Hybrid thematic analysis reveals themes for assessing student understanding of biotechnology

Despite efforts to increase teaching of biotechnology worldwide, there are concerns that public literacy of genetic technologies remains insufficient. Improved education strategies are expected to empower individuals to make informed decisions about biotechnology. To evaluate the teaching and learning of this complex topic, qualitative assessment tools are needed. In this case study, we performed a hybrid thematic analysis to identify a set of overarching themes that can be used to evaluate individuals’ understanding of genetic technologies. We analysed the written justifications students gave for their attitudes on a range of genetic technologies, before and after peer-led discussion of each topic. We identified seven themes commonly detected in student responses, five of which have been previously described in studies of mass media communication of biotechnology. Our preliminary analysis suggests that peer-led discourse can promote changes in student understanding of biotechnology. We conclude that hybrid thematic analysis is a useful approach for evaluating the teaching and learning of genetic technologies. We discuss the utility of the hybrid approach and the themes described here for future studies of biotechnology education.     

Biotechnology: the language of multiple views in Māori communities

In Aotearoa (New Zealand), the government funded studies on communicating biotechnology to different sectors in the community from 2003 to 2006. Subsequently, a researcher covering the Māori sector performed a content analysis of data gathered in the community. Qualitative analysis methods included examining text from participant interviews, focus groups, government documents, newspapers, Internet sites, and current literature. Content was coded by identifying common themes in the English and the Māori language. Words like genetic modification (GM), genetic engineering (GE), and biotechnology were explained to provide a basic understanding between the communities and researcher. The terminology applied in the research was essential to achieve communication between the researcher and the community. The resultant themes represented seven views to interpret the communities association with biotechnology: purist Māori, religious Māori, anti Māori, pro Māori, no Māori, uncertain Māori, and middle Māori views. The themes are taken from the analysis of data compiled after 3 years of completing different stages of a research project. The views indicate that a common understanding can be achieved in the diverse range of Māori tribal communities providing those communicating biotechnology can identify the view and interpretations communities associate with biotechnology. This knowledge is essential for government agencies, researchers, community practitioners, scientist, and businesses that desire to dialogue with Māori communities in the language of biotechnology.     

葛根资源遗传多样性和性状关联分析

通过研究葛根资源的遗传多样性和葛根表型性状与分子标记的关联分析,为葛根的分子育种和指纹图谱构建提供理论依据。鉴定分析了127份不同来源葛根资源的10个表型性状,并用ISSR标记研究127份葛根资源的遗传多样性,对ISSR标记与表型性状进行关联分析。表型性状鉴定结果显示葛根资源的10个性状变异大、多样性较好。利用ISSR标记获得多态性条带109条,平均每个引物扩增5.73条、平均Nei's基因多样性0.2085、平均Shannon's指数0.3378,最远遗传距离为0.46。ISSR分子标记聚类分析将127份资源聚为两大类,群体结构分析和PCo A分析结果类似将127份资源分为2个亚群。GLM分析发现3个与茸毛性状关联标记,MLM分析未发现与表型性状关联的标记。本研究收集的资源遗传多样性较好,葛根分子标记聚类结果与地域关系不大,综合GLM和MLM关联分析结果,本试验未发现与表型关联位点。     

基因水平的关联分析方法

全基因组关联研究(Genome wide association study, GWAS)已经在国内外的医学遗传学研究中得到广泛应用, 但是GWAS数据中所蕴含的与多基因复杂性状疾病机制相关的丰富信息尚未得到深度挖掘。近年来, 研究者采用生物网络分析和生物通路分析等生物信息学和生物统计学手段分析GWAS数据, 并探索潜在的疾病机制。生物网络分析和生物通路分析主要是以基因为单位进行的, 因此必须在分析前将基因上全部或者部分单个单核苷酸多态性(Single nucleotide polymorphism, SNP)的遗传关联结果综合起来, 即基因水平的关联分析。基因水平的关联分析需要考虑单个SNP的遗传关联、基因上SNP数量和SNP之间的连锁不平衡结构等多种因素, 因此不仅在遗传学的概念上也在统计方法方面具有一定的复杂性和挑战性。文章对基因水平的关联分析的研究进展、原理和应用进行了综述。     

Inference for set-based effects in genetic association studies with interval-censored outcomes

The rapid acceleration of genetic data collection in biomedical settings has recently resulted in the rise of genetic compendiums filled with rich longitudinal disease data. One common feature of these data sets is their plethora of interval-censored outcomes. However, very few tools are available for the analysis of genetic data sets with interval-censored outcomes, and in particular, there is a lack of methodology available for set-based inference. Set-based inference is used to associate a gene, biological pathway, or other genetic construct with outcomes and is one of the most popular strategies in genetics research. This work develops three such tests for interval-censored settings beginning with a variance components test for interval-censored outcomes, the interval-censored sequence kernel association test (ICSKAT). We also provide the interval-censored version of the Burden test, and then we integrate ICSKAT and Burden to construct the interval censored sequence kernel association test—optimal (ICSKATO) combination. These tests unlock set-based analysis of interval-censored data sets with analogs of three highly popular set-based tools commonly applied to continuous and binary outcomes. Simulation studies illustrate the advantages of the developed methods over ad hoc alternatives, including protection of the type I error rate at very low levels and increased power. The proposed approaches are applied to the investigation that motivated this study, an examination of the genes associated with bone mineral density deficiency and fracture risk.     

The Multi-allelic Genetic Architecture of a Variance-Heterogeneity Locus for Molybdenum Concentration in Leaves Acts as a Source of Unexplained Additive Genetic Variance

Genome-wide association (GWA) analyses have generally been used to detect individual loci contributing to the phenotypic diversity in a population by the effects of these loci on the trait mean. More rarely, loci have also been detected based on variance differences between genotypes. Several hypotheses have been proposed to explain the possible genetic mechanisms leading to such variance signals. However, little is known about what causes these signals, or whether this genetic variance-heterogeneity reflects mechanisms of importance in natural populations. Previously, we identified a variance-heterogeneity GWA (vGWA) signal for leaf molybdenum concentrations in Arabidopsis thaliana. Here, fine-mapping of this association reveals that the vGWA emerges from the effects of three independent genetic polymorphisms that all are in strong LD with the markers displaying the genetic variance-heterogeneity. By revealing the genetic architecture underlying this vGWA signal, we uncovered the molecular source of a significant amount of hidden additive genetic variation or “missing heritability”. Two of the three polymorphisms underlying the genetic variance-heterogeneity are promoter variants for Molybdate transporter 1 (MOT1), and the third a variant located ~25 kb downstream of this gene. A fourth independent association was also detected ~600 kb upstream of MOT1. Use of a T-DNA knockout allele highlights Copper Transporter 6; COPT6 (AT2G26975) as a strong candidate gene for this association. Our results show that an extended LD across a complex locus including multiple functional alleles can lead to a variance-heterogeneity between genotypes in natural populations. Further, they provide novel insights into the genetic regulation of ion homeostasis in A. thaliana, and empirically confirm that variance-heterogeneity based GWA methods are a valuable tool to detect novel associations of biological importance in natural populations.     

Localization of Canine Brachycephaly Using an Across Breed Mapping Approach

The domestic dog, Canis familiaris, exhibits profound phenotypic diversity and is an ideal model organism for the genetic dissection of simple and complex traits. However, some of the most interesting phenotypes are fixed in particular breeds and are therefore less tractable to genetic analysis using classical segregation-based mapping approaches. We implemented an across breed mapping approach using a moderately dense SNP array, a low number of animals and breeds carefully selected for the phenotypes of interest to identify genetic variants responsible for breed-defining characteristics. Using a modest number of affected (10–30) and control (20–60) samples from multiple breeds, the correct chromosomal assignment was identified in a proof of concept experiment using three previously defined loci; hyperuricosuria, white spotting and chondrodysplasia. Genome-wide association was performed in a similar manner for one of the most striking morphological traits in dogs: brachycephalic head type. Although candidate gene approaches based on comparable phenotypes in mice and humans have been utilized for this trait, the causative gene has remained elusive using this method. Samples from nine affected breeds and thirteen control breeds identified strong genome-wide associations for brachycephalic head type on Cfa 1. Two independent datasets identified the same genomic region. Levels of relative heterozygosity in the associated region indicate that it has been subjected to a selective sweep, consistent with it being a breed defining morphological characteristic. Genotyping additional dogs in the region confirmed the association. To date, the genetic structure of dog breeds has primarily been exploited for genome wide association for segregating traits. These results demonstrate that non-segregating traits under strong selection are equally tractable to genetic analysis using small sample numbers.     

No genetic association of the human prolyl endopeptidase gene in the Dutch celiac disease population

Celiac disease (CD) is a complex genetic disorder of the small intestine. The DQ2/DQ8 human leucocyte antigen (HLA) genes explain approximately 40% of the genetic component of the disease, but the remaining non-HLA genes have not yet been identified. The key environmental factor known to be involved in the disease is gluten, a major protein present in wheat, barley, and rye. Integrating microarray data and linkage data from chromosome 6q21-22 revealed the prolyl endopeptidase (PREP) gene as a potential CD candidate in the Dutch population. Interestingly, this gene encodes for the only enzyme that is able to cleave the proline-rich gluten peptides. To investigate the role of the human PREP gene as a primary genetic factor in CD, we conducted gene expression, sequence analysis, and genetic association studies of the PREP gene and determined PREP enzyme activity in biopsies from CD patients and controls. Sequence analysis of the coding region of the PREP gene revealed two novel polymorphisms. Genetic association studies using two novel polymorphisms and three known PREP variants excluded a genetic association between PREP and CD. Determination of PREP activity revealed weak but significant differences between treated and untreated CD biopsies (P < 0.05). Our results from the association study indicate that PREP is not a causative gene for CD in the Dutch population. These are further supported by the activity determinations in which we observed no differences in PREP activity between CD patients and controls.     

Identification of single nucleotide polymorphisms and haplotypes associated with yield and yield components in soybean (<Emphasis Type="Italic">Glycine max</Emphasis>) landraces across multiple environments

Genome-wide association analysis is a powerful approach to identify the causal genetic polymorphisms underlying complex traits. In this study, we evaluated a population of 191 soybean landraces in five environments to detect molecular markers associated with soybean yield and its components using 1,536 single-nucleotide polymorphisms (SNPs) and 209 haplotypes. The analysis revealed that abundant phenotypic and genetic diversity existed in the studied population. This soybean population could be divided into two subpopulations and no or weak relatedness was detected between pair-wise landraces. The level of intra-chromosomal linkage disequilibrium was about 500 kb. Genome-wide association analysis based on the unified mixed model identified 19 SNPs and 5 haplotypes associated with soybean yield and yield components in three or more environments. Nine markers were found co-associated with two or more traits. Many markers were located in or close to previously reported quantitative trait loci mapped by linkage analysis. The SNPs and haplotypes identified in this study will help to further understand the genetic basis of soybean yield and its components, and may facilitate future high-yield breeding by marker-assisted selection in soybean.     

Improving Power for Testing Genetic Association in Case–Control Studies by Reducing the Alternative Space

Summary .  To detect association between a genetic marker and a disease in case–control studies, the Cochran–Armitage trend test is typically used. The trend test is locally optimal when the genetic model is correctly specified. However, in practice, the underlying genetic model, and hence the optimal trend test, are usually unknown. In this case, Pearson's chi-squared test, the maximum of three trend test statistics (optimal for the recessive, additive, and dominant models), and the test based on genetic model selection (GMS) are useful. In this article, we first modify the existing GMS method so that it can be used when the risk allele is unknown. Then we propose a new approach by excluding a genetic model that is not supported by the data. Using either the model selection or exclusion, the alternative space is reduced conditional on the observed data, and hence the power to detect a true association can be increased. Simulation results are reported and the proposed methods are applied to the genetic markers identified from the genome-wide association studies conducted by the Wellcome Trust Case–Control Consortium. The results demonstrate that the genetic model exclusion approach usually performs better than existing methods under its worst situation across scientifically plausible genetic models we considered.     

The Impact of Phenotypic and Genetic Heterogeneity on Results of Genome Wide Association Studies of Complex Diseases

Phenotypic misclassification (between cases) has been shown to reduce the power to detect association in genetic studies. However, it is conceivable that complex traits are heterogeneous with respect to individual genetic susceptibility and disease pathophysiology, and that the effect of heterogeneity has a larger magnitude than the effect of phenotyping errors. Although an intuitively clear concept, the effect of heterogeneity on genetic studies of common diseases has received little attention. Here we investigate the impact of phenotypic and genetic heterogeneity on the statistical power of genome wide association studies (GWAS). We first performed a study of simulated genotypic and phenotypic data. Next, we analyzed the Wellcome Trust Case-Control Consortium (WTCCC) data for diabetes mellitus (DM) type 1 (T1D) and type 2 (T2D), using varying proportions of each type of diabetes in order to examine the impact of heterogeneity on the strength and statistical significance of association previously found in the WTCCC data. In both simulated and real data, heterogeneity (presence of “non-cases”) reduced the statistical power to detect genetic association and greatly decreased the estimates of risk attributed to genetic variation. This finding was also supported by the analysis of loci validated in subsequent large-scale meta-analyses. For example, heterogeneity of 50% increases the required sample size by approximately three times. These results suggest that accurate phenotype delineation may be more important for detecting true genetic associations than increase in sample size.     

Evidence for linkage of a new region (11p14) to eczema and allergic diseases

Asthma, allergic rhinitis (AR) and atopic dermatitis also called eczema are allergic co-morbidites, which are likely to depend on pleiotropic genetic effects as well as on specific genetic factors. After a previous genome-wide linkage screen conducted for asthma and AR in a sample of 295 French EGEA families ascertained through asthmatic subjects, the aim here was to search for genetic factors involved in eczema and more particularly the ones shared by the three allergic diseases using the same EGEA data. In this sake, eczema and phenotypes of “allergic disease” accounting for the joint information on the presence/absence of the three diseases were examined by linkage analyses using the maximum likelihood binomial method. A fine mapping was carried out in regions detected for potential linkage, followed by association studies using the family-based association test (FBAT). Evidence for linkage to 11p14 region was shown for “allergic disease” and eczema. Linkage was also indicated between eczema and 5q13 and between “allergic disease” and both 5p15 and 17q21 regions. Fine mapping supported the evidence of linkage to 11p14 and FBAT analyses showed the association between “allergic disease” and a marker located at the linkage peak on 11p14. Further investigations in this region will allow identifying genetic factor(s) which could have pleiotropic effect in the three allergic diseases.     

Genetic diversity,population structure and association analysis in linseed (<Emphasis Type="Italic">Linum usitatissimum</Emphasis> L.)

The present investigation aimed to explore the level of genetic diversity, determine the population structure in a larger set of germplasm of linseed using microsatellite marker and identify linked markers through association mapping. A total of 168 accessions of linseed were evaluated for major agro-economic traits and SSRs markers deployed for diversity assessment. A total of 337 alleles were amplified by 50 SSRs ranging from 2 to 13 with an average of 6.74 ± 2.8 alleles per loci. The neighbor joining based clustering grouped all the accessions into three major clusters that were also confirmed by scatter plot of PCoA. While model based clustering determined four sub-populations (K = 4). Further, analysis of molecular variance analysis considering three population showed that maximum variation (79%) was within the population. We identified one putative SSR marker (Lu_3043) linked with days to 50% flowering through both GLM and MLM analysis of association mapping. The results of this preliminary study revealed genetic diversity, population structure in linseed and linked marker which could be utilized in future breeding program.     

Population genetic study of allozyme variation in natural populations of Drosophila antonietae (Insecta, Diptera)

Drosophila antonietae is an endemic South American cactophilic species found in relictual xerophytic vegetation, mostly associated with Cereus hildmaniannus cactus. Low differentiation among populations of this species has been detected using several markers. In this work, we performed an allozyme genetic variability analysis of 11 natural populations of D. antonietae and included a discussion about the possible influences of several evolutionary processes that might be acting to maintain the pattern observed. The genetic variability of 14 isoenzyme loci was analysed and showed a high genetic diversity (average observed heterozygosity = 0.319) and a moderate genetic differentiation among populations ( F statistics = 0.0723). A correlation between genetic and geographical and ecological distances was detected among pairs of populations and the regional equilibrium analysis was thus applied. This analysis resulted in Nm (number of migrants) of approximately 3.21, indicating that moderate levels of both gene flow and genetic drift occur in this species, with gene flow overlapping genetic drift. However, considering ecological features of drosophilids, we propose a hypothesis to explain the moderate differentiation encountered as a result of three different processes, or a combination of them: (1) gene flow; (2) a short period of differentiation, i.e. maintenance of ancestral polymorphism; and (3) action of natural selection. Moreover, if gene flow is present, the high genetic diversity compared with other cactophilic and non-cactophilic species could be due to differential selection in different populations followed by gene exchange among them. These factors are discussed in the light of D. antonietae 's historical and evolutionary association with the host cactus.     

Meta-analysis of Correlated Traits via Summary Statistics from GWASs with an Application in Hypertension

Genome-wide association studies (GWASs) have identified many genetic variants underlying complex traits. Many detected genetic loci harbor variants that associate with multiple—even distinct—traits. Most current analysis approaches focus on single traits, even though the final results from multiple traits are evaluated together. Such approaches miss the opportunity to systemically integrate the phenome-wide data available for genetic association analysis. In this study, we propose a general approach that can integrate association evidence from summary statistics of multiple traits, either correlated, independent, continuous, or binary traits, which might come from the same or different studies. We allow for trait heterogeneity effects. Population structure and cryptic relatedness can also be controlled. Our simulations suggest that the proposed method has improved statistical power over single-trait analysis in most of the cases we studied. We applied our method to the Continental Origins and Genetic Epidemiology Network (COGENT) African ancestry samples for three blood pressure traits and identified four loci (CHIC2, HOXA-EVX1, IGFBP1/IGFBP3, and CDH17; p < 5.0 × 10⁻⁸) associated with hypertension-related traits that were missed by a single-trait analysis in the original report. Six additional loci with suggestive association evidence (p < 5.0 × 10⁻⁷) were also observed, including CACNA1D and WNT3. Our study strongly suggests that analyzing multiple phenotypes can improve statistical power and that such analysis can be executed with the summary statistics from GWASs. Our method also provides a way to study a cross phenotype (CP) association by using summary statistics from GWASs of multiple phenotypes.     

HBV-related hepatocellular carcinoma susceptibility gene KIF1B is not associated with development of chronic hepatitis B

Background

A recent genome-wide association study has identified a new susceptibility locus, kinesin family member 1B gene (KIF1B), strongly associated with progression from chronic hepatitis B (CHB) to hepatitis B virus-related hepatocellular carcinoma (HCC) in Chinese population, this study was carried out to explore the role of the genetic variants in KIF1B in the development of chronic hepatitis B.

Methodology/Principal Findings

Three KIF1B polymorphisms (rs8019, rs17401924, and rs17401966) were selected and genotyped in 473 CHB patients and 580 controls with no history of CHB. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated by logistic regression model. None of these three SNPs showed association with CHBs after adjusting for age and gender. Equivalence-based method analysis confirmed the absence of association. In the further haplotype analysis, three common haplotypes were observed in this study population, but no significant effect was also found for haplotypes in the progression to CHB.

Conclusions/Significance

This study showed the new locus identified for HCC, KIF1B, was not associated with progression to CHB, implying distinct genetic susceptibility factor contributes to the progression from hepatitis B virus infection to HCC. Nevertheless, further comprehensive analyses are warranted to dissect the mechanism.     

Colour polymorphism in Drosophila mediopunctata: genetic (chromosomal) analysis and nonrandom association with chromosome inversions

The presence of three dark spots on the abdomen is typical of the tripunctata group of Drosophila, which is the second largest Neotropical group, with 56 species. In some species, such as D. mediopunctata, the colour pattern varies considerably: ranging from flies showing no spots up to flies with three dark spots. In this paper, we present a genetic (chromosomal) analysis of this character showing that this colour polymorphism is genetically determined mainly by the second chromosome. Since this chromosome is the most polymorphic for inversions in this species, we also examined the influence of the inversions on this character. We used strains in which different second chromosomes were placed on the same genetic background and the offspring between them. We found a nonrandom association between the number of spots and the inversions PA0 and PC0. Thus, our results are consistent with the idea that the factors or genes determining a conspicuous polymorphism are likely to be associated, forming a supergene, and this association would be most efficiently accomplished through a chromosome inversion. Moreover, this is the first time that an association between a conspicuous morphological polymorphism and chromosome inversions has been described.     

CTLA4 and generalized vitiligo: two genetic association studies and a meta‐analysis of published data

Several lines of evidence have implicated the gene encoding cytotoxic T lymphocyte antigen 4 (CTLA4) in susceptibility to various autoimmune diseases. However, published studies of genetic association between CTLA4 polymorphisms and vitiligo have yielded conflicting results. Here, we describe two new genetic association studies of CTLA4 single‐nucleotide polymorphisms (SNPs) and generalized vitiligo in two independent Romanian Caucasian (CEU) case‐control cohorts. The first study, of SNPs rs1863800, rs231806, rs231775, rs3087243, rs11571302, rs11571297, and rs10932037, showed no allelic, genotypic, or haplotypic association with generalized vitiligo. The second study, of SNP rs231775, likewise showed no significant association. To enhance statistical power over that of any individual study, we carried out a meta‐analysis that incorporated these two new studies and all other published genetic association studies of CTLA4 SNPs and vitiligo in CEU populations. While there was no association with vitiligo overall, the meta‐analysis showed significant association of SNP rs231775 in that subgroup of vitiligo patients who also had other concomitant autoimmune diseases. Similarly, there was near‐significant association in this same patient subgroup with several other CTLA4 SNPs that are in linkage disequilibrium with rs231775. Our results indicate that the association of CTLA4 with vitiligo is weak, and indeed may be secondary, driven by primary genetic association of CTLA4 with other autoimmune diseases that are epidemiologically associated with vitiligo.     

Genetic diversity and population structure of pummelo (<Emphasis Type="Italic">Citrus maxima</Emphasis>) germplasm in China

Pummelo (Citrus maxima) is one of the basic species of Citrus. It has been cultivated for about 4000 years in China, and therefore, there are abundant germplasm during the long time of culture. However, there is still a lack of a detailed study of the genetic characteristics of pummelo population. In this study, genetic diversity and population structure among 274 pummelo accessions collected in China were analyzed using 31 nuclear simple sequence repeat (nSSR) markers. The observed heterozygosity was calculated as 0.325 and genetic differentiation Fst as 0.077. Genetic structure analysis divided the whole germplasm into three subpopulations, Pop-a, Pop-b, and Pop-c. Pop-a was composed of accessions mostly from Southeast China, Pop-b was composed of accessions from the central region of South China, and Pop-c was composed of accessions from Southwest China. Meanwhile, the analysis of principal coordinate analysis and neighbor-join tree supported the viewpoint of three subpopulations, and then the possible dispersal routes of pummelos in China were proposed. This study provides an insight into the genetic diversity, facilitates future genome-wide association studies, and promotes the breeding program of pummelo as well.     

Genetic Association Studies: An Information Content Perspective

The availability of high-density single nucleotide polymorphisms (SNPs) data has made the human genetic association studies possible to identify common and rare variants underlying complex diseases in a genome-wide scale. A handful of novel genetic variants have been identified, which gives much hope and prospects for the future of genetic association studies. In this process, statistical and computational methods play key roles, among which information-based association tests have gained large popularity. This paper is intended to give a comprehensive review of the current literature in genetic association analysis casted in the framework of information theory. We focus our review on the following topics: (1) information theoretic approaches in genetic linkage and association studies; (2) entropy-based strategies for optimal SNP subset selection; and (3) the usage of theoretic information criteria in gene clustering and gene regulatory network construction.