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Reconstruction of Gene Regulatory Networks from RNA-Seq Data Jianlin Jack Cheng Computer Science Department University of Missouri, Columbia

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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 Presentation

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Page 1: Reconstruction of Gene Regulatory Networks from RNA-Seq Data

Reconstruction of Gene Regulatory Networks from RNA-Seq Data

Jianlin Jack ChengComputer Science Department

University of Missouri, ColumbiaACM-BCB, 2014

Page 2: Reconstruction of Gene Regulatory Networks from RNA-Seq Data

Big Data Challenge in Genomic Era

DNA/RNA Sequencing

Mass Spectrometry

Biological Experiments

Biological Experiments

GenomicsTranscriptomics

ProteomicsMetabolomics

…

GenomicsTranscriptomics

ProteomicsMetabolomics

…

Biological System

AnalysisKnowledge

Omics Data

Page 3: Reconstruction of Gene Regulatory Networks from RNA-Seq Data

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

….

Page 4: Reconstruction of Gene Regulatory Networks from RNA-Seq Data

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

Page 5: Reconstruction of Gene Regulatory Networks from RNA-Seq Data

Bayesian Probabilistic Modeling

• Assign genes into co-regulated modules

• Construct regulatory relations of each module

Posterior Likelihood Prior

Page 6: Reconstruction of Gene Regulatory Networks from RNA-Seq Data

Gene Regulatory Network Modeling

Zhu et al., 2013

JoinJoin

Page 7: Reconstruction of Gene Regulatory Networks from RNA-Seq Data

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

Page 8: Reconstruction of Gene Regulatory Networks from RNA-Seq Data

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

Page 9: Reconstruction of Gene Regulatory Networks from RNA-Seq Data

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

Gaussian Mixture

• Repeat at next level

Page 10: Reconstruction of Gene Regulatory Networks from RNA-Seq Data

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

p g e

Zhu et al., 2013

g1g2.gi..gn

Gaussian Mixture

Algorithm

Page 11: Reconstruction of Gene Regulatory Networks from RNA-Seq Data

Gene Re-Assignment

μ1

σ1

μ2

σ2

. . . . . . . . .

0.3 0.2 1.5 . . . . . . . .gi

RegulatoryTree ofa Module

2

2

( )

2

1

1( )

2

ij k

k

k

xs

ik j S k

p g e

Page 12: Reconstruction of Gene Regulatory Networks from RNA-Seq Data

RNA-Seq Data of Soybean Nodulation

• An important source of protein and oil

• Nitrogen fixation enabled by soybean-rhizobia symbiotic interactions

Nodule

Page 13: Reconstruction of Gene Regulatory Networks from RNA-Seq Data

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

Page 14: Reconstruction of Gene Regulatory Networks from RNA-Seq Data

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

Page 15: Reconstruction of Gene Regulatory Networks from RNA-Seq Data

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

Page 16: Reconstruction of Gene Regulatory Networks from RNA-Seq Data

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.

Page 17: Reconstruction of Gene Regulatory Networks from RNA-Seq Data

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

Page 18: Reconstruction of Gene Regulatory Networks from RNA-Seq Data

I: TF-TF interactions by STRING, L: Literature Function Support

Protein Interaction and Literature Validation

Zhu et al., 2013

Page 19: Reconstruction of Gene Regulatory Networks from RNA-Seq Data

Computational Model Evaluation

Page 20: Reconstruction of Gene Regulatory Networks from RNA-Seq Data

GRN of Human Prostate Cancer Under Botanical Treatments

Lu et al., submitted

Page 21: Reconstruction of Gene Regulatory Networks from RNA-Seq Data

Li et al., submitted.


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