3d model of the folded yeast genome
DESCRIPTION
3D model of the folded yeast genome. Zhijun Duan , Mirela Andronescu , Kevin Schutz , Sean McIlwain , Yoo Jung Kim, Choli Lee, Jay Shendure , Stanley Fields, C. Anthony Blau & William S. Noble, “A three-dimensional model of the yeast genome,” Nature 2010, 465:363-67 - PowerPoint PPT PresentationTRANSCRIPT
9 March 2011
3D model of the folded yeast genomeZhijun Duan, Mirela Andronescu, Kevin Schutz, Sean McIlwain, Yoo Jung Kim, Choli Lee, Jay Shendure, Stanley Fields, C. Anthony Blau & William S. Noble, “A three-dimensional model of the yeast genome,” Nature 2010, 465:363-67
Presented by Hershel Safer in Ron Shamir’s group meeting on 9.3.2011.
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OutlineContext
Experimental technique & validation
Tools & calculations
Findings
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Chromosome conformation enables interactionsActivity in the cell’s nucleus depends on physical interactions: DNA functional elements can only interact if they are physically close in 3D space.
In this work, physical interactions between chromosomal locations are identified and used to infer 3D conformations of chromosomes:
• Folding of individual chromosomes: interactions between loci on the same chromosome (intra-chromosomal)
• Relative locations of chromosomes: interactions between loci on different chromosomes (inter-chromosomal)
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OutlineContext
Experimental technique & validation
Tools & calculations
Findings
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Chromosome conformation capture on a chip (4C)Chromosome conformation capture (3C) is an experimental technique for identifying DNA-DNA interactions. Loci of interest are selected in advance.
3C on a chip (4C) does 3C on a genome-wide basis, so results are not biased by choice of specific loci.
In this work, the measurement done by chip in the 4C protocol is replaced by deep sequencing.
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Experimental technique
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Sequence dataUsed Illumina paired-end sequencing with 20 bp reads.
Read pairs were mapped to S. cerevisiae genome using MAQ.
• Kept reads with MAQ score ≥20
• Read locations had to be consistent w.r.t. position of corresponding RE1 (HindIII or EcoRI) recognition site
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Validation: Controls1. Constructed four libraries using all combinations of RE1
(HindIII, EcoRI) and RE2 (MseI, MspI)
2. Constructed two independent sets of experimental libraries differing by DNA concentration
3. Constructed five control libraries, one with non-cross linked cells, and four with yeast genomic DNA and the different combinations of restriction enzymes
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Validation: Interaction vs. genomic distanceInteraction frequency decreases with genomic distance in experimental but not control libraries. Graph considers only long-distance interactions, >20kb.
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Validation: Biases related to restriction sites Looked for bias from different efficiencies of restriction enzyme digestion or ligation.
Examined fraction of instances that each HindIII site had an intra-chromosomal interaction.
Strong correlation between independent experimental libraries, not with control.
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Validation: Reproducibility given DNA concentrationDNA concentration during proximity-based ligation has large effect on signal-to-noise ratio.
Interaction patterns are broadly similar for two independent experimental libraries.
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Validation: Consistency between HindIII & EcoRILibraries constructed with different restriction enzymes exhibit similar interactions, especially for intra-chromosomal interactions.
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OutlineContext
Experimental technique & validation
Tools & calculations
Findings
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Circos: Visualize data in a circular layouthttp://mkweb.bcgsc.ca/circos/
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Circos for network visualization
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Converting interaction frequencies to 3D mapsModel each chromosome as a string of beads spaced at 10 kb.
Attempt to place beads so that each pair is at a distance that is inversely proportional to their interaction frequency.
Intra-chromosomal:
• Divide chromosome into 5 kb bins. Find mean interaction frequency between each pair of bins.
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• Estimate 3D distance as a function of interaction frequency based on physical properties of polymers
Inter-chromosomal: Use same distance as an intra-chromosomal interaction with the same frequency
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Optimization to place interacting pairs of lociFormulate problem as
subject to various physical constraints
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OutlineContext
Experimental technique & validation
Tools & calculations
Findings
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Density of self-interactionsDensity of intra-chromosomal interaction does not vary much with chromosome size
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Ratios of self- to non-self interactionsRatio of intra-chromosomal to inter-chromosomal interactions is inversely correlated with chromosome length
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Interaction among pairs of chromosomeCompare ratios of observed vs. expected interactions
Interactions are more prevalent between smaller chromosomes
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Self-interactions between regions of similar size
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Self-interactions within local regions
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Self-interaction between telomeric endsIntra-chromosomal interaction between telomeric ends varied widely
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Chromosome XII Chromosome XII has a very different conformation from all the other chromosomes.
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Inter-chromosomal interactions: CentromeresInter-chromosomal interactions are dominated by interactions between centromeres
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Enrichment of chromosomal features: tRNAHindIII sites adjacent to tRNA genes were significantly enriched for interactions with sites neighboring other tRNA genes
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Enrichment: Early origins of DNA replicationObserved enrichment of sites near early (but not late) origins of DNA replication
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Findings consistent with Rabl configurationThese observations are consistent with the Rabl configuration of yeast chromosomes.
• Chromosomes tethered by centromeres to one pole of nucleus
• Telomeres extend outward toward nuclear membrane
• Small chromosome arms crowded within all 32 arms & so make frequent inter-chromosomal contact
• Distal regions of long arms are in relatively uncrowded regions & so make less contact
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Picture of yeast chromosome arms
From Bystricky et al., “Chromosome looping in yeast,” J Cell Biology (2005), 168(3):375-87
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Chromosome territories & arm flexibilityEnrichment for self-interaction compared to non-self
Enrichment decreased with increased distance from centromere
Yeast chromosome arms more flexible than in mammals
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Interactions between chromosome pairs
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3D model of yeast genome
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Comparing yeast & human genomes
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A few notesLieberman-Aiden work on the human genome was at Mb resolution. This work is at kb resolution.
Map resolution is constrained by cost of deep sequencing.
Methods based on 3C detect chromatin interactions in a collection of cells. Findings should be confirmed in single cells using methods such as FISH.
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References3C method: Dekker et al., “Capturing chromosome conformation,” Science (2002), 295:1306-11
4C method: Simonis et al., “Nuclear organization of active and inactive chromatin domains uncovered by chromosome conformation capture-on-chip (4C),” Nature Genetics 2006, 38(11):1348-54
3D model of human genome: Lieberman-Aiden et al., “Comprehensive mapping of long-range interactions reveals folding principles of the human genome,” Science 2009, 326:289-93
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