The quantitative genetics of the prevalence of infectious diseases: hidden genetic variation due to indirect genetic effects dominates heritable variation and response to selection

Infectious diseases have profound effects on life, both in nature and agriculture. However, a quantitative genetic theory of the host population for the endemic prevalence of infectious diseases is almost entirely lacking. While several studies have demonstrated the relevance of transmission of infections for heritable variation and response to selection, current quantitative genetics ignores transmission. Thus, we lack concepts of breeding value and heritable variation for endemic prevalence, and poorly understand response of endemic prevalence to selection. Here, we integrate quantitative genetics and epidemiology, and propose a quantitative genetic theory for the basic reproduction number R₀ and for the endemic prevalence of an infection. We first identify the genetic factors that determine the prevalence. Subsequently, we investigate the population-level consequences of individual genetic variation, for both R0 and the endemic prevalence. Next, we present expressions for the breeding value and heritable variation, for endemic prevalence and individual binary disease status, and show that these depend strongly on the prevalence. Results show that heritable variation for endemic prevalence is substantially greater than currently believed, and increases strongly when prevalence decreases, while heritability of disease status approaches zero. As a consequence, response of the endemic prevalence to selection for lower disease status accelerates considerably when prevalence decreases, in contrast to classical predictions. Finally, we show that most heritable variation for the endemic prevalence is hidden in indirect genetic effects, suggesting a key role for kin-group selection in the evolutionary history of current populations and for genetic improvement in animals and plants.     

A Novel Statistical Model to Estimate Host Genetic Effects Affecting Disease Transmission

There is increasing recognition that genetic diversity can affect the spread of diseases, potentially affecting plant and livestock disease control as well as the emergence of human disease outbreaks. Nevertheless, even though computational tools can guide the control of infectious diseases, few epidemiological models can simultaneously accommodate the inherent individual heterogeneity in multiple infectious disease traits influencing disease transmission, such as the frequently modeled propensity to become infected and infectivity, which describes the host ability to transmit the infection to susceptible individuals. Furthermore, current quantitative genetic models fail to fully capture the heritable variation in host infectivity, mainly because they cannot accommodate the nonlinear infection dynamics underlying epidemiological data. We present in this article a novel statistical model and an inference method to estimate genetic parameters associated with both host susceptibility and infectivity. Our methodology combines quantitative genetic models of social interactions with stochastic processes to model the random, nonlinear, and dynamic nature of infections and uses adaptive Bayesian computational techniques to estimate the model parameters. Results using simulated epidemic data show that our model can accurately estimate heritabilities and genetic risks not only of susceptibility but also of infectivity, therefore exploring a trait whose heritable variation is currently ignored in disease genetics and can greatly influence the spread of infectious diseases. Our proposed methodology offers potential impacts in areas such as livestock disease control through selective breeding and also in predicting and controlling the emergence of disease outbreaks in human populations.     

An SIS patch model with variable transmission coefficients

In this paper, an SIS patch model with non-constant transmission coefficients is formulated to investigate the effect of media coverage and human movement on the spread of infectious diseases among patches. The basic reproduction number R₀ is determined. It is shown that the disease-free equilibrium is globally asymptotically stable if R₀?1, and the disease is uniformly persistent and there exists at least one endemic equilibrium if R₀>1. In particular, when the disease is non-fatal and the travel rates of susceptible and infectious individuals in each patch are the same, the endemic equilibrium is unique and is globally asymptotically stable as R₀>1. Numerical calculations are performed to illustrate some results for the case with two patches.     

Quantitative genetics of taura syndrome resistance in pacific white shrimp (penaeus vannamei): a cure model approach

Background

In aquaculture breeding, resistance against infectious diseases is commonly assessed as time until death under exposure to a pathogen. For some diseases, a fraction of the individuals may appear as "cured" (non-susceptible), and the resulting survival time may thus be a result of two confounded underlying traits, i.e., endurance (individual hazard) and susceptibility (whether at risk or not), which may be accounted for by fitting a cure survival model. We applied a cure model to survival data of Pacific white shrimp (Penaeus vannamei) challenged with the Taura syndrome virus, which is one of the major pathogens of Panaeid shrimp species.

Methods

In total, 15,261 individuals of 513 full-sib families from three generations were challenge-tested in 21 separate tests (tanks). All challenge-tests were run until mortality naturally ceased. Time-until-event data were analyzed with a mixed cure survival model using Gibbs sampling, treating susceptibility and endurance as separate genetic traits.

Results

Overall mortality at the end of test was 28%, while 38% of the population was considered susceptible to the disease. The estimated underlying heritability was high for susceptibility (0.41 ± 0.07), but low for endurance (0.07 ± 0.03). Furthermore, endurance and susceptibility were distinct genetic traits (r_g = 0.22 ± 0.25). Estimated breeding values for endurance and susceptibility were only moderately correlated (0.50), while estimated breeding values from classical models for analysis of challenge-test survival (ignoring the cured fraction) were closely correlated with estimated breeding values for susceptibility, but less correlated with estimated breeding values for endurance.

Conclusions

For Taura syndrome resistance, endurance and susceptibility are apparently distinct genetic traits. However, genetic evaluation of susceptibility based on the cure model showed clear associations with standard genetic evaluations that ignore the cure fraction for these data. Using the current testing design, genetic variation in observed survival time and absolute survival at the end of test were most likely dominated by genetic variation in susceptibility. If the aim is to reduce susceptibility, earlier termination of the challenge-test or back-truncation of the follow-up period should be avoided, as this may shift focus of selection towards endurance rather than susceptibility.     

Why genetic selection to reduce the prevalence of infectious diseases is way more promising than currently believed

Genetic selection for improved disease resistance is an important part of strategies to combat infectious diseases in agriculture. Quantitative genetic analyses of binary disease status, however, indicate low heritability for most diseases, which restricts the rate of genetic reduction in disease prevalence. Moreover, the common liability threshold model suggests that eradication of an infectious disease via genetic selection is impossible because the observed-scale heritability goes to zero when the prevalence approaches zero. From infectious disease epidemiology, however, we know that eradication of infectious diseases is possible, both in theory and practice, because of positive feedback mechanisms leading to the phenomenon known as herd immunity. The common quantitative genetic models, however, ignore these feedback mechanisms. Here, we integrate quantitative genetic analysis of binary disease status with epidemiological models of transmission, aiming to identify the potential response to selection for reducing the prevalence of endemic infectious diseases. The results show that typical heritability values of binary disease status correspond to a very substantial genetic variation in disease susceptibility among individuals. Moreover, our results show that eradication of infectious diseases by genetic selection is possible in principle. These findings strongly disagree with predictions based on common quantitative genetic models, which ignore the positive feedback effects that occur when reducing the transmission of infectious diseases. Those feedback effects are a specific kind of Indirect Genetic Effects; they contribute substantially to the response to selection and the development of herd immunity (i.e., an effective reproduction ratio less than one).     

Potential Response to Selection of HSP70 as a Component of Innate Immunity in the Abalone Haliotis rufescens

Assessing components of the immune system may reflect disease resistance. In some invertebrates, heat shock proteins (HSPs) are immune effectors and have been described as potent activators of the innate immune response. Several diseases have become a threat to abalone farming worldwide; therefore, increasing disease resistance is considered to be a long-term goal for breeding programs. A trait will respond to selection only if it is determined partially by additive genetic variation. The aim of this study was to estimate the heritability (h ²) and the additive genetic coefficient of variation (CV _A) of HSP70 as a component of innate immunity of the abalone Haliotis rufescens, in order to assess its potential response to selection. These genetic components were estimated for the variations in the intracellular (in haemocytes) and extracellular (serum) protein levels of HSP70 in response to an immunostimulant agent in 60 full-sib families of H. rufescens. Levels of HSP70 were measured twice in the same individuals, first when they were young and again when they were pre-harvest adults, to estimate the repeatability (R), the h ² and the potential response to selection of these traits at these life stages. High HSP70 levels were observed in abalones subjected to immunostimulation in both the intracellular and extracellular haemolymph fractions. This is the first time that changes in serum levels of HSP70 have been reported in response to an immune challenge in molluscs. HSP70 levels in both fractions and at both ages showed low h ² and R, with values that were not significantly different from zero. However, HSP70 induced levels had a CV _A of 13.3–16.2% in young adults and of 2.7–8.1% in pre-harvest adults. Thus, despite its low h ², HSP70 synthesis in response to an immune challenge in red abalone has the potential to evolve through selection because of its large phenotypic variation and the presence of additive genetic variance, especially in young animals.     

Malaria's Missing Number: Calculating the Human Component of R0 by a Within-Host Mechanistic Model of Plasmodium falciparum Infection and Transmission

Human infection by malarial parasites of the genus Plasmodium begins with the bite of an infected Anopheles mosquito. Current estimates place malaria mortality at over 650,000 individuals each year, mostly in African children. Efforts to reduce disease burden can benefit from the development of mathematical models of disease transmission. To date, however, comprehensive modeling of the parameters defining human infectivity to mosquitoes has remained elusive. Here, we describe a mechanistic within-host model of Plasmodium falciparum infection in humans and pathogen transmission to the mosquito vector. Our model incorporates the entire parasite lifecycle, including the intra-erythrocytic asexual forms responsible for disease, the onset of symptoms, the development and maturation of intra-erythrocytic gametocytes that are transmissible to Anopheles mosquitoes, and human-to-mosquito infectivity. These model components were parameterized from malaria therapy data and other studies to simulate individual infections, and the ensemble of outputs was found to reproduce the full range of patient responses to infection. Using this model, we assessed human infectivity over the course of untreated infections and examined the effects in relation to transmission intensity, expressed by the basic reproduction number R₀ (defined as the number of secondary cases produced by a single typical infection in a completely susceptible population). Our studies predict that net human-to-mosquito infectivity from a single non-immune individual is on average equal to 32 fully infectious days. This estimate of mean infectivity is equivalent to calculating the human component of malarial R₀. We also predict that mean daily infectivity exceeds five percent for approximately 138 days. The mechanistic framework described herein, made available as stand-alone software, will enable investigators to conduct detailed studies into theories of malaria control, including the effects of drug treatment and drug resistance on transmission.     

Molecular Evolution of the Sorghum Maturity Gene Ma3

Time to maturity is a critical trait in sorghum (Sorghum bicolor) breeding, as it determines whether a variety can be grown in a particular cropping system or ecosystem. Understanding the nucleotide variation and the mechanisms of molecular evolution of the maturity genes would be helpful for breeding programs. In this study, we analyzed the nucleotide diversity of Ma₃, an important maturity gene in sorghum, using 252 cultivated and wild sorghum materials from all over the world. The nucleotide variation and diversity were analyzed based both on race- and usage-based groups. We also sequenced 12 genes around the Ma₃ gene in 185 of these materials to search for a selective sweep and found that purifying selection was the strongest force on Ma₃, as low nucleotide diversity and low-frequency amino acid variants were observed. However, a very special mutation, described as ma₃^R, seemed to be under positive selection, as indicated by dramatically reduced nucleotide variation not only at the loci but also in the surrounding regions among individuals carrying the mutations. In addition, in an association study using the Ma₃ nucleotide variations, we detected 3 significant SNPs for the heading date at a high-latitude environment (Beijing) and 17 at a low-latitude environment (Hainan). The results of this study increases our understanding of the evolutionary mechanisms of the maturity genes in sorghum and will be useful in sorghum breeding.     

Sheep Movement Networks and the Transmission of Infectious Diseases

Background and Methodology

Various approaches have been used to investigate how properties of farm contact networks impact on the transmission of infectious diseases. The potential for transmission of an infection through a contact network can be evaluated in terms of the basic reproduction number, R ₀. The magnitude of R ₀ is related to the mean contact rate of a host, in this case a farm, and is further influenced by heterogeneities in contact rates of individual hosts. The latter can be evaluated as the second order moments of the contact matrix (variances in contact rates, and co-variance between contacts to and from individual hosts). Here we calculate these quantities for the farms in a country-wide livestock network: >15,000 Scottish sheep farms in each of 4 years from July 2003 to June 2007. The analysis is relevant to endemic and chronic infections with prolonged periods of infectivity of affected animals, and uses different weightings of contacts to address disease scenarios of low, intermediate and high animal-level prevalence.

Principal Findings and Conclusions

Analysis of networks of Scottish farms via sheep movements from July 2003 to June 2007 suggests that heterogeneities in movement patterns (variances and covariances of rates of movement on and off the farms) make a substantial contribution to the potential for the transmission of infectious diseases, quantified as R ₀, within the farm population. A small percentage of farms (<20%) contribute the bulk of the transmission potential (>80%) and these farms could be efficiently targeted by interventions aimed at reducing spread of diseases via animal movement.     

Genetic variation in outcrossing rate and correlated floral traits in a population of grain amaranth (Amaranthus cruentus L.)

The genetic control of breeding system in a population of grain amaranth is described here by the estimates of outcrossing rate variation among individuals and their response to mass selection. In the first generation (S₀), a single morphological marker locus(R/r) controlling plant pigmentation was used for the estimation of outcrossing rate. A mixture of genotypes RR (red) and rr (green) mixed in equal proportions was grown and all rr plants were progeny-tested for estimating the outcrossing rate (t), using the relationship t=H/p, where H = proportion of heterozygotes (Rr) in the progeny, and p = frequency of alleleR. A full range (0 to 100%) of outcrossing rates was found in the first generation, % MathType!MTEF!2!1!+-% feaafiart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGabeiDayaara% Gaeyypa0JaaGimaiaac6cacaaIZaGaaGymaiaacYcacqGHGaaicqGH% GaaicuaHdpWCgaqcamaaBaaaleaacaqG0baabeaakiabg2da9iaaic% dacaGGUaGaaGOmaiaaiwdaaaa!441B!\[{\text{\bar t}} = 0.31, \hat \sigma _{\text{t}} = 0.25\], and the distribution was significantly skewed toward high outcrossing.A bidirectional mass selection experiment was initiated for high and low outcrossing rates. In the Hi and Lo lines (Generation S₁), the rate of outcrossing was estimated using the R locus in addition to two other completely dominant morphological markers(B, G1). Relative sex ratios in the monoecious inflorescences of selected lines were estimated by the number of male flowers per glomerule. Outcrossing rate was significantly different between the Hi and Lo lines, and Lo line exhibited much higher male fertility than the Hi line. Such a response to selection indicated a polygenic control of sex expression, and consequently, of the potential for outcrossing in this population. In the second generation (S₂), selection was based on the number of male flowers/glomerule as an index of outcrossing ability. Differences in sex expression between the Hi and Lo lines in S₂ generation had 1.0 male flower/glomerule, while the Hi selection individuals had more or less rectangular distribution from 0.1 to 1.0 male flowers/glomerule.Thus, breeding system in amaranth, as represented by the sex ratios within glomerules and the outcrossing rate parameters, responded to bidirectional selection. Such a genetic component of variation in breeding system has significant implications in the evolution of amaranth species and landraces under domestication.     

Heterogeneity in susceptibility to infection can explain high reinfection rates

Heterogeneity in susceptibility and infectivity is inherent to infectious disease transmission in nature. Here we are concerned with the formulation of mathematical models that capture the essence of heterogeneity while keeping a simple structure suitable of analytical treatment. We explore the consequences of host heterogeneity in the susceptibility to infection for epidemiological models for which immunity conferred by infection is partially protective, known as susceptible-infected-recovered-infected (SIRI) models. We analyze the impact of heterogeneity on disease prevalence and contrast the susceptibility profiles of the subpopulations at risk for primary infection and reinfection. We present a systematic study in the case of two frailty groups.We predict that the average rate of reinfection may be higher than the average rate of primary infection, which may seem paradoxical given that primary infection induces life-long partial protection. Infection generates a selection mechanism whereby fit individuals remain in S and frail individuals are transferred to R. If this effect is strong enough we have a scenario where, on average, the rate of reinfection is higher than the rate of primary infection even though each individual has a risk reduction following primary infection. This mechanism may explain high rates of tuberculosis reinfection recently reported.Finally, the enhanced benefits of vaccination strategies that target the high-risk groups are quantified.     

MSH1-Induced Non-Genetic Variation Provides a Source of Phenotypic Diversity in Sorghum bicolor

MutS Homolog 1 (MSH1) encodes a plant-specific protein that functions in mitochondria and chloroplasts. We showed previously that disruption or suppression of the MSH1 gene results in a process of developmental reprogramming that is heritable and non-genetic in subsequent generations. In Arabidopsis, this developmental reprogramming process is accompanied by striking changes in gene expression of organellar and stress response genes. This developmentally reprogrammed state, when used in crossing, results in a range of variation for plant growth potential. Here we investigate the implications of MSH1 modulation in a crop species. We found that MSH1-mediated phenotypic variation in Sorghum bicolor is heritable and potentially valuable for crop breeding. We observed phenotypic variation for grain yield, plant height, flowering time, panicle architecture, and above-ground biomass. Focusing on grain yield and plant height, we found some lines that appeared to respond to selection. Based on amenability of this system to implementation in a range of crops, and the scope of phenotypic variation that is derived, our results suggest that MSH1 suppression provides a novel approach for breeding in crops.     

A general definition of the heritable variation that determines the potential of a population to respond to selection

Genetic selection is a major force shaping life on earth. In classical genetic theory, response to selection is the product of the strength of selection and the additive genetic variance in a trait. The additive genetic variance reflects a population's intrinsic potential to respond to selection. The ordinary additive genetic variance, however, ignores the social organization of life. With social interactions among individuals, individual trait values may depend on genes in others, a phenomenon known as indirect genetic effects. Models accounting for indirect genetic effects, however, lack a general definition of heritable variation. Here I propose a general definition of the heritable variation that determines the potential of a population to respond to selection. This generalizes the concept of heritable variance to any inheritance model and level of organization. The result shows that heritable variance determining potential response to selection is the variance among individuals in the heritable quantity that determines the population mean trait value, rather than the usual additive genetic component of phenotypic variance. It follows, therefore, that heritable variance may exceed phenotypic variance among individuals, which is impossible in classical theory. This work also provides a measure of the utilization of heritable variation for response to selection and integrates two well-known models of maternal genetic effects. The result shows that relatedness between the focal individual and the individuals affecting its fitness is a key determinant of the utilization of heritable variance for response to selection.     

Stability of differential susceptibility and infectivity epidemic models

We introduce classes of differential susceptibility and infectivity epidemic models. These models address the problem of flows between the different susceptible, infectious and infected compartments and differential death rates as well. We prove the global stability of the disease free equilibrium when the basic reproduction ratio R₀ ￡ 1{\mathcal{R}_0 \leq 1} and the existence and uniqueness of an endemic equilibrium when ${\mathcal{R}_0 >1 }${\mathcal{R}_0 >1 } . We also prove the global asymptotic stability of the endemic equilibrium for a differential susceptibility and staged progression infectivity model, when ${\mathcal{R}_0 >1 }${\mathcal{R}_0 >1 } . Our results encompass and generalize those of Hyman and Li (J Math Biol 50:626–644, 2005; Math Biosci Eng 3:89–100, 2006).     

The basic reproduction number and the probability of extinction for a dynamic epidemic model

We consider the spread of an epidemic through a population divided into n sub-populations, in which individuals move between populations according to a Markov transition matrix Σ and infectives can only make infectious contacts with members of their current population. Expressions for the basic reproduction number, R₀, and the probability of extinction of the epidemic are derived. It is shown that in contrast to contact distribution models, the distribution of the infectious period effects both the basic reproduction number and the probability of extinction of the epidemic in the limit as the total population size N → ∞. The interactions between the infectious period distribution and the transition matrix Σ mean that it is not possible to draw general conclusions about the effects on R₀ and the probability of extinction. However, it is shown that for n = 2, the basic reproduction number, R₀, is maximised by a constant length infectious period and is decreasing in ?, the speed of movement between the two populations.     

Experimental evolution of infectious behaviour in a facultative ectoparasite

Parasitic lifestyles have evolved many times in animals, but how such life‐history strategies evolved from free‐living ancestors remains a great puzzle. Transitional symbiotic strategies, such as facultative parasitism, are hypothesized evolutionary stepping stones towards obligate parasitism. However, to consider this hypothesis, heritable genetic variation in infectious behaviour of transitional symbiotic strategies must exist. In this study, we experimentally evolved infectivity and estimated the additive genetic variation in a facultative parasite. We performed artificial selection experiments in which we selected for either increased or decreased propensity to infect in a facultatively parasitic mite (Macrocheles muscaedomesticae). Here, infectiousness was expressed in terms of mite attachment to a host (Drosophila hydei) and modelled as a threshold trait. Mites responded positively to selection for increased infectivity; realized heritability of infectious behaviour was significantly different from zero and estimated to be 16.6% (±4.4% SE). Further, infection prevalence was monitored for 20 generations post‐selection. Selected lines continued to display relatively high levels of infection, demonstrating a degree of genetic stability in infectiousness. Our study is the first to provide an estimate of heritability and additive genetic variation for infectious behaviour in a facultative parasite, which suggests natural selection can act upon facultative strategies with important implications for the evolution of parasitism.     

Multilevel selection 1: Quantitative genetics of inheritance and response to selection

Interaction among individuals is universal, both in animals and in plants, and substantially affects evolution of natural populations and responses to artificial selection in agriculture. Although quantitative genetics has successfully been applied to many traits, it does not provide a general theory accounting for interaction among individuals and selection acting on multiple levels. Consequently, current quantitative genetic theory fails to explain why some traits do not respond to selection among individuals, but respond greatly to selection among groups. Understanding the full impacts of heritable interactions on the outcomes of selection requires a quantitative genetic framework including all levels of selection and relatedness. Here we present such a framework and provide expressions for the response to selection. Results show that interaction among individuals may create substantial heritable variation, which is hidden to classical analyses. Selection acting on higher levels of organization captures this hidden variation and therefore always yields positive response, whereas individual selection may yield response in the opposite direction. Our work provides testable predictions of response to multilevel selection and reduces to classical theory in the absence of interaction. Statistical methodology provided elsewhere enables empirical application of our work to both natural and domestic populations.     

Seasonal dynamics and thresholds governing recurrent epidemics

Driven by seasonality, many common recurrent infectious diseases are characterized by strong annual, biennial and sometimes irregular oscillations in the absence of vaccination programs. Using the seasonally forced SIR epidemic model, we are able to provide new insights into the dynamics of recurrent diseases and, in some cases, specific predictions about individual outbreaks. The analysis reveals a new threshold effect that gives clear conditions for the triggering of future disease outbreaks or their absence. The threshold depends critically on the susceptibility S ₀ of the population after an outbreak. We show that in the presence of seasonality, forecasts based on the susceptibility S ₀ are more reliable than those based on the classical reproductive number R ₀ from the conventional theory.      

Indirect genetic effects underlie oxygen-limited thermal tolerance within a coastal population of chinook salmon

With global temperatures projected to surpass the limits of thermal tolerance for many species, evaluating the heritable variation underlying thermal tolerance is critical for understanding the potential for adaptation to climate change. We examined the evolutionary potential of thermal tolerance within a population of chinook salmon (Oncorhynchus tshawytscha) by conducting a full-factorial breeding design and measuring the thermal performance of cardiac function and the critical thermal maximum (CT_max) of offspring from each family. Additive genetic variation in offspring phenotype was mostly negligible, although these direct genetic effects explained 53% of the variation in resting heart rate (f_H). Conversely, maternal effects had a significant influence on resting f_H, scope for f_H, cardiac arrhythmia temperature and CT_max. These maternal effects were associated with egg size, as indicated by strong relationships between the mean egg diameter of mothers and offspring thermal tolerance. Because egg size can be highly heritable in chinook salmon, our finding indicates that the maternal effects of egg size constitute an indirect genetic effect contributing to thermal tolerance. Such indirect genetic effects could accelerate evolutionary responses to the selection imposed by rising temperatures and could contribute to the population-specific thermal tolerance that has recently been uncovered among Pacific salmon populations.     

A DNA test for routine prediction in breeding of peach blush,Ppe-R<Subscript>f</Subscript>-SSR

Blush, the proportion of red overcolor on the skin surface of fruit, is highly variable in peach breeding germplasm and is important in the marketing of peach fruit. The fresh market peach industry demands a high level of blush to entice consumers, while the processing peach industry requires minimal blush. Therefore, blush is a major selection criterion in breeding programs. The use of DNA-based information could improve breeding efficiency and accuracy for fruit blush coverage, but a predictive DNA test is required. The objective of this study was to develop a DNA test for the prediction of blush coverage by targeting the major locus, R _f , associated with blush variation. Initially, haplotypes were developed based on five SNP markers associated with variation in blush coverage. To convert the 5-SNP haplotype test into a single, simple PCR-based assay, 11 simple sequence repeat markers were designed and used to screen individuals representing all SNP haplotypes. The most informative assay, named Ppe-R_f-SSR, was chosen to screen 200 individuals of the RosBREED peach reference germplasm set that incorporated germplasm from four breeding programs. Ppe-R_f-SSR accurately differentiated individuals with high-, medium-, and low-blush coverage in most lineages. Outcomes highlighted that DNA tests can be quite predictive for some breeding programs or specific germplasm sets, while for others the predictiveness can falter. Therefore, the confirmation of genotype effects for any DNA test is recommended in new germplasm before routine use. The prediction accuracy and breeding utility of Ppe-R_f-SSR in the University of Arkansas breeding program were subsequently confirmed by screening 443 seedlings, independent of the initial DNA test development process, derived from 18 cross-combinations of 28 parents. Ppe-R_f-SSR can be used to efficiently and accurately predict fruit blush coverage, especially in fresh market germplasm, and has been deployed for routine use in the University of Arkansas peach breeding program.