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Deciphering Cis-Regulatory Element Mediated Combinatorial Regulation in Rice under Blast Infected Condition.

Deb A, Kundu S - PLoS ONE (2015)

Bottom Line: Our analysis includes a wide spectrum of biologically important results.We couple the network approach with experimental results of plant gene regulation and defense mechanisms and find evidences of auto and cross regulation among TF families, cross-talk among multiple hormone signaling pathways, similarities and dissimilarities in regulatory combinatorics between different tissues, etc.It can be further applied to unravel the tissue and/or condition specific combinatorial gene regulation in other eukaryotic systems with the availability of annotated genomic sequences and suitable experimental data.

View Article: PubMed Central - PubMed

Affiliation: Department of Biophysics Molecular Biology and Bioinformatics, University of Calcutta, Kolkata, West Bengal, India.

ABSTRACT
Combinations of cis-regulatory elements (CREs) present at the promoters facilitate the binding of several transcription factors (TFs), thereby altering the consequent gene expressions. Due to the eminent complexity of the regulatory mechanism, the combinatorics of CRE-mediated transcriptional regulation has been elusive. In this work, we have developed a new methodology that quantifies the co-occurrence tendencies of CREs present in a set of promoter sequences; these co-occurrence scores are filtered in three consecutive steps to test their statistical significance; and the significantly co-occurring CRE pairs are presented as networks. These networks of co-occurring CREs are further transformed to derive higher order of regulatory combinatorics. We have further applied this methodology on the differentially up-regulated gene-sets of rice tissues under fungal (Magnaporthe) infected conditions to demonstrate how it helps to understand the CRE-mediated combinatorial gene regulation. Our analysis includes a wide spectrum of biologically important results. The CRE pairs having a strong tendency to co-occur often exhibit very similar joint distribution patterns at the promoters of rice. We couple the network approach with experimental results of plant gene regulation and defense mechanisms and find evidences of auto and cross regulation among TF families, cross-talk among multiple hormone signaling pathways, similarities and dissimilarities in regulatory combinatorics between different tissues, etc. Our analyses have pointed a highly distributed nature of the combinatorial gene regulation facilitating an efficient alteration in response to fungal attack. All together, our proposed methodology could be an important approach in understanding the combinatorial gene regulation. It can be further applied to unravel the tissue and/or condition specific combinatorial gene regulation in other eukaryotic systems with the availability of annotated genomic sequences and suitable experimental data.

No MeSH data available.


Related in: MedlinePlus

COR value distribution pattern.(A) probability density plot of COR values (B) frequency distribution plot of COR values. (C) magnified view of y axis of the frequency plot of COR values. The red line stands for the COR values of the CRE pairs occurring in < 3 promoters and the black line stands for the COR values of the CRE pairs occurring in ≥ 3 promoters.
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pone.0137295.g003: COR value distribution pattern.(A) probability density plot of COR values (B) frequency distribution plot of COR values. (C) magnified view of y axis of the frequency plot of COR values. The red line stands for the COR values of the CRE pairs occurring in < 3 promoters and the black line stands for the COR values of the CRE pairs occurring in ≥ 3 promoters.

Mentions: We calculated COR values for all possible pairs (465C2) of CREs using the rice promoters. A probability distribution plot of the COR values is provided in Fig 3. The upper-bound confidence interval of the data was computed at 10−6 significance level by performing a permutation Z-statistics. In this step, calculation started with the highest COR value (observed set) and permuted the remaining values (background) to check whether the difference met the desired significance level. Next, gradually lower COR values were added with the observed set and the former step was repeated until it reached 10−6 significance level. This enabled us to identify the minimum value of the upper-bound set, which was 1.498. Next, a non-parametric permutation Mann-Whitney U-test (10000 permutation steps) was performed to check whether this upper-bound COR values significantly differ from the rest of the dataset. This U-test showed that data above the COR value 1.498 was significantly higher than rest of the dataset with a very strong statistical significance (p < 10−170). Therefore, a COR value > 1.5 was considered as the stringent cutoff (S1 Text).


Deciphering Cis-Regulatory Element Mediated Combinatorial Regulation in Rice under Blast Infected Condition.

Deb A, Kundu S - PLoS ONE (2015)

COR value distribution pattern.(A) probability density plot of COR values (B) frequency distribution plot of COR values. (C) magnified view of y axis of the frequency plot of COR values. The red line stands for the COR values of the CRE pairs occurring in < 3 promoters and the black line stands for the COR values of the CRE pairs occurring in ≥ 3 promoters.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4556519&req=5

pone.0137295.g003: COR value distribution pattern.(A) probability density plot of COR values (B) frequency distribution plot of COR values. (C) magnified view of y axis of the frequency plot of COR values. The red line stands for the COR values of the CRE pairs occurring in < 3 promoters and the black line stands for the COR values of the CRE pairs occurring in ≥ 3 promoters.
Mentions: We calculated COR values for all possible pairs (465C2) of CREs using the rice promoters. A probability distribution plot of the COR values is provided in Fig 3. The upper-bound confidence interval of the data was computed at 10−6 significance level by performing a permutation Z-statistics. In this step, calculation started with the highest COR value (observed set) and permuted the remaining values (background) to check whether the difference met the desired significance level. Next, gradually lower COR values were added with the observed set and the former step was repeated until it reached 10−6 significance level. This enabled us to identify the minimum value of the upper-bound set, which was 1.498. Next, a non-parametric permutation Mann-Whitney U-test (10000 permutation steps) was performed to check whether this upper-bound COR values significantly differ from the rest of the dataset. This U-test showed that data above the COR value 1.498 was significantly higher than rest of the dataset with a very strong statistical significance (p < 10−170). Therefore, a COR value > 1.5 was considered as the stringent cutoff (S1 Text).

Bottom Line: Our analysis includes a wide spectrum of biologically important results.We couple the network approach with experimental results of plant gene regulation and defense mechanisms and find evidences of auto and cross regulation among TF families, cross-talk among multiple hormone signaling pathways, similarities and dissimilarities in regulatory combinatorics between different tissues, etc.It can be further applied to unravel the tissue and/or condition specific combinatorial gene regulation in other eukaryotic systems with the availability of annotated genomic sequences and suitable experimental data.

View Article: PubMed Central - PubMed

Affiliation: Department of Biophysics Molecular Biology and Bioinformatics, University of Calcutta, Kolkata, West Bengal, India.

ABSTRACT
Combinations of cis-regulatory elements (CREs) present at the promoters facilitate the binding of several transcription factors (TFs), thereby altering the consequent gene expressions. Due to the eminent complexity of the regulatory mechanism, the combinatorics of CRE-mediated transcriptional regulation has been elusive. In this work, we have developed a new methodology that quantifies the co-occurrence tendencies of CREs present in a set of promoter sequences; these co-occurrence scores are filtered in three consecutive steps to test their statistical significance; and the significantly co-occurring CRE pairs are presented as networks. These networks of co-occurring CREs are further transformed to derive higher order of regulatory combinatorics. We have further applied this methodology on the differentially up-regulated gene-sets of rice tissues under fungal (Magnaporthe) infected conditions to demonstrate how it helps to understand the CRE-mediated combinatorial gene regulation. Our analysis includes a wide spectrum of biologically important results. The CRE pairs having a strong tendency to co-occur often exhibit very similar joint distribution patterns at the promoters of rice. We couple the network approach with experimental results of plant gene regulation and defense mechanisms and find evidences of auto and cross regulation among TF families, cross-talk among multiple hormone signaling pathways, similarities and dissimilarities in regulatory combinatorics between different tissues, etc. Our analyses have pointed a highly distributed nature of the combinatorial gene regulation facilitating an efficient alteration in response to fungal attack. All together, our proposed methodology could be an important approach in understanding the combinatorial gene regulation. It can be further applied to unravel the tissue and/or condition specific combinatorial gene regulation in other eukaryotic systems with the availability of annotated genomic sequences and suitable experimental data.

No MeSH data available.


Related in: MedlinePlus