Marker gene elimination from transgenic barley, using co-transformation with adjacent 'twin T-DNAs' on a standard Agrobacterium transformation vector

We have tested a methodology for the elimination of the selectable marker gene after Agrobacterium-mediated transformation of barley. This involves segregation of the selectable marker gene away from the gene of interest following co-transformation using a plasmid carrying two T-DNAs, which were located adjacent to each other with no intervening region. A standard binary transformation vector was modified by insertion of a small section composed of an additional left and right T-DNA border, so that the selectable marker gene and the site for insertion of the gene of interest (GOI) were each flanked by a left and right border. Using this vector three different GOIs were transformed into barley. Analysis of transgene inheritance was facilitated by a novel and rapid assay utilizing PCR amplification from macerated leaf tissue. Co-insertion was observed in two thirds of transformants, and among these approximately one quarter had transgene inserts which segregated in the next generation to yield selectable marker-free transgenic plants. Insertion of non-T-DNA plasmid sequences was observed in only one of fourteen SMF lines tested. This technique thus provides a workable system for generating transgenic barley free from selectable marker genes, thereby obviating public concerns regarding proliferation of these genes.

Development of polymorphic microsatellite markers suitable for genetic linkage mapping of olive flounder Paralichthys olivaceus

Microsatellite markers are important for gene mapping and for marker-assisted selection. Sixty-five polymorphic microsatellite markers were developed with an enriched partial genomic library from olive flounder Paralichthys olivaceus an important commercial fish species in Korea. The variability of these markers was tested in 30 individuals collected from the East Sea (Korea). The number of alleles for each locus ranged from 2 to 33 (mean, 17.1). Observed and expected heterozygosity as well as polymorphism information content varied from 0.313 to 1.000 (mean, 0.788), from 0.323 to 0.977 (mean, 0.820), and from 0.277 to 0.960 (mean, 0.787), respectively. Nine loci showed significant deviation from the Hardy-Weinberg equilibrium after sequential Bonferroni correction. Analysis with MICROCHECKER suggested the presence of null alleles at five of these loci with estimated null allele frequencies of 0.126-0.285. These new microsatellite markers from genomic libraries will be useful for constructing a P. olivaceus linkage map.

Genetic and genomic studies of PADI4 in rheumatoid arthritis

Objectives. Strong genetic association of rheumatoid arthritis (RA) with PADI4 (peptidyl arginine deiminase) has previously been described in Japanese, although this was not confirmed in a subsequent study in the UK. We therefore undertook a further study of genetic association between PADI4 and RA in UK Caucasians and also studied expression of PADI4 in the peripheral blood of patients with RA. Methods. Seven single-nucleotide polymorphisms (SNP) were genotyped using polymerase chain reaction (PCR)-restriction fragment length polymorphism in 111 RA cases and controls. A marker significantly associated with RA (PADI4_100, rs#2240339) in this first data set (P = 0.03) was then tested for association in a larger group of 439 RA patients and 428 controls. PADI4 transcription was also assessed by real-time quantitative PCR using RNA extracted from peripheral blood mononuclear cells from 13 RA patients and 11 healthy controls. Results. A single SNP was weakly associated with RA (P = 0.03) in the initial case-control study, a single SNP (PADI4_100) and a two marker haplotype of that SNP and the neighbouring SNP (PADI4_04) were significantly associated with RA (P = 0.02 and P = 0.03 respectively). PADI4_100 was not associated with RA in a second sample set. PADI4 expression was four times greater in cases than controls (P = 0.004), but expression levels did not correlate with the levels of markers of inflammation. Conclusion. PADI4 is significantly overexpressed in the blood of RA patients but genetic variation within PADI4 is not a major risk factor for RA in Caucasians.

No evidence for genetic association with the let-7 microRNA-binding site or other common KRAS variants in risk of endometriosis

STUDY QUESTION Is there a contribution of the minor allele at the KRAS single nucleotide polymorphism (SNP) rs61764370 in the let-7 microRNA-binding site to endometriosis risk? SUMMARY ANSWER We found no evidence for association between endometriosis risk and rs61764370 or any other SNPs in KRAS. WHAT IS KNOWN ALREADY The rs61764370 SNP in the 3' untranslated region of the KRAS gene is predicted to disrupt a complementary binding site (LCS6) for the let-7 microRNA, and was recently reported to be at a high frequency (31%) in 132 women of varying ancestry with endometriosis compared with frequencies in a database of population controls (up to 7.6% depending on ancestry), suggesting a strong effect of this KRAS SNP in the aetiology of endometriosis. STUDY DESIGN, SIZE AND DURATION This was a case-control study with a total of 11 206 subjects. The study was performed between February 2012 and July 2012. PARTICIPANTS/MATERIALS, SETTINGAND METHODS We first investigated a possible association between common markers in KRAS and endometriosis risk from our genome-wide association (GWA) data in 3194 surgically confirmed endometriosis cases and 7060 controls of European ancestry. Although rs61764370 was not genotyped on the GWA arrays, five SNPs typed in the study were highly correlated with this variant. The rs61764370 and two SNPs highly correlated with rs61764370 were then genotyped in 933 endometriosis cases and 952 controls using the Sequenom MassARRAY platform. MAIN RESULTS AND THE ROLE OF CHANCE There was no evidence for an association between rs61764370 and endometriosis risk P = 0.411 and odds ratio = 1.10 (95% confidence intervals: 0.88-1.36). We also found no evidence for an association between the highly correlated SNP rs17387019 and endometriosis. Their minor allele frequencies in cases and controls were of 0.087-0.091 similar to the population frequency reported previously for this variant in controls. Analyses of endometriosis cases with revised American Fertility Society stage III/IV disease also showed no evidence for an association between these SNPs and endometriosis risk. LIMITATIONS AND REASONS FOR CAUTION The GWA and genotyped data sets were not independent since individuals and cases from some families overlap. Controls in our GWA study were not screened for endometriosis. WIDER IMPLICATIONS OF THE FINDINGS The key SNP, rs61764370, was genotyped in a subset of samples. Our results do not support the suggestion that carrying the minor allele at rs61764370 contributes to a significant number of endometriosis cases and rs61764370 is, therefore, unlikely to be a useful marker of endometriosis risk. STUDY FUNDING/COMPETING INTEREST(S) The research was funded by grants from the Australian National Health and Medical Research Council and Wellcome Trust. None of the authors has competing interests for the study.

Marker selection by Akaike information criterion and Bayesian information criterion

We carried out a discriminant analysis with identity by descent (IBD) at each marker as inputs, and the sib pair type (affected-affected versus affected-unaffected) as the output. Using simple logistic regression for this discriminant analysis, we illustrate the importance of comparing models with different number of parameters. Such model comparisons are best carried out using either the Akaike information criterion (AIC) or the Bayesian information criterion (BIC). When AIC (or BIC) stepwise variable selection was applied to the German Asthma data set, a group of markers were selected which provide the best fit to the data (assuming an additive effect). Interestingly, these 25-26 markers were not identical to those with the highest (in magnitude) single-locus lod scores.

Cross-sectional study of a microsatellite marker in the low density lipoprotein receptor gene in obese normotensives

1. The low density lipoprotein receptor is an important regulator of serum cholesterol which may have implications for the development of both hypertension and obesity. In this study, genotypes for a low density lipoprotein receptor gene (LDLR) dinucleotide polymorphism were determined in both lean and obese normotensive populations. 2. In previous cross-sectional association studies an ApaLI and a HincII polymorphism for LDLR were shown to be associated with obesity in essential hypertensives. However, these polymorphisms did not show an association with obesity in normotensives. 3. In contrast, this study reports that preliminary results for an LDLR microsatellite marker, located more towards the 3' end of the gene, show a significant association with obesity in the normotensive population studied. These results indicate that LDLR could play an important role in the development of obesity, which might be independent of hypertension.

Evaluation of a 7-gene genetic profile for athletic endurance phenotype in Ironman championship triathletes

Polygenic profiling has been proposed for elite endurance performance, using an additive model determining the proportion of optimal alleles in endurance athletes. To investigate this model’s utility for elite triathletes, we genotyped seven polymorphisms previously associated with an endurance polygenic profile (ACE Ins/Del, ACTN3 Arg577Ter, AMPD1 Gln12Ter, CKMM 1170bp/985+185bp, HFE His63Asp, GDF8 Lys153Arg and PPARGC1A Gly482Ser) in a cohort of 196 elite athletes who participated in the 2008 Kona Ironman championship triathlon. Mean performance time (PT) was not significantly different in individual marker analysis. Age, sex, and continent of origin had a significant influence on PT and were adjusted for. Only the AMPD1 endurance-optimal Gln allele was found to be significantly associated with an improvement in PT (model p=5.79 x 10-17, AMPD1 genotype p=0.01). Individual genotypes were combined into a total genotype score (TGS); TGS distribution ranged from 28.6 to 92.9, concordant with prior studies in endurance athletes (mean±SD: 60.75±12.95). TGS distribution was shifted toward higher TGS in the top 10% of athletes, though the mean TGS was not significantly different (p=0.164) and not significantly associated with PT even when adjusted for age, sex, and origin. Receiver operating characteristic curve analysis determined that TGS alone could not significantly predict athlete finishing time with discriminating sensitivity and specificity for three outcomes (less than median PT, less than mean PT, or in the top 10%), though models with the age, sex, continent of origin, and either TGS or AMPD1 genotype could. These results suggest three things: that more sophisticated genetic models may be necessary to accurately predict athlete finishing time in endurance events; that non-genetic factors such as training are hugely influential and should be included in genetic analyses to prevent confounding; and that large collaborations may be necessary to obtain sufficient sample sizes for powerful and complex analyses of endurance performance.