genome-wide regulatory complexity in yeast promoters
DESCRIPTION
Genome-wide Regulatory Complexity in Yeast Promoters. Zhu YANG 15 th Mar, 2006. Reference. C. S. Chin, J. H. Chuang, & H. Li. 2005. Genome-wide regulatory complexity in yeast promoters: Separation of functionally conserved and neutral sequence . Genome Research. 15(2):205-13. Outline. - PowerPoint PPT PresentationTRANSCRIPT
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Genome-wide Regulatory Complexity in Yeast Promoters
Zhu YANG15th Mar, 2006
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Reference
• C. S. Chin, J. H. Chuang, & H. Li. 2005. Genome-wide regulatory complexity in yeast promoters: Separation of functionally conserved and neutral sequence. Genome Research. 15(2):205-13.
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Outline
• Purposes
• Methods
• Results
• Discussion
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Purposes
• To separate functionally conserved and neutral sequence.
• To know how much promoter sequence is functional.
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Methods
• Determine the local neutral mutation rates by measuring the degree of sequence conservation across the genome
• Determine what parts of yeast promoters evolve neutrally
• Estimate the total amount of promoter sequence under selection in promoters.
• Find out how much regulation acts on each gene roughly by analyzing the length of sequence in high conservation regions for each promoter.
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Algorithms
• Calculation of substitution rates from fourfold sites
• Mutational uniformity
• Separation of high and low conserved regions with a hidden Markov model
• Genome-wide percentage of promoter sites under selection
• z-score in Gene Ontology analysis
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Neutral mutation rates are uniform genome-wide
• Mutation rates are uncorrelated along the yeast genome
• In contrast, mouse-human conservation rates are significantly correlated along the human genome at separations up to several megabases
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Autocorrelation in conservation rates
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Neutral mutation rates are uniform genome-wide (Cont’d)
• There is a subset of genes was biased toward high conservation by some secondary effect
• There are 92% of the genes mutate neutrally at fourfold degenerate sites. The high conservation values for the remaining 8% of the genes were explainable by codon usage selection
• correlation of the normalized substitution rate with codon adaptation index (CAI) was 0.67.
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Distribution of normalized conservation rates
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Neutral conservation rates in promoters
• Functional elements should be separated from the neutral background, since conservation can be due to shared ancestry.
• Hidden Markov model (HMM)• Break the promoters into high conservation regio
ns (HCR) and low conservation regions (LCR).• the HCRs and LCRs gave a good approximation
to functional and neutral regions.
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Separation of conserved blocks from the background
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Neutral conservation rates in promoters (Cont’d)
• The HCRs, on the other hand, contained an excess of functional elements.
• While the HCRs covered only 34.3% of the promoter regions, they contained 71.6% motifs in the promoters.
• The neutral rates in the LCRs were consistent with the neutral rates obtained from the fourfold site analysis
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Distribution of the conservation rate for promoter sequences
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Genome-wide amount of promoter sequence under selection
• Frequency of Conserved Blocks (FCB) method was more robust than the HMM for inferring the amount of selectively conserved sequence
• Count the numbers of blocks of n consecutive conserved bases in the promoter sequences, which were then compared to neutral expectations.
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Requirements
• The frequency distribution of conserved blocks in neutral sequence is known
• This neutral component can be extracted from the real frequency distribution.
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Distribution of the counts of blocks of n consecutive conserved
bases
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Estimate of the percentage of sites evolving neutrally among various s
pecies
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Gene-specific selection in promoters
• The HCRs provide a rough characterization of the transcriptional regulation in each promoter.
• most genes having 15%–25% of their promoter sequence in HCRs.
• Protein sequence conservation was correlated on a gene-by-gene basis with HCR length
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The Gene Ontology terms
• With the largest HCR length biases were those involved in the energy generation and steroid synthesis pathways, suggesting that these types of genes have unusually complex regulation.
• The genes with the strongest protein sequence conservation were not always those having the longest HCR lengths, Catalysis, Basic Biosynthesis, and Ribosomal Genes, for example.
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Nonsynonymous conservation versus lengths of HCR
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Discussion
• The neutral conservation rate is uniform across yeast genomes. One nonselective possibility is that yeast chromosomes are too short to have heterogeneity in their mutational environment
• A significant fraction of promoter sequence was under purifying selection.
• A typical function block may contain one or two protein-binding sites; an upper bound of 10 tran∼scription-factor-binding sites in a promoter.
• Genes involved in energy generation and steroid synthesis may be subject to complex transcriptional regulation.