- Email: [email protected]
Disclosing the subterranean treasury of plants
Update
TRENDS in Biotechnology
Vol.22 No.8 August 2004
| Research Focus
Disclosing the subterranean treasury of plants Tom Beeckman Department of Plant Systems Biology, Flanders Interuniversity Institute for Biotechnology (VIB), Ghent University, Technologiepark 927, B-9052 Ghent, Belgium
Roots are crucial for plant growth and development but, so far, their beneficial qualities have not been used in genetic engineering strategies. To exploit this missed opportunity, a thorough understanding is required of the genetic mechanisms that control gene expression in response to different cues. A global map of gene expression for the Arabidopsis root has recently been published that consists of high-resolution spatial- and temporal-expression profiles. This new dataset will be a valuable starting point for understanding the hidden organ of plants. Although vital for plant growth and development, until now, roots have never been intensively genetically modified. Their subterranean growth habit, adaptability to the complex and fluctuating soil environment, and the lack of suitable experimental approaches have hampered the study of root biology. However, roots could also be the central target for genetic engineering in light of some of their functions. For example, because crop roots guarantee the uptake of nutrients and water, and interact with beneficial and pathogenic organisms, they could be engineered to be better adapted for nutrient uptake in low-quality soils, better hosts for beneficial organisms and resistant against soil-borne pathogens [1]. The modification of root systems requires the availability of the necessary molecular tools, namely functionally characterized tissue-specific genes and promoters. Such genetic elements, especially those of roots, have been detected only occasionally by using differential and subtractive hybridization techniques. However, with the sequencing of the genome of Arabidopsis thaliana now complete and the availability of genome-wide microarrays, it is now possible to monitor the expression of several thousands of genes simultaneously. This will speed up the search for root-specific genes that could be valuable for enhancing crop productivity. However, availability of the molecular tools is not enough. A thorough understanding of how a root develops and works is indispensable to engineer effectively a root system. Instead of trying to understand the function of each element individually, a global insight into how all these elements work together in a growing root should be the (albeit ambitious) objective of root biologists from now on. The benefits of the Arabidopsis root At the end of 2003, the root biology community was blessed with a historic paper that described a genome-wide Corresponding author: Tom Beeckman ([email protected]). Available online 26 June 2004 www.sciencedirect.com
expression analysis of Arabidopsis root development for the first time [2]. The strength of this article lies in three fundamental points. First, gene expression was analyzed by using microarrays that contained probes for . 22 000 Arabidopsis genes. Although reports on genome-wide expression analyses are becoming increasingly common, analyzing global gene expression in roots is still an infrequent event. Second, because the Arabidopsis root was used as sampling material, the data obtained had additional value from a developmental viewpoint. In this species, the accessibility of the root excels by virtue of its regular and simple architecture. Most tissues (e.g. epidermis, cortex, endodermis and pericycle) are organized in concentric cylinders composed of only one cell layer. Furthermore, because of the strictly radial symmetry and the lack of cell movement, the different root cell types are found mostly on cell files, which makes it possible to trace their origin [3]. The formation of new cells starts in the tip of the root and is a fairly continuous process. Once formed, the development of a cell continues through a cell division (or meristematic) zone, which is followed by a zone that is characterized by rapid polar cell expansion (also known as the elongation zone). The cell finally reaches the differentiation zone, at which point, elongation stops and it acquires differentiated characteristics. Thus, the further the cells are from the root tip, the closer they are to their final, differentiated phase. This situation is ideal for the developmental biologist: all the developmental phases are present in a given root at all times during its growth. Because of these qualities of the Arabidopsis root, it is straightforward to design transcript-profiling experiments that record root development by taking RNA from different regions of the root (i.e. different developmental stages). Although it is possible to discern roughly a meristematic, elongation and differentiation zone in each growing root, the processes that take place in each region overlap. At a given distance from the tip, certain cell types might have stopped dividing and started expanding, whereas others might still be dividing. For example, analysis of the expression patterns of cell-cycle genes in the Arabidopsis root has shown that the outer tissue layers, such as epidermis and cortex, leave the cell-division cycle earlier than the central tissue layers, which implies the existance of a cell file-dependent exit from the cell cycle [4]. Therefore, when the root samples used for transcript profiling comprise all cell types, some essential developmental changes in gene expression risk dilution by the ubiquitousness of other cell types that are not involved in a given developmental process. The third fundamental point made by
380
Update
TRENDS in Biotechnology
Birnbaum et al. [2] presents a solution to this problem by using roots of plants that express green fluorescent protein (GFP) in specific cell types: after the cell walls had been digested enzymatically, the GFP-expressing cells were isolated using fluorescence-activated cell sorting, followed by transcript profiling on distinct cell types. Digital in situ hybridizations Birnbaum et al. processed five GFP lines and three developmental stages for microarray analysis [2]. The sampling procedure covered 15 subzones in the root, resulting in a detailed expression map of each gene. In total, 5 717 genes were differentially expressed across the subzones. By merging the expression data that was derived from the 15 subzones via digital reconstruction, expression maps – or ‘digital in situs’ – of the root tip could be made. The combination of all these digital in situ hybridizations provides those working in plant biology with a detailed organ expression map. Such a tool will be helpful for reverse genetics and for tracking down individual, or groups of, genes that play parts in the specification of certain cell types in the root. Nevertheless, without any further research, the dataset obtained by Birnbaum et al. [2] already confers interesting and refreshing ideas concerning root development. For instance, localized expression domains (LEDs) could be defined in the root that represents clusters of genes, the induction and repression of which are coordinated in one or more of the 15 subzones. Hormone-activity centers Through closer examination of the content of LEDs, putative hormone-activity centers could be detected in the root. In brief, aggregation of hormone-related genes in certain regions enabled speculation regarding the existence of signaling centers for auxin, jasmonic acid and gibberellic acid. This is particularly true for auxin because it has long been linked with root formation and is known to influence various processes, such as cell division, cell elongation, cell differentiation [5] and the initiation of lateral roots [6]. Recently, high levels of free auxin have been observed in the distal tip – more precisely in root cap cells – of Arabidopsis roots. This ‘distal auxin maximum’ is essential for the entire cell patterning and polarity of the root meristem [7]. Furthermore, another study on Arabidopsis has reported that auxin in the root apex accumulates as a result of the auxin permease AUX1-mediated polar transport [8]. In this latter study, segments of 1 mm were used and high auxin accumulation was found in the most apical 1 mm. Curiously, Birnbaum et al. [2] did not localize the putative auxin signaling center in the root tip but, rather, in a zone some distance behind the root apex: above the meristem in the basal part of the elongation zone. There are three reasons for the discrepancy between these results. First, the so-called auxin signaling center was defined on the basis of the coordinated expression of only seven of the 49 auxin-related genes expressed in the root. The other auxin-related genes were encountered in the large group of nondifferentially expressed genes or in wider expression domains. Second, one cell type from the www.sciencedirect.com
Vol.22 No.8 August 2004
root tip – the central root cap (or columella cells) – had not been included, although this cell type displayed maximal b-glucuronidase (GUS) activity in previous studies when a synthetic auxin-responsive promoter– GUS construct was used to visualize responses to auxin [7]. Third, this divergence in results indicates that more than one auxin activity center might be present in the root tip. However, most intriguingly, this transcript-profiling dataset has enabled clear demonstration of certain root zones, such as the hormone-activity centers. These zones are not confined to a certain cell type neither do they entirely cover any of the classic zones of meristematic, elongation and differentiation. As an example, Figure 1 shows a comparison of the classic root zonation with the putative auxin activity centers. Concluding remarks These new insights can now be used to detect and analyze regulatory mechanisms present in hormone-activity centers and might help us to understand how roots are formed and how they react to environmental stimuli. Let
Differentiation zone
Elongation zone
Root apical meristem
Root cap
TRENDS in Biotechnology
Figure 1. Auxin activity centers versus classical root zonation. Gene expression studies reveal the presence of previously unknown root zones that show distinct responses to certain plant hormones. These hormone-activity centers do not fall within the borders of the classical zones of the root, namely the root cap, root apical meristem, elongation zone and differentiation zone (indicated by decreasing gray shading). As an example, the putative auxin activity centers are shown (red). The auxin activity center at the root tip has been reported in earlier work [7], whereas the larger activity center behind the root meristem became apparent during the study by Birnbaum et al. [2].
Update
TRENDS in Biotechnology
us hope that there is no curse on this subterranean treasury of plants, but that its discovery will evolve into a better understanding of root growth and will open the way to improve the root systems of crops by using genetic engineering.
Vol.22 No.8 August 2004
4 5 6
References 1 Bucher, M. (2002) Molecular root bioengineering. In Plant Roots, the Hidden Half, 3rd edn, (Waisel, Y. et al., eds), pp. 279– 294, Marcel Dekker 2 Birnbaum, K. et al. (2003) A gene expression map of the Arabidopsis root. Science 302, 1956– 1960 3 Scheres, B. et al. (2002) Root development. In The Arabidopsis Book (Somerville, C.R. and Meyerowitz, E.M., eds), American
7 8
381
Society of Plant Biologists (http://www.bioone.org/bioone/?request ¼ get-toc&issn ¼ 1543-8120) Beeckman, T. et al. (2001) The peri-cell-cycle in Arabidopsis. J. Exp. Bot. 52, 403 – 411 Davies, P.J. ed. (1995) Plant Hormones: Physiology, Biochemistry and Molecular Biology Kluwer Academic Publishers Casimiro, I. et al. (2003) Dissecting Arabidopsis lateral root development. Trends Plant Sci. 8, 165 – 171 Sabatini, S. et al. (1999) An auxin-dependent distal organizer of pattern and polarity in the Arabidopsis root. Cell 99, 463 – 472 Swarup, R. et al. (2001) Localization of the auxin permease AUX1 suggests two functionally distinct hormone transport pathways operate in the Arabidopsis root apex. Genes Dev. 15, 2648– 2653
0167-7799/$ - see front matter q 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.tibtech.2004.04.016
Extracting novel information from gene expression data Zheng Li and Christina Chan Department of Chemical Engineering and Material Science, Michigan State University, East Lansing, MI 48824, USA
Data from high throughput technologies, such as DNA microarrays, necessitated the development of new computational methodologies for analyzing the high dimensional information contained within the gene expression data. Liao’s group suggested the use of network component analysis to predict transcription factor activities by integrating gene expression data from Escherichia coli with known connectivity information between their genes and transcription factors. This introduces an approach for obtaining novel information from gene expression data. Recent advances in high throughput technologies have generated a plethora of biological information, such as gene expression, protein – protein interaction, and metabolic data. These various types of data capture different aspects of the cellular response to environmental factors and contain information about the underlying regulatory network structure. Much effort has been devoted to analyzing these datasets to reconstruct the regulatory features. The majority of the mathematical approaches, such as clustering [1], independent component analysis (ICA) [2], principal component analysis (PCA) [3], Boolean networks [4], and Bayesian networks [5] have been applied to infer biological information from high dimensional microarray data. These methods typically do not incorporate known regulatory information into the structure of the models. Methods such as clustering, ICA and PCA attempt to identify functionally similar groups of genes, whereas Boolean and Bayesian networks try to uncover the reguCorresponding author: Christina Chan ([email protected]). Available online 26 June 2004 www.sciencedirect.com
latory interaction between genes, all without a priori information on the regulatory network structure. However, the completion of genome sequences and the recent development of a method for genome-wide location (binding) analysis provides a means for identifying sets of genes that can be bound by each transcription factor [6]. The genome-wide binding analysis involves micro-array analysis of epitope-tagged transcription factors coupled to chromatin immunoprecipitation (ChIP) [6]. The binding data provides information on the presence of a regulator at a promoter site, suggestive of binding ability but not necessarily function. Coupling the information obtained through location (binding) data with gene expression data provides functional information to facilitate the reconstruction of regulatory signals and networks. Lee et al. have attempted to apply this approach to detect transcriptional interactions in Saccharomyces cerevisiae [7]. In addition, Hartemink et al. [8], using expression data alone, found the results to be inconsistent with location data. Therefore, they combined known location data with expression data in a Bayesian network framework to infer unknown genetic regulatory networks involved in S. cerevisiae pheromone response. Bar-Joseph et al. [9] combined gene expression and binding information for 106 transcription factors of S. cerevisiae and identified groups of co-expressed genes to which a set of transcription factors bind and reconstructed their regulatory networks. They identified both established regulatory interactions as well as unexpected interactions that suggest models of transcriptional regulation for further studies. Using similar data modalities, Liao et al. [10] developed network component analysis (NCA) to reconstruct regulatory
TRENDS in Biotechnology
Vol.22 No.8 August 2004
| Research Focus
Disclosing the subterranean treasury of plants Tom Beeckman Department of Plant Systems Biology, Flanders Interuniversity Institute for Biotechnology (VIB), Ghent University, Technologiepark 927, B-9052 Ghent, Belgium
Roots are crucial for plant growth and development but, so far, their beneficial qualities have not been used in genetic engineering strategies. To exploit this missed opportunity, a thorough understanding is required of the genetic mechanisms that control gene expression in response to different cues. A global map of gene expression for the Arabidopsis root has recently been published that consists of high-resolution spatial- and temporal-expression profiles. This new dataset will be a valuable starting point for understanding the hidden organ of plants. Although vital for plant growth and development, until now, roots have never been intensively genetically modified. Their subterranean growth habit, adaptability to the complex and fluctuating soil environment, and the lack of suitable experimental approaches have hampered the study of root biology. However, roots could also be the central target for genetic engineering in light of some of their functions. For example, because crop roots guarantee the uptake of nutrients and water, and interact with beneficial and pathogenic organisms, they could be engineered to be better adapted for nutrient uptake in low-quality soils, better hosts for beneficial organisms and resistant against soil-borne pathogens [1]. The modification of root systems requires the availability of the necessary molecular tools, namely functionally characterized tissue-specific genes and promoters. Such genetic elements, especially those of roots, have been detected only occasionally by using differential and subtractive hybridization techniques. However, with the sequencing of the genome of Arabidopsis thaliana now complete and the availability of genome-wide microarrays, it is now possible to monitor the expression of several thousands of genes simultaneously. This will speed up the search for root-specific genes that could be valuable for enhancing crop productivity. However, availability of the molecular tools is not enough. A thorough understanding of how a root develops and works is indispensable to engineer effectively a root system. Instead of trying to understand the function of each element individually, a global insight into how all these elements work together in a growing root should be the (albeit ambitious) objective of root biologists from now on. The benefits of the Arabidopsis root At the end of 2003, the root biology community was blessed with a historic paper that described a genome-wide Corresponding author: Tom Beeckman ([email protected]). Available online 26 June 2004 www.sciencedirect.com
expression analysis of Arabidopsis root development for the first time [2]. The strength of this article lies in three fundamental points. First, gene expression was analyzed by using microarrays that contained probes for . 22 000 Arabidopsis genes. Although reports on genome-wide expression analyses are becoming increasingly common, analyzing global gene expression in roots is still an infrequent event. Second, because the Arabidopsis root was used as sampling material, the data obtained had additional value from a developmental viewpoint. In this species, the accessibility of the root excels by virtue of its regular and simple architecture. Most tissues (e.g. epidermis, cortex, endodermis and pericycle) are organized in concentric cylinders composed of only one cell layer. Furthermore, because of the strictly radial symmetry and the lack of cell movement, the different root cell types are found mostly on cell files, which makes it possible to trace their origin [3]. The formation of new cells starts in the tip of the root and is a fairly continuous process. Once formed, the development of a cell continues through a cell division (or meristematic) zone, which is followed by a zone that is characterized by rapid polar cell expansion (also known as the elongation zone). The cell finally reaches the differentiation zone, at which point, elongation stops and it acquires differentiated characteristics. Thus, the further the cells are from the root tip, the closer they are to their final, differentiated phase. This situation is ideal for the developmental biologist: all the developmental phases are present in a given root at all times during its growth. Because of these qualities of the Arabidopsis root, it is straightforward to design transcript-profiling experiments that record root development by taking RNA from different regions of the root (i.e. different developmental stages). Although it is possible to discern roughly a meristematic, elongation and differentiation zone in each growing root, the processes that take place in each region overlap. At a given distance from the tip, certain cell types might have stopped dividing and started expanding, whereas others might still be dividing. For example, analysis of the expression patterns of cell-cycle genes in the Arabidopsis root has shown that the outer tissue layers, such as epidermis and cortex, leave the cell-division cycle earlier than the central tissue layers, which implies the existance of a cell file-dependent exit from the cell cycle [4]. Therefore, when the root samples used for transcript profiling comprise all cell types, some essential developmental changes in gene expression risk dilution by the ubiquitousness of other cell types that are not involved in a given developmental process. The third fundamental point made by
380
Update
TRENDS in Biotechnology
Birnbaum et al. [2] presents a solution to this problem by using roots of plants that express green fluorescent protein (GFP) in specific cell types: after the cell walls had been digested enzymatically, the GFP-expressing cells were isolated using fluorescence-activated cell sorting, followed by transcript profiling on distinct cell types. Digital in situ hybridizations Birnbaum et al. processed five GFP lines and three developmental stages for microarray analysis [2]. The sampling procedure covered 15 subzones in the root, resulting in a detailed expression map of each gene. In total, 5 717 genes were differentially expressed across the subzones. By merging the expression data that was derived from the 15 subzones via digital reconstruction, expression maps – or ‘digital in situs’ – of the root tip could be made. The combination of all these digital in situ hybridizations provides those working in plant biology with a detailed organ expression map. Such a tool will be helpful for reverse genetics and for tracking down individual, or groups of, genes that play parts in the specification of certain cell types in the root. Nevertheless, without any further research, the dataset obtained by Birnbaum et al. [2] already confers interesting and refreshing ideas concerning root development. For instance, localized expression domains (LEDs) could be defined in the root that represents clusters of genes, the induction and repression of which are coordinated in one or more of the 15 subzones. Hormone-activity centers Through closer examination of the content of LEDs, putative hormone-activity centers could be detected in the root. In brief, aggregation of hormone-related genes in certain regions enabled speculation regarding the existence of signaling centers for auxin, jasmonic acid and gibberellic acid. This is particularly true for auxin because it has long been linked with root formation and is known to influence various processes, such as cell division, cell elongation, cell differentiation [5] and the initiation of lateral roots [6]. Recently, high levels of free auxin have been observed in the distal tip – more precisely in root cap cells – of Arabidopsis roots. This ‘distal auxin maximum’ is essential for the entire cell patterning and polarity of the root meristem [7]. Furthermore, another study on Arabidopsis has reported that auxin in the root apex accumulates as a result of the auxin permease AUX1-mediated polar transport [8]. In this latter study, segments of 1 mm were used and high auxin accumulation was found in the most apical 1 mm. Curiously, Birnbaum et al. [2] did not localize the putative auxin signaling center in the root tip but, rather, in a zone some distance behind the root apex: above the meristem in the basal part of the elongation zone. There are three reasons for the discrepancy between these results. First, the so-called auxin signaling center was defined on the basis of the coordinated expression of only seven of the 49 auxin-related genes expressed in the root. The other auxin-related genes were encountered in the large group of nondifferentially expressed genes or in wider expression domains. Second, one cell type from the www.sciencedirect.com
Vol.22 No.8 August 2004
root tip – the central root cap (or columella cells) – had not been included, although this cell type displayed maximal b-glucuronidase (GUS) activity in previous studies when a synthetic auxin-responsive promoter– GUS construct was used to visualize responses to auxin [7]. Third, this divergence in results indicates that more than one auxin activity center might be present in the root tip. However, most intriguingly, this transcript-profiling dataset has enabled clear demonstration of certain root zones, such as the hormone-activity centers. These zones are not confined to a certain cell type neither do they entirely cover any of the classic zones of meristematic, elongation and differentiation. As an example, Figure 1 shows a comparison of the classic root zonation with the putative auxin activity centers. Concluding remarks These new insights can now be used to detect and analyze regulatory mechanisms present in hormone-activity centers and might help us to understand how roots are formed and how they react to environmental stimuli. Let
Differentiation zone
Elongation zone
Root apical meristem
Root cap
TRENDS in Biotechnology
Figure 1. Auxin activity centers versus classical root zonation. Gene expression studies reveal the presence of previously unknown root zones that show distinct responses to certain plant hormones. These hormone-activity centers do not fall within the borders of the classical zones of the root, namely the root cap, root apical meristem, elongation zone and differentiation zone (indicated by decreasing gray shading). As an example, the putative auxin activity centers are shown (red). The auxin activity center at the root tip has been reported in earlier work [7], whereas the larger activity center behind the root meristem became apparent during the study by Birnbaum et al. [2].
Update
TRENDS in Biotechnology
us hope that there is no curse on this subterranean treasury of plants, but that its discovery will evolve into a better understanding of root growth and will open the way to improve the root systems of crops by using genetic engineering.
Vol.22 No.8 August 2004
4 5 6
References 1 Bucher, M. (2002) Molecular root bioengineering. In Plant Roots, the Hidden Half, 3rd edn, (Waisel, Y. et al., eds), pp. 279– 294, Marcel Dekker 2 Birnbaum, K. et al. (2003) A gene expression map of the Arabidopsis root. Science 302, 1956– 1960 3 Scheres, B. et al. (2002) Root development. In The Arabidopsis Book (Somerville, C.R. and Meyerowitz, E.M., eds), American
7 8
381
Society of Plant Biologists (http://www.bioone.org/bioone/?request ¼ get-toc&issn ¼ 1543-8120) Beeckman, T. et al. (2001) The peri-cell-cycle in Arabidopsis. J. Exp. Bot. 52, 403 – 411 Davies, P.J. ed. (1995) Plant Hormones: Physiology, Biochemistry and Molecular Biology Kluwer Academic Publishers Casimiro, I. et al. (2003) Dissecting Arabidopsis lateral root development. Trends Plant Sci. 8, 165 – 171 Sabatini, S. et al. (1999) An auxin-dependent distal organizer of pattern and polarity in the Arabidopsis root. Cell 99, 463 – 472 Swarup, R. et al. (2001) Localization of the auxin permease AUX1 suggests two functionally distinct hormone transport pathways operate in the Arabidopsis root apex. Genes Dev. 15, 2648– 2653
0167-7799/$ - see front matter q 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.tibtech.2004.04.016
Extracting novel information from gene expression data Zheng Li and Christina Chan Department of Chemical Engineering and Material Science, Michigan State University, East Lansing, MI 48824, USA
Data from high throughput technologies, such as DNA microarrays, necessitated the development of new computational methodologies for analyzing the high dimensional information contained within the gene expression data. Liao’s group suggested the use of network component analysis to predict transcription factor activities by integrating gene expression data from Escherichia coli with known connectivity information between their genes and transcription factors. This introduces an approach for obtaining novel information from gene expression data. Recent advances in high throughput technologies have generated a plethora of biological information, such as gene expression, protein – protein interaction, and metabolic data. These various types of data capture different aspects of the cellular response to environmental factors and contain information about the underlying regulatory network structure. Much effort has been devoted to analyzing these datasets to reconstruct the regulatory features. The majority of the mathematical approaches, such as clustering [1], independent component analysis (ICA) [2], principal component analysis (PCA) [3], Boolean networks [4], and Bayesian networks [5] have been applied to infer biological information from high dimensional microarray data. These methods typically do not incorporate known regulatory information into the structure of the models. Methods such as clustering, ICA and PCA attempt to identify functionally similar groups of genes, whereas Boolean and Bayesian networks try to uncover the reguCorresponding author: Christina Chan ([email protected]). Available online 26 June 2004 www.sciencedirect.com
latory interaction between genes, all without a priori information on the regulatory network structure. However, the completion of genome sequences and the recent development of a method for genome-wide location (binding) analysis provides a means for identifying sets of genes that can be bound by each transcription factor [6]. The genome-wide binding analysis involves micro-array analysis of epitope-tagged transcription factors coupled to chromatin immunoprecipitation (ChIP) [6]. The binding data provides information on the presence of a regulator at a promoter site, suggestive of binding ability but not necessarily function. Coupling the information obtained through location (binding) data with gene expression data provides functional information to facilitate the reconstruction of regulatory signals and networks. Lee et al. have attempted to apply this approach to detect transcriptional interactions in Saccharomyces cerevisiae [7]. In addition, Hartemink et al. [8], using expression data alone, found the results to be inconsistent with location data. Therefore, they combined known location data with expression data in a Bayesian network framework to infer unknown genetic regulatory networks involved in S. cerevisiae pheromone response. Bar-Joseph et al. [9] combined gene expression and binding information for 106 transcription factors of S. cerevisiae and identified groups of co-expressed genes to which a set of transcription factors bind and reconstructed their regulatory networks. They identified both established regulatory interactions as well as unexpected interactions that suggest models of transcriptional regulation for further studies. Using similar data modalities, Liao et al. [10] developed network component analysis (NCA) to reconstruct regulatory