Browsing by Author "Li, Wen-Hsiung"

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A simple method using Pyrosequencing (TM) to identify de novo SNPs in pooled DNA samples
(2011-03-01)
Lin, Yeong-Shin
;
Liu, Fu-Guo Robert
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Wang, Tzi-Yuan
;
Pan, Cheng-Tsung
;
Chang, Wei-Ting
A practical way to reduce the cost of surveying single-nucleotide polymorphism (SNP) in a large number of individuals is to measure the allele frequencies in pooled DNA samples. Pyrosequencing (TM) has been frequently used for this application because signals generated by this approach are proportional to the amount of DNA templates. The Pyrosequencing (TM) pyrogram is determined by the dispensing order of dNTPs, which is usually designed based on the known SNPs to avoid asynchronistic extensions of heterozygous sequences. Therefore, utilizing the pyrogram signals to identify de novo SNPs in DNA pools has never been undertook. Here, in this study we developed an algorithm to address this issue. With the sequence and pyrogram of the wild-type allele known in advance, we could use the pyrogram obtained from the pooled DNA sample to predict the sequence of the unknown mutant allele (de novo SNP) and estimate its allele frequency. Both computational simulation and experimental Pyrosequencing(TM) test results suggested that our method performs well. The web interface of our method is available at http://life.nctu.edu.tw/similar to yslin/PSM/.
Codon-usage bias versus gene conversion in the evolution of yeast duplicate genes
(2006-09-26)
Lin, Yeong-Shin
;
Byrnes, Jake K.
;
Hwang, Jenn-Kang
;
Li, Wen-Hsiung
;
生物科技學系
Many Saccharomyces cerevisiae duplicate genes that were derived from an ancient whole-genome duplication (WGD) unexpectedly show a small synonymous divergence (K-S), a higher sequence similarity to each other than to orthologues in Saccharomyces bayanus, or slow evolution compared with the orthologue in Kluyveromyces waltii, a non-WGD species. This decelerated evolution was attributed to gene conversion between duplicates. Using approximate to 300 WGD gene pairs in four species and their orthologues in non-WGD species, we show that codon-usage bias and protein-sequence conservation are two important causes for decelerated evolution of duplicate genes, whereas gene conversion is effective only in the presence of strong codon-usage bias or protein-sequence conservation. Furthermore, we find that change in mutation pattern or in tDNA copy number changed codon-usage bias and increased the K-S distance between K. waltii and S. cerevisiae. Intriguingly, some proteins showed fast evolution before the radiation of WGD species but little or no sequence divergence between orthologues and paralogues thereafter, indicating that functional conservation after the radiation may also be responsible for decelerated evolution in duplicates.
Increasing MicroRNA target prediction confidence by the relative R(2) method
(2009-08-21)
Wang, Hsiuying
;
Li, Wen-Hsiung
;
統計學研究所
;
Institute of Statistics
MicroRNAs (miRNAs) are short noncoding RNAs involved in post-transcriptional gene regulation via binding to mRNAs. Studies show that in a multicellular organism microRNAs (miRNAs) downregulate a large number of target mRNAs. However, predicting the target genes of a miRNA is challenging. Microarray expression pro. ling has been proposed as a complementary method to increase the confidence of miRNA target prediction, but it can become computationally costly or even intractable when many miRNAs and their effects across multiple tissues are to be considered. Here, we propose a statistical method, the relative R(2) method, to find high-confidence targets among the set of potential targets predicted by a computational method such as TargetScanS or by microarray analysis, when expression data of both miRNAs and mRNAs are available for multiple tissues. Applying this method to existing data, we obtain many high-confidence targets in mouse. (C) 2009 Elsevier Ltd. All rights reserved.
Increasing MicroRNA target prediction confidence by the relative R-2 method
(2009-08-21)
Wang, Hsiuying
;
Li, Wen-Hsiung
;
統計學研究所
;
Institute of Statistics
MicroRNAs (miRNAs) are short noncoding RNAs involved in post-transcriptional gene regulation via binding to mRNAs. Studies show that in a multicellular organism microRNAs (miRNAs) downregulate a large number of target mRNAs. However, predicting the target genes of a miRNA is challenging. Microarray expression pro. ling has been proposed as a complementary method to increase the confidence of miRNA target prediction, but it can become computationally costly or even intractable when many miRNAs and their effects across multiple tissues are to be considered. Here, we propose a statistical method, the relative R-2 method, to find high-confidence targets among the set of potential targets predicted by a computational method such as TargetScanS or by microarray analysis, when expression data of both miRNAs and mRNAs are available for multiple tissues. Applying this method to existing data, we obtain many high-confidence targets in mouse. (C) 2009 Elsevier Ltd. All rights reserved.
Method for identifying transcription factor binding sites in yeast
(2006-07-15)
Tsai, Huai-Kuang
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Huang, Grace Tzu-Wei
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Chou, Meng-Yuan
;
Lu, Henry Horng-Shing
;
Li, Wen-Hsiung
Motivation: Identifying transcription factor binding sites (TFBSs) is helpful for understanding the mechanism of transcriptional regulation. The abundance and the diversity of genomic data provide an excellent opportunity for identifying TFBSs. Developing methods to integrate various types of data has become a major trend in this pursuit. Results: We develop a TFBS identification method, TFBSfinder, which utilizes several data sources, including DNA sequences, phylogenetic information, microarray data and ChIP-chip data. Fora TF, TFBSfinder rigorously selects a set of reliable target genes and a set of non-target genes (as a background set) to find overrepresented and conserved motifs in target genes. A new metric for measuring the degree of conservation at a binding site across species and methods for clustering motifs and for inferring position weight matrices are proposed. For synthetic data and yeast cell cycle TFs, TFBSfinder identifies motifs that are highly similar to known consensuses. Moreover, TFBSfinder outperforms well-known methods.
Multidimensional scaling for large genomic data sets
(2008-04-04)
Tzeng, Jengnan
;
Lu, Henry Horng-Shing
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Li, Wen-Hsiung
;
統計學研究所
;
Institute of Statistics
Background: Multi-dimensional scaling (MDS) is aimed to represent high dimensional data in a low dimensional space with preservation of the similarities between data points. This reduction in dimensionality is crucial for analyzing and revealing the genuine structure hidden in the data. For noisy data, dimension reduction can effectively reduce the effect of noise on the embedded structure. For large data set, dimension reduction can effectively reduce information retrieval complexity. Thus, MDS techniques are used in many applications of data mining and gene network research. However, although there have been a number of studies that applied MDS techniques to genomics research, the number of analyzed data points was restricted by the high computational complexity of MDS. In general, a non-metric MDS method is faster than a metric MDS, but it does not preserve the true relationships. The computational complexity of most metric MDS methods is over O(N(2)), so that it is difficult to process a data set of a large number of genes N, such as in the case of whole genome microarray data. Results: We developed a new rapid metric MDS method with a low computational complexity, making metric MDS applicable for large data sets. Computer simulation showed that the new method of split-and-combine MDS (SC-MDS) is fast, accurate and efficient. Our empirical studies using microarray data on the yeast cell cycle showed that the performance of K-means in the reduced dimensional space is similar to or slightly better than that of K-means in the original space, but about three times faster to obtain the clustering results. Our clustering results using SC-MDS are more stable than those in the original space. Hence, the proposed SC-MDS is useful for analyzing whole genome data. Conclusion: Our new method reduces the computational complexity from O(N(3)) to O(N) when the dimension of the feature space is far less than the number of genes N, and it successfully reconstructs the low dimensional representation as does the classical MDS. Its performance depends on the grouping method and the minimal number of the intersection points between groups. Feasible methods for grouping methods are suggested; each group must contain both neighboring and far apart data points. Our method can represent high dimensional large data set in a low dimensional space not only efficiently but also effectively.
Natural selection on cis and trans regulation in yeasts
(2010-06-01)
Emerson, J. J.
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Hsieh, Li-Ching
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Sung, Huang-Mo
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Wang, Tzi-Yuan
;
Huang, Chih-Jen
Gene expression is regulated both by cis elements, which are DNA segments closely linked to the genes they regulate, and by trans factors, which are usually proteins capable of diffusing to unlinked genes. Understanding the patterns and sources of regulatory variation is crucial for understanding phenotypic and genome evolution. Here, we measure genome-wide allele-specific expression by deep sequencing to investigate the patterns of cis and trans expression variation between two strains of Saccharomyces cerevisiae. We propose a statistical modeling framework based on the binomial distribution that simultaneously addresses normalization of read counts derived from different parents and estimating the cis and trans expression variation parameters. We find that expression polymorphism in yeast is common for both cis and trans, though trans variation is more common. Constraint in expression evolution is correlated with other hallmarks of constraint, including gene essentiality, number of protein interaction partners, and constraint in amino acid substitution, indicating that both cis and trans polymorphism are clearly under purifying selection, though trans variation appears to be more sensitive to selective constraint. Comparing interspecific expression divergence between S. cerevisiae and S. paradoxus to our intraspecific variation suggests a significant departure from a neutral model of molecular evolution. A further examination of correlation between polymorphism and divergence within each category suggests that cis divergence is more frequently mediated by positive Darwinian selection than is trans divergence.
Proportion of solvent-exposed amino acids in a protein and rate of protein evolution
(2007-04-01)
Lin, Yeong-Shin
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Hsu, Wei-Lun
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Hwang, Jenn-Kang
;
Li, Wen-Hsiung
;
生物科技學系
Translational selection, including gene expression, protein abundance, and codon usage bias, has been suggested as the single dominant determinant of protein evolutionary rate in yeast. Here, we show that protein structure is also an important determinant. Buried residues, which are responsible for maintaining protein structure or are located on a stable interaction surface between 2 subunits, are usually under stronger evolutionary constraints than solvent-exposed residues. Our partial correlation analysis shows that, when whole proteins are included, the variance of evolutionary rate explained by the proportion of solvent-exposed residues (P-exposed) can reach two-thirds of that explained by translational selection, indicating that P-exposed is the most important determinant of protein evolutionary rate next only to translational selection. Our result suggests that proteins with many residues under selective constraint (e.g., maintaining structure or intermolecular interaction) tend to evolve slowly, supporting the "fitness (functional) density" hypothesis.
Protein complexity, gene duplicability and gene dispensability in the yeast genome
(2007-01-31)
Lin, Yeong-Shin
;
Hwang, Jenn-Kang
;
Li, Wen-Hsiung
;
生物科技學系
;
Department of Biological Science and Technology
Using functional genomic and protein structural data we studied the effects of protein complexity (here defined as the number of subunit types in a protein) on gene dispensability and gene duplicability. We found that in terms of gene duplicability the major distinction in protein complexity is between hetero-complexes, each of which includes at least two different types of subunits (polypeptides), and homo-complexes, which include monomers and complexes that consist of only subunits of one polypeptide type. However, gene dispensability decreases only gradually as the number of subunit types in a protein complex increases. These observations suggest that the dosage balance hypothesis can explain well gene duplicability of complex proteins, but cannot completely explain the difference in dispensabilities between hetero-complex subunits. It is likely that knocking out a gene coding for a hetero-complex subunit would disrupt the function of the whole complex, so that the deletion effect on fitness would increase with protein complexity. We also found that multi-domain polypeptide genes are less dispensable but more duplicable than single-domain polypeptide genes. Duplicate genes derived from the whole genuine duplication event in yeast are more dispensable (except for ribosomal protein genes) than other duplicate genes. Further, we found that subunits of the same protein complex tend to have similar expression levels and similar effects of gene deletion on fitness. Finally, we estimated that in yeast the contribution of duplicate genes to genetic robustness against null mutation is similar to 9%, smaller than previously estimated. In yeast, protein complexity may serve as a better indicator of gene dispensability than do duplicate genes. (c) 2006 Elsevier B.V All rights reserved.