Paper review The long-range interaction landscape of gene promoters.pptx by malj

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									Paper review: The long-range
interaction landscape of gene
          promoters
                  ——Li Yanjian
                   2012/9/19
                          Outline
• Why we study DNA-DNA interaction
• 3C and 5C technology
• Experiment results—Interaction landscape
  1.   Experiment design
  2.   Data validation
  3.   Analysis by cell lines and states
  4.   Important features
• Conclusion
• Q&A
 Why we study DNA-DNA interaction
• How target genes interact with distal
  regulatory elements is still unknown.
• Promoters and distal elements can form
  looping interactions which have been
  implicated in gene regulation.
• Chromosome is not simply linear and has its
  special spatial structure. To learn DNA-DNA
  interactions is the first step to know
  chromosome’s 3D structure in vivo.
   3C and 5C technology
• 3C (Chromosome
  Conformation Capture) is
  the first technology to
  detect DNA-DNA
  interaction invented by
  Job Dekker
   3C and 5C technology
• 3C can only detect one pair of
  interaction at a time by PCR, so
  they improved it and invent 5C
  (Chromosome Conformation
  Capture Carbon Copy)
• The experiment detail is quite
  complicated, so you can simply
  focus on the aim of 5C: to detect
  lots of interactions at a time
        Interaction landscape——
            Experiment design
• Using 5C to detect 44 ENCODE region’s (0.5~1.9Mb,
  30Mb in total) DNA-DNA interaction in 3 cell lines
  (GM12878, K562, HeLa-S3)
• Analysing interactions between 628 TSS regions and
  4535 distal regions
        Interaction landscape——
              Data validation
• Interaction strength:
1. Within region > Between region
2. Within ENCODE region > Merely neighbour in
   genome
3. Different regions from same chromosome >
   Different regions from different chromosome
• Consistent with previous 4C and Hi-C data
       Interaction landscape——
     Analysis by cell lines and states
• Authors defined 7 distinct chromatin states based
  on histone modifications, the presence of DHSs
  and the localization of proteins such as RNA
  polymerase II and CTCF
1. enhancer (E)
2. weak enhancer(WE)
3. TSS
4. predicted promoter flanking regions (PF)
5. insulator element (CTCF)
6. predicted repressed region (R)
7. predicted transcribed region (T).
      Interaction landscape——
    Analysis by cell lines and states
• ACSL6 region in K562 cell
       Interaction landscape——
     Analysis by cell lines and states
• γ-δ globin region in K562 cell
      Interaction landscape——
    Analysis by cell lines and states
• α-globin region in K562 cell
• Important regulatory interaction can be found
          Interaction landscape——
        Analysis by cell lines and states
• α-globin region in
  GM12878 and
  HeLa-S3 cells
• Same interactions
  were not detected
  because these 2
  cells express little
  or no globin
      Interaction landscape——
    Analysis by cell lines and states
• Conclusion: The 5C data shown in this paper
  consists well with previous study, so it’s
  convincing.
• Interactions found by 5C are very likely to be
  functional
• Good Pearson correlation coefficient between
  replicates (>90%)
      Interaction landscape——
    Analysis by cell lines and states
• ~60% of the interactions only occurred in one
  cell line
       Interaction landscape——
     Analysis by cell lines and states
• Authors defined 7 distinct chromatin states based
  on histone modifications, the presence of DHSs
  and the localization of proteins such as RNA
  polymerase II and CTCF
1. enhancer (E)
2. weak enhancer(WE)
3. TSS
4. predicted promoter flanking regions (PF)
5. insulator element (CTCF)
6. predicted repressed region (R)
7. predicted transcribed region (T).
      Interaction landscape——
    Analysis by cell lines and states
• Then they categorized interactions into 4
  broader functional groups:
1. Putative enhancer (‘E’ (E or WE))
2. Putative promoter (‘P’ (TSS or PF))
3. CTCF-bound element (CTCF)
4. Not contain any elements belongs to the
   above 3 groups (‘U’, unclassified)
• This is non-exclusive classification
      Interaction landscape——
    Analysis by cell lines and states
• Regions which have interactions usually enrich
  active functional markers
      Interaction landscape——
    Analysis by cell lines and states
• Many U group regions have
  active marker——
  conservative segmentation
  approach
       Interaction landscape——
     Analysis by cell lines and states
• Conclusion: Unclassified group is relatively
  large and still enriched in active marker such
  as H3K4me1
• The restriction used by the author is very strict,
  so only very significant interactions can be
  taken into consideration (high false negative
  rate)
       Interaction landscape——
     Analysis by cell lines and states
• We found that TSS–E and TSS–P interactions are
  more cell-type specific than TSS–CTCF interactions




                         TSS-E/TSS-P   TSS-CTCF
        Only one: more   ~4:1          ~1:1
        than one
      Interaction landscape——
    Analysis by cell lines and states
• Conclusion: TSS-CTCF interactions are more
  conservative among different cell types
       Interaction landscape——
     Analysis by cell lines and states
• Looping interactions with E elements were
  significantly enriched for those that involved
  expressed TSSs
      Interaction landscape——
    Analysis by cell lines and states
• Conclusion: TSSs interacted with E elements
  are more likely to be expressed
       Interaction landscape——
       upstream or downstream
• Long-range interaction is asymmetric
• A peak at 120kb upstream of TSSs
       Interaction landscape——
       upstream or downstream
• Conclusions: Interactions between TSS and
  distal fragments are asymmetric
         Interaction landscape——
          Affect of elements order
• Only,7% of the looping
  interactions are between an
  element and the nearest TSS
  (for active TSS, it goes up to
  22%)
• 27% of the distal elements
  have an interaction with the
  nearest TSS, and 47% of
  elements have interactions
  with the nearest expressed
  TSS.
        Interaction landscape——
         Affect of elements order
• Conclusion: Interactions don’t always occur
  between nearest TSS and distal fragment
         Interaction landscape——
         CTCF’s insulation function
• We found that 79% of longrange interactions are
  unaffected by the presence of one or more CTCF-
  bound sites
• 58% of looping interactions skip sites co-bound by
  CTCF and cohesin
        Interaction landscape——
        CTCF’s insulation function
• Conclusions: CTCF or CTCF&cohesin binding
  seems to have little affect on interactions’
  forming
• Other factors are needed to complete
  insulation function
        Interaction landscape——
           Multiple interactions
• 50% of TSSs display one or more long-range
  interaction, with some interacting with as many as
  20 distal fragments
• 10% of distal fragments interacted with one or more
  TSS
        Interaction landscape——
           Multiple interactions
• an example of the complex long-range interaction
  networks in the ENr132 region in K562 cell
                    Conclusion
1. Generate a rich data set reflecting specific gene-
   element interactions
2. Interactions between TSS and distal elements are
   correlated with expression
3. Interactions between TSS and distal elements prefer to
   occur in the upstream (~120kb)
4. Interactions are often not blocked by CTCF and cohesin
5. Very few interactions occur between genes and its
   nearest elements
6. Promoters and distal elements are engaged in multiple
   interaction networks
Q&A
Thank you

								
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