An Efficient Hierarchical Generalized Linear Mixed Model for Mapping QTL of Ordinal Traits in Crop Cultivars

Many important phenotypic traits in plants are ordinal. However, relatively little is known about the methodologies for ordinal trait association studies. In this study, we proposed a hierarchical generalized linear mixed model for mapping quantitative trait locus (QTL) of ordinal traits in crop cultivars. In this model, all the main-effect QTL and QTL-by-environment interaction were treated as random, while population mean, environmental effect and population structure were fixed. In the estimation of parameters, the pseudo data normal approximation of likelihood function and empirical Bayes approach were adopted. A series of Monte Carlo simulation experiments were performed to confirm the reliability of new method. The result showed that new method works well with satisfactory statistical power and precision. The new method was also adopted to dissect the genetic basis of soybean alkaline-salt tolerance in 257 soybean cultivars obtained, by stratified random sampling, from 6 geographic ecotypes in China. As a result, 6 main-effect QTL and 3 QTL-by-environment interactions were identified.     

Community Based Promotion on VCT Acceptance among Rural Migrants in Shanghai,China

Objective

Voluntary counseling and testing (VCT) plays an important integral role in response to the HIV/AIDS epidemic. However, VCT service has not been effectively utilized among rural migrants, a high risk group in China. In this study, we developed a community based intervention to examine if community mobilization with comprehensive VCT is more effective than current HIV preventions with routine VCT service in promoting VCT acceptability among rural migrants in Shanghai, China.

Methods

A comprehensive intervention with community mobilization and comprehensive VCT services including community-based VCT and mobile VCT was implemented during 2007–2009. Three communities in Minhang District of Shanghai were randomly selected and were designed to receive community mobilization and comprehensive VCT, traditional VCT and none intervention, respectively. After 24 months intervention, effects were evaluated by comparing outcome indicators between the baseline (2,690 participants) and follow-up surveys (1,850 participants).

Findings

A substantial increase in VCT acceptance was observed among community mobilization group (94.9% vs. 88.5%, P<0.001), whereas the reverse effect was seen in the traditional VCT group (86.1% vs. 94.6%, P<0.001) and control group (69.0% vs. 91.7%, P<0.001). Rural migrants from community mobilization group were more likely to accept VCT (OR = 2.91, 95% CI 1.69–4.97). Rural migrants from community mobilization group also showed significant increase in HIV/AIDS knowledge, positive attitude towards HIV positive individuals and condom use.

Conclusion

Community mobilization with comprehensive VCT has significant impact on promotion of VCT acceptance and utilization among rural migrants in Shanghai. These findings provide evidence to support community mobilization as a suitable strategy for VCT promotion among rural migrants in Shanghai, China.     

Massive-Scale Gene Co-Expression Network Construction and Robustness Testing Using Random Matrix Theory

The study of gene relationships and their effect on biological function and phenotype is a focal point in systems biology. Gene co-expression networks built using microarray expression profiles are one technique for discovering and interpreting gene relationships. A knowledge-independent thresholding technique, such as Random Matrix Theory (RMT), is useful for identifying meaningful relationships. Highly connected genes in the thresholded network are then grouped into modules that provide insight into their collective functionality. While it has been shown that co-expression networks are biologically relevant, it has not been determined to what extent any given network is functionally robust given perturbations in the input sample set. For such a test, hundreds of networks are needed and hence a tool to rapidly construct these networks. To examine functional robustness of networks with varying input, we enhanced an existing RMT implementation for improved scalability and tested functional robustness of human (Homo sapiens), rice (Oryza sativa) and budding yeast (Saccharomyces cerevisiae). We demonstrate dramatic decrease in network construction time and computational requirements and show that despite some variation in global properties between networks, functional similarity remains high. Moreover, the biological function captured by co-expression networks thresholded by RMT is highly robust.     

Smoking and risk of meningioma: A meta-analysis

Objective: The relationship between smoking and the development of meningioma has been investigated in several epidemiological studies. However, the results of these studies are inconsistent. We conducted a meta-analysis in order to identify any potential association. Methods: PubMed, the Cochrane Library, and EMBASE databases were searched to identify relevant articles that investigated the risk of meningioma following cigarette smoking. Two researchers evaluated study eligibility and extracted the data independently, and disagreements were resolved by discussion. The variables used to estimate the pooled risk of smoking in meningioma development were the multivariate-adjusted risk estimates presented in the literature. Results: Seven case–control and two cohort studies were included in this meta-analysis. The pooled estimated risks associated with ever smoking for meningioma were 1.02 (95% confidence interval (CI): 0.85–1.21) in the case–control studies, 0.93 (95% CI: 0.83–1.04) in the cohort studies and 0.95 (95% CI: 0.87–1.05, P = 0.32) in all studies when the cohort and case–control data were combined. Subgroup analyses suggested that the risk estimates were 1.49 (95% CI: 1.06–2.09, P = 0.02), 0.86 (95% CI: 0.65–1.13), 0.79 (95% CI: 0.50–1.25) and 0.84 (95% CI: 0.69–1.03) for men, women, current and past smoking respectively. Sensitivity analyses restricted to studies with different adjustments for confounders yielded similar results. No evidence of publication bias was observed. Conclusion: Our meta-analysis suggests that there is no association between ever smoking and the risk of meningioma. However, a small but significant risk elevation is present among men smokers.     

QTL Analysis Using SNP Markers Developed by Next-Generation Sequencing for Identification of Candidate Genes Controlling 4-Methylthio-3-Butenyl Glucosinolate Contents in Roots of Radish,Raphanus sativus L

SNP markers for QTL analysis of 4-MTB-GSL contents in radish roots were developed by determining nucleotide sequences of bulked PCR products using a next-generation sequencer. DNA fragments were amplified from two radish lines by multiplex PCR with six primer pairs, and those amplified by 2,880 primer pairs were mixed and sequenced. By assembling sequence data, 1,953 SNPs in 750 DNA fragments, 437 of which have been previously mapped in a linkage map, were identified. A linkage map of nine linkage groups was constructed with 188 markers, and five QTLs were detected in two F₂ populations, three of them accounting for more than 50% of the total phenotypic variance being repeatedly detected. In the identified QTL regions, nine SNP markers were newly produced. By synteny analysis of the QTLs regions with Arabidopsis thaliana and Brassica rapa genome sequences, three candidate genes were selected, i.e., RsMAM3 for production of aliphatic glucosinolates linked to GSL-QTL-4, RsIPMDH1 for leucine biosynthesis showing strong co-expression with glucosinolate biosynthesis genes linked to GSL-QTL-2, and RsBCAT4 for branched-chain amino acid aminotransferase linked to GSL-QTL-1. Nucleotide sequences and expression of these genes suggested their possible function in 4MTB-GSL biosynthesis in radish roots.     

CD106 Identifies a Subpopulation of Mesenchymal Stem Cells with Unique Immunomodulatory Properties

Mesenchymal stem cells (MSCs) reside in almost all of the body tissues, where they undergo self-renewal and multi-lineage differentiation. MSCs derived from different tissues share many similarities but also show some differences in term of biological properties. We aim to search for significant differences among various sources of MSCs and to explore their implications in physiopathology and clinical translation. We compared the phenotype and biological properties among different MSCs isolated from human term placental chorionic villi (CV), umbilical cord (UC), adult bone marrow (BM) and adipose (AD). We found that CD106 (VCAM-1) was expressed highest on the CV-MSCs, moderately on BM-MSCs, lightly on UC-MSCs and absent on AD-MSCs. CV-MSCs also showed unique immune-associated gene expression and immunomodulation. We thus separated CD106⁺cells and CD106⁻cells from CV-MSCs and compared their biological activities. Both two subpopulations were capable of osteogenic and adipogenic differentiation while CD106⁺CV-MSCs were more effective to modulate T helper subsets but possessed decreased colony formation capacity. In addition, CD106⁺CV-MSCs expressed more cytokines than CD106⁻CV-MSCs. These data demonstrate that CD106 identifies a subpopulation of CV-MSCs with unique immunoregulatory activity and reveal a previously unrecognized mechanism underlying immunomodulation of MSCs.     

Clinical Profiles Associated with Influenza Disease in the Ferret Model

Influenza A viruses continue to pose a threat to human health; thus, various vaccines and prophylaxis continue to be developed. Testing of these products requires various animal models including mice, guinea pigs, and ferrets. However, because ferrets are naturally susceptible to infection with human influenza viruses and because the disease state resembles that of human influenza, these animals have been widely used as a model to study influenza virus pathogenesis. In this report, a statistical analysis was performed to evaluate data involving 269 ferrets infected with seasonal influenza, swine influenza, and highly pathogenic avian influenza (HPAI) from 16 different studies over a five year period. The aim of the analyses was to better qualify the ferret model by identifying relationships among important animal model parameters (endpoints) and variables of interest, which include survival, time-to-death, changes in body temperature and weight, and nasal wash samples containing virus, in addition to significant changes from baseline in selected hematology and clinical chemistry parameters. The results demonstrate that a disease clinical profile, consisting of various changes in the biological parameters tested, is associated with various influenza A infections in ferrets. Additionally, the analysis yielded correlates of protection associated with HPAI disease in ferrets. In all, the results from this study further validate the use of the ferret as a model to study influenza A pathology and to evaluate product efficacy.