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author:("Yin, yanbian")
1.  Computational analyses of transcriptomic data reveal the dynamic organization of the Escherichia coli chromosome under different conditions 
Nucleic Acids Research  2013;41(11):5594-5603.
The circular chromosome of Escherichia coli has been suggested to fold into a collection of sequentially consecutive domains, genes in each of which tend to be co-expressed. It has also been suggested that such domains, forming a partition of the genome, are dynamic with respect to the physiological conditions. However, little is known about which DNA segments of the E. coli genome form these domains and what determines the boundaries of these domain segments. We present a computational model here to partition the circular genome into consecutive segments, theoretically suggestive of the physically folded supercoiled domains, along with a method for predicting such domains under specified conditions. Our model is based on a hypothesis that the genome of E. coli is partitioned into a set of folding domains so that the total number of unfoldings of these domains in the folded chromosome is minimized, where a domain is unfolded when a biological pathway, consisting of genes encoded in this DNA segment, is being activated transcriptionally. Based on this hypothesis, we have predicted seven distinct sets of such domains along the E. coli genome for seven physiological conditions, namely exponential growth, stationary growth, anaerobiosis, heat shock, oxidative stress, nitrogen limitation and SOS responses. These predicted folding domains are highly stable statistically and are generally consistent with the experimental data of DNA binding sites of the nucleoid-associated proteins that assist the folding of these domains, as well as genome-scale protein occupancy profiles, hence supporting our proposed model. Our study established for the first time a strong link between a folded E. coli chromosomal structure and the encoded biological pathways and their activation frequencies.
PMCID: PMC3675479  PMID: 23599001
2.  Caldicellulosiruptor Core and Pangenomes Reveal Determinants for Noncellulosomal Thermophilic Deconstruction of Plant Biomass 
Journal of Bacteriology  2012;194(15):4015-4028.
Extremely thermophilic bacteria of the genus Caldicellulosiruptor utilize carbohydrate components of plant cell walls, including cellulose and hemicellulose, facilitated by a diverse set of glycoside hydrolases (GHs). From a biofuel perspective, this capability is crucial for deconstruction of plant biomass into fermentable sugars. While all species from the genus grow on xylan and acid-pretreated switchgrass, growth on crystalline cellulose is variable. The basis for this variability was examined using microbiological, genomic, and proteomic analyses of eight globally diverse Caldicellulosiruptor species. The open Caldicellulosiruptor pangenome (4,009 open reading frames [ORFs]) encodes 106 GHs, representing 43 GH families, but only 26 GHs from 17 families are included in the core (noncellulosic) genome (1,543 ORFs). Differentiating the strongly cellulolytic Caldicellulosiruptor species from the others is a specific genomic locus that encodes multidomain cellulases from GH families 9 and 48, which are associated with cellulose-binding modules. This locus also encodes a novel adhesin associated with type IV pili, which was identified in the exoproteome bound to crystalline cellulose. Taking into account the core genomes, pangenomes, and individual genomes, the ancestral Caldicellulosiruptor was likely cellulolytic and evolved, in some cases, into species that lost the ability to degrade crystalline cellulose while maintaining the capacity to hydrolyze amorphous cellulose and hemicellulose.
PMCID: PMC3416521  PMID: 22636774
3.  Genome-scale identification of cell-wall related genes in Arabidopsis based on co-expression network analysis 
BMC Plant Biology  2012;12:138.
Identification of the novel genes relevant to plant cell-wall (PCW) synthesis represents a highly important and challenging problem. Although substantial efforts have been invested into studying this problem, the vast majority of the PCW related genes remain unknown.
Here we present a computational study focused on identification of the novel PCW genes in Arabidopsis based on the co-expression analyses of transcriptomic data collected under 351 conditions, using a bi-clustering technique. Our analysis identified 217 highly co-expressed gene clusters (modules) under some experimental conditions, each containing at least one gene annotated as PCW related according to the Purdue Cell Wall Gene Families database. These co-expression modules cover 349 known/annotated PCW genes and 2,438 new candidates. For each candidate gene, we annotated the specific PCW synthesis stages in which it is involved and predicted the detailed function. In addition, for the co-expressed genes in each module, we predicted and analyzed their cis regulatory motifs in the promoters using our motif discovery pipeline, providing strong evidence that the genes in each co-expression module are transcriptionally co-regulated. From the all co-expression modules, we infer that 108 modules are related to four major PCW synthesis components, using three complementary methods.
We believe our approach and data presented here will be useful for further identification and characterization of PCW genes. All the predicted PCW genes, co-expression modules, motifs and their annotations are available at a web-based database:
PMCID: PMC3463447  PMID: 22877077
Plant cell wall; Arabidopsis; Co-expression network analysis; Bi-clustering; Cis regulatory motifs
4.  Integration of sequence-similarity and functional association information can overcome intrinsic problems in orthology mapping across bacterial genomes 
Nucleic Acids Research  2011;39(22):e150.
Existing methods for orthologous gene mapping suffer from two general problems: (i) they are computationally too slow and their results are difficult to interpret for automated large-scale applications when based on phylogenetic analyses; or (ii) they are too prone to making mistakes in dealing with complex situations involving horizontal gene transfers and gene fusion due to the lack of a sound basis when based on sequence similarity information. We present a novel algorithm, Global Optimization Strategy (GOST), for orthologous gene mapping through combining sequence similarity and contextual (working partners) information, using a combinatorial optimization framework. Genome-scale applications of GOST show substantial improvements over the predictions by three popular sequence similarity-based orthology mapping programs. Our analysis indicates that our algorithm overcomes the intrinsic issues faced by sequence similarity-based methods, when orthology mapping involves gene fusions and horizontal gene transfers. Our program runs as efficiently as the most efficient sequence similarity-based algorithm in the public domain. GOST is freely downloadable at
PMCID: PMC3239196  PMID: 21965536

Results 1-4 (4)