Rainbow trout resistance to bacterial cold water disease: two new quantitative trait loci identified after a natural disease outbreak on a French farm

In rainbow trout farming, Flavobacterium psychrophilum, the causative agent of bacterial cold water disease, is responsible for important economic losses. Resistance to F. psychrophilum is heritable, and several quantitative trait loci (QTL) with moderate effects have been detected, opening up promising perspectives for the genetic improvement of resistance. In most studies however, resistance to F. psychrophilum was assessed in experimental infectious challenges using injection as the infection route, which is not representative of natural infection. Indeed, injection bypasses external barriers, such as mucus and skin, that likely play a protective role against the infection. In this study, we aimed at describing the genetic architecture of the resistance to F. psychrophilum after a natural disease outbreak. In a 2000‐fish cohort, reared on a French farm, 720 fish were sampled and genotyped using the medium‐throughput Axiom? Trout Genotyping Array. Overall mortality at the end of the outbreak was 25%. Genome‐wide association studies were performed under two different models for time to death measured on 706 fish with validated genotypes for 30 060 SNPs. This study confirms the polygenic inheritance of resistance to F. psychrophilum with a few QTL with moderate effects and a large polygenic background, the heritability of the trait being estimated at 0.34. Two new chromosome‐wide significant QTL and three suggestive QTL were detected, each of them explaining between 1% and 4% of genetic variance.     

Using progenitor strain information to identify quantitative trait nucleotides in outbred mice

We have developed a fast and economical strategy for dissecting the genetic architecture of quantitative trait loci at a molecular level. The method uses two pieces of information: mapping data from crosses that involve more than two inbred strains and sequence variants in the progenitor strains within the interval containing a quantitative trait locus (QTL). By testing whether the strain distribution pattern in the progenitor strains is consistent with the observed genetic effect of the QTL we can assign a probability that any sequence variant is a quantitative trait nucleotide (QTN). It is not necessary to genotype the animals except at a skeleton of markers; the genotypes at all other polymorphisms are estimated by a multipoint analysis. We apply the method to a 4.8-Mb region on mouse chromosome 1 that contains a QTL influencing anxiety segregating in a heterogeneous stock and show that, under the assumption that a single QTN is present and lies in a region conserved between the human and mouse genomes, it is possible to reduce the number of variants likely to be the quantitative trait nucleotide from many thousands to <20.     

Identification of quantitative trait nucleotides that regulate cancer growth: a simulation approach

A general growth model derived from basic cellular properties can be used to describe the dynamic process of cancer growth with mathematical equations. It has been recognized that cancer growth is under genetic control, with a multitude of interacting genes each segregating in a Mendelian fashion and displaying environmental sensitivity. In this article, we integrate the mathematical aspects of the pervasive growth model into a statistical framework for the identification of quantitative trait nucleotides that underlie cancer growth. This integrative framework is constructed with a single nucleotide polymorphism-based haplotype blocking analysis. Simulation studies have been performed to demonstrate the usefulness of the model. The proposed model provides a generic platform model for testing and detecting specific DNA sequence variants that regulates the timing of cancer emergence, growth and differentiation.     

Mapping quantitative trait loci for binary trait in the F2:3 design

In the analysis of inheritance of quantitative traits with low heritability, an F_2:3 design that genotypes plants in F₂ and phenotypes plants in F_2:3 progeny is often used in plant genetics. Although statistical approaches for mapping quantitative trait loci (QTL) in the F_2:3 design have been well developed, those for binary traits of biological interest and economic importance are seldom addressed. In this study, an attempt was made to map binary trait loci (BTL) in the F_2:3 design. The fundamental idea was: the F₂ plants were genotyped, all phenotypic values of each F_2:3 progeny were measured for binary trait, and these binary trait values and the marker genotype informations were used to detect BTL under the penetrance and liability models. The proposed method was verified by a series of Monte-Carlo simulation experiments. These results showed that maximum likelihood approaches under the penetrance and liability models provide accurate estimates for the effects and the locations of BTL with high statistical power, even under of low heritability. Moreover, the penetrance model is as efficient as the liability model, and the F_2:3 design is more efficient than classical F₂ design, even though only a single progeny is collected from each F_2:3 family. With the maximum likelihood approaches under the penetrance and the liability models developed in this study, we can map binary traits as we can do for quantitative trait in the F_2:3 design.     

Tsc2, a positional candidate gene underlying a quantitative trait locus for hepatic steatosis

Nonalchoholic fatty liver disease (NAFLD) is the most common cause of liver dysfunction and is associated with metabolic diseases, including obesity, insulin resistance, and type 2 diabetes. We mapped a quantitative trait locus (QTL) for NAFLD to chromosome 17 in a cross between C57BL/6 (B6) and BTBR mouse strains made genetically obese with the Lep(ob/ob) mutation. We identified Tsc2 as a gene underlying the chromosome 17 NAFLD QTL. Tsc2 functions as an inhibitor of mammalian target of rapamycin, which is involved in many physiological processes, including cell growth, proliferation, and metabolism. We found that Tsc2(+/-) mice have increased lipogenic gene expression in the liver in an insulin-dependent manner. The coding single nucleotide polymorphism between the B6 and BTBR strains leads to a change in the ability to inhibit the expression of lipogenic genes and de novo lipogenesis in AML12 cells and to promote the proliferation of Ins1 cells. This difference is due to a different affinity of binding to Tsc1, which affects the stability of Tsc2.     

Identifying and monitoring pain in farm animals: a review

One important objective for animal welfare is to maintain animals free from pain, injury or disease. Therefore, detecting and evaluating the intensity of animal pain is crucial. As animals cannot directly communicate their feelings, it is necessary to identify sensitive and specific indicators that can be easily used. The aim of the present paper is to review relevant indicators to assess pain in several farm species. The term pain is used for mammals, birds and fish, even though the abilities of the various species to experience the emotional component of pain may be different. Numerous behavioural changes are associated with pain and many of them could be used on farms to assess the degree of pain being experienced by an animal. Pain, as a stressor, is associated with variations in the hypothalamic–pituitary–adrenal axis as well as in the sympathetic and immune systems that can be used to identify the presence of pain rapidly after it started. However, most of these measures need sophisticated equipment for their assessment. Therefore, they are mainly adapted to experimental situations. Injuries and other lesional indicators give information on the sources of pain and are convenient to use in all types of situations. Histopathological analyses can identify sources of pain in experimental studies. When pronounced and/or long lasting, the pain-induced behavioural and physiological changes can decrease production performance. Some indicators are very specific and sensitive to pain, whereas others are more generally related to stressful situations. The latter can be used to indicate that animals are suffering from something, which may be pain. Overall, this literature review shows that several indicators exist to assess pain in mammals, a few in birds and very few in fish. Even if in some cases, a single indicator, usually a behavioural indicator, may be sufficient to detect pain, combining various types of indicators increases sensitivity and specificity of pain assessment. Research is needed to build and validate new indicators and to develop systems of pain assessment adapted to each type of situation and each species.     

Estimation of genetical parameters for a quantitative trait subject to major gene influences

Both regression and correlation estimates of genetical variance and heritability for a quantitative trait influenced by a major gene can be obtained from the error variance-covariance matrix of MANOVA using relative-relative phenotype pairs as factors. The method is illustrated with parent-offspring data on red cell acid phosphatase phenotypes and serum acid phosphatase activity.     

Light-response quantitative trait loci identified with composite interval and eXtreme array mapping in Arabidopsis thaliana

Genetic analysis of natural variation in ecotypes of Arabidopsis thaliana can facilitate the discovery of new genes or of allelic variants of previously identified genes controlling physiological processes in plants. We mapped quantitative trait loci (QTL) for light response in recombinant inbred lines (RILs) derived from the Columbia and Kashmir accessions via two methods: composite interval mapping and eXtreme array mapping (XAM). After measuring seedling hypocotyl lengths in blue, red, far-red, and white light, and in darkness, eight QTL were identified by composite interval mapping and five localized near photoreceptor loci. Two QTL in blue light were associated with CRY1 and CRY2, two in red light were near PHYB and PHYC, and one in far-red light localized near PHYA. The RED2 and RED5 QTL were verified in segregating lines. XAM was tested for the identification of QTL in red light with pools of RILs selected for extreme phenotypes. Thousands of single feature polymorphisms detected by differential DNA hybridized to high-density oligo-nucleotide arrays were used to estimate allele frequency differences between the pools. The RED2 QTL was identified clearly; differences exceeded a threshold of significance determined by simulations. The sensitivities of XAM to population type and size and genetic models were also determined by simulation analysis.     

Emotions in farm animals: a new approach to animal welfare in applied ethology

One of the major topics of applied ethology is the welfare of animals reared by humans. Welfare can be defined as a state of harmony between an individual and its environment. Any marked deviation from this state, if perceived by the individual, results in a welfare deficit due to negative emotional experiences. In humans, verbal language helps to assess emotional experiences. In animals, only behavioural and physiological measurements help to detect emotions. However, how to interpret these responses in terms of emotional experiences remains an open question. The information on the cognitive abilities of farm animals, which are available but scattered, could help the understanding of their emotions. We propose a behavioural approach based on cognitive psychology: emotions can be investigated in farm animals in terms of the individual's appraisal of the situation. This evaluative process depends on: (a) the intrinsic characteristics of the eliciting event (suddenness, novelty, pleasantness); (b) the degree of conflict of that event with the individual's needs or expectations; and (c) the individual's coping possibilities offered by the environment. The result of such an evaluation determines the negative versus positive emotions. We propose an analysis of the emotional repertoire of farm animals in terms of the relationship between the evaluative process of the event on the one hand and the behavioural and physiological responses on the other hand.     

Responses to nutrients in farm animals: implications for production and quality

It is well known that any quantitative (energy and protein levels) and qualitative (nature of the diet, nutrient dynamic) changes in the feeding of animals affect metabolism. Energy expenditure and feed efficiency at the whole-body level, nutrient partitioning between and within tissues and organs and, ultimately, tissue and organ characteristics are the major regulated traits with consequences on the quality of the meat and milk produced. Recent progress in biology has brought to light important biological mechanisms which explain these observations: for instance, regulation by the nutrients of gene expression or of key metabolic enzyme activity, interaction and sometimes cross-regulation or competition between nutrients to provide free energy (ATP) to living cells, indirect action of nutrients through a complex hormonal action, and, particularly in herbivores, interactions between trans-fatty acids produced in the rumen and tissue metabolism. One of the main targets of this nutritional regulation is a modification of tissue insulin sensitivity and hence of insulin action. In addition, the nutritional control of mitochondrial activity (and hence of nutrient catabolism) is another major mechanism by which nutrients may affect body composition and tissue characteristics. These regulations are of great importance in the most metabolically active tissues (the digestive tract and the liver) and may have undesirable (i.e. diabetes and obesity in humans) or desirable consequences (such as the production of fatty liver by ducks and geese, and the production of fatty and hence tasty meat or milk with an adapted fatty acid profile).     

养殖动物及其相关环境耐药组的研究进展

畜牧养殖业中大量抗生素的使用,导致养殖动物及其相关环境中存在大量的耐药基因/耐药细菌。这些耐药基因可以借助基因水平转移等方式在环境中进一步扩散,甚至进入食品动物随食物链传播,对生态环境、食品安全和人类健康造成极大的威胁。随着基因组学研究手段的不断进步,养殖动物及其相关环境中耐药基因的多样性和生态学分布规律被广泛揭示。文中综述了相关领域耐药基因的研究进展,探讨了其对人体健康的潜在影响,并对未来的研究方向进行了展望。     

Expression quantitative trait loci analysis of the Rubisco activase gene in maize

Expression quantitative trait loci (eQTL) analyses were applied in order to identify genetic factors that are relevant to the expression of a β-isoform Rubisco activase gene in maize, namely ZmRCAβ, in this study. During two years, a maize recombinant inbred line population was measured for ZmRCAβ expression levels at the grain filling stage. Based on a genetic map containing 916 molecular markers, we detected five eQTLs, namely qRCA2.1 on chromosome 2, and qRCA4.1, qRCA4.2, qRCA4.3, and qRCA4.4 on chromosome 4. These eQTLs explained the phenotypic variation ranging from 6.14% to 7.50% with the logarithm of the odd values ranging from 3.11 to 4.96. Based on the position of the eQTLs and ZmRCAβ on the chromosome, qRCA4.2 was inferred as a cis-eQTL and the remaining as a trans-eQTL, suggesting that a combination of both cis- and trans-acting elements might control ZmRCAβ expression. qRCA4.2, qRCA4.3, and qRCA4.4 were repeatedly detected during two years.     

Phenotypic variation and natural selection at catsup, a pleiotropic quantitative trait gene in Drosophila

Quantitative traits are shaped by networks of pleiotropic genes . To understand the mechanisms that maintain genetic variation for quantitative traits in natural populations and to predict responses to artificial and natural selection, we must evaluate pleiotropic effects of underlying quantitative trait genes and define functional allelic variation at the level of quantitative trait nucleotides (QTNs). Catecholamines up (Catsup), which encodes a negative regulator of tyrosine hydroxylase , the rate-limiting step in the synthesis of the neurotransmitter dopamine, is a pleiotropic quantitative trait gene in Drosophila melanogaster. We used association mapping to determine whether the same or different QTNs at Catsup are associated with naturally occurring variation in multiple quantitative traits. We sequenced 169 Catsup alleles from a single population and detected 33 polymorphisms with little linkage disequilibrium (LD). Different molecular polymorphisms in Catsup are independently associated with variation in longevity, locomotor behavior, and sensory bristle number. Most of these polymorphisms are potentially functional variants in protein coding regions, have large effects, and are not common. Thus, Catsup is a pleiotropic quantitative trait gene, but individual QTNs do not have pleiotropic effects. Molecular population genetic analyses of Catsup sequences are consistent with balancing selection maintaining multiple functional polymorphisms.     

Aroma in rice: genetic analysis of a quantitative trait

A new approach was developed which succeeded in tagging for the first time a major gene and two QTLs controlling grain aroma in rice. It involved a combination of two techniques, quantification of volatile compounds in the cooking water by gas chromatography, and molecular marker mapping. Four types of molecular marker were used (RFLPs, RAPDs, STSs, isozymes). Evaluation and mapping were performed on a doubled haploid line population which (1) conferred a precise character evaluation by enabling the analysis of large quantities of grains per genotype and (2) made possible the comparison of gas chromatography results and sensitive tests. The population size (135 lines) provided a good mapping precision. Several markers on chromosome 8 were found to be closely linked to a major gene controlling the presence of 2-acetyl-1-pyrroline (AcPy), the main compound of rice aroma. Moreover, our results showed that AcPy concentration in plants is regulated by at least two chromosomal regions. Estimations of recombination fractions on chromosome 8 were corrected for strong segregation distortion. This study confirms that AcPy is the major component of aroma. Use of the markers linked to AcPy major gene and QTLs for marker-assisted selection by successive backcrosses may be envisaged.     

The F7 gene and clotting factor VII levels: dissection of a human quantitative trait locus

Localization of human quantitative trait loci (QTLs) is now routine. However, identifying their functional DNA variants is still a formidable challenge. We present a complete dissection of a human QTL using novel statistical techniques to infer the most likely functional polymorphisms of a QTL that influence plasma levels of clotting factor VII (FVII), a risk factor for cardiovascular disease. Resequencing of 15 kb in and around the F7 gene identified 49 polymorphisms, which were then genotyped in 398 people. Using a Bayesian quantitative trait nucleotide (BQTN) method, we identified four to seven functional variants that completely account for this QTL. These variants include both rare coding variants and more common, potentially regulatory polymorphisms in intronic and promoter regions.     

Gene expression in placentation of farm animals: an overview of gene function during development

Eutherian mammals share a common ancestor that evolved into two main placental types, i.e., hemotrophic (e.g., human and mouse) and histiotrophic (e.g., farm animals), which differ in invasiveness. Pregnancies initiated with assisted reproductive techniques (ART) in farm animals are at increased risk of failure; these losses were associated with placental defects, perhaps due to altered gene expression. Developmentally regulated genes in the placenta seem highly phylogenetically conserved, whereas those expressed later in pregnancy are more species-specific. To elucidate differences between hemotrophic and epitheliochorial placentae, gene expression data were compiled from microarray studies of bovine placental tissues at various stages of pregnancy. Moreover, an in silico subtractive library was constructed based on homology of bovine genes to the database of zebrafish — a nonplacental vertebrate. In addition, the list of placental preferentially expressed genes for the human and mouse were collected using bioinformatics tools (Tissue-specific Gene Expression and Regulation [TiGER] — for humans, and tissue-specific genes database (TiSGeD) — for mice and humans). Humans, mice, and cattle shared 93 genes expressed in their placentae. Most of these were related to immune function (based on analysis of gene ontology). Cattle and women shared expression of 23 genes, mostly related to hormonal activity, whereas mice and women shared 16 genes (primarily sexual differentiation and glycoprotein biology). Because the number of genes expressed by the placentae of both cattle and mice were similar (based on cluster analysis), we concluded that both cattle and mice were suitable models to study the biology of the human placenta.     

Estimation of the contribution of quantitative trait loci (QTL) to the variance of a quantitative trait by means of genetic markers

The estimation of the contribution of an individual quantitative trait locus (QTL) to the variance of a quantitative trait is considered in the framework of an analysis of variance (ANOVA). ANOVA mean squares expectations which are appropriate to the specific case of QTL mapping experiments are derived. These expectations allow the specificities associated with the limited number of genotypes at a given locus to be taken into account. Discrepancies with classical expectations are particularly important for two-class experiments (backcross, recombinant inbred lines, doubled haploid populations) and F₂ populations. The result allows us firstly to reconsider the power of experiments (i.e. the probability of detecting a QTL with a given contribution to the variance of the trait). It illustrates that the use of classical formulae for mean squares expectations leads to a strong underestimation of the power of the experiments. Secondly, from the observed mean squares it is possible to estimate directly the variance associated with a locus and the fraction of the total variance associated to this locus (r _l ² ). When compared to other methods, the values estimated using this method are unbiased. Considering unbiased estimators increases in importance when (1) the experimental size is limited; (2) the number of genotypes at the locus of interest is large; and (3) the fraction of the variation associated with this locus is small. Finally, specific mean squares expectations allows us to propose a simple analytical method by which to estimate the confidence interval of r _l ² . This point is particularly important since results indicate that 95% confidence intervals for r _l ² can be rather wide:2–23% for a 10% estimate and 8–34% for a 20% estimate if 100 individuals are considered.