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Introduction to Regulatory Genomics

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Title: Introduction to Regulatory Genomics


1
Introduction to Regulatory Genomics
  • CS195-L 4/22/08

2
Overview
  • DNA gt RNA gt Protein
  • Exons/Introns
  • Alternative Splicing
  • Transcription
  • Promoter, Transcription Factorsgt enhance binding
    to RNA Polymerase IIgt allows for initiation of
    transcription.

3
Transcription in eukaryotic organisms
  • Cis-regulatory sequences
  • Short (usually 5-10nt) DNA sequences associated
    with each gene
  • Degenerate similar sequences confer equivalent
    binding site

4
Transcription in Eukaryotic Organisms
  • Variable positions relative to gene proximal or
    distal
  • Sequences often cluster together forming
    "cis-regulatory modules
  • Modules act independently to direct transcription
    of gene

5
Transcription Factors
  • DNA-binding proteins that bind cis-regulatory
    sequences and can enhance or repress
    transcription
  • Bind cooperatively to adjacent sites
  • TFTF interactions are relatively weak and
    nonspecificsmall changes (point mutations) can
    have large effects.
  • Combinatorial control of transcription

6
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7
The framework
  • Animal body plans and their structure/function
    are the result of development processes in time
    and space
  • Development is mediated by the regulation of
    thousands of genes in time and space.

8
The framework
  • This regulation is largely done by the
    interaction of DNA-binding proteins called
    transcription factors with other TFs and gene
    promoters.
  • Often, binding sites upstream of the gene
    promoter as also involved in these regulatory
    processes.

9
The framework
  • The DNA sequence of these binding sites can
    change over evolutionary time due to mutations.
  • Alterations in the animal body plan are caused by
    changes in the organization of these regulatory
    sequences.

10
Regulatory Information and the Genome
  • The genome contains the information for all cell
    types in the body.
  • In order for an organism to develop, different
    sets of genes need to be expressed or repressed
    at the right place and time.
  • If this does not occur properly, the effects are
    usually lethal.

11
Regulatory Information and the Genome
  • Often, what is regulated in development are the
    expression of transcription factors.
  • These factors then influence the expression of
    other TFs as well as intercellular signals.

12
General Principles of Organization of Regulation
in Development
  • 1) Signalling affects regulatory gene expression
    Cells often send chemical signals to other cells
    which help to pattern gene expression in space.
  • This means that gene regulatory elements often
    contain sequence that is responsive to
    intracellular signal transduction pathways.

13
General Principles of Organization of Regulation
in Development
  • Intracellular signal transduction pathways are
    the biochemical pathways by which the cell takes
    external signals and changes gene expression.
  • 2) Development is controlled by networks of genes
    (often coding for TFs) that regulate other genes.

14
General Principles of Organization of Regulation
in Development
  • Transcription factors often target hundreds of
    genes. Which genes are actually activated (or
    repressed) depends on the combination of TFs
    present at the promoter region of the gene.

15
Gene Regulatory Networks
  • Davidson conceives of these gene regulatory
    networks in the following way each node is a
    gene, which takes multiple inputs.
  • Depending on the specific combination of inputs,
    the gene provides multiple outputs to other genes
    in the network.

16
Regulatory Genes perform multiple roles in
development
  • The number of regulatory genes is limited, and
    all animals use more or less the same number of
    DNA-binding motifs used by different
    transcription factors.
  • Transcription factors are often required for
    different processes at different times in
    development, and they are often used for many
    unrelated purposes in the life cycle.

17
C-value paradox
18
C-value paradox
  • Genome size does not scale with complexity of the
    organism
  • Number of protein-coding genes does not scale
    with complexity of the organism
  • Biologists assume this is due to more complex
    ways of regulating genes.
  • Alternative splicing also different domains to be
    swapping in and out of proteins.

19
Overview of Regulatory Architecture
  • The short size and degeneracy of regulatory DNA
    motifs means that they will occur at random in
    enormous number.
  • Functional distribution of these motifs is highly
    non-random.
  • Functional regulatory elements that have been
    isolated consist of relatively dense clusters of
    distinct sites recognized by diverse DNA binding
    proteins.

20
Overview of Regulatory Architecture
  • Specific clusters of sites specify regulatory
    activity.
  • Cis-regulatory modules produce unique regulatory
    outputs in time and space in the organism.
  • In other words, these functional groupings are
    associated with certain cells at certain times in
    development.

21
Overview of Regulatory Architecture
  • Davidson defines enhancers as cis-regulatory
    modules located many kB distant from the basal
    transcriptional apparatus
  • AKA the BTA the promoter, the transcriptional
    start site, etc.
  • Enhancers communicate with the BTA by DNA
    looping.

22
Overview of Regulatory Architecture
  • Others might function as silencers by preventing
    proteins from binding to each other or to the
    BTA.
  • Only by experimentally verifying the function of
    target sites within a cis-regulatory element do
    we understand what the genomic regulatory
    sequence means.

23
Gene Regulatory Networks
  • At the periphery of developmental gene networks
    are the sets of protein-coding differentiation
    genes that define particular cell types.
  • These genes do not have outputs affecting other
    developmental genes.
  • Developmental gene networks progressively specify
    exclusionary fates for cell types.

24
Cell types and the Genome
  • All the specificity for each cell in the organism
    is ultimately contained in the genome.
  • Spatial expressionEve2 as example
  • One of the most important regulatory objectives
    in development is the control of spatial gene
    expression.

25
Cell types and the Genome
  • Cis-regulatory modules are sufficient to drive
    spatial expression, given the presence of the
    appropriate TF input.
  • Ectopically incorporated cis-regulatory modules
    are sufficient to generate correct patterns of
    spatial gene expression

26
Regulation
  • Methylation of DNA-inhibits transcription
  • Methylation (transcriptional repression) and
    acetylation (transcriptional activation) of
    nucleosomal histones
  • Polycomb proteins remodel chromatin so TFs cant
    bind to promoters
  • microRNAs repress expression via
    post-transcriptional binding.

27
Cis-regulatory modules
  • CRMs non random clusters of certain target sites
    that usually span a few hundred bases.
  • Modules dictate where, when, and how genes are
    expressed in development
  • CRMs can be repressive or activating
  • Output can be considered the combinatorial
    product of multiple operations.

28
Cis-regulatory modules
  • CRMs present their information as inputs.
  • The DNA binding proteins must bind and these
    outputs must be effectively communicated
    elsewhere to incorporate changes, such as the
    basal transcription apparatus or molecules
    associated with it.

29
Computational Identification
  • CRMs tend to be highly conserved functional
    significance inferred from less than expected DNA
    divergence.
  • Putative binding sites can be detected upon
    examination of highly conserved sites.

30
More on CRMs
  • Davidson calls the active TFs that drive
    different regulatory states by appearing and
    activating genes at different times and place
    drivers.
  • These drivers do not contain the whole story.
  • There are many more tightly and specifically
    bound sites than just the subset occupied by
    drivers.

31
CRM example cyIIIa
  • Network of conditional logic interactions
    programmed into the DNA

32
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33
The combinatorial cis-regulatory logic code
  • Genomic regulatory code how do different
    combinations of binding sites regulate genes?
  • Sorin is working to solve this problem in
    conjunction with Eric Davidson and Ryan Tarpine.

34
Steps to doing this computationally
  • Identify target sites (and the factors that bind
    them)
  • Interpret the functions mediated by these sites
    and factors
  • Find rules for combining these functions to infer
    overall cis-regulatory output.

35
Steps to doing this computationally
  • Need a sufficiently useful, discriminatory and
    general target site database.
  • A given TF can activate or repress, depending on
    combinations of protein partners.
  • Want to find functional combinations of target
    sites/proteins.

36
Logic Functions
  • Certain sites within Modules can be activated in
    a cooperative fashion and associate with other
    modules
  • Can develop logic functions for the proper
    expression of a gene.
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