A latent variable partial least squares path modeling approach to regional association and polygenic effect with applications to a human obesity study

Genetic association studies are now routinely used to identify single nucleotide polymorphisms (SNPs) linked with human diseases or traits through single SNP-single trait tests. Here we introduced partial least squares path modeling (PLSPM) for association between single or multiple SNPs and a latent trait that can involve single or multiple correlated measurement(s). Furthermore, the framework naturally provides estimators of polygenic effect by appropriately weighting trait-attributing alleles. We conducted computer simulations to assess the performance via multiple SNPs and human obesity-related traits as measured by body mass index (BMI), waist and hip circumferences. Our results showed that the associate statistics had type I error rates close to nominal level and were powerful for a range of effect and sample sizes. When applied to 12 candidate regions in data (N = 2,417) from the European Prospective Investigation of Cancer (EPIC)-Norfolk study, a region in FTO was found to have stronger association (rs7204609∼rs9939881 at the first intron P = 4.29×10⁻⁷) than single SNP analysis (all with P>10⁻⁴) and a latent quantitative phenotype was obtained using a subset sample of EPIC-Norfolk (N = 12,559). We believe our method is appropriate for assessment of regional association and polygenic effect on a single or multiple traits.     

A theory of natural selection incorporating interaction among individuals. VIII. Use of groups consisting of a sire and several dams

The previous paper, (VII), in this series dealt with a group structure that consisted of a single mating pair. It was demonstrated that selection operating on such groups produced optimum short- and long-term results. The present study extends this group structure to include a single sire and several, (n ? 1), dams. The objective of the present study is to determine whether or not the optimum evolutionary results inherent with groups consisting of a single mating pair extend to groups consisting of multiple matings.It is demonstrated that extending the group from a single mating pair to include multiple matings converts the strictly symmetric into a modified-symmetric selection procedure that combines symmetric and non-symmetric properties. Thus the optimum evolutionary results of groups consisting of a single mating pair do not extend completely to groups consisting of multiple matings.     

Force-Induced Dynamical Properties of Multiple Cytoskeletal Filaments Are Distinct from that of Single Filaments

How cytoskeletal filaments collectively undergo growth and shrinkage is an intriguing question. Collective properties of multiple bio-filaments (actin or microtubules) undergoing hydrolysis have not been studied extensively earlier within simple theoretical frameworks. In this paper, we study the collective dynamical properties of multiple filaments under force, and demonstrate the distinct properties of a multi-filament system in comparison to a single filament. Comparing stochastic simulation results with recent experimental data, we show that multi-filament collective catastrophes are slower than catastrophes of single filaments. Our study also shows further distinctions as follows: (i) force-dependence of the cap-size distribution of multiple filaments are quantitatively different from that of single filaments, (ii) the diffusion constant associated with the system length fluctuations is distinct for multiple filaments, and (iii) switching dynamics of multiple filaments between capped and uncapped states and the fluctuations therein are also distinct. We build a unified picture by establishing interconnections among all these collective phenomena. Additionally, we show that the collapse times during catastrophes can be sharp indicators of collective stall forces exceeding the additive contributions of single filaments.     

Controlling Meiotic Recombinational Repair – Specifying the Roles of ZMMs,Sgs1 and Mus81/Mms4 in Crossover Formation

Crossovers (COs) play a critical role in ensuring proper alignment and segregation of homologous chromosomes during meiosis. How the cell balances recombination between CO vs. noncrossover (NCO) outcomes is not completely understood. Further lacking is what constrains the extent of DNA repair such that multiple events do not arise from a single double-strand break (DSB). Here, by interpreting signatures that result from recombination genome-wide, we find that synaptonemal complex proteins promote crossing over in distinct ways. Our results suggest that Zip3 (RNF212) promotes biased cutting of the double Holliday-junction (dHJ) intermediate whereas surprisingly Msh4 does not. Moreover, detailed examination of conversion tracts in sgs1 and mms4-md mutants reveal distinct aberrant recombination events involving multiple chromatid invasions. In sgs1 mutants, these multiple invasions are generally multichromatid involving 3–4 chromatids; in mms4-md mutants the multiple invasions preferentially resolve into one or two chromatids. Our analysis suggests that Mus81/Mms4 (Eme1), rather than just being a minor resolvase for COs is crucial for both COs and NCOs in preventing chromosome entanglements by removing 3′- flaps to promote second-end capture. Together our results force a reevaluation of how key recombination enzymes collaborate to specify the outcome of meiotic DNA repair.     

RT-qPCR based quantitative analysis of gene expression in single bacterial cells

Recent evidence suggests that cell-to-cell difference at the gene expression level is an order of magnitude greater than previously thought even for isogenic bacterial populations. Such gene expression heterogeneity determines the fate of individual bacterial cells in populations and could also affect the ultimate fate of populations themselves. To quantify the heterogeneity and its biological significance, quantitative methods to measure gene expression in single bacterial cells are needed. In this work, we developed two SYBR Green-based RT-qPCR methods to determine gene expression directly in single bacterial cells. The first method involves a single-tube operation that can analyze one gene from each bacterial cell. The second method is featured by a two-stage protocol that consists of RNA isolation from a single bacterial cell and cDNA synthesis in the first stage, and qPCR in the second stage, which allows determination of expression level of multiple genes simultaneously for single bacterial cells of both gram-positive and negative. We applied the methods to stress-treated (i.e. low pH and high temperature) Escherichia coli populations. The reproducible results demonstrated that the method is sensitive enough not only for measuring cellular responses at the single-cell level, but also for revealing gene expression heterogeneity among the bacterial cells. Furthermore, our results showed that the two-stage method can reproducibly measure multiple highly expressed genes from a single E. coli cell, which exhibits important foundation for future development of a high throughput and lab-on-chips whole-genome RT-qPCR methodology for single bacterial cells.     

A Multi-Trait,Meta-analysis for Detecting Pleiotropic Polymorphisms for Stature,Fatness and Reproduction in Beef Cattle

Polymorphisms that affect complex traits or quantitative trait loci (QTL) often affect multiple traits. We describe two novel methods (1) for finding single nucleotide polymorphisms (SNPs) significantly associated with one or more traits using a multi-trait, meta-analysis, and (2) for distinguishing between a single pleiotropic QTL and multiple linked QTL. The meta-analysis uses the effect of each SNP on each of n traits, estimated in single trait genome wide association studies (GWAS). These effects are expressed as a vector of signed t-values (t) and the error covariance matrix of these t values is approximated by the correlation matrix of t-values among the traits calculated across the SNP (V). Consequently, t''V⁻¹t is approximately distributed as a chi-squared with n degrees of freedom. An attractive feature of the meta-analysis is that it uses estimated effects of SNPs from single trait GWAS, so it can be applied to published data where individual records are not available. We demonstrate that the multi-trait method can be used to increase the power (numbers of SNPs validated in an independent population) of GWAS in a beef cattle data set including 10,191 animals genotyped for 729,068 SNPs with 32 traits recorded, including growth and reproduction traits. We can distinguish between a single pleiotropic QTL and multiple linked QTL because multiple SNPs tagging the same QTL show the same pattern of effects across traits. We confirm this finding by demonstrating that when one SNP is included in the statistical model the other SNPs have a non-significant effect. In the beef cattle data set, cluster analysis yielded four groups of QTL with similar patterns of effects across traits within a group. A linear index was used to validate SNPs having effects on multiple traits and to identify additional SNPs belonging to these four groups.     

A simple, bead-based approach for multi-SNP molecular haplotyping

Single nucleotide polymorphisms (SNPs) within a gene region have often been studied to determine their effect on phenotype. Although a single base pair change can produce a phenotypic change, phenotype is often influenced by the presence of multiple polymorphisms and their relative positions within a given region. For example, if multiple changes occur in a promoter region, how they influence gene expression will depend on their cis/trans configuration. As such, it is essential to consider the haplotype, or the alignment of multiple SNP alleles on each chromosome when attempting to associate genomic changes with phenotype. Unfortunately, no method of high-throughput molecular haplotyping of multiple SNPs currently exists. In response to this unmet need, we have developed an inexpensive, reliable bead-based capture-based haplotyping (CBH) assay to determine the phase, or haplotype, of multiple SNP alleles in a high-throughput manner. The CBH assay requires minimal setup and handling, requires no centrifugation steps and can be performed in <1 h. Data collection is performed via flow cytometry and the assay yields plus/minus results allowing for automated calling by a simple computer application. We will present data demonstrating the molecular haplotyping of 11 SNPs within exon 2 of the N-acetyltransferase-2 (NAT2) gene, which expresses an important drug-metabolizing enzyme. This assay has applications in diagnostic testing, promoter analysis, association studies and pharmacogenetic analysis.     

Genetic homogeneity between Korean and Japanese populations of the broad-leaved evergreen tree Machilus thunbergii (Lauraceae): A massive post-glacial immigration through the Korea Strait or something else?

The warm-temperate vegetation of Korea, currently limited to southern coastal areas, shifted during the Last Glacial Maximum (LGM) towards glacial refugia, putatively located in southern Japan. We hypothesized two scenarios of post-glacial re-colonization of warm-temperate species in relation to current levels of genetic diversity within their populations. If extant Korean populations originated from a single source (a single glacial refugium), we expect significantly lower levels of genetic diversity relative to those from Japan due to founder effects. Alternatively, if they were derived from multiple source populations, levels of genetic diversity within Korean populations will not be significantly reduced compared to those of Japanese ones. To test which of these scenarios is more likely, we investigated the patterns of genetic diversity in 14 populations (seven from southern Korea and seven from southern Japan) of the broad-leaved evergreen tree Machilus thunbergii, employing 11 allozyme loci. High levels of genetic variation in M. thunbergii were found both in southern Korea and southern Japan, with a considerable genetic homogeneity not only between the two regions but also between populations within the two regions. These results suggest a pattern of re-colonization after the LGM fitting the second scenario (immigration from multiple refugia), probably through multiple waves and/or with large founder populations.     

Clonal Strain Persistence of Candida albicans Isolates from Chronic Mucocutaneous Candidiasis Patients

Chronic mucocutaneous candidiasis (CMC) is a primary immunodeficiency disorder characterised by susceptibility to chronic Candida and fungal dermatophyte infections of the skin, nails and mucous membranes. Molecular epidemiology studies of CMC infection are limited in number and scope and it is not clear whether single or multiple strains inducing CMC persist stably or are exchanged and replaced. We subjected 42 C. albicans individual single colony isolates from 6 unrelated CMC patients to multilocus sequence typing (MLST). Multiple colonies were typed from swabs taken from multiple body sites across multiple time points over a 17-month period. Among isolates from each individual patient, our data show clonal and persistent diploid sequence types (DSTs) that were stable over time, identical between multiple infection sites and exhibit azole resistant phenotypes. No shared origin or common source of infection was identified among isolates from these patients. Additionally, we performed C. albicans MLST SNP genotype frequency analysis to identify signatures of past loss of heterozygosity (LOH) events among persistent and azole resistant isolates retrieved from patients with autoimmune disorders including CMC.     

Benzimidazole resistance allele haplotype diversity in United Kingdom isolates of Teladorsagia circumcincta supports a hypothesis of multiple origins of resistance by recurrent mutation

Polymorphisms in the isotype I β-tubulin gene are important genetic determinants of benzimidazole (BZ) resistance in a number of parasitic nematode species including Teladorsagia circumcincta, a major gastrointestinal nematode of sheep. This study investigates the genetic diversity at this locus in a BZ-resistant isolate of T. circumcincta (MTci5) derived from a sheep farm in the United Kingdom (UK) that was open to animal, and therefore parasite, migration. Pyrosequencing was used to determine the frequency of single nucleotide polymorphisms (SNPs) known to be associated with BZ resistance. This was followed by a combination of single strand conformation polymorphism (SSCP) analysis and nucleotide sequencing to sample allelic diversity in a 276 bp fragment immediately surrounding the isotype I β-tubulin F200Y mutation. The genetic diversity at this locus was extremely high, with seven different haplotypes found to contain the resistant F200Y polymorphism in this single resistant isolate. Genotyping by SSCP interfaced with pyrosequencing demonstrated that the P200^Y mutation is also present on multiple haplotypes in two other BZ-resistant T. circumcincta isolates from the UK. This contrasts with much lower levels of haplotype diversity in BZ-resistant alleles present in T. circumcincta isolates from French goat farms that are closed to parasite migration. Taken together with our knowledge of T. circumcincta population genetic structure, these results are most consistent with multiple independent origins of resistance and mixing of alleles due to the large amount of livestock movement in the UK.     

The mechanism of gene targeting in Physcomitrella patens: homologous recombination, concatenation and multiple integration

The model bryophyte Physcomitrella patens exhibits high frequencies of gene targeting when transformed with DNA constructs containing sequences homologous with genomic loci. ‘Targeted gene replacement’ (TGR) resulting from homologous recombination (HR) between each end of a targeting construct and the targeted locus occurs when either single or multiple targeting vectors are delivered. In the latter instance simultaneous, multiple, independent integration of different transgenes occurs at the targeted loci. In both single gene and ‘batch’ transformations, DNA can also be found to undergo ‘targeted insertion’ (TI), integrating at one end of the targeted locus by HR with one flanking sequence of the vector accompanied by an apparent non-homologous end-joining (NHEJ) event at the other. Untargeted integration at nonhomologous sites also occurs, but at a lower frequency. Molecular analysis of TI at a single locus shows that this occurs as a consequence of concatenation of the transforming DNA, in planta, prior to integration, followed by HR between a single site in the genomic target and two of its repeated homologues in the concatenated vector. This reinforces the view that HR is the major pathway by which transforming DNA is integrated in Physcomitrella.     

Multifactor dimensionality reduction-phenomics: a novel method to capture genetic heterogeneity with use of phenotypic variables

Complex human diseases do not have a clear inheritance pattern, and it is expected that risk involves multiple genes with modest effects acting independently or interacting. Major challenges for the identification of genetic effects are genetic heterogeneity and difficulty in analyzing high-order interactions. To address these challenges, we present MDR-Phenomics, a novel approach based on the multifactor dimensionality reduction (MDR) method, to detect genetic effects in pedigree data by integration of phenotypic covariates (PCs) that may reflect genetic heterogeneity. The P value of the test is calculated using a permutation test adjusted for multiple tests. To validate MDR-Phenomics, we compared it with two MDR-based methods: (1) traditional MDR pedigree disequilibrium test (PDT) without consideration of PCs (MDR-PDT) and (2) stratified phenotype (SP) analysis based on PCs, with use of MDR-PDT with a Bonferroni adjustment (SP-MDR). Using computer simulations, we examined the statistical power and type I error of the different approaches under several genetic models and sampling scenarios. We conclude that MDR-Phenomics is more powerful than MDR-PDT and SP-MDR when there is genetic heterogeneity, and the statistical power is affected by sample size and the number of PC levels. We further compared MDR-Phenomics with conditional logistic regression (CLR) for testing interactions across single or multiple loci with consideration of PC. The results show that CLR with PC has only slightly smaller power than does MDR-Phenomics for single-locus analysis but has considerably smaller power for multiple loci. Finally, by applying MDR-Phenomics to autism, a complex disease in which multiple genes are believed to confer risk, we attempted to identify multiple gene effects in two candidate genes of interest—the serotonin transporter gene (SLC6A4) and the integrin beta 3 gene (ITGB3) on chromosome 17. Analyzing four markers in SLC6A4 and four markers in ITGB3 in 117 white family triads with autism and using sex of the proband as a PC, we found significant interaction between two markers—rs1042173 in SLC6A4 and rs3809865 in ITGB3.     

Enhancement of Heterologous Gene Expression in Flammulina velutipes Using Polycistronic Vectors Containing a Viral 2A Cleavage Sequence

Agrobacterium tumefaciens-mediated transformation for edible mushrooms has been previously established. However, the enhancement of heterologous protein production and the expression of multi-target genes remains a challenge. In this study, heterologous protein expression in the enoki mushroom Flammulina velutipes was notably enhanced using 2A peptide-mediated cleavage to co-express multiple copies of single gene. The polycistronic expression vectors were constructed by connecting multi copies of the enhanced green fluorescent protein (egfp) gene using 2A peptides derived from porcine teschovirus-1. The P2A peptides properly self-cleaved as shown by the formation of the transformants with antibiotic resistant capacity and exciting green fluorescence levels after introducing the vectors into F. velutipes mycelia. The results of western blot analysis, epifluorescent microscopy and EGFP production showed that heterologous protein expression in F. velutipes using the polycistronic strategy increased proportionally as the gene copy number increased from one to three copies. In contrast, much lower EGFP levels were detected in the F. velutipes transformants harboring four copies of the egfp gene due to mRNA instability. The polycistronic strategy using 2A peptide-mediated cleavage developed in this study can not only be used to express single gene in multiple copies, but also to express multiple genes in a single reading frame. It is a promising strategy for the application of mushroom molecular pharming.     

Ensemble Positive Unlabeled Learning for Disease Gene Identification

An increasing number of genes have been experimentally confirmed in recent years as causative genes to various human diseases. The newly available knowledge can be exploited by machine learning methods to discover additional unknown genes that are likely to be associated with diseases. In particular, positive unlabeled learning (PU learning) methods, which require only a positive training set P (confirmed disease genes) and an unlabeled set U (the unknown candidate genes) instead of a negative training set N, have been shown to be effective in uncovering new disease genes in the current scenario. Using only a single source of data for prediction can be susceptible to bias due to incompleteness and noise in the genomic data and a single machine learning predictor prone to bias caused by inherent limitations of individual methods. In this paper, we propose an effective PU learning framework that integrates multiple biological data sources and an ensemble of powerful machine learning classifiers for disease gene identification. Our proposed method integrates data from multiple biological sources for training PU learning classifiers. A novel ensemble-based PU learning method EPU is then used to integrate multiple PU learning classifiers to achieve accurate and robust disease gene predictions. Our evaluation experiments across six disease groups showed that EPU achieved significantly better results compared with various state-of-the-art prediction methods as well as ensemble learning classifiers. Through integrating multiple biological data sources for training and the outputs of an ensemble of PU learning classifiers for prediction, we are able to minimize the potential bias and errors in individual data sources and machine learning algorithms to achieve more accurate and robust disease gene predictions. In the future, our EPU method provides an effective framework to integrate the additional biological and computational resources for better disease gene predictions.     

Interactive effects of salinity and a predator on mosquito oviposition and larval performance

Oviposition habitat selection (OHS) is increasingly being recognized as playing a large role in explaining mosquito distributions and community assemblages. Most studies have assessed the role of single factors affecting OHS, while in nature, oviposition patterns are most likely explained by multiple, interacting biotic and abiotic factors. Determining how various factors interact to affect OHS is important for understanding metapopulation and metacommunity dynamics. We investigated the individual and interactive effects of three water salinities (0, 15 and 30 p.p.t. NaCl added) and the aquatic predator Anisops debilis Perplexa (Hemiptera: Notonectidae) on OHS and larval performance of the mosquitoes Ochlerotatus caspius Pallas and Culiseta longiareolata Macquart (Diptera: Culicidae) in outdoor-artificial-pool and laboratory experiments. C. longiareolata inhabited only freshwater pools, strongly avoided pools containing A. debilis, and larvae experienced lower survival in the presence of A. debilis. Salinity concentration interacted strongly with the predator in affecting OHS and larval survival of O. caspius; oviposition increased with increasing salinity in the absence of the predator and decreased with increasing salinity in the presence of the predator. O. caspius larval survival in predator-free pools was lowest in freshwater and highest at intermediate salinity. In predator pools, survival was highest at high salinity, where predation rate was shown to be lowest in the laboratory. Our results highlight that assessing the role of single factors in affecting mosquito distributions can be misleading. Instead, multiple factors may interact to affect oviposition patterns and larval performance.