A phasing and imputation method for pedigreed populations that results in a single-stage genomic evaluation

Background

Efficient, robust, and accurate genotype imputation algorithms make large-scale application of genomic selection cost effective. An algorithm that imputes alleles or allele probabilities for all animals in the pedigree and for all genotyped single nucleotide polymorphisms (SNP) provides a framework to combine all pedigree, genomic, and phenotypic information into a single-stage genomic evaluation.

Methods

An algorithm was developed for imputation of genotypes in pedigreed populations that allows imputation for completely ungenotyped animals and for low-density genotyped animals, accommodates a wide variety of pedigree structures for genotyped animals, imputes unmapped SNP, and works for large datasets. The method involves simple phasing rules, long-range phasing and haplotype library imputation and segregation analysis.

Results

Imputation accuracy was high and computational cost was feasible for datasets with pedigrees of up to 25 000 animals. The resulting single-stage genomic evaluation increased the accuracy of estimated genomic breeding values compared to a scenario in which phenotypes on relatives that were not genotyped were ignored.

Conclusions

The developed imputation algorithm and software and the resulting single-stage genomic evaluation method provide powerful new ways to exploit imputation and to obtain more accurate genetic evaluations.     

The importance of information on relatives for the prediction of genomic breeding values and the implications for the makeup of reference data sets in livestock breeding schemes

Background

The theory of genomic selection is based on the prediction of the effects of genetic markers in linkage disequilibrium with quantitative trait loci. However, genomic selection also relies on relationships between individuals to accurately predict genetic value. This study aimed to examine the importance of information on relatives versus that of unrelated or more distantly related individuals on the estimation of genomic breeding values.

Methods

Simulated and real data were used to examine the effects of various degrees of relationship on the accuracy of genomic selection. Genomic Best Linear Unbiased Prediction (gBLUP) was compared to two pedigree based BLUP methods, one with a shallow one generation pedigree and the other with a deep ten generation pedigree. The accuracy of estimated breeding values for different groups of selection candidates that had varying degrees of relationships to a reference data set of 1750 animals was investigated.

Results

The gBLUP method predicted breeding values more accurately than BLUP. The most accurate breeding values were estimated using gBLUP for closely related animals. Similarly, the pedigree based BLUP methods were also accurate for closely related animals, however when the pedigree based BLUP methods were used to predict unrelated animals, the accuracy was close to zero. In contrast, gBLUP breeding values, for animals that had no pedigree relationship with animals in the reference data set, allowed substantial accuracy.

Conclusions

An animal''s relationship to the reference data set is an important factor for the accuracy of genomic predictions. Animals that share a close relationship to the reference data set had the highest accuracy from genomic predictions. However a baseline accuracy that is driven by the reference data set size and the overall population effective population size enables gBLUP to estimate a breeding value for unrelated animals within a population (breed), using information previously ignored by pedigree based BLUP methods.     

Accuracy of pedigree and genomic predictions of carcass and novel meat quality traits in multi-breed sheep data assessed by cross-validation

Background

Genomic predictions can be applied early in life without impacting selection candidates. This is especially useful for meat quality traits in sheep. Carcass and novel meat quality traits were predicted in a multi-breed sheep population that included Merino, Border Leicester, Polled Dorset and White Suffolk sheep and their crosses.

Methods

Prediction of breeding values by best linear unbiased prediction (BLUP) based on pedigree information was compared to prediction based on genomic BLUP (GBLUP) and a Bayesian prediction method (BayesR). Cross-validation of predictions across sire families was used to evaluate the accuracy of predictions based on the correlation of predicted and observed values and the regression of observed on predicted values was used to evaluate bias of methods. Accuracies and regression coefficients were calculated using either phenotypes or adjusted phenotypes as observed variables.

Results and conclusions

Genomic methods increased the accuracy of predicted breeding values to on average 0.2 across traits (range 0.07 to 0.31), compared to an average accuracy of 0.09 for pedigree-based BLUP. However, for some traits with smaller reference population size, there was no increase in accuracy or it was small. No clear differences in accuracy were observed between GBLUP and BayesR. The regression of phenotypes on breeding values was close to 1 for all methods, indicating little bias, except for GBLUP and adjusted phenotypes (regression = 0.78). Accuracies calculated with adjusted (for fixed effects) phenotypes were less variable than accuracies based on unadjusted phenotypes, indicating that fixed effects influence the latter. Increasing the reference population size increased accuracy, indicating that adding more records will be beneficial. For the Merino, Polled Dorset and White Suffolk breeds, accuracies were greater than for the Border Leicester breed due to the smaller sample size and limited across-breed prediction. BayesR detected only a few large marker effects but one region on chromosome 6 was associated with large effects for several traits. Cross-validation produced very similar variability of accuracy and regression coefficients for BLUP, GBLUP and BayesR, showing that this variability is not a property of genomic methods alone. Our results show that genomic selection for novel difficult-to-measure traits is a feasible strategy to achieve increased genetic gain.     

Mayan diver-fishers as citizen scientists: detection and monitoring of the invasive red lionfish in the Parque Nacional Arrecife Alacranes,southern Gulf of Mexico

Biological invasions research has increasingly incorporated the participation of citizen scientists to collect data for monitoring and management purposes. This study outlines collaborative efforts with Mayan lobster diver-fishers, who participated voluntarily as citizen scientists in surveys, to detect and monitor the invasive red lionfish, Pterois volitans, in a marine protected area off the northern Yucatan Peninsula, Mexico. We engaged these fishers by building local capacity and awareness of the threats of the lionfish invasion on the fishery resources of the area. During the lobster fishing season (July 2010–February 2011), 30 fishers collected 248 red lionfish (9–29 cm TL) and recorded ancillary data (day, month, depth, and approximate coordinates of capture site). This collaboration not only allowed the first lionfish detection in the Parque Nacional Arrecife Alacranes in 2010, but the volunteer-based monitoring effort revealed that the invasion reached levels from intermediate to advanced, with more than 200 specimens captured in less than a year. Our results support the notion that engaging citizen scientists can enhance research, reduce costs, and improve the possibility of a long term monitoring survey.     

Normal vs. high‐protein weight loss diets in men: Effects on body composition and indices of metabolic syndrome

Objective:

This study assessed the effectiveness of a prescribed weight‐loss diet with 0.8 versus 1.4 g protein·kg^?1 day^?1 on changes in weight, body composition, indices of metabolic syndrome, and resting energy expenditure (REE) in overweight and obese men.

Design and Methods:

Men were randomized to groups that consumed diets containing 750 kcal day^?1 less than daily energy needs for weight maintenance with either normal protein (NP, n = 21) or higher protein (HP, n = 22) content for 12 weeks. The macronutrient distributions of the NP and HP diets were 25:60:15, and 25:50:25 percent energy from fat, carbohydrate, and protein, respectively. Assessments were made pre and post intervention. The subjects were retrospectively subgrouped into overweight and obese groups.

Results and Conclusion:

Both diet groups lost comparable body weight and fat. The HP group lost less lean body mass than the NP group (?1.9 ± 0.3 vs. ?3.0 ± 0.4 kg). The effects of protein and BMI status on lean body mass loss were additive. The reductions in total cholesterol, HDL‐C, triacylglycerol, glucose, and insulin, along with LDL‐C, total cholesterol‐to‐HDL‐C ratio, and HOMA‐IR, were not statistically different between NP and HP. Likewise, macronutrient distributions of the diet did not affect the reductions in REE, and blood pressure. In conclusion, energy restriction effectively improves multiple clinical indicators of cardiovascular health and glucose control, and consumption of a higher‐protein diet and accomplishing weight loss when overweight versus obese help men preserve lean body mass over a short period of time.

     

Membrane restructuring by phospholipase A2 is regulated by the presence of lipid domains

Secretory phospholipase A₂ (sPLA₂) catalyzes the hydrolysis of glycerophospholipids. This enzyme is sensitive to membrane structure, and its activity has been shown to increase in the presence of liquid-crystalline/gel (L_α/L_β) lipid domains. In this work, we explore whether lipid domains can also direct the activity of the enzyme by inducing hydrolysis of certain lipid components due to preferential activity of the enzyme toward lipid domains susceptible to sPLA₂. Specifically, we show that the presence of L_α/L_β and L_α/P_β′ phase coexistence in a 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC)/1,2 distearoyl-sn-glycero-3-phosphocholine (DSPC) system results in the preferential hydrolysis of the shorter-chained lipid component in the mixture, leading to an enrichment in the longer-chained component. The restructuring process is monitored by atomic force microscopy on supported single and double bilayers formed by vesicle fusion. We observe that during preferential hydrolysis of the DMPC-rich L_α regions, the L_β and P_β′ regions grow and reseal, maintaining membrane integrity. This result indicates that a sharp reorganization of the membrane structure can occur during sPLA₂ hydrolysis without necessarily destroying the membrane. We confirm by high-performance liquid chromatography the preferential hydrolysis of DMPC within the phase coexistence region of the DMPC/DSPC phase diagram, showing that this preferential hydrolysis is accentuated close to the solidus phase boundary. Differential scanning calorimetry results show that this preferential hydrolysis in the presence of lipid domains leads to a membrane system with a higher-temperature melting profile due to enrichment in DSPC. Together, these results show that the presence of lipid domains can induce specificity in the hydrolytic activity of the enzyme, resulting in marked differences in the physical properties of the membrane end-product.     

A novel tetravalent bispecific TandAb (CD30/CD16A) efficiently recruits NK cells for the lysis of CD30+ tumor cells

To improve recruitment and activation of natural killer (NK) cells to lyse tumor cells, we isolated a human anti-CD16A antibody with similar affinity for the CD16A 158F/V allotypes, but no binding to the CD16B isoform. Using CD16A-targeting Fv domains, we constructed a tetravalent bispecific CD30/CD16A tandem diabody (TandAb®) consisting solely of Fv domains. This TandAb has two binding sites for CD16A and two for CD30, the antigen identifying Hodgkin lymphoma cells. The binding and cytotoxicity of the TandAb were compared with antibodies with identical anti-CD30 domains: (1) a native IgG, (2) an IgG optimized for binding to Fc receptors, and (3) a bivalent bispecific CD30/CD16A diabody. Due to its CD16A-bivalency and reduced k_off, the TandAb was retained longer on the surface of NK cells than the IgGs or the diabody. This contributed to the higher potency and efficacy of the TandAb relative to those of the other anti-CD30 antibodies. TandAb cytotoxicity was independent of the CD16A allotype, whereas the anti-CD30 IgGs were substantially less cytotoxic when NK cells with low affinity CD16A allotype were employed. TandAb activation of NK cells was strictly dependent on the presence of CD30⁺ target cells. Therefore, the CD30/CD16A TandAb may represent a promising therapeutic for the treatment of Hodgkin’s lymphoma; further, anti-CD16A TandAbs may function as potent immunotherapeutics that specifically recruit NK cells to destroy cancer cells.     

Responses of woody vegetation to exclusion of large herbivores in semi‐arid savannas

The Nkuhlu large‐scale long‐term exclusion experiment in Kruger National Park was designed to study the long‐term effects of large herbivores on vegetation. One treatment excludes elephants, another excludes all herbivores larger than hares and another one comprises an open, control area. Vegetation monitoring was implemented in 2002 when a baseline survey was conducted prior to exclusion. Monitoring was repeated 5 years after exclusion. Data from the surveys were analysed to establish how structure and composition of woody vegetation had changed 5 years after herbivore exclusion. The analysis showed that neither plant assemblage nor mean vegetation height had changed significantly since exclusion. However, both species richness and density of woody plants increased 5 years after exclusion of all large herbivores, but not after the exclusion of elephants alone. One already common species, Dichrostachys cinerea, became more common after excluding all large herbivores compared with either no exclusion or elephant exclusion, possibly leading to competitive suppression of other species. Species other than D. cinerea tended to either increase or decrease in density, but the changes were insufficient to induce significant shifts in the overall assemblage of woody plants. The results indicate that after 5 years of exclusion, the combined assemblage of large herbivores, and not elephants alone, could induce changes in species richness and abundances of woody plants, but the effect was so far insufficient to induce measureable shifts in the assemblages of woody plants. It is possible that assemblages will change with time and increasing elephant numbers may amplify future changes.