Interval mapping methods for detecting QTL affecting survival and time-to-event phenotypes

Quantitative trait loci for resistance to Flavobacterium psychrophilum in rainbow trout: effect of the mode of infection and evidence of epistatic interactions

Background

Bacterial cold-water disease, which is caused by Flavobacterium psychrophilum, is one of the major diseases that affect rainbow trout (Oncorhynchus mykiss) and a primary concern for trout farming. Better knowledge of the genetic basis of resistance to F. psychrophilum would help to implement this trait in selection schemes and to investigate the immune mechanisms associated with resistance. Various studies have revealed that skin and mucus may contribute to response to infection. However, previous quantitative trait loci (QTL) studies were conducted by using injection as the route of infection. Immersion challenge, which is assumed to mimic natural infection by F. psychrophilum more closely, may reveal different defence mechanisms.

Results

Two isogenic lines of rainbow trout with contrasting susceptibilities to F. psychrophilum were crossed to produce doubled haploid F2 progeny. Fish were infected with F. psychrophilum either by intramuscular injection (115 individuals) or by immersion (195 individuals), and genotyped for 9654 markers using RAD-sequencing. Fifteen QTL associated with resistance traits were detected and only three QTL were common between the injection and immersion. Using a model that accounted for epistatic interactions between QTL, two main types of interactions were revealed. A “compensation-like” effect was detected between several pairs of QTL for the two modes of infection. An “enhancing-like” interaction effect was detected between four pairs of QTL. Integration of the QTL results with results of a previous transcriptomic analysis of response to F. psychrophilum infection resulted in a list of potential candidate immune genes that belong to four relevant functional categories (bacterial sensors, effectors of antibacterial immunity, inflammatory factors and interferon-stimulated genes).

Conclusions

These results provide new insights into the genetic determinism of rainbow trout resistance to F. psychrophilum and confirm that some QTL with large effects are involved in this trait. For the first time, the role of epistatic interactions between resistance-associated QTL was evidenced. We found that the infection protocol used had an effect on the modulation of defence mechanisms and also identified relevant immune functional candidate genes.

Electronic supplementary material

The online version of this article (10.1186/s12711-018-0431-9) contains supplementary material, which is available to authorized users.

Genetic and transcriptomic analyses provide new insights on the early antiviral response to VHSV in resistant and susceptible rainbow trout

BACKGROUND

The viral hemorrhagic septicemia virus (VHSV) is a major threat for salmonid farming and for wild fish populations worldwide. Previous studies have highlighted the importance of innate factors regulated by a major quantitative trait locus (QTL) for the natural resistance to waterborne VHSV infection in rainbow trout. The aim of this study was to analyze the early transcriptomic response to VHSV inoculation in cell lines derived from previously described resistant and susceptible homozygous isogenic lines of rainbow trout to obtain insights into the molecular mechanisms responsible for the resistance to the viral infection.

RESULTS

We first confirmed the presence of the major QTL in a backcross involving a highly resistant fish isogenic line (B57) and a highly susceptible one (A22), and were able to define the confidence interval of the QTL and to identify its precise position. We extended the definition of the QTL since it controls not only resistance to waterborne infection but also the kinetics of mortality after intra-peritoneal injection. Deep sequencing of the transcriptome of B57 and A22 derived cell lines exposed to inactivated VHSV showed a stronger response to virus inoculation in the resistant background. In line with our previous observations, an early and strong induction of interferon and interferon-stimulated genes was correlated with the resistance to VHSV, highlighting the major role of innate immune factors in natural trout resistance to the virus. Interestingly, major factors of the antiviral innate immunity were much more expressed in naive B57 cells compared to naive A22 cells, which likely contributes to the ability of B57 to mount a fast antiviral response after viral infection. These observations were further extended by the identification of several innate immune-related genes localized close to the QTL area on the rainbow trout genome.

CONCLUSIONS

Taken together, our results improve our knowledge in virus-host interactions in vertebrates and provide novel insights in the molecular mechanisms explaining the resistance to VHSV in rainbow trout. Our data also provide a collection of potential markers for resistance and susceptibility of rainbow trout to VHSV infection.

Cox regression model for dissecting genetic architecture of survival time

Common quantitative trait locus (QTL) mapping methods fail to analyze survival traits of skewed normal distributions. As a result, some mapping methods for survival traits have been proposed based on survival analysis. Under a single QTL model, however, those methods perform poorly in detecting multiple QTLs and provide biased estimates of QTL parameters. For sparse oversaturated model used to map survival time loci, the least absolute shrinkage and selection operator (LASSO) for Cox regression model can be employed to efficiently shrink most of genetic effects to zero. Then, a few non-zero genetic effects are re-estimated and statistically tested using the standard maximum Cox partial likelihood method. Simulation shows that the proposed method has higher statistic power for QTL detection than that of the LASSO for logarithmic linear model or the interval mapping based on Cox model, although it somewhat underestimates QTL effects. Especially, computational speed of the method is very fast. An application of this method illustrates mapping main effect and interacting QTLs for heading time in the North American Barley Genome Mapping Project.

Identification of quantitative trait loci associated with resistance to viral haemorrhagic septicaemia (VHS) in turbot (Scophthalmus maximus ): a comparison between bacterium, parasite and virus diseases

One of the main objectives of genetic breeding programs in turbot industry is to reduce disease-related mortality. In the present study, a genome scan to detect quantitative trait loci (QTL) affecting resistance and survival to viral haemorrhagic septicaemia (VHS) was carried out. Three full-sib families with approximately 90 individuals each were genotyped and evaluated by linear regression and maximum likelihood approaches. In addition, a comparison between QTL detected for resistance and survival time to other important bacterial and parasite diseases affecting turbot (furunculosis and scuticociliatosis) was also carried out. Finally, the relationship between QTL affecting resistance/survival time to the virus and growth-related QTL was also evaluated. Several genomic regions controlling resistance and survival time to VHS were detected. Also significant associations between the evaluated traits and genotypes at particular markers were identified, explaining up to 14 % of the phenotypic variance. Several genomic regions controlling general and specific resistance to different diseases in turbot were detected. A preliminary gene mining approach identified candidate genes related to general or specific immunity. This information will be valuable to develop marker-assisted selection programs and to discover candidate genes related to disease resistance to improve turbot production.

Resistance to a rhabdovirus (VHSV) in rainbow trout: identification of a major QTL related to innate mechanisms

Health control is a major issue in animal breeding and a better knowledge of the genetic bases of resistance to diseases is needed in farm animals including fish. The detection of quantitative trait loci (QTL) will help uncovering the genetic architecture of important traits and understanding the mechanisms involved in resistance to pathogens. We report here the detection of QTL for resistance to Viral Haemorrhagic Septicaemia Virus (VHSV), a major threat for European aquaculture industry. Two induced mitogynogenetic doubled haploid F2 rainbow trout (Oncorhynchus mykiss) families were used. These families combined the genome of susceptible and resistant F0 breeders and contained only fully homozygous individuals. For phenotyping, fish survival after an immersion challenge with the virus was recorded, as well as in vitro virus replication on fin explants. A bidirectional selective genotyping strategy identified seven QTL associated to survival. One of those QTL was significant at the genome-wide level and largely explained both survival and viral replication in fin explants in the different families of the design (up to 65% and 49% of phenotypic variance explained respectively). These results evidence the key role of innate defence in resistance to the virus and pave the way for the identification of the gene(s) responsible for resistance. The identification of a major QTL also opens appealing perspectives for selective breeding of fish with improved resistance.

Parametric proportional hazards model for mapping genomic imprinting of survival traits

A number of imprinted genes have been observed in plants, animals and humans. They not only control growth and developmental traits, but may also be responsible for survival traits. Based on the Cox proportional hazards (PH) model, we constructed a general parametric model for dissecting genomic imprinting, in which a baseline hazard function is selectable for fitting the effects of imprinted quantitative trait loci (iQTL) genotypes on the survival curve. The expectation-maximisation (EM) algorithm is derived for solving the maximum likelihood estimates of iQTL parameters. The imprinting patterns of the detected iQTL are statistically tested under a series of null hypotheses. The Bayesian information criterion (BIC) model selection criterion is employed to choose an optimal baseline hazard function with maximum likelihood and parsimonious parameterisation. We applied the proposed approach to analyse the published data in an F(2) population of mice and concluded that, among five commonly used survival distributions, the log-logistic distribution is the optimal baseline hazard function for the survival time of hyperoxic acute lung injury (HALI). Under this optimal model, five QTL were detected, among which four are imprinted in different imprinting patterns.

Uncovering QTL for resistance and survival time to Philasterides dicentrarchi in turbot (Scophthalmus maximus)

Disease resistance-related traits have received increasing importance in aquaculture breeding programs worldwide. Currently, genomic information offers new possibilities in breeding to address the improvement of this kind of traits. The turbot is one of the most promising European aquaculture species, and Philasterides dicentrarchi is a scuticociliate parasite causing fatal disease in farmed turbot. An appealing approach to fight against disease is to achieve a more robust broodstock, which could prevent or diminish the devastating effects of scuticociliatosis on farmed individuals. In the present study, a genome scan for quantitative trait loci (QTL) affecting resistance and survival time to P. dicentrarchi in four turbot families was carried out. The objectives were to identify QTL using different statistical approaches [linear regression (LR) and maximum likelihood (ML)] and to locate significantly associated markers for their application in genetic breeding strategies. Several genomic regions controlling resistance and survival time to P. dicentrarchi were detected. When analyzing each family separately, significant QTL for resistance were identified by the LR method in two linkage groups (LG1 and LG9) and for survival time in LG1, while the ML methodology identified QTL for resistance in LG9 and LG23 and for survival time in LG6 and LG23. The analysis of the total data set identified an additional significant QTL for resistance and survival time in LG3 with the LR method. Significant association between disease resistance-related traits and genotypes was detected for several markers, a single one explaining up to 22% of the phenotypic variance. Obtained results will be essential to identify candidate genes for resistance and to apply them in marker-assisted selection programs to improve turbot production.

Characterization of genomic imprinting effects and patterns with parametric accelerated failure time model

Genomic imprinting, a genetic phenomenon of non-equivalent allele expression that depends on parental origins, has been ubiquitously observed in nature. It does not only control the traits of growth and development but also may be responsible for survival traits. Based on the accelerated failure time model, we construct a general parametric model for mapping the imprinted QTL (iQTL). Within the framework of interval mapping, maximum likelihood estimation of iQTL parameters is implemented via EM algorithm. The imprinting patterns of the detected iQTL are statistically tested according to a series of null hypotheses. BIC model selection criterion is employed to choose an optimal baseline hazard function with maximum likelihood and parsimonious parameters. Simulations are used to validate the proposed mapping procedure. A published dataset from a mouse model system was used to illustrate the proposed framework. Results show that among the five commonly used survival distributions, Log-logistic distribution is the optimal baseline hazard function for mapping QTL of hyperoxic acute lung injury (HALI) survival; under the log-logistic distribution, four QTLs were identified, in which only one QTL was inherited in Mendelian fashion, whereas others were imprinted in different imprinting patterns.

QTL detection for Aeromonas salmonicida resistance related traits in turbot (Scophthalmus maximus)

Background

Interactions between fish and pathogens, that may be harmless under natural conditions, often result in serious diseases in aquaculture systems. This is especially important due to the fact that the strains used in aquaculture are derived from wild strains that may not have had enough time to adapt to new disease pressures. The turbot is one of the most promising European aquaculture species. Furunculosis, caused by the bacterium Aeromonas salmonicida, produces important losses to turbot industry. An appealing solution is to achieve more robust broodstock, which can prevent or diminish the devastating effects of epizooties. Genomics strategies have been developed in turbot to look for candidate genes for resistance to furunculosis and a genetic map with appropriate density to screen for genomic associations has been also constructed. In the present study, a genome scan for QTL affecting resistance and survival to A. salmonicida in four turbot families was carried out. The objectives were to identify consistent QTL using different statistical approaches (linear regression and maximum likelihood) and to locate the tightest associated markers for their application in genetic breeding strategies.

Results

Significant QTL for resistance were identified by the linear regression method in three linkage groups (LGs 4, 6 and 9) and for survival in two LGs (6 and 9). The maximum likelihood methodology identified QTL in three LGs (5, 6 and 9) for both traits. Significant association between disease traits and genotypes was detected for several markers, some of them explaining up to 17% of the phenotypic variance. We also identified candidate genes located in the detected QTL using data from previously mapped markers.

Conclusions

Several regions controlling resistance to A. salmonicida in turbot have been detected. The observed concordance between different statistical methods at particular linkage groups gives consistency to our results. The detected associated markers could be useful for genetic breeding strategies. A finer mapping will be necessary at the detected QTL intervals to narrow associations and around the closely associated markers to look for candidate genes through comparative genomics or positional cloning strategies. The identification of associated variants at specific genes will be essential, together with the QTL associations detected in this study, for future marker assisted selection programs.

Evaluating markers in selected genes for association with functional longevity of dairy cattle

Background

Longevity expressed as the number of days between birth and death is a trait of great importance for both human and animal populations. In our analysis we use dairy cattle to demonstrate how the association of Single Nucleotide Polymorphisms (SNPs) located within selected genes with longevity can be modeled. Such an approach can be extended to any genotyped population with time to endpoint information available. Our study is focused on selected genes in order to answer the question whether genes, known to be involved into the physiological determination of milk production, also influence individual's survival.

Results

Generally, the highest risk differences among animals with different genotypes are observed for polymorphisms located within the leptin gene. The polymorphism with a highest effect on functional longevity is LEP-R25C, for which the relative risk of culling for cows with genotype CC is 3.14 times higher than for the heterozygous animals. Apart from LEP-R25C, also FF homozygotes at the LEP-Y7F substitution attribute 3.64 times higher risk of culling than the YY homozygotes and VV homozygotes at LEP-A80V have 1.83 times higher risk of culling than AA homozygotes. Differences in risks between genotypes of polymorphisms within the other genes (the butyrophilin subfamily 1 member A1 gene, BTN1A1; the acyl-CoA:diacylglycerol acyltransferase 1 gene, DGAT1; the leptin receptor gene, LEPR; the ATP-binding cassette sub-family G member 2, ABCG2) are much smaller.

Conclusions

Our results indicate association between LEP and longevity and are very well supported by results of other studies related to dairy cattle. In view of the growing importance of functional traits in dairy cattle, LEP polymorphisms should be considered as markers supporting selection decisions. Furthermore, since the relationship between both LEP polymorphism and its protein product with longevity in humans is well documented, with our result we were able to demonstrate that livestock with its detailed records of family structure, genetic, and environmental factors as well as extensive trait recording can be a good model organism for research aspects related to humans.

Identification of new quantitative trait Loci (other than the PRNP gene) modulating the scrapie incubation period in sheep

Although susceptibility to scrapie is largely controlled by the PRNP gene, we have searched for additional genomic regions that affect scrapie incubation time in sheep, using two half-sib families with a susceptible PRNP genotype and naturally infected by scrapie. Quantitative trait loci were detected on OAR6 and OAR18.

Mapping quantitative trait loci from a single-tail sample of the phenotype distribution including survival data

A new effective Bayesian quantitative trait locus (QTL) mapping approach for the analysis of single-tail selected samples of the phenotype distribution is presented. The approach extends the affected-only tests to single-tail sampling with quantitative traits such as the log-normal survival time or censored/selected traits. A great benefit of the approach is that it enables the utilization of multiple-QTL models, is easy to incorporate into different data designs (experimental and outbred populations), and can potentially be extended to epistatic models. In inbred lines, the method exploits the fact that the parental mating type and the linkage phases (haplotypes) are known by definition. In outbred populations, two-generation data are needed, for example, selected offspring and one of the parents (the sires) in breeding material. The idea is to statistically (computationally) generate a fully complementary, maximally dissimilar, observation for each offspring in the sample. Bayesian data augmentation is then used to sample the space of possible trait values for the pseudoobservations. The benefits of the approach are illustrated using simulated data sets and a real data set on the survival of F(2) mice following infection with Listeria monocytogenes.

Mapping temporally varying quantitative trait loci in time-to-failure experiments

Existing methods for mapping quantitative trait loci (QTL) in time-to-failure experiments assume that the QTL effect is constant over the course of the study. This assumption may be violated when the gene(s) underlying the QTL are up- or downregulated on a biologically meaningful timescale. In such situations, models that assume a constant effect can fail to detect QTL in a whole-genome scan. To investigate this possibility, we utilize an extension of the Cox model (EC model) within an interval-mapping framework. In its simplest form, this model assumes that the QTL effect changes at some time point t0 and follows a linear function before and after this change point. The approximate time point at which this change occurs is estimated. Using simulated and real data, we compare the mapping performance of the EC model to the Cox proportional hazards (CPH) model, which explicitly assumes a constant effect. The results show that the EC model detects time-dependent QTL, which the CPH model fails to detect. At the same time, the EC model recovers all of the QTL the CPH model detects. We conclude that potentially important QTL may be missed if their time-dependent effects are not accounted for.

A simple linear regression method for quantitative trait loci linkage analysis with censored observations

Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using simulation we compare this method to both the Cox and Weibull proportional hazards models and a standard linear regression method that ignores censoring. The grouped linear regression method is of equivalent power to both the Cox and Weibull proportional hazards methods and is significantly better than the standard linear regression method when censored observations are present. The method is also robust to the proportion of censored individuals and the underlying distribution of the trait. On the basis of linear regression methodology, the grouped linear regression model is computationally simple and fast and can be implemented readily in freely available statistical software.