Mutations in the bovine ABCG2 and the ovine MSTN gene added to the few quantitative trait nucleotides identified in farm animals: a mini-review

The progress in molecular genetics in animal breeding is moderately effective as compared to traditional animal breeding using quantitative genetic approaches. There is an extensive disparity between the number of reported quantitative trait loci (QTLs) and their linked genetic variations in cattle, pig, and chicken. The identification of causative mutations affecting quantitative traits is still very challenging and hampered by the cloudy relationship between genotype and phenotype. There are relatively few reports in which a successful identification of a causative mutation for an animal production trait was demonstrated. The examples that have attracted considerable attention from the animal breeding community are briefly summarized and presented in a table. In this mini-review, the recent progress in mapping quantitative trait nucleotides (QTNs) are reviewed, including the ABCG2 gene mutation that underlies a QTL for fat and protein content and the ovine MSTN gene mutation that causes muscular hypertrophy in Texel sheep. It is concluded that the progress in molecular genetics might facilitate the elucidation of the genetic architecture of QTLs, so that also the high-hanging fruits can be harvested in order to contribute to efficient and sustainable animal production.

Common obesity risk alleles in childhood attention-deficit/hyperactivity disorder

Children with attention-deficit/hyperactivity disorder (ADHD) have a higher rate of obesity than children without ADHD. Obesity risk alleles may overlap with those relevant for ADHD. We examined whether risk alleles for an increased body mass index (BMI) are associated with ADHD and related quantitative traits (inattention and hyperactivity/impulsivity). We screened 32 obesity risk alleles of single nucleotide polymorphisms (SNPs) in a genome-wide association study (GWAS) for ADHD based on 495 patients and 1,300 population-based controls and performed in silico analyses of the SNPs in an ADHD meta-analysis comprising 2,064 trios, 896 independent cases, and 2,455 controls. In the German sample rs206936 in the NUDT3 gene (nudix; nucleoside diphosphate linked moiety X-type motif 3) was associated with ADHD risk (OR: 1.39; P = 3.4 × 10(-4) ; Pcorr  = 0.01). In the meta-analysis data we found rs6497416 in the intronic region of the GPRC5B gene (G protein-coupled receptor, family C, group 5, member B; P = 7.2 × 10(-4) ; Pcorr  = 0.02) as a risk allele for ADHD. GPRC5B belongs to the metabotropic glutamate receptor family, which has been implicated in the etiology of ADHD. In the German sample rs206936 (NUDT3) and rs10938397 in the glucosamine-6-phosphate deaminase 2 gene (GNPDA2) were associated with inattention, whereas markers in the mitogen-activated protein kinase 5 gene (MAP2K5) and in the cell adhesion molecule 2 gene (CADM2) were associated with hyperactivity. In the meta-analysis data, MAP2K5 was associated with inattention, GPRC5B with hyperactivity/impulsivity and inattention and CADM2 with hyperactivity/impulsivity. Our results justify further research on the elucidation of the common genetic background of ADHD and obesity.

High variability and non-neutral evolution of the mammalian avpr1a gene

BACKGROUND: The arginine-vasopressin 1a receptor has been identified as a key determinant for social behaviour in Microtus voles, humans and other mammals. Nevertheless, the genetic bases of complex phenotypic traits like differences in social and mating behaviour among species and individuals remain largely unknown. Contrary to previous studies focusing on differences in the promotor region of the gene, we investigate here the level of functional variation in the coding region (exon 1) of this locus. RESULTS: We detected high sequence diversity between higher mammalian taxa as well as between species of the genus Microtus. This includes length variation and radical amino acid changes, as well as the presence of distinct protein variants within individuals. Additionally, negative selection prevails on most parts of the first exon of the arginine-vasopressin receptor 1a (avpr1a) gene but it contains regions with higher rates of change that harbour positively selected sites. Synonymous and non-synonymous substitution rates in the avpr1a gene are not exceptional compared to other genes, but they exceed those found in related hormone receptors with similar functions. DISCUSSION: These results stress the importance of considering variation in the coding sequence of avpr1a in regards to associations with life history traits (e.g. social behaviour, mating system, habitat requirements) of voles, other mammals and humans in particular.

STrengthening the REporting of Genetic Association studies (STREGA)--an extension of the STROBE statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of OBservational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed, but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct or analysis.

STrengthening the REporting of Genetic Association Studies (STREGA)--an extension of the STROBE statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of OBservational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

Strengthening the reporting of genetic association studies (STREGA): an extension of the strengthening the reporting of observational studies in epidemiology (STROBE) statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence, the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association (STREGA) studies initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed, but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

STrengthening the REporting of Genetic Association Studies (STREGA): an extension of the STROBE statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

STrengthening the REporting of Genetic Association studies (STREGA): an extension of the STROBE Statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information into the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and issues of data volume that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

Strengthening the reporting of genetic association studies (STREGA): an extension of the STROBE statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

Strengthening the reporting of genetic association studies (STREGA): an extension of the STROBE Statement

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

Stable two-element control of dTph1 transposition in mutator strains of Petunia by an inactive ACT1 introgression from a wild species

The high copy dTph1 transposon system of Petunia (Solanaceae) is one of the most powerful insertion mutagens in plants, but its activity cannot be controlled in the commonly used mutator strains. We analysed the regulation of dTph1 activity by QTL analysis in recombinant inbred lines of the mutator strain W138 and a wild species (P. integrifolia spp. inflata). Two genetic factors were identified that control dTph1 transposition. One corresponded to the ACT1 locus on chromosome I. A second, previously undescribed locus ACT2 mapped on chromosome V. As a 6-cM introgression in W138, the P. i. inflata act1(S6) allele behaved as a single recessive locus that fully eliminated transposition of all dTph1 elements in all stages of plant development and in a heritable fashion. Weak dTph1 activity was restored in act1(S6)/ACT2(S6) double introgression lines, indicating that the P. i. inflata allele at ACT2 conferred a low level of transposition. Thus, the act1(S6) allele is useful for simple and predictable control of transposition of the entire dTph1 family when introgressed into an ultra-high copy W138 mutator strain. We demonstrate the use of the ACT1(W138)/act1(S6) allele pair in a two-element dTph1 transposition system by producing 10 000 unique and fixed dTph1 insertions in a population of 1250 co-isogenic lines. This Petunia system produces the highest per plant insertion number of any known two-element system, providing a powerful and logistically simple tool for transposon mutagenesis of qualitative as well as quantitative traits.

Genome-wide identification of quantitative trait loci in a cross between Hampshire and Landrace I: carcass traits

We report the identification of quantitative trait loci (QTL) affecting carcass composition, carcass length, fat deposition and lean meat content using a genome scan across 462 animals from a combined intercross and backcross between Hampshire and Landrace pigs. Data were analysed using multiple linear regression fitting additive and dominance effects. This model was compared with a model including a parent-of-origin effect to spot evidence of imprinting. Several precisely defined muscle phenotypes were measured in order to dissect body composition in more detail. Three significant QTL were detected in the study at the 1% genome-wide level, and twelve significant QTL were detected at the 5% genome-wide level. These QTL comprise loci affecting fat deposition and lean meat content on SSC1, 4, 9, 10, 13 and 16, a locus on SSC2 affecting the ratio between weight of meat and bone in back and weight of meat and bone in ham and two loci affecting carcass length on SSC12 and 17. The well-defined phenotypes in this study enabled us to detect QTL for sizes of individual muscles and to obtain information of relevance for the description of the complexity underlying other carcass traits.

Heterosis for biomass-related traits in Arabidopsis investigated by quantitative trait loci analysis of the triple testcross design with recombinant inbred lines

Arabidopsis thaliana has emerged as a leading model species in plant genetics and functional genomics including research on the genetic causes of heterosis. We applied a triple testcross (TTC) design and a novel biometrical approach to identify and characterize quantitative trait loci (QTL) for heterosis of five biomass-related traits by (i) estimating the number, genomic positions, and genetic effects of heterotic QTL, (ii) characterizing their mode of gene action, and (iii) testing for presence of epistatic effects by a genomewide scan and marker x marker interactions. In total, 234 recombinant inbred lines (RILs) of Arabidopsis hybrid C24 x Col-0 were crossed to both parental lines and their F1 and analyzed with 110 single-nucleotide polymorphism (SNP) markers. QTL analyses were conducted using linear transformations Z1, Z2, and Z3 calculated from the adjusted entry means of TTC progenies. With Z1, we detected 12 QTL displaying augmented additive effects. With Z2, we mapped six QTL for augmented dominance effects. A one-dimensional genome scan with Z3 revealed two genomic regions with significantly negative dominance x additive epistatic effects. Two-way analyses of variance between marker pairs revealed nine digenic epistatic interactions: six reflecting dominance x dominance effects with variable sign and three reflecting additive x additive effects with positive sign. We conclude that heterosis for biomass-related traits in Arabidopsis has a polygenic basis with overdominance and/or epistasis being presumably the main types of gene action.

Quantitative multi-slice computed tomography assessment of the mitral valvular complex for transcatheter mitral valve interventions part 1: systematic measurement methodology and inter-observer variability

AIMS Transcatheter mitral valve replacement (TMVR) is an emerging technology with the potential to treat patients with severe mitral regurgitation at excessive risk for surgical mitral valve surgery. Multimodal imaging of the mitral valvular complex and surrounding structures will be an important component for patient selection for TMVR. Our aim was to describe and evaluate a systematic multi-slice computed tomography (MSCT) image analysis methodology that provides measurements relevant for transcatheter mitral valve replacement. METHODS AND RESULTS A systematic step-by-step measurement methodology is described for structures of the mitral valvular complex including: the mitral valve annulus, left ventricle, left atrium, papillary muscles and left ventricular outflow tract. To evaluate reproducibility, two observers applied this methodology to a retrospective series of 49 cardiac MSCT scans in patients with heart failure and significant mitral regurgitation. For each of 25 geometrical metrics, we evaluated inter-observer difference and intra-class correlation. The inter-observer difference was below 10% and the intra-class correlation was above 0.81 for measurements of critical importance in the sizing of TMVR devices: the mitral valve annulus diameters, area, perimeter, the inter-trigone distance, and the aorto-mitral angle. CONCLUSIONS MSCT can provide measurements that are important for patient selection and sizing of TMVR devices. These measurements have excellent inter-observer reproducibility in patients with functional mitral regurgitation.

Quantitative 1-Step DNA Methylation Analysis with Native Genomic DNA as Template

DNA methylation analysis currently requires complex multistep procedures based on bisulfite conversion of unmethylated cytosines or on methylation-sensitive endonucleases. To facilitate DNA methylation analysis, we have developed a quantitative 1-step assay for DNA methylation analysis.