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Liu G.,Inner Mongolia University of Science and Technology | Liu G.,Inner Mongolia Key Laboratory of Biomass Energy Conversion | Liu J.,Inner Mongolia University of Science and Technology | Zhang B.,Inner Mongolia University of Science and Technology
Journal of Molecular Evolution | Year: 2012

Palindromic sequences are important DNA motifs related to gene regulation, DNA replication and recombination, and thus, investigating the evolutionary forces shaping the distribution pattern and abundance of palindromes in the genome is substantially important. In this article, we analyzed the abundance of palindromes in the genome, and then explored the possible effects of several genomic factors on the palindrome distribution and abundance in Drosophila melanogaster. Our results show that the palindrome abundance in D. melanogaster deviates from random expectation and the uneven distribution of palindromes across the genome is associated with local GC content, recombination rate, and coding exon density. Our data suggest that base composition is the major determinant of the distribution pattern and abundance of palindromes and the correlation between palindrome density and recombination is a side-product of the effect of compositional bias on the palindrome abundance. © Springer Science+Business Media New York 2012.


Xing Y.-Q.,Inner Mongolia University of Technology | Xing Y.-Q.,Inner Mongolia University of Science and Technology | Liu G.-Q.,Inner Mongolia University of Science and Technology | Zhao X.-J.,Inner Mongolia University of Science and Technology | And 2 more authors.
Chromosome Research | Year: 2013

Nucleosome positioning plays a key role in the regulation of many biological processes. In this study, the statistical difference of information content was investigated in nucleosome and linker DNA regions across eukaryotic organisms. By analyzing the information redundancy, D k, in Saccharomyces cerevisiae, Drosophila melanogaster, and Caenorhabditis elegans genomes, the short-range dominance of nucleotide correlation in nucleosome and linker DNA regions was confirmed. Significant difference of the D k value between the nucleosome and linker DNA regions was also found. The underlying reason for many successful oligonucleotide-based predictions of nucleosome positioning in eukaryotic model organisms may be attributed to the short-range dominance of nucleotide correlation in the nucleosome and linker DNA regions. When applying power spectrum analysis to the nucleosome and linker DNA regions, some obvious differences in sequence periodic signals were observed. The parameter F k was introduced to describe particular base correlation. Furthermore, the support vector machine combining F k was used to classify nucleosome and linker DNA regions in Homo sapiens, Oryzias latipes, C. elegans, Candida albicans, and S. cerevisiae. Independent test demonstrated that a good performance can be achieved by using this algorithm. This result further revealed that base correlation information has an important role in nucleosome positioning. © 2013 Springer Science+Business Media Dordrecht.


Jiang H.-M.,Inner Mongolia University of Science and Technology | Jiang H.-M.,Inner Mongolia Key Laboratory of Biomass Energy Conversion | Si W.-T.,Inner Mongolia University of Science and Technology | Pan J.-G.,Inner Mongolia University of Science and Technology | Pan J.-G.,Inner Mongolia Key Laboratory of Biomass Energy Conversion
Gao Xiao Hua Xue Gong Cheng Xue Bao/Journal of Chemical Engineering of Chinese Universities | Year: 2015

A novel microbial electrolysis cell (MEC) based biosensor for rapid determination of biochemical oxygen demand (BOD) was developed, and its performance was evaluated with glucose-glutamic acid containing artificial wastewater. The results show that when the applied voltage is kept at 0.7 V, the maximum current of the biosensor follows Monod equation under BOD concentration of 10~400 mg×L-1, and the maximum current has linear relationship with BOD when the BOD concentration is in the range of 10~100 mg×L-1. The results also indicate that the measurement time is about 10 min when the BOD concentration is in the range of 10~400 mg×L-1. The relative standard deviation of repeatability was less than ±12.2%, while the relative standard deviation of stability was less than ±6% over a period of 12 days. These results demonstrate that the development of novel biosensors based on MEC for rapid determination of BOD is feasible, and the biosensor has advantages of high sensitivity, wide linear range, short detection time, good repeatability and good stability. © 2015, Editorial Board of "Journal of Chemical Engineering of Chinese Univesities". All right reserved.


Xing Y.-Q.,Inner Mongolia University of Science and Technology | Xing Y.-Q.,Inner Mongolia University of Technology | Liu G.-Q.,Inner Mongolia University of Science and Technology | Zhao X.-J.,Inner Mongolia University of Science and Technology | And 4 more authors.
BioSystems | Year: 2014

Identification of replication origins is crucial for the faithful duplication of genomic DNA. The frequencies of single nucleotides and dinucleotides, GC/AT bias and GC/AT profile in the vicinity of Arabidopsis thaliana replication origins were analyzed in the present work. The guanine content or cytosine content is higher in origin of replication (Ori) than in non-Ori. The SS (S. = G or C) dinucleotides are favoured in Ori whereas WW (W. = A or T) dinucleotides are favoured in non-Ori. GC/AT bias and GC/AT profile in Ori are significantly different from that in non-Ori. Furthermore, by inputting DNA sequence features into support vector machine, we distinguished between the Ori and non-Ori regions in A. thaliana. The total prediction accuracy is about 69.5% as evaluated by the 10-fold cross-validation. This result suggested that apart from DNA sequence, deciphering the selection of replication origin must integrate many other factors including nucleosome positioning, DNA methylation, histone modification, etc. In addition, by comparing predictive performance we found that the predictive accuracy of SVM using sequence features on the context of WS language is significantly better than that of RY language. Furthermore, the same conclusion was also obtained in S. cerevisiae and D. melanogaster. © 2014 Elsevier Ireland Ltd.


Liu G.,Inner Mongolia University of Science and Technology | Liu G.,Inner Mongolia Key Laboratory of Biomass Energy Conversion | Liu J.,Inner Mongolia University of Science and Technology | Cui X.,Inner Mongolia University of Science and Technology | And 3 more authors.
Journal of Theoretical Biology | Year: 2012

Meiotic recombination does not occur randomly across the genome, but instead occurs at relatively high frequencies in some genomic regions (hotspots) and relatively low frequencies in others (coldspots). Hotspots and coldspots would shed light on the mechanism of recombination, but the accurate prediction of hot/cold spots is still an open question. In this study, we presented a model to predict hot/cold spots in yeast using increment of diversity combined with quadratic discriminant analysis (IDQD) based on sequence k-mer frequencies. 5-fold cross validation showed a total prediction accuracy of 80.3%. Compared with other machine-learning algorithms, IDQD approach is as powerful as random forest (RF) and outperforms support vector machine (SVM) in identifying hotspots and coldspots. We also predicted increased recombination rates in the upstream regions of transcription start sites and in the downstream regions of transcription termination sites. Additionally, genome-wide recombination map in yeast obtained by IDQD model is in close agreement with the experimentally generated map, especially for the Peak locations, although some fine-scale differences exist. Our results highlight the sequence dependency of recombination. © 2011 Elsevier Ltd.

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