The effect of genomic information on optimal contribution selection in livestock breeding programs

Background

Long-term benefits in animal breeding programs require that increases in genetic merit be balanced with the need to maintain diversity (lost due to inbreeding). This can be achieved by using optimal contribution selection. The availability of high-density DNA marker information enables the incorporation of genomic data into optimal contribution selection but this raises the question about how this information affects the balance between genetic merit and diversity.

Methods

The effect of using genomic information in optimal contribution selection was examined based on simulated and real data on dairy bulls. We compared the genetic merit of selected animals at various levels of co-ancestry restrictions when using estimated breeding values based on parent average, genomic or progeny test information. Furthermore, we estimated the proportion of variation in estimated breeding values that is due to within-family differences.

Results

Optimal selection on genomic estimated breeding values increased genetic gain. Genetic merit was further increased using genomic rather than pedigree-based measures of co-ancestry under an inbreeding restriction policy. Using genomic instead of pedigree relationships to restrict inbreeding had a significant effect only when the population consisted of many large full-sib families; with a half-sib family structure, no difference was observed. In real data from dairy bulls, optimal contribution selection based on genomic estimated breeding values allowed for additional improvements in genetic merit at low to moderate inbreeding levels. Genomic estimated breeding values were more accurate and showed more within-family variation than parent average breeding values; for genomic estimated breeding values, 30 to 40% of the variation was due to within-family differences. Finally, there was no difference between constraining inbreeding via pedigree or genomic relationships in the real data.

Conclusions

The use of genomic estimated breeding values increased genetic gain in optimal contribution selection. Genomic estimated breeding values were more accurate and showed more within-family variation, which led to higher genetic gains for the same restriction on inbreeding. Using genomic relationships to restrict inbreeding provided no additional gain, except in the case of very large full-sib families.     

Design of reference populations for genomic selection in crossbreeding programs

Background

In crossbreeding programs, genomic selection offers the opportunity to make efficient use of information on crossbred (CB) individuals in the selection of purebred (PB) candidates. In such programs, reference populations often contain genotyped PB animals, although the breeding objective is usually more focused on CB performance. The question is what would be the benefit of including a larger proportion of CB individuals in the reference population.

Methods

In a deterministic simulation study, we evaluated the benefit of including various proportions of CB animals in a reference population for genomic selection of PB animals in a crossbreeding program. We used a pig breeding scheme with selection for a moderately heritable trait and a size of 6000 for the reference population.

Results

Applying genomic selection to improve the performance of CB individuals, with a genetic correlation between PB and CB performance (r_PC) of 0.7, selection accuracy of PB candidates increased from 0.49 to 0.52 if the reference population consisted of PB individuals, it increased to 0.55 if the reference population consisted of the same number of CB individuals, and to 0.60 if the size of the CB reference population was twice that of the reference population for each PB line. The advantage of using CB rather than PB individuals increased linearly with the proportion of CB individuals in the reference population. This advantage disappeared quickly if r_PC was higher or if the breeding objective put some emphasis on PB performance. The benefit of adding CB individuals to an existing PB reference population was limited for high r_PC.

Conclusions

Using CB rather than PB individuals in a reference population for genomic selection can provide substantial advantages, but only when correlations between PB and CB performances are not high and PB performance is not part of the breeding objective.     

A comparison of methods to calculate a total merit index using stochastic simulation

Background

Modern dairy cattle breeding goals include several production and more and more functional traits. Estimated breeding values (EBV) that are combined in the total merit index usually come from single-trait models or from multivariate models for groups of traits. In most cases, a multivariate animal model based on phenotypic data for all traits is not feasible and approximate methods based on selection index theory are applied to derive the total merit index. Therefore, the objective of this study was to compare a full multitrait animal model with two approximate multitrait models and a selection index approach based on simulated data.

Methods

Three production and two functional traits were simulated to mimic the national Austrian Brown Swiss population. The reference method for derivation of the total merit index was a multitrait evaluation based on all phenotypic data. Two of the approximate methods were variations of an approximate multitrait model that used either yield deviations or de-regressed breeding values. The final method was an adaptation of the selection index method that is used in routine evaluations in Austria and Germany. Three scenarios with respect to residual covariances were set up: residual covariances were equal to zero, or half of or equal to the genetic covariances.

Results

Results of both approximate multitrait models were very close to those of the reference method, with rank correlations of 1. Both methods were nearly unbiased. Rank correlations for the selection index method showed good results when residual covariances were zero but correlations with the reference method decreased when residual covariances were large. Furthermore, EBV were biased when residual covariances were high.

Conclusions

We applied an approximate multitrait two-step procedure to yield deviations and de-regressed breeding values, which led to nearly unbiased results. De-regressed breeding values gave even slightly better results. Our results confirmed that ignoring residual covariances when a selection index approach is applied leads to remarkable bias. This could be relevant in terms of selection accuracy. Our findings suggest that the approximate multitrait approach applied to de-regressed breeding values can be used in routine genetic evaluation.     

Comparison of molecular breeding values based on within- and across-breed training in beef cattle

Background

Although the efficacy of genomic predictors based on within-breed training looks promising, it is necessary to develop and evaluate across-breed predictors for the technology to be fully applied in the beef industry. The efficacies of genomic predictors trained in one breed and utilized to predict genetic merit in differing breeds based on simulation studies have been reported, as have the efficacies of predictors trained using data from multiple breeds to predict the genetic merit of purebreds. However, comparable studies using beef cattle field data have not been reported.

Methods

Molecular breeding values for weaning and yearling weight were derived and evaluated using a database containing BovineSNP50 genotypes for 7294 animals from 13 breeds in the training set and 2277 animals from seven breeds (Angus, Red Angus, Hereford, Charolais, Gelbvieh, Limousin, and Simmental) in the evaluation set. Six single-breed and four across-breed genomic predictors were trained using pooled data from purebred animals. Molecular breeding values were evaluated using field data, including genotypes for 2227 animals and phenotypic records of animals born in 2008 or later. Accuracies of molecular breeding values were estimated based on the genetic correlation between the molecular breeding value and trait phenotype.

Results

With one exception, the estimated genetic correlations of within-breed molecular breeding values with trait phenotype were greater than 0.28 when evaluated in the breed used for training. Most estimated genetic correlations for the across-breed trained molecular breeding values were moderate (> 0.30). When molecular breeding values were evaluated in breeds that were not in the training set, estimated genetic correlations clustered around zero.

Conclusions

Even for closely related breeds, within- or across-breed trained molecular breeding values have limited prediction accuracy for breeds that were not in the training set. For breeds in the training set, across- and within-breed trained molecular breeding values had similar accuracies. The benefit of adding data from other breeds to a within-breed training population is the ability to produce molecular breeding values that are more robust across breeds and these can be utilized until enough training data has been accumulated to allow for a within-breed training set.     

Effect of non-random mating on genomic and BLUP selection schemes

Background

The risk of long-term unequal contribution of mating pairs to the gene pool is that deleterious recessive genes can be expressed. Such consequences could be alleviated by appropriately designing and optimizing breeding schemes i.e. by improving selection and mating procedures.

Methods

We studied the effect of mating designs, random, minimum coancestry and minimum covariance of ancestral contributions on rate of inbreeding and genetic gain for schemes with different information sources, i.e. sib test or own performance records, different genetic evaluation methods, i.e. BLUP or genomic selection, and different family structures, i.e. factorial or pair-wise.

Results

Results showed that substantial differences in rates of inbreeding due to mating design were present under schemes with a pair-wise family structure, for which minimum coancestry turned out to be more effective to generate lower rates of inbreeding. Specifically, substantial reductions in rates of inbreeding were observed in schemes using sib test records and BLUP evaluation. However, with a factorial family structure, differences in rates of inbreeding due mating designs were minor. Moreover, non-random mating had only a small effect in breeding schemes that used genomic evaluation, regardless of the information source.

Conclusions

It was concluded that minimum coancestry remains an efficient mating design when BLUP is used for genetic evaluation or when the size of the population is small, whereas the effect of non-random mating is smaller in schemes using genomic evaluation.     

Biased morph ratios and skewed mating success contribute to loss of genetic diversity in the distylous Pulmonaria officinalis

Background and Aims

In heterostylous plant species, skewed morph ratios are not uncommon and may arise from a range of factors. Despite the recognized importance of skewed morph ratios on overall reproductive success within populations, little is known about the impact of skewed morph ratios on population genetic diversity and differentiation in heterostylous species. This study specifically aimed to clarify the effect of population size and morph bias on population genetic diversity and differentiation in the temperate forest herb Pulmonaria officinalis. This species is characterized by a distylous breeding system and shows morph-specific differences in reproductive success.

Methods

Genetic diversity was determined for 27 P. officinalis populations in northern Belgium by using eight recently developed microsatellite markers. Multiple regressions were used to assess the relationship between genetic diversity, morph bias and population size, and F_ST-values were calculated for short- and long-styled morphs separately to study genetic differentiation as a function of morph type.

Key Results

For all genetic measures used, morph bias was more important in explaining patterns of genetic diversity than population size, and in all cases patterns of population genetic diversity followed a quadratic function, which showed a symmetrical decrease in genetic diversity with increasing morph bias. However, probably due to the reproductive advantage of L-morphs relative to S-morphs, maximum genetic diversity was found in populations showing an excess of L-morphs (60·7 % L-morph). On the other hand, no significant difference in pairwise genetic distances between populations was observed between L- (0·107) and S-morphs (0·106).

Conclusions

Our results indicate that significant deviations from equal morph ratios not only affect plant reproductive success but also population genetic diversity of heterostylous plant species. Hence, when defining conservation measures for populations of heterostylous plant species, morph ratios should be considered as an important trait affecting their long-term population viability.     

Estimation of relatedness among non-pedigreed Yakutian cryo-bank bulls using molecular data: implications for conservation and breed management

Background

Yakutian cattle, the last remaining native cattle breed in Siberia, are well adapted to the extreme sub-arctic conditions. Nowadays only ca. 1200 purebred animals are left in Yakutia. The semen of six Yakutian bulls was stored in a cryo-bank without any pedigree documentation because of the traditional free herding style of the population.

Methods

To clarify the genetic relatedness between these bulls and to provide recommendations to use their semen in future conservation and breed management programs, we have analysed 30 autosomal microsatellites and mitochondrial DNA sequences in 60 individuals including the six for which semen has been stored. Four relatedness estimators were calculated. In addition, we assessed the value of the cryo-bank bulls for the preservation of genetic variation of the contemporary Yakutian cattle by calculating allelic and gene diversity estimates and mean molecular coancestries.

Results

On the basis of microsatellite variability, including the Yakutian cryo-bank bulls increases the allelic variation in the contemporary population by 3% and in the male subpopulation by 13%. In terms of the mean molecular coancestries, they are less related to the contemporary cow population than the breeding bulls and therefore could be used to reduce inbreeding in the living population. Although 30 loci are insufficient to resolve definitely their relatedness categories, the data suggest four pairs of cryo-bank bulls as possible half-sibs.

Conclusions

Our results show that even relatively limited cryo-bank storage of semen can carry allelic variation through a bottleneck. We propose a breeding scheme based on the rotation of breeding females and the division of cryo-bank bulls into three groups. Thus, if molecular data (e.g. autosomal microsatellite genotypes) for the contemporary population are available and based on relatively small-scale laboratory analyses, it is possible to avoid serious mistakes in their use for breeding applications. The approach suggested here based on the use of Yakutian cryo-bank semen can be easily extended to cryo-bank materials of other animals in future breeding programs.     

Genomic prediction when some animals are not genotyped

Background

The use of genomic selection in breeding programs may increase the rate of genetic improvement, reduce the generation time, and provide higher accuracy of estimated breeding values (EBVs). A number of different methods have been developed for genomic prediction of breeding values, but many of them assume that all animals have been genotyped. In practice, not all animals are genotyped, and the methods have to be adapted to this situation.

Results

In this paper we provide an extension of a linear mixed model method for genomic prediction to the situation with non-genotyped animals. The model specifies that a breeding value is the sum of a genomic and a polygenic genetic random effect, where genomic genetic random effects are correlated with a genomic relationship matrix constructed from markers and the polygenic genetic random effects are correlated with the usual relationship matrix. The extension of the model to non-genotyped animals is made by using the pedigree to derive an extension of the genomic relationship matrix to non-genotyped animals. As a result, in the extended model the estimated breeding values are obtained by blending the information used to compute traditional EBVs and the information used to compute purely genomic EBVs. Parameters in the model are estimated using average information REML and estimated breeding values are best linear unbiased predictions (BLUPs). The method is illustrated using a simulated data set.

Conclusions

The extension of the method to non-genotyped animals presented in this paper makes it possible to integrate all the genomic, pedigree and phenotype information into a one-step procedure for genomic prediction. Such a one-step procedure results in more accurate estimated breeding values and has the potential to become the standard tool for genomic prediction of breeding values in future practical evaluations in pig and cattle breeding.     

Unravelling genetics at the top: mountain islands or isolated belts?

Background and Aims

In mountain plant populations, local adaptation has been described as one of the main responses to climate warming, allowing plants to persist under stressful conditions. This is especially the case for marginal populations at their lowest elevation, as they are highly vulnerable. Adequate levels of genetic diversity are required for selection to take place, while high levels of altitudinal gene flow are seen as a major limiting factor potentially precluding local adaptation processes. Thus, a compromise between genetic diversity and gene flow seems necessary to guarantee persistence under oncoming conditions. It is therefore critical to determine if gene flow occurs preferentially between mountains at similar altitudinal belts, promoting local adaptation at the lowest populations, or conversely along altitude within each mountain.

Methods

Microsatellite markers were used to unravel genetic diversity and population structure, inbreeding and gene flow of populations at two nearby altitudinal gradients of Silene ciliata, a Mediterranean high-mountain cushion plant.

Key Results

Genetic diversity and inbreeding coefficients were similar in all populations. Substantial gene flow was found both along altitudinal gradients and horizontally within each elevation belt, although greater values were obtained along altitudinal gradients. Gene flow may be responsible for the homogeneous levels of genetic diversity found among populations. Bayesian cluster analyses also suggested that shifts along altitudinal gradients are the most plausible scenario.

Conclusions

Past population shifts associated with glaciations and interglacial periods in temperate mountains may partially explain current distributions of genetic diversity and population structure. In spite of the predominance of gene flow along the altitudinal gradients, local genetic differentiation of one of the lower populations together with the detection of one outlier locus might support the existence of different selection forces at low altitudes.     

Population history and genomic signatures for high-altitude adaptation in Tibetan pigs

Background

The Tibetan pig is one of domestic animals indigenous to the Qinghai-Tibet Plateau. Several geographically isolated pig populations are distributed throughout the Plateau. It remained an open question if these populations have experienced different demographic histories and have evolved independent adaptive loci for the harsh environment of the Plateau. To address these questions, we herein investigated ~ 40,000 genetic variants across the pig genome in a broad panel of 678 individuals from 5 Tibetan geographic populations and 34 lowland breeds.

Results

Using a series of population genetic analyses, we show that Tibetan pig populations have marked genetic differentiations. Tibetan pigs appear to be 3 independent populations corresponding to the Tibetan, Gansu and Sichuan & Yunnan locations. Each population is more genetically similar to its geographic neighbors than to any of the other Tibetan populations. By applying a locus-specific branch length test, we identified both population-specific and -shared candidate genes under selection in Tibetan pigs. These genes, such as PLA2G12A, RGCC, C9ORF3, GRIN2B, GRID1 and EPAS1, are involved in high-altitude physiology including angiogenesis, pulmonary hypertension, oxygen intake, defense response and erythropoiesis. A majority of these genes have not been implicated in previous studies of highlanders and high-altitude animals.

Conclusion

Tibetan pig populations have experienced substantial genetic differentiation. Historically, Tibetan pigs likely had admixture with neighboring lowland breeds. During the long history of colonization in the Plateau, Tibetan pigs have developed a complex biological adaptation mechanism that could be different from that of Tibetans and other animals. Different Tibetan pig populations appear to have both distinct and convergent adaptive loci for the harsh environment of the Plateau.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-834) contains supplementary material, which is available to authorized users.     

Quantitative estimation of genetic risk for atypical scrapie in French sheep and potential consequences of the current breeding programme for resistance to scrapie on the risk of atypical scrapie

Background

Since 2002, active surveillance programmes have detected numerous atypical scrapie (AS) and classical scrapie cases (CS) in French sheep with almost all the PrP genotypes. The aim of this study was 1) to quantify the genetic risk of AS in French sheep and to compare it with the risk of CS, 2) to quantify the risk of AS associated with the increase of the ARR allele frequency as a result of the current genetic breeding programme against CS.

Methods

We obtained genotypes at codons 136, 141, 154 and 171 of the PRNP gene for representative samples of 248 AS and 245 CS cases. We used a random sample of 3,317 scrapie negative animals genotyped at codons 136, 154 and 171 and we made inferences on the position 141 by multiple imputations, using external data. To estimate the risk associated with PrP genotypes, we fitted multivariate logistic regression models and we estimated the prevalence of AS for the different genotypes. Then, we used the risk of AS estimated for the ALRR-ALRR genotype to analyse the risk of detecting an AS case in a flock homogenous for this genotype.

Results

Genotypes most at risk for AS were those including an AFRQ or ALHQ allele while genotypes including a VLRQ allele were less commonly associated with AS. Compared to ALRQ-ALRQ, the ALRR-ALRR genotype was significantly at risk for AS and was very significantly protective for CS. The prevalence of AS among ALRR-ALRR animals was 0.6‰ and was not different from the prevalence in the general population.

Conclusion

In conclusion, further selection of ALRR-ALRR animals will not result in an overall increase of AS prevalence in the French sheep population although this genotype is clearly susceptible to AS. However the probability of detecting AS cases in flocks participating in genetic breeding programme against CS should be considered.     

Genetic structure,relationships and admixture with wild relatives in native pig breeds from Iberia and its islands

Background

Native pig breeds in the Iberian Peninsula are broadly classified as belonging to either the Celtic or the Mediterranean breed groups, but there are other local populations that do not fit into any of these groups. Most of the native pig breeds in Iberia are in danger of extinction, and the assessment of their genetic diversity and population structure, relationships and possible admixture between breeds, and the appraisal of conservation alternatives are crucial to adopt appropriate management strategies.

Methods

A panel of 24 microsatellite markers was used to genotype 844 animals representing the 17 most important native swine breeds and wild populations existing in Portugal and Spain and various statistical tools were applied to analyze the results.

Results

Genetic diversity was high in the breeds studied, with an overall mean of 13.6 alleles per locus and an average expected heterozygosity of 0.80. Signs of genetic bottlenecks were observed in breeds with a small census size, and population substructure was present in some of the breeds with larger census sizes. Variability among breeds accounted for about 20% of the total genetic diversity, and was explained mostly by differences among the Celtic, Mediterranean and Basque breed groups, rather than by differences between domestic and wild pigs. Breeds clustered closely according to group, and proximity was detected between wild pigs and the Mediterranean cluster of breeds. Most breeds had their own structure and identity, with very little evidence of admixture, except for the Retinto and Entrepelado varieties of the Mediterranean group, which are very similar. Genetic influence of the identified breed clusters extends beyond the specific geographical areas across borders throughout the Iberian Peninsula, with a very sharp transition from one breed group to another. Analysis of conservation priorities confirms that the ranking of a breed for conservation depends on the emphasis placed on its contribution to the between- and within-breed components of genetic diversity.

Conclusions

Native pig breeds in Iberia reveal high levels of genetic diversity, a solid breed structure and a clear organization in well-defined clusters.     

Total cost estimation for implementing genome-enabled selection in a multi-level swine production system

Background

Determining an animal’s genetic merit using genomic information can improve estimated breeding value (EBV) accuracy; however, the magnitude of the accuracy improvement must be large enough to recover the costs associated with implementing genome-enabled selection. One way to reduce costs is to genotype nucleus herd selection candidates using a low-density chip and to use high-density chip genotyping for animals that are used as parents in the nucleus breeding herd. The objective of this study was to develop a tool to estimate the cost structure associated with incorporating genome-enabled selection into multi-level commercial breeding programs.

Results

For the purpose of this deterministic study, it was assumed that a commercial pig is created from a terminal line sire and a dam that is a cross between two maternal lines. It was also assumed that all male and female selection candidates from the 1000 sow maternal line nucleus herds were genotyped at low density and all animals used for breeding at high density. With the assumptions used in this analysis, it was estimated that genome-enabled selection costs for a maternal line would be approximately US$0.082 per weaned pig in the commercial production system. A total of US$0.164 per weaned pig is needed to incorporate genome-enabled selection into the two maternal lines. Similarly, for a 600 sow terminal line nucleus herd and genotyping only male selection candidates with the low-density panel, the cost per weaned pig in the commercial herd was estimated to be US$0.044. This means that US$0.21 per weaned pig produced at the commercial level and sired by boars obtained from the nucleus herd breeding program needs to be added to the genetic merit value in order to break even on the additional cost required when genome-enabled selection is used in both maternal lines and the terminal line.

Conclusions

By modifying the input values, such as herd size and genotyping strategy, a flexible spreadsheet tool developed from this work can be used to estimate the additional costs associated with genome-enabled selection. This tool will aid breeders in estimating the economic viability of incorporating genome-enabled selection into their specific breeding program.     

Diverse spore rains and limited local exchange shape fern genetic diversity in a recently created habitat colonized by long-distance dispersal

Background and Aims

Populations established by long-distance colonization are expected to show low levels of genetic variation per population, but strong genetic differentiation among populations. Whether isolated populations indeed show this genetic signature of isolation depends on the amount and diversity of diaspores arriving by long-distance dispersal, and time since colonization. For ferns, however, reliable estimates of long-distance dispersal rates remain largely unknown, and previous studies on fern population genetics often sampled older or non-isolated populations. Young populations in recent, disjunct habitats form a useful study system to improve our understanding of the genetic impact of long-distance dispersal.

Methods

Microsatellite markers were used to analyse the amount and distribution of genetic diversity in young populations of four widespread calcicole ferns (Asplenium scolopendrium, diploid; Asplenium trichomanes subsp. quadrivalens, tetraploid; Polystichum setiferum, diploid; and Polystichum aculeatum, tetraploid), which are rare in The Netherlands but established multiple populations in a forest (the Kuinderbos) on recently reclaimed Dutch polder land following long-distance dispersal. Reference samples from populations throughout Europe were used to assess how much of the existing variation was already present in the Kuinderbos.

Key Results

A large part of the Dutch and European genetic diversity in all four species was already found in the Kuinderbos. This diversity was strongly partitioned among populations. Most populations showed low genetic variation and high inbreeding coefficients, and were assigned to single, unique gene pools in cluster analyses. Evidence for interpopulational gene flow was low, except for the most abundant species.

Conclusions

The results show that all four species, diploids as well as polyploids, were capable of frequent long-distance colonization via single-spore establishment. This indicates that even isolated habitats receive dense and diverse spore rains, including genotypes capable of self-fertilization. Limited gene flow may conserve the genetic signature of multiple long-distance colonization events for several decades.     

Long-term response to genomic selection: effects of estimation method and reference population structure for different genetic architectures

Background

Genomic selection has become an important tool in the genetic improvement of animals and plants. The objective of this study was to investigate the impacts of breeding value estimation method, reference population structure, and trait genetic architecture, on long-term response to genomic selection without updating marker effects.

Methods

Three methods were used to estimate genomic breeding values: a BLUP method with relationships estimated from genome-wide markers (GBLUP), a Bayesian method, and a partial least squares regression method (PLSR). A shallow (individuals from one generation) or deep reference population (individuals from five generations) was used with each method. The effects of the different selection approaches were compared under four different genetic architectures for the trait under selection. Selection was based on one of the three genomic breeding values, on pedigree BLUP breeding values, or performed at random. Selection continued for ten generations.

Results

Differences in long-term selection response were small. For a genetic architecture with a very small number of three to four quantitative trait loci (QTL), the Bayesian method achieved a response that was 0.05 to 0.1 genetic standard deviation higher than other methods in generation 10. For genetic architectures with approximately 30 to 300 QTL, PLSR (shallow reference) or GBLUP (deep reference) had an average advantage of 0.2 genetic standard deviation over the Bayesian method in generation 10. GBLUP resulted in 0.6% and 0.9% less inbreeding than PLSR and BM and on average a one third smaller reduction of genetic variance. Responses in early generations were greater with the shallow reference population while long-term response was not affected by reference population structure.

Conclusions

The ranking of estimation methods was different with than without selection. Under selection, applying GBLUP led to lower inbreeding and a smaller reduction of genetic variance while a similar response to selection was achieved. The reference population structure had a limited effect on long-term accuracy and response. Use of a shallow reference population, most closely related to the selection candidates, gave early benefits while in later generations, when marker effects were not updated, the estimation of marker effects based on a deeper reference population did not pay off.     

Somatic mutations contribute to genotypic diversity in sterile and fertile populations of the threatened shrub, Grevillea rhizomatosa (Proteaceae)

Background and Aims

Grevillea rhizomatosa is a spreading shrub which exhibits multiple breeding strategies within a narrow area in the fire-prone heathlands of eastern Australia. Reproductive strategies include self-compatibility, self-incompatibility and clonality (with and without sterility). The close proximity of contrasting breeding systems provides an opportunity to explore the evolution of sterility and to compare and contrast the origins of genotypic diversity (recombinant or somatic) against degrees of sexual expression.

Methods

ISSR markers for 120 band positions (putative loci) were used to compare genetic diversity among five populations at a macro-scale of 5 m between samples (n = 244 shrubs), and at a micro-scale of nearest neighbours for all plants in five 25-m² quadrats with contrasting fertilities (n = 162 shrubs). Nearest-neighbour sampling included several clusters of connected ramets. Matrix incompatibility (MIC) analyses were used to evaluate the relative contribution of recombination and somatic mutation to genotype diversity.

Key Results

High levels of genotypic diversity were found in all populations regardless of fertilities (fertile populations, G/N ≥ 0·94; sterile populations, G/N ≥ 0·97) and most sterile populations had a unique genetic profile. Somatic mutations were detected along connected ramets in ten out of 42 ramet clusters. MIC analyses showed that somatic mutations have contributed to diversity in all populations and particularly so in sterile populations.

Conclusions

Somatic mutations contribute significantly to gene diversity in sterile populations of Grevillea rhizomatosa, the accumulation of which is the likely cause of male and female sterility. High levels of genetic diversity therefore may not always be synonymous with sexual fitness and genetic health. We hypothesize that frequent fires drive selection for clonal reproduction, at the cost of flowering such that sexual functions are not maintained through selection, and the build-up of somatic mutations in meristems results in high genotype diversity at the cost of pollen and ovule fertilities.     

Methods to estimate effective population size using pedigree data: Examples in dog,sheep, cattle and horse

Background

Effective population sizes of 140 populations (including 60 dog breeds, 40 sheep breeds, 20 cattle breeds and 20 horse breeds) were computed using pedigree information and six different computation methods. Simple demographical information (number of breeding males and females), variance of progeny size, or evolution of identity by descent probabilities based on coancestry or inbreeding were used as well as identity by descent rate between two successive generations or individual identity by descent rate.

Results

Depending on breed and method, effective population sizes ranged from 15 to 133 056, computation method and interaction between computation method and species showing a significant effect on effective population size (P < 0.0001). On average, methods based on number of breeding males and females and variance of progeny size produced larger values (4425 and 356, respectively), than those based on identity by descent probabilities (average values between 93 and 203). Since breeding practices and genetic substructure within dog breeds increased inbreeding, methods taking into account the evolution of inbreeding produced lower effective population sizes than those taking into account evolution of coancestry. The correlation level between the simplest method (number of breeding males and females, requiring no genealogical information) and the most sophisticated one ranged from 0.44 to 0.60 according to species.

Conclusions

When choosing a method to compute effective population size, particular attention should be paid to the species and the specific genetic structure of the population studied.     

Genomic and resistance gene homolog diversity of the dominant tallgrass prairie species across the U.S. Great Plains precipitation gradient

Background

Environmental variables such as moisture availability are often important in determining species prevalence and intraspecific diversity. The population genetic structure of dominant plant species in response to a cline of these variables has rarely been addressed. We evaluated the spatial genetic structure and diversity of Andropogon gerardii populations across the U.S. Great Plains precipitation gradient, ranging from approximately 48 cm/year to 105 cm/year.

Methodology/Principal Findings

Genomic diversity was evaluated with AFLP markers and diversity of a disease resistance gene homolog was evaluated by PCR-amplification and digestion with restriction enzymes. We determined the degree of spatial genetic structure using Mantel tests. Genomic and resistance gene homolog diversity were evaluated across prairies using Shannon''s index and by averaging haplotype dissimilarity. Trends in diversity across prairies were determined using linear regression of diversity on average precipitation for each prairie. We identified significant spatial genetic structure, with genomic similarity decreasing as a function of distance between samples. However, our data indicated that genome-wide diversity did not vary consistently across the precipitation gradient. In contrast, we found that disease resistance gene homolog diversity was positively correlated with precipitation.

Significance

Prairie remnants differ in the genetic resources they maintain. Selection and evolution in this disease resistance homolog is environmentally dependent. Overall, we found that, though this environmental gradient may not predict genomic diversity, individual traits such as disease resistance genes may vary significantly.     

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.