reconstruction of gene regulatory networks from rna-seq data
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Reconstruction of Gene Regulatory Networks from RNA-Seq Data. Jianlin Jack Cheng Computer Science Department University of Missouri, Columbia ACM-BCB, 2014. Big Data Challenge in Genomic Era. Omics Data. Biological Experiments. DNA/RNA Sequencing. Genomics Transcriptomics Proteomics - PowerPoint PPT PresentationTRANSCRIPT
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Reconstruction of Gene Regulatory Networks from RNA-Seq Data
Jianlin Jack ChengComputer Science Department
University of Missouri, ColumbiaACM-BCB, 2014
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Big Data Challenge in Genomic Era
DNA/RNA Sequencing
Mass Spectrometry
Biological Experiments
Biological Experiments
GenomicsTranscriptomics
ProteomicsMetabolomics
…
GenomicsTranscriptomics
ProteomicsMetabolomics
…
Biological System
AnalysisKnowledge
Omics Data
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Expression Profiles of Genes under Multiple Conditions / Time
PointsCon 1 Con 2 Con 3 Con 4 Con 5 Con 6 Con 7 Con 8 ….
Gene 1 10 30 40 35 20 100 5 60 …
Gene 2
Gene 3
Gene 4
….
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Gene Regulatory Networks (GRN)
Bar-Joseph et al., 2003
GRN of yeast in rich mediumTranscription factor (TF) regulates a gene
TF1TF1 TF2TF2 TF3TF3
Gene regulatory module
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Bayesian Probabilistic Modeling
• Assign genes into co-regulated modules
• Construct regulatory relations of each module
Posterior Likelihood Prior
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Gene Regulatory Network Modeling
Zhu et al., 2013
JoinJoin
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Gene Regulatory Logic of a Gene Module as a Decision Tree
OneGeneModule
gene 1gene 2gene 3….….gene n
Biological Conditions (Treatments) in Columns
Transcriptionfactors and binaryregulatorytree
Low Expression
High Expression
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Regulatory Tree Construction
2
2
( )
2
1
1( )
2
ij k
k
k
xs
ik j S k
p g e
Zhu et al., 2013
g1
g2
.gi
.
.gn
μ1, σ1 μ2, σ2
Gaussian Mixture
• Pick a TF• Divide conditions into
two subsets based expression states
• Calculate probability
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Regulatory Tree Construction
2
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2
1
1( )
2
ij k
k
k
xs
ik j S k
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Zhu et al., 2013
g1
g2
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.gn
Gaussian Mixture
• Repeat at next level
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Regulatory Tree Construction• Pick a TF• Divide conditions
based on TF states• Calculate likelihood • Select TF maximizing
likelihood• Repeat
2
2
( )
2
1
1( )
2
ij k
k
k
xs
ik j S k
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Zhu et al., 2013
g1g2.gi..gn
Gaussian Mixture
Algorithm
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Gene Re-Assignment
μ1
σ1
μ2
σ2
. . . . . . . . .
0.3 0.2 1.5 . . . . . . . .gi
RegulatoryTree ofa Module
2
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( )
2
1
1( )
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ij k
k
k
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ik j S k
p g e
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RNA-Seq Data of Soybean Nodulation
• An important source of protein and oil
• Nitrogen fixation enabled by soybean-rhizobia symbiotic interactions
Nodule
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Gene Regulatory Modules of Differentially Expressed Genes
A TF functioning in nodulation accordingto literature.
NSP, whose homologous protein is a nodulation signaling in rice.
One out of 10 modules
Zhu et al., 2013
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Application to Other Species
• Arabidopsis• Drosophila• Mouse • Human• …
Soybean proteins affect TWIST2 – a novel protein related to Kidney disease?
Helix-loop-helix transcription factor 2
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AcknowledgementsStudents• Deb Bhattacharya• Renzhi Cao• Jie Hou• Jilong Li• Matt Spencer• Trieu Tuan• Mingzhu Zhu
CollaboratorsJim Birchler, Bill Folk, Kevin Fritsche, Michael Greenlief, Zezong Gu, Mark
Hannink, Trupti Joshi, Dennis Lubahn, Valeri Mossine, Alan Parrish, Frank Schmidt, Gary Stacey, Grace Sun, John Walker, Dong Xu
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Binding Site Analysis
• MEME + TomTom to identify two binding sites: BetabetaAlphazinc, finger and Leucine Zipper
• TFs in GRAS family contain proteins binding to the motifs.
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Function Enrichment Validation
Function predicted by MULTICOM-PDCNP-value calculated by hypergeometric distribution.Some functions are related to formation of nodule organ.
Zhu et al., 2013
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I: TF-TF interactions by STRING, L: Literature Function Support
Protein Interaction and Literature Validation
Zhu et al., 2013
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Computational Model Evaluation
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GRN of Human Prostate Cancer Under Botanical Treatments
Lu et al., submitted
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Li et al., submitted.