - 1882 A lowly worm
Example of rearranged genomes : Mitochondrial Genomes The invariant parts Homo sapiens mitochondrial genome (proteins and rRNAs) ND4L ND4 ND5 RNS RNL ND1 COX1 COX2 ATP6 ATP8 COX3 ND3 ND4L ND4 ND5 CYTB RNS RNL ND1 ND2 ND6 COX1 stands for the gene cytochrome c oxidase I. ND6 COX1 COX2 ATP6 ATP8 COX3 ND3 ND6 ND6 CYTB ND2 ND5 ND5 ND4 ND4 ND4L ND4L ND1 ND1 RNL RNL RNS RNS COX1 stands for the gene cytochrome c oxidase I. Bombyx mori mitochondrial genome (proteins and rRNAs)
Example of rearranged genomes : Mitochondrial Genomes Homo sapiens mitochondrial genome (proteins and rRNAs) COX1 COX2 ATP6 ATP8 COX3 ND3 ND4L ND4 ND4 ND5 ND5 CYTB RNS RNS RNL RNL ND1 ND1 ND2 ND6 ND6 Bombyx mori mitochondrial genome (proteins and rRNAs) COX1 COX2 ATP6 ATP8 COX3 ND3 ND6 ND6 CYTB ND2 ND5 ND5 ND4 ND4 ND4L ND1 ND1 RNL RNL RNS RNS The modified parts
Fruit Fly Mosquito Silkworm Locust Tick Centipede Example of rearranged genomes : Mitochondrial Genomes of 6 Arthropoda Identical ‘runs’ of genes have been grouped.
Example of rearranged genomes : mammal X chromosomes (Art work by Guillaume Bourque, scientific work by Guillaume Bourque, Pavel Pevzner and Glenn Tesler, 2004) Sixteen large synteny blocks are ordered differently in the X chromosomes of the human, mouse and rat. Blocks have similar gene content and order. Note that the estimated number of genes in the X chromosome is 2000.
Example of rearranged genomes : mammal X chromosomes (Art work by Guillaume Bourque, scientific work by Guillaume Bourque, Pavel Pevzner and Glenn Tesler, 2004)
Problem: Given two or more genomes, How do we measure their similarity and/or distance with respect to gene order and gene content? Sub-problem: How do we know that two genes or blocks are the "same" in two different species?
1. General introduction to genome rearrangements Examples of rearranged genomes 2. Measures of distance Rearrangement operations The Hannenhalli-Pevzner distance equation 3. A unifying view of genome rearrangements The Double-Cut-and-Join operation The adjacency graph and the distance equation
Rearrangement operations Rearrangement operations affect gene order and gene content. There are various types: • Inversions • Transpositions • Reverse transpositions • Translocations, fusions and fissions • Duplications and losses • Others... Any set of operations yields a distance between genomes, by counting the minimum number of operations needed to transform one genome into the other.
Rearrangement operations • Inversions
• Inversions Rearrangement operations
Rearrangement operations • Inversions
Example: Mitochondrial Genomes of 6 Arthropoda Fruit Fly Mosquito Silkworm Locust Tick Centipede An inversion.
Rearrangement operations • Transpositions
Rearrangement operations • Transpositions
Rearrangement operations • Transpositions
Example: Mitochondrial Genomes of 6 Arthropoda Fruit Fly Mosquito Silkworm Locust Tick Centipede A transposition
Rearrangement operations • Reverse transpositions
Rearrangement operations • Reverse transpositions
Rearrangement operations • Reverse transpositions
Example: Mitochondrial Genomes of 6 Arthropoda Fruit Fly Mosquito Silkworm Locust Tick Centipede A reverse transposition
Rearrangement operations • Translocations, fusions and fissions
Rearrangement operations • Translocations, fusions and fissions
Rearrangement operations • Translocations, fusions and fissions
Rearrangement operations • Translocations, fusions and fissions
Rearrangement operations • Translocations, fusions and fissions
Rearrangement operations • Translocations, fusions and fissions
From 24 chromosomes To 21 chromosomes [Source: Linda Ashworth, LLNL] DOE Human Genome Program Report
1. General introduction to genome rearrangements Examples of rearranged genomes 2. Measures of distance Rearrangement operations The Hannenhalli-Pevzner distance equation 3. A unifying view of genome rearrangements The Double-Cut-and-Join operation The adjacency graph and the distance equation
The Hannenhalli-Pevzner distance equation In 1995, Hannenhalli and Pevzner found a formula to compute the minimum number of inversions, translocations, fusions or fissions necessary to transform a multichromosomal genome into another. Sketch of the approach: • Cap the chromosomes • Concatenate all the chromosomes • Sort the resulting genome by inversions
1. General introduction to genome rearrangements Examples of rearranged genomes 2. Measures of distance Rearrangement operations The Hannenhalli-Pevzner distance equation 3. A unifying view of genome rearrangements The Double-Cut-and-Join operation The adjacency graph and the distance equation
The Double-Cut-and-Join operation Acts on up to 4 gene extremities: , , , Reminder Yancopoulos et al. 2005
The Double-Cut-and-Join operation Linear chromosomes Translocation Translocation Translocation Translocation Translocation Translocation Reminder
The Double-Cut-and-Join operation Linear and circular chromosomes Inversion Inversion Fusion Fusion Fission Fission Reminder
The Double-Cut-and-Join operation Circular chromosomes Inversion Inversion Fusion Fusion Fission Fission Reminder
1. General introduction to genome rearrangements Examples of rearranged genomes 2. Measures of distance Rearrangement operations The Hannenhalli-Pevzner distance equation 3. A unifying view of genome rearrangements The Double-Cut-and-Join operation The adjacency graph and the distance equation 4. Breakpoint reuse Breakpoint reuse estimates Minimizing breakpoint reuse
The adjacency graph and the distance equation Genome A Genome B 4 1 6 3 5 2 1 2 3 4 5 6 Joint work with Julia Mixtacki and Jens Stoye
The adjacency graph and the distance equation 4 1 6 3 5 2 Genome A Genome B 1 2 3 4 5 6 Joint work with Julia Mixtacki and Jens Stoye
The adjacency graph and the distance equation 4 1 6 3 5 2 Genome A Genome B 1 2 3 4 5 6 Joint work with Julia Mixtacki and Jens Stoye
The adjacency graph and the distance equation 4 1 6 3 5 2 Genome A Genome B 1 2 3 4 5 6 Joint work with Julia Mixtacki and Jens Stoye
The adjacency graph and the distance equation 4 1 6 3 5 2 Genome A Genome B 1 2 3 4 5 6 Joint work with Julia Mixtacki and Jens Stoye
The adjacency graph and the distance equation 4 1 6 3 5 2 Genome A Genome B 1 2 3 4 5 6 Joint work with Julia Mixtacki and Jens Stoye
The adjacency graph and the distance equation 4 1 6 3 5 2 Genome A Genome B 1 2 3 4 5 6 C = number of cycles I = number of odd paths G = number of “genes” D = G - (C + I/2) D = 6 - (1 + 2/2) = 4 Joint work with Julia Mixtacki and Jens Stoye