Impact of reconstructed pedigrees on progeny-test breeding values in red spruce

Pedigrees reconstructed through DNA marker assigned paternities in polymix (PMX) and open pollinated (OP) progeny tests were analyzed using mixed models to test the effect of unequal male reproductive success and pedigree errors on quantitative genetic parameters. The reconstructed pedigree increased heritabilities in the larger PMX test. Increased heritability resulted from adding the paternities to the pedigree per se, not by correcting the male reproductive bias by specifying the exact pedigree. Removing hypothesized pedigree errors had no effect on quantitative parameters, either because the magnitude of the errors was too small (PMX) or the progeny test was too small to detect variance components reliably (OP). Although there was no advantage in backwards selection, the increased additive variance, heritabilities and accuracy of progeny with assigned paternities in the pedigree, should permit forward selection of offspring with greater genetic gain and complete control of coancestry for future breeding decisions. Some possible breeding population structures with the new genetic information are discussed.     

Domestic estimated breeding values and genomic enhanced breeding values of bulls in comparison with their foreign genomic enhanced breeding values

Estimated breeding values (EBVs) and genomic enhanced breeding values (GEBVs) for milk production of young genotyped Holstein bulls were predicted using a conventional BLUP – Animal Model, a method fitting regression coefficients for loci (RRBLUP), a method utilizing the realized genomic relationship matrix (GBLUP), by a single-step procedure (ssGBLUP) and by a one-step blending procedure. Information sources for prediction were the nation-wide database of domestic Czech production records in the first lactation combined with deregressed proofs (DRP) from Interbull files (August 2013) and domestic test-day (TD) records for the first three lactations. Data from 2627 genotyped bulls were used, of which 2189 were already proven under domestic conditions. Analyses were run that used Interbull values for genotyped bulls only or that used Interbull values for all available sires. Resultant predictions were compared with GEBV of 96 young foreign bulls evaluated abroad and whose proofs were from Interbull method GMACE (August 2013) on the Czech scale. Correlations of predictions with GMACE values of foreign bulls ranged from 0.33 to 0.75. Combining domestic data with Interbull EBVs improved prediction of both EBV and GEBV. Predictions by Animal Model (traditional EBV) using only domestic first lactation records and GMACE values were correlated by only 0.33. Combining the nation-wide domestic database with all available DRP for genotyped and un-genotyped sires from Interbull resulted in an EBV correlation of 0.60, compared with 0.47 when only Interbull data were used. In all cases, GEBVs had higher correlations than traditional EBVs, and the highest correlations were for predictions from the ssGBLUP procedure using combined data (0.75), or with all available DRP from Interbull records only (one-step blending approach, 0.69). The ssGBLUP predictions using the first three domestic lactation records in the TD model were correlated with GMACE predictions by 0.69, 0.64 and 0.61 for milk yield, protein yield and fat yield, respectively.     

Impact of environmental disturbances on estimated genetic parameters and breeding values for growth traits in pigs

Due to the diversification of farming systems and climate change, farm animals are exposed to environmental disturbances to which they respond differently depending on their robustness. Disturbances such as heat stress or sanitary challenges (not always recorded, especially when they are of short duration and low intensity) have a transitory impact on animals, resulting in changes in phenotypes of production (feed intake, BW, etc.). The aim of this study was to evaluate the impact of such unknown disturbances on the estimated genetic parameters and breeding values (BV) for production traits. A population of 6 120 individuals over five generations divided into eight batches of 10 pens was generated, each individual underwent an ?100-day test period. A longitudinal phenotype mimicking piglet weight during the fattening period was simulated for each individual in two situations: disturbed and non-disturbed. The disturbed phenotype was modified according to the robustness of the animal and the intensity and duration of the disturbance that the animal was subjected to. Various sets of simulations (1 000 replicates per set) were considered depending on the type of disturbance (at the level of the batch, pen, or individual), the genetic correlation (negative, neutral, or positive) between the two components of the robustness (resistance and resilience), the genetic correlation (negative, neutral, or positive) between growth and the components of robustness, and the heritability of the components of robustness (weak or moderate). An animal model was used to estimate the genetic parameters and BV for two production traits: the BW at 100 days of age (BW₁₀₀) and average daily gain (ADG). The estimated heritability of the production traits was lower in the disturbed situation compared to the non-disturbed one (reduction of 0.08 and 0.05 points respectively for BW₁₀₀ and ADG). The correlations between estimated breeding values of the observed phenotypes (EBV) and BV for production traits in absence of disturbance were lower in the disturbed situation (reduction of 0.04 and 0.06 points for BW₁₀₀ and ADG respectively) while the partial correlation between EBV and BV for robustness was not significantly different from 0 in the two situations. These results suggest that selection in a well-controlled environment with random disturbances of low intensities does not allow to improve animal robustness while it is less effective for improving production traits than selection under no environmental disturbances.     

Old-growth red spruce communities in the mid-Appalachians

Old-growth stands of red spruce (Picea rubens) were sampled at the only four localities in the mountains of southwestern Virginia and central West Virginia where examples of such are known to exist. Based upon mean ages (±SE) of cored trees, sampled stands ranged in age from 164±18 to 201±10 yr. Dendro-ecological (tree-ring) analysis showed a marked decline in growth of trees at three localities during the late 1800s, followed by recovery to previous levels of growth within two decades. This growth-trend decline generally coincides with a period of extensive mortality of red spruce reported to have occurred in central West Virginia. Basal area of trees 2.5 cm DBH ranged from 35.4 to 46.1 m²/ha. These figures are considerably lower than those recorded at earlier dates for similar old-growth stands in the Appalachians, which suggests that a general decline has occurred over the last half-century.     

Impact of depth of pedigree and inclusion of historical data on the estimation of additive variance and breeding values in a sugarcane breeding program

Sugarcane breeders in Australia combine data across four selection programs to obtain estimates of breeding value for parents. When these data are combined with full pedigree information back to founding parents, computing limitations mean it is not possible to obtain information on all parents. Family data from one sugarcane selection program were analysed using two different genetic models to investigate how different depths of pedigree and amount of data affect the reliability of estimating breeding value of sugarcane parents. These were the parental and animal models. Additive variance components and breeding values estimated from different amounts of information were compared for both models. The accuracy of estimating additive variance components and breeding values improved as more pedigree information and historical data were included in analyses. However, adding years of data had a much larger effect on the estimation of variance components of the population, and breeding values of the parents. To accurately estimate breeding values of all sugarcane parents, a minimum of three generations of pedigree and 5 years of historical data were required, while more information (four generations of pedigree and 7 years of historical data) was required when identifying top parents to be selected for future cross pollination.     

Monitoring and managing genetic variation in group breeding populations without individual pedigrees

The genetic management of captive populations to conserve genetic variation is currently based on analyses of individual pedigrees to infer inbreeding and kinship coefficients and values of individuals as breeders. Such analyses require that individual pedigrees are known and individual pairing (mating) can be controlled. Many species in captivity, however, breed in groups due to various reasons, such as space constraints and fertility considerations for species living naturally in social groups, and thus have no pedigrees available for the traditional genetic analyses and management. In the absence of individual pedigree, such group breeding populations can still be genetically monitored, evaluated and managed by suitable population genetics models using population level information (such as census data). This article presents a simple genetic model of group breeding populations to demonstrate how to estimate the genetic variation maintained within and among populations and to optimise management based on these estimates. A numerical example is provided to illustrate the use of the proposed model. Some issues relevant to group breeding, such as the development and robustness evaluation of the population genetics model appropriate for a particular species under specific management and recording systems and the genetic monitoring with markers, are also briefly discussed.     

Characterization of the short needle phenomenon in red spruce

Red spruce trees (Picea rubens Sarg.) occasionally produce short twigs bearing short needles. The frequency of short needle cohorts is positively correlated with both elevation and defoliation and they are found in greater numbers on trees that regularly experience winter injury. Short needles are smaller, have lower fresh and dry weights, and reduced volumes compared with normal needles. They have reduced cross-sectional areas due to smaller areas of stelar and mesophyll tissue systems. Individual mesophyll cells, however, have the same cross- and longitudinal sectional areas. On a weight or volume basis, both short and normal needles contain similar amounts of chlorophyll and carotenoid pigments. When pigment concentration was calculated on a unit needle or a needle area base, short needles contain more pigment than normal needles. Short needles appear to have a greater photosynthetic efficiency as determined by fluorescence measurements.     

Congruence between selection on breeding values and farmers' selection criteria in sheep breeding under conventional nucleus breeding schemes

Designing breeding schemes suitable for smallholder livestock production systems in developing regions has hitherto been a challenge. The suggested schemes either do not address farmers' breeding goals (centralized station-based nucleus schemes) or yield slow genetic progress (village-based schemes). A new breeding scheme that integrates the merits of previously suggested schemes has been designed for Menz sheep improvement in Ethiopia. It involves selection based on breeding values in nucleus flocks to produce elite rams, a one-time only provision of improved rams to villagers and a follow-up village-based selection to sustain genetic progress in village flocks. Here, we assessed whether conventional selection of breeding rams based on breeding values for production traits, which is the practice in station-based nucleus flocks, meets farmers' breeding objectives. We also elicited determinants of farmers' ram choice. Low but significant correlations were found between rankings of rams based on farmers' selection criteria, estimated breeding values (EBV) and body weight (BW). Appearance traits (such as color and horn) and meat production traits (BW and linear size traits) significantly determined farmers' breeding ram choice. The results imply that conventional selection criteria based solely on EBV for production traits do not address farmers' trait preferences fully, but only partially. Thus, a two-stage selection procedure involving selection on breeding values in nucleus centers followed by farmers' selection among top- ranking candidate rams is recommended. This approach accommodates farmers' preferences and speeds up genetic progress in village-based selection. The Menz sheep scheme could be applied elsewhere with similar situations to transform conventional station-based nucleus breeding activities into participatory breeding programs.     

Conservation of element concentration in xylem sap of red spruce

We investigated the chemistry of xylem sap as a marker of red spruce metabolism and soil chemistry at three locations in northern New England. A Scholander pressure chamber was used to extract xylem sap from roots and branches cut from mature trees in early June and September. Root sap contained significantly greater concentrations of K, Ca, Mg, Mn, and Al than branch sap. Sap collected in June contained a signficantly greater concentration of Mn than sap collected in September. Sap concentration was related to forest location for N and Mn. Variations in concentrations of N and K were significantly related to the interaction of tree organ and month of collection. Variations in concentrations of P, Cu, Zn, and Fe were not attributable to tree organ, month of collection, or forest location. Patterns of element concentration in xylem sap compared to previously published data on soil solution chemistry indicated a high degree of homeostatic control of xylem sap chemistry. This control likely represents a significant allocation of resources within the tree energy budget.     

Relative quantification of membrane-associated calcium in red spruce mesophyll cells

We describe a method for localizing and comparing relative amounts of plasma membrane-associated calcium ions (mCa) in complex tissues and verify the procedure for mesophyll cells of red spruce (Picea rubens Sarg.) needles. This technique incorporates epifluorescence microscopy using the fluorescent probe chlorotetracycline (CTC) with computer image processing and analysis. Using an appropriate standardization for image brightness, the procedure allows relative quantitative comparison of CTC-fluorescence in the plasma membrane-cell wall region that corresponds to relative amounts of mCa. The technique effectively discerned mCa differences among red spruce needle sections exposed to treatments designed to alter mCa levels in vitro. Estimates of mCa for nine red spruce seedlings, were highly repeatable over a 6 week period in late summer. This repeatability verifies that the described methods produce reliable and reproducible estimates of foliar mCa in woody plant foliage. By incorporating image analysis, this technique allows for relative quantitative estimates of mCa specific to the physiologically-important and labile pool of Ca associated with the plasma membrane-wall complex. Such measurements have not previously been reported for woody plant tissues and thus may provide new insights into the relative roles and responsiveness of mCa vs total foliar Ca pools.     

Methods to estimate breeding values in honey bees

Background

Efficient methodologies based on animal models are widely used to estimate breeding values in farm animals. These methods are not applicable in honey bees because of their mode of reproduction. Observations are recorded on colonies, which consist of a single queen and thousands of workers that descended from the queen mated to 10 to 20 drones. Drones are haploid and sperms are copies of a drone’s genotype. As a consequence, Mendelian sampling terms of full-sibs are correlated, such that the covariance matrix of Mendelian sampling terms is not diagonal.

Results

In this paper, we show how the numerator relationship matrix and its inverse can be obtained for honey bee populations. We present algorithms to derive the covariance matrix of Mendelian sampling terms that accounts for correlated terms. The resulting matrix is a block-diagonal matrix, with a small block for each full-sib family, and is easy to invert numerically. The method allows incorporating the within-colony distribution of progeny from drone-producing queens and drones, such that estimates of breeding values weigh information from relatives appropriately. Simulation shows that the resulting estimated breeding values are unbiased predictors of true breeding values. Benefits for response to selection, compared to an existing approximate method, appear to be limited (~5%). Benefits may however be greater when estimating genetic parameters.

Conclusions

This work shows how the relationship matrix and its inverse can be developed for honey bee populations, and used to estimate breeding values and variance components.     

The impact of genetic relationship information on genome-assisted breeding values

The success of genomic selection depends on the potential to predict genome-assisted breeding values (GEBVs) with high accuracy over several generations without additional phenotyping after estimating marker effects. Results from both simulations and practical applications have to be evaluated for this potential, which requires linkage disequilibrium (LD) between markers and QTL. This study shows that markers can capture genetic relationships among genotyped animals, thereby affecting accuracies of GEBVs. Strategies to validate the accuracy of GEBVs due to LD are given. Simulations were used to show that accuracies of GEBVs obtained by fixed regression-least squares (FR-LS), random regression-best linear unbiased prediction (RR-BLUP), and Bayes-B are nonzero even without LD. When LD was present, accuracies decrease rapidly in generations after estimation due to the decay of genetic relationships. However, there is a persistent accuracy due to LD, which can be estimated by modeling the decay of genetic relationships and the decay of LD. The impact of genetic relationships was greatest for RR-BLUP. The accuracy of GEBVs can result entirely from genetic relationships captured by markers, and to validate the potential of genomic selection, several generations have to be analyzed to estimate the accuracy due to LD. The method of choice was Bayes-B; FR-LS should be investigated further, whereas RR-BLUP cannot be recommended.     

Reliabilities of genomic estimated breeding values in Danish Jersey

In order to optimize the use of genomic selection in breeding plans, it is essential to have reliable estimates of the genomic breeding values. This study investigated reliabilities of direct genomic values (DGVs) in the Jersey population estimated by three different methods. The validation methods were (i) fivefold cross-validation and (ii) validation on the most recent 3 years of bulls. The reliability of DGV was assessed using squared correlations between DGV and deregressed proofs (DRPs). In the recent 3-year validation model, estimated reliabilities were also used to assess the reliabilities of DGV. The data set consisted of 1003 Danish Jersey bulls with conventional estimated breeding values (EBVs) for 14 different traits included in the Nordic selection index. The bulls were genotyped for Single-nucleotide polymorphism (SNP) markers using the Illumina 54 K chip. A Bayesian method was used to estimate the SNP marker effects. The corrected squared correlations between DGV and DRP were on average across all traits 0.04 higher than the squared correlation between DRP and the pedigree index. This shows that there is a gain in accuracy due to incorporation of marker information compared with parent index pre-selection only. Averaged across traits, the estimates of reliability of DGVs ranged from 0.20 for validation on the most recent 3 years of bulls and up to 0.42 for expected reliabilities. Reliabilities from the cross-validation were on average 0.24. For the individual traits, the reliability varied from 0.12 (direct birth) to 0.39 (milk). Bulls whose sires were included in the reference group had an average reliability of 0.25, whereas the bulls whose sires were not included in the reference group had an average reliability that was 0.05 lower.     

Reducing dimensionality for prediction of genome-wide breeding values

Partial least square regression (PLSR) and principal component regression (PCR) are methods designed for situations where the number of predictors is larger than the number of records. The aim was to compare the accuracy of genome-wide breeding values (EBV) produced using PLSR and PCR with a Bayesian method, ''BayesB''. Marker densities of 1, 2, 4 and 8 N_e markers/Morgan were evaluated when the effective population size (N_e) was 100. The correlation between true breeding value and estimated breeding value increased with density from 0.611 to 0.681 and 0.604 to 0.658 using PLSR and PCR respectively, with an overall advantage to PLSR of 0.016 (s.e = 0.008). Both methods gave a lower accuracy compared to the ''BayesB'', for which accuracy increased from 0.690 to 0.860. PLSR and PCR appeared less responsive to increased marker density with the advantage of ''BayesB'' increasing by 17% from a marker density of 1 to 8N_e/M. PCR and PLSR showed greater bias than ''BayesB'' in predicting breeding values at all densities. Although, the PLSR and PCR were computationally faster and simpler, these advantages do not outweigh the reduction in accuracy, and there is a benefit in obtaining relevant prior information from the distribution of gene effects.     

Estimation of breeding values using selected pedigree records

Fish bred in tanks or ponds cannot be easily tagged individually. The parentage of any individual may be determined by DNA fingerprinting, but is sufficiently expensive that large numbers cannot be so finger-printed. The measurement of the objective trait can be made on a much larger sample relatively cheaply. This article deals with experimental designs for selecting individuals to be finger-printed and for the estimation of the individual and family breeding values. The general setup provides estimates for both genetic effects regarded as fixed or random and for fixed effects due to known regressors. The family effects can be well estimated when even very small numbers are finger-printed, provided that they are the individuals with the most extreme phenotypes.