Peng Xiao

Bio: Peng Xiao is an academic researcher from City University of Hong Kong. The author has contributed to research in topics: Quantitative trait locus & Population. The author has an hindex of 28, co-authored 63 publications receiving 2830 citations. Previous affiliations of Peng Xiao include Creighton University & Hunan Normal University.

How is mRNA expression predictive for protein expression? A correlation study on human circulating monocytes

Abstract: A key assumption in studying mRNA expression is that it is informative in the prediction of protein expression. However, only limited studies have explored the mRNA-protein expression correlation in yeast or human tissues and the results have been relatively inconsistent. We carried out correlation analyses on mRNA-protein expressions in freshly isolated human circulating monocytes from 30 unrelated women. The expressed proteins for 71 genes were quantified and identified by 2-D electrophoresis coupled with mass spectrometry. The corresponding mRNA expressions were quantified by Affymetrix gene chips. Significant correlation (r=0.235, P<0.0001) was observed for the whole dataset including all studied genes and all samples. The correlations varied in different biological categories of gene ontology. For example, the highest correlation was achieved for genes of the extracellular region in terms of cellular component (r=0.643, P<0.0001) and the lowest correlation was obtained for genes of regulation (r=0.099, P=0.213) in terms of biological process. In the genome, half of the samples showed significant positive correlation for the 71 genes and significant correlation was found between the average mRNA and the average protein expression levels in all samples (r=0.296, P<0.01). However, at the study group level, only five studied genes had significant positive correlation across all the samples. Our results showed an overall positive correlation between mRNA and protein expression levels. However, the moderate and varied correlations suggest that mRNA expression might be sometimes useful, but certainly far from perfect, in predicting protein expression levels.

Genetic diversity and population structure of a diverse set of rice germplasm for association mapping

Abstract: Germplasm diversity is the mainstay for crop improvement and genetic dissection of complex traits. Understanding genetic diversity, population structure, and the level and distribution of linkage disequilibrium (LD) in target populations is of great importance and a prerequisite for association mapping. In this study, 100 genome-wide simple sequence repeat (SSR) markers were used to assess genetic diversity, population structure, and LD of 416 rice accessions including landraces, cultivars and breeding lines collected mostly in China. A model-based population structure analysis divided the rice materials into seven subpopulations. 63% of the SSR pairs in these accessions were in LD, which was mostly due to an overall population structure, since the number of locus pairs in LD was reduced sharply within each subpopulation, with the SSR pairs in LD ranging from 5.9 to 22.9%. Among those SSR pairs showing significant LD, the intrachromosomal LD had an average of 25-50 cM in different subpopulations. Analysis of the phenotypic diversity of 25 traits showed that the population structure accounted for an average of 22.4% of phenotypic variation. An example association mapping for starch quality traits using both the candidate gene mapping and genome-wide mapping strategies based on the estimated population structure was conducted. Candidate gene mapping confirmed that the Wx and starch synthase IIa (SSIIa) genes could be identified as strongly associated with apparent amylose content (AAC) and pasting temperature (PT), respectively. More importantly, we revealed that the Wx gene was also strongly associated with PT. In addition to the major genes, we found five and seven SSRs were associated with AAC and PT, respectively, some of which have not been detected in previous linkage mapping studies. The results suggested that the population may be useful for the genome-wide marker-trait association mapping. This new association population has the potential to identify quantitative trait loci (QTL) with small effects, which will aid in dissecting complex traits and in exploiting the rich diversity present in rice germplasm.

Molecular Genetic Studies of Gene Identification for Osteoporosis: A 2004 Update

Abstract: This review summarizes comprehensively the most important and representative molecular genetics studies of gene identification for osteoporosis published up to the end of December 2004. It is intended to constitute a sequential update of our previously published review covering the available data up to the end of 2002. Evidence from candidate gene association studies and genome-wide linkage studies in humans, as well as quantitative trait locus mapping animal models are reviewed separately. Studies of transgenic and knockout mice models relevant to osteoporosis are summarized. An important extension of this update is incorporation of functional genomic studies (including DNA microarrays and proteomics) on osteogenesis and osteoporosis, in light of the rapid advances and the promising prospects of the field. Comments are made on the most notable findings and representative studies for their potential influence and implications on our present understanding of genetics of osteoporosis. The format adopted by this review should be ideal for accommodating future new advances and studies.

An Introduction To The Event Related Potential Technique

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Ten years of pathway analysis: current approaches and outstanding challenges.

Abstract: Pathway analysis has become the first choice for gaining insight into the underlying biology of differentially expressed genes and proteins, as it reduces complexity and has increased explanatory power. We discuss the evolution of knowledge base-driven pathway analysis over its first decade, distinctly divided into three generations. We also discuss the limitations that are specific to each generation, and how they are addressed by successive generations of methods. We identify a number of annotation challenges that must be addressed to enable development of the next generation of pathway analysis methods. Furthermore, we identify a number of methodological challenges that the next generation of methods must tackle to take advantage of the technological advances in genomics and proteomics in order to improve specificity, sensitivity, and relevance of pathway analysis.

Chronic high-fat diet in fathers programs β-cell dysfunction in female rat offspring

Abstract: Childhood obesity and diabetes are closely related to these conditions in either parent, but how the father contributes is unclear. A study in rats shows that normal females mated with obese, glucose-intolerant fathers on a high-fat diet produce female offspring who develop glucose intolerance due to impaired insulin secretion and pancreatic function. This is the first report in any species that a father's diet can initiate progression to diabetes in his offspring. The work highlights a novel role for environmentally induced paternal factors in influencing metabolic disease in offspring and in the growing epidemics of obesity and diabetes. Here it is shown that the consumption of a high-fat diet by male rats has an intergenerational effect: it leads to the dysfunction of pancreatic β-cells in female offspring. Relative to controls, these offspring showed an early onset of impaired insulin secretion and glucose tolerance, which worsened with time. The results add to our understanding of the complex genetic and environmental factors that are leading to the global epidemic of obesity and type 2 diabetes. The global prevalence of obesity is increasing across most ages in both sexes. This is contributing to the early emergence of type 2 diabetes and its related epidemic1,2. Having either parent obese is an independent risk factor for childhood obesity3. Although the detrimental impacts of diet-induced maternal obesity on adiposity and metabolism in offspring are well established4, the extent of any contribution of obese fathers is unclear, particularly the role of non-genetic factors in the causal pathway. Here we show that paternal high-fat-diet (HFD) exposure programs β-cell ‘dysfunction’ in rat F1 female offspring. Chronic HFD consumption in Sprague–Dawley fathers induced increased body weight, adiposity, impaired glucose tolerance and insulin sensitivity. Relative to controls, their female offspring had an early onset of impaired insulin secretion and glucose tolerance that worsened with time, and normal adiposity. Paternal HFD altered the expression of 642 pancreatic islet genes in adult female offspring (P < 0.01); genes belonged to 13 functional clusters, including cation and ATP binding, cytoskeleton and intracellular transport. Broader pathway analysis of 2,492 genes differentially expressed (P < 0.05) demonstrated involvement of calcium-, MAPK- and Wnt-signalling pathways, apoptosis and the cell cycle. Hypomethylation of the Il13ra2 gene, which showed the highest fold difference in expression (1.76-fold increase), was demonstrated. This is the first report in mammals of non-genetic, intergenerational transmission of metabolic sequelae of a HFD from father to offspring.

Global signatures of protein and mRNA expression levels

Abstract: Cellular states are determined by differential expression of the cell’s proteins. The relationship between protein and mRNA expression levels informs about the combined outcomes of translation and protein degradation which are, in addition to transcription and mRNA stability, essential contributors to gene expression regulation. This review summarizes the state of knowledge about large-scale measurements of absolute protein and mRNA expression levels, and the degree of correlation between the two parameters. We summarize the information that can be derived from comparison of protein and mRNA expression levels and discuss how corresponding sequence characteristics suggest modes of regulation.