Genetic markers for stallion fertility - lessons from humans and mice

Our knowledge on the many aspects of mammalian reproduction in general and equine reproduction in particular has greatly increased during the last 15 years. Advances in the understanding of the physiology, cell biology, and biochemistry of reproduction have facilitated genetic analyses of fertility. Currently, there are more than 200 genes known that are involved in the production of fertile sperm cells. The completion of a number of mammalian genome projects will aid in the investigation of these genes in different species. Great progress has been made in the understanding of genetic aberrations that lead to male infertility. Additionally, the first genetic mechanisms are being discovered that contribute to the quantitative variation of fertility traits in fertile male animals. As artificial insemination (AI) represents a widespread technology in horse breeding, semen quality traits may eventually become an additional selection criterion for breeding stallions. Current research activities try to identify genetic markers that correlate to these semen quality traits. Here, we will review the current state of genetic research in male fertility and offer some perspectives for future research in horses.

Evaluation of Knowledge Regarding Diagnostic Strategies for Genetic Diseases in Select Residents

Genetics education for physicians has been a popular publication topic in the United States and in Europe for over 20 years. Decreasing numbers of medical genetics professionals and an increasing volume of genetic information has created a dire need for increased genetics training in medical school and in clinical practice. This study aimed to assess how well pediatrics-focused primary care physicians apply their general genetics knowledge to clinical genetic testing using scenario-based questions. We chose to specifically focus on knowledge of the diagnostic applicability of Chromosomal Microarray (CMA) technology in pediatrics because of its recent recommendation by the International Standard Cytogenomic Array (ISCA) Consortium as a first-tier genetic test for individuals with developmental disabilities and/or congenital anomalies. Proficiency in ordering baseline genetic testing was evaluated for eighty-one respondents from four pediatrics-focused residencies (categorical pediatrics, pediatric neurology, internal medicine/pediatrics, and family practice) at two large residency programs in Houston, Texas. Similar to other studies, we found an overall deficit of genetic testing knowledge, especially among family practice residents. Interestingly, residents who elected to complete a genetics rotation in medical school scored significantly better than expected, as well as better than residents who did not elect to complete a genetics rotation. We suspect that the insufficient knowledge among physicians regarding a baseline genetics work-up is leading to redundant (i.e. concurrent karyotype and CMA) and incorrect (i.e. ordering CMA to detect achondroplasia) genetic testing and is contributing to rising health care costs in the United States. Our results provide specific teaching points upon which medical schools can focus education about clinical genetic testing and suggest that increased collaboration between primary care physicians and genetics professionals could benefit patient health care overall.

Genetic Predictors of Clinical Outcomes in Non-Small Cell Lung Cancer Patients

Lung cancer is the leading cause of cancer-related mortality in the US. Emerging evidence has shown that host genetic factors can interact with environmental exposures to influence patient susceptibility to the diseases as well as clinical outcomes, such as survival and recurrence. We aimed to identify genetic prognostic markers for non-small cell lung cancer (NSCLC), a major (85%) subtype of lung cancer, and also in other subgroups. With the fast evolution of genotyping technology, genetic association studies have went through candidate gene approach, to pathway-based approach, to the genome wide association study (GWAS). Even in the era of GWAS, pathway-based approach has its own advantages on studying cancer clinical outcomes: it is cost-effective, requiring a smaller sample size than GWAS easier to identify a validation population and explore gene-gene interactions. In the current study, we adopted pathway-based approach focusing on two critical pathways - miRNA and inflammation pathways. MicroRNAs (miRNA) post-transcriptionally regulate around 30% of human genes. Polymorphisms within miRNA processing pathways and binding sites may influence patients’ prognosis through altered gene regulation. Inflammation plays an important role in cancer initiation and progression, and also has shown to impact patients’ clinical outcomes. We first evaluated 240 single nucleotide polymorphisms (SNPs) in miRNA biogenesis genes and predicted binding sites in NSCLC patients to determine associations with clinical outcomes in early-stage (stage I and II) and late-stage (stage III and IV) lung cancer patients, respectively. First, in 535 early-stage patients, after correcting multiple comparisons, FZD4:rs713065 (hazard ratio [HR]:0.46, 95% confidence interval [CI]:0.32-0.65) showed a significant inverse association with survival in early stage surgery-only patients. SP1:rs17695156 (HR:2.22, 95% CI:1.44-3.41) and DROSHA:rs6886834 (HR:6.38, 95% CI:2.49-16.31) conferred increased risk of progression in the all patients and surgery-only populations, respectively. FAS:rs2234978 was significantly associated with improved survival in all patients (HR:0.59, 95% CI:0.44-0.77) and in the surgery plus chemotherapy populations (HR:0.19, 95% CI:0.07-0.46).. Functional genomics analysis demonstrated that this variant creates a miR-651 binding site resulting in altered miRNA regulation of FAS, providing biological plausibility for the observed association. We then analyzed these associations in 598 late-stage patients. After multiple comparison corrections, no SNPs remained significant in the late stage group, while the top SNP NAT1:rs15561 (HR=1.98, 96%CI=1.32-2.94) conferred a significantly increased risk of death in the chemotherapy subgroup. To test the hypothesis that genetic variants in the inflammation-related pathways may be associated with survival in NSCLC patients, we first conducted a three-stage study. In the discovery phase, we investigated a comprehensive panel of 11,930 inflammation-related SNPs in three independent lung cancer populations. A missense SNP (rs2071554) in HLA-DOB was significantly associated with poor survival in the discovery population (HR: 1.46, 95% CI: 1.02-2.09), internal validation population (HR: 1.51, 95% CI: 1.02-2.25), and external validation (HR: 1.52, 95% CI: 1.01-2.29) population. Rs2900420 in KLRK1 was significantly associated with a reduced risk for death in the discovery (HR: 0.76, 95% CI: 0.60-0.96) and internal validation (HR: 0.77, 95% CI: 0.61-0.99) populations, and the association reached borderline significance in the external validation population (HR: 0.80, 95% CI: 0.63-1.02). We also evaluated these inflammation-related SNPs in NSCLC patients in never smokers. Lung cancer in never smokers has been increasingly recognized as distinct disease from that in ever-smokers. A two-stage study was performed using a discovery population from MD Anderson (411 patients) and a validation population from Mayo Clinic (311 patients). Three SNPs (IL17RA:rs879576, BMP8A:rs698141, and STK:rs290229) that were significantly associated with survival were validated (pCD74:rs1056400 and CD38:rs10805347) were borderline significant (p=0.08) in the Mayo Clinic population. In the combined analysis, IL17RA:rs879576 resulted in a 40% reduction in the risk for death (p=4.1 × 10-5 [p=0.61, heterogeneity test]). We also validated a survival tree created in MD Anderson population in the Mayo Clinic population. In conclusion, our results provided strong evidence that genetic variations in specific pathways that examined (miRNA and inflammation pathways) influenced clinical outcomes in NSCLC patients, and with further functional studies, the novel loci have potential to be translated into clinical use.

Isozyme systems as markers of genetic deterioration in stored seeds of Brassicaceae species

The main objective of this study was to determine if isozyme systems can be used as markers of genetic deterioration in Brassicaceae seed accessions under different storage conditions. Seed samples of Brassica oleracea, Cardaria draba, Erysimum cheiri, Iberis sempervirens and Rapistrum rugosum were stored for periods of 9 to 30 years at -10°C and 3-4% seed moisture content (long-term or LT conditions) and at 5°C and uncontrolled relative humidity (RH) (short-term or ST conditions). Starch Gel Electrophoresis (SGE) was used to analyse six enzyme systems oriented to determine the genetic deterioration of the accessions studied. The results obtained show that long-term storage conditions (LT) were extremely effective in maintaining the viability of seeds of the five Brassicaceae species studied. The final germination percentages reached by seeds from LT samples ranged from 75 to 100%, while the germination percentages of ST samples (except for B. oleracea) were very low (from 0 to 10%). Similar conclusions were obtained studying the integrity of electrophoretic bands for several isozymes. Two enzyme systems were of special interest: malate dehydrogenase and alcohol dehydrogenase.

Aerodynamic optimization of the ICE2 high-speed train nose using a genetic algorithm and metamodels

An aerodynamic optimization of the ICE 2 high-speed train nose in term of front wind action sensitivity is carried out in this paper. The nose is parametrically defined by Be?zier Curves, and a three-dimensional representation of the nose is obtained using thirty one design variables. This implies a more complete parametrization, allowing the representation of a real model. In order to perform this study a genetic algorithm (GA) is used. Using a GA involves a large number of evaluations before finding such optimal. Hence it is proposed the use of metamodels or surrogate models to replace Navier-Stokes solver and speed up the optimization process. Adaptive sampling is considered to optimize surrogate model fitting and minimize computational cost when dealing with a very large number of design parameters. The paper introduces the feasi- bility of using GA in combination with metamodels for real high-speed train geometry optimization.

Genetic algorithms and Gaussian Bayesian networks to uncover the predictive core set of bibliometric indices

The diversity of bibliometric indices today poses the challenge of exploiting the relationships among them. Our research uncovers the best core set of relevant indices for predicting other bibliometric indices. An added difficulty is to select the role of each variable, that is, which bibliometric indices are predictive variables and which are response variables. This results in a novel multioutput regression problem where the role of each variable (predictor or response) is unknown beforehand. We use Gaussian Bayesian networks to solve the this problem and discover multivariate relationships among bibliometric indices. These networks are learnt by a genetic algorithm that looks for the optimal models that best predict bibliometric data. Results show that the optimal induced Gaussian Bayesian networks corroborate previous relationships between several indices, but also suggest new, previously unreported interactions. An extended analysis of the best model illustrates that a set of 12 bibliometric indices can be accurately predicted using only a smaller predictive core subset composed of citations, g-index, q2-index, and hr-index. This research is performed using bibliometric data on Spanish full professors associated with the computer science area.

Diversity Arrays: a solid state technology for sequence information independent genotyping

Here we present the successful application of the microarray technology platform to the analysis of DNA polymorphisms. Using the rice genome as a model, we demonstrate the potential of a high-throughput genome analysis method called Diversity Array Technology, DArT‘. In the format presented here the technology is assaying for the presence (or amount) of a specific DNA fragment in a representation derived from the total genomic DNA of an organism or a population of organisms. Two different approaches are presented: the first involves contrasting two representations on a single array while the second involves contrasting a representation with a reference DNA fragment common to all elements of the array. The Diversity Panels created using this method allow genetic fingerprinting of any organism or group of organisms belonging to the gene pool from which the panel was developed. Diversity Arrays enable rapid and economical application of a highly parallel, solid-state genotyping technology to any genome or complex genomic mixtures.

Plant genetic resources: What can they contribute toward increased crop productivity?

To feed a world population growing by up to 160 people per minute, with >90% of them in developing countries, will require an astonishing increase in food production. Forecasts call for wheat to become the most important cereal in the world, with maize close behind; together, these crops will account for ≈80% of developing countries’ cereal import requirements. Access to a range of genetic diversity is critical to the success of breeding programs. The global effort to assemble, document, and utilize these resources is enormous, and the genetic diversity in the collections is critical to the world’s fight against hunger. The introgression of genes that reduced plant height and increased disease and viral resistance in wheat provided the foundation for the “Green Revolution” and demonstrated the tremendous impact that genetic resources can have on production. Wheat hybrids and synthetics may provide the yield increases needed in the future. A wild relative of maize, Tripsacum, represents an untapped genetic resource for abiotic and biotic stress resistance and for apomixis, a trait that could provide developing world farmers access to hybrid technology. Ownership of genetic resources and genes must be resolved to ensure global access to these critical resources. The application of molecular and genetic engineering technologies enhances the use of genetic resources. The effective and complementary use of all of our technological tools and resources will be required for meeting the challenge posed by the world’s expanding demand for food.

Genetic association of CD247 (CD3ζ) with SLE in a large-scale multiethnic study

A classic T-cell phenotype in systemic lupus erythematosus (SLE) is the downregulation and replacement of the CD3ζ chain that alters T-cell receptor signaling. However, genetic associations with SLE in the human CD247 locus that encodes CD3ζ are not well established and require replication in independent cohorts. Our aim was therefore to examine, localize and validate CD247-SLE association in a large multiethnic population. We typed 44 contiguous CD247 single-nucleotide polymorphisms (SNPs) in 8922 SLE patients and 8077 controls from four ethnically distinct populations. The strongest associations were found in the Asian population (11 SNPs in intron 1, 4.99 × 10(-4) < P < 4.15 × 10(-2)), where we further identified a five-marker haplotype (rs12141731-rs2949655-rs16859085-rs12144621-rs858554; G-G-A-G-A; P(hap) = 2.12 × 10(-5)) that exceeded the most associated single SNP rs858554 (minor allele frequency in controls = 13%; P = 4.99 × 10(-4), odds ratio = 1.32) in significance. Imputation and subsequent association analysis showed evidence of association (P < 0.05) at 27 additional SNPs within intron 1. Cross-ethnic meta-analysis, assuming an additive genetic model adjusted for population proportions, showed five SNPs with significant P-values (1.40 × 10(-3) < P< 3.97 × 10(-2)), with one (rs704848) remaining significant after Bonferroni correction (P(meta) = 2.66 × 10(-2)). Our study independently confirms and extends the association of SLE with CD247, which is shared by various autoimmune disorders and supports a common T-cell-mediated mechanism.

Next-generation sequencing of iron-metabolism related genes in Portuguese patients with iron overload: novel pathogenic genetic variants

Objective: In Southern European countries up to one-third of the patients with hereditary hemochromatosis (HH) do not present the common HFE risk genotype. In order to investigate the molecular basis of these cases we have designed a gene panel for rapid and simultaneous analysis of 6 HH-related genes (HFE, TFR2, HJV, HAMP, SLC40A1 and FTL) by next-generation sequencing (NGS). Materials and Methods: Eighty-eight iron overload Portuguese patients, negative for the common HFE mutations, were analysed. A TruSeq Custom Amplicon kit (TSCA, by Illumina) was designed in order to generate 97 amplicons covering exons, intron/exon junctions and UTRs of the mentioned genes with a cumulative target sequence of 12115bp. Amplicons were sequenced in the MiSeq instrument (IIlumina) using 250bp paired-end reads. Sequences were aligned against human genome reference hg19 using alignment and variant caller algorithms in the MiSeq reporter software. Novel variants were validated by Sanger sequencing and their pathogenic significance were assessed by in silico studies. Results: We found a total of 55 different genetic variants. These include novel pathogenic missense and splicing variants (in HFE and TFR2), a very rare variant in IRE of FTL, a variant that originates a novel translation initiation codon in the HAMP gene, among others. Conclusion: The merging of TSCA methodology and NGS technology appears to be an appropriate tool for simultaneous and fast analysis of HH-related genes in a large number of samples. However, establishing the clinical relevance of NGS-detected variants for HH development remains a hard-working task, requiring further functional studies.

Investigating genetic discrimination in Australia: Opportunities and challenges in the early stages

Genetic discrimination, defined as the differential treatment of individuals or their relatives on the basis of actual or presumed genetic differences, is an emerging issue of interest in academic, clinical, social and legal contexts. While its potential significance has been discussed widely, verified empirical data are scarce. Genetic discrimination is a complex phenomenon to describe and investigate, as evidenced by the recent Australian Law Reform Commission inquiry in Australia. The authors research project, which commenced in 2002, aims to document the multiple perspectives and experiences regarding genetic discrimination in Australia and inform future policy development and law reform. Data are being collected from consumers, employers, insurers and the legal system. Attempted verification of alleged accounts of genetic discrimination will be a novel feature of the research. This paper overviews the early stages of the research, including conceptual challenges and their methodological implications.

Methodological Considerations in the Study of Genetic Discrimination

The potential significance and dimensions of genetic discrimination have been described extensively in published literature, but epidemiological and verified case data are limited. Obtaining unbiased data from individuals about discrimination which has been based on erroneous or unjustifiable assumptions about their genetic predispositions poses unique challenges. Through review and discussion of research literature, we identify methodological considerations for collecting valid epidemiological data on genetic discrimination from individuals in the community; in particular, we consider issues which relate to sampling, selection and response. We identify issues to promote sound study design, with particular attention to verification of genetic discrimination, and highlight the importance of clinical and genetic knowledge of complex genotype-phenotype relationships.

Predictive genetic test decisions for Huntington's disease: context, appraisal and new moral imperatives

Predictive testing is one of the new genetic technologies which, in conjunction with developing fields such as pharmacogenomics, promises many benefits for preventive and population health. Understanding how individuals appraise and make genetic test decisions is increasingly relevant as the technology expands. Lay understandings of genetic risk and test decision-making, located within holistic life frameworks including family or kin relationships, may vary considerably from clinical representations of these phenomena. The predictive test for Huntington's disease (HD), whilst specific to a single-gene, serious, mature-onset but currently untreatable disorder, is regarded as a model in this context. This paper reports upon a qualitative Australian study which investigated predictive test decision-making by individuals at risk for HD, the contexts of their decisions and the appraisals which underpinned them. In-depth interviews were conducted in Australia with 16 individuals at 50% risk for HD, with variation across testing decisions, gender, age and selected characteristics. Findings suggested predictive testing was regarded as a significant life decision with important implications for self and others, while the right not to know genetic status was staunchly and unanimously defended. Multiple contexts of reference were identified within which test decisions were located, including intra- and inter-personal frameworks, family history and experience of HID, and temporality. Participants used two main criteria in appraising test options: perceived value of, or need for the test information, for self and/or significant others, and degree to which such information could be tolerated and managed, short and long-term, by self and/or others. Selected moral and ethical considerations involved in decision-making are examined, as well as the clinical and socio-political contexts in which predictive testing is located. The paper argues that psychosocial vulnerabilities generated by the availability of testing technologies and exacerbated by policy imperatives towards individual responsibility and self-governance should be addressed at broader societal levels. (C) 2003 Elsevier Science Ltd. All rights reserved.

Genetic and economic analysis of a targeted marker-assisted wheat breeding strategy

The advent of molecular markers as a tool to aid selection has provided plant breeders with the opportunity to rapidly deliver superior genetic solutions to problems in agricultural production systems. However, a major constraint to the implementation of marker-assisted selection (MAS) in pragmatic breeding programs in the past has been the perceived high relative cost of MAS compared to conventional phenotypic selection. In this paper, computer simulation was used to design a genetically effective and economically efficient marker-assisted breeding strategy aimed at a specific outcome. Under investigation was a strategy involving the integration of both restricted backcrossing and doubled haploid (DH) technology. The point at which molecular markers are applied in a selection strategy can be critical to the effectiveness and cost efficiency of that strategy. The application of molecular markers was considered at three phases in the strategy: allele enrichment in the BC1F1 population, gene selection at the haploid stage and the selection for recurrent parent background of DHs prior to field testing. Overall, incorporating MAS at all three stages was the most effective, in terms of delivering a high frequency of desired outcomes and at combining the selected favourable rust resistance, end use quality and grain yield alleles. However, when costs were included in the model the combination of MAS at the BC1F1 and haploid stage was identified as the optimal strategy. A detailed economic analysis showed that incorporation of marker selection at these two stages not only increased genetic gain over the phenotypic alternative but actually reduced the over all cost by 40%.