Genomic estimation of quantitative genetic parameters in wild admixed populations

Heritable genetic variation among free-living animals or plants is essential for populations to respond to selection and adapt. It is therefore important to be able to estimate additive genetic variance VA, which can be obtained using a generalized linear mixed model known as the animal model. An underlying assumption of the standard animal model is that the study population is genetically unstructured, which is often unrealistic. In fact, admixture might be the norm rather than the exception in the wild, like in geographically structured populations, in the presence of (im)migration, or in re-introduction and conservation contexts. Unfortunately, animal model estimators may be biased in such cases. So-called genetic group animal models that account for genetically differentiated subpopulations have recently become popular, but methodology is currently only available for cases where relatedness among individuals can be estimated from pedigrees.To ensure that the animal model remains useful in future applications, there is a clear need to generalize genetic group animal models with heterogeneous VA to the case when exclusively genomic data is available. We therefore introduce such methodology for wild admixed systems by extending methods that were recently suggested in the context of plant breeding. Our extension relaxes the limiting assumptions that currently restrict their use to artificial breeding setups.We illustrate the usefulness of the extended genomic genetic groups animal model on a wild admixed population of house sparrows resident in an island system in Northern Norway, where genome-wide data on more than 180 000 single nucleotide polymorphisms (SNPs) is available to derive genomic relatedness. We compare our estimates of quantitative genetic parameters to those derived from a corresponding pedigree-based genetic groups animal model. The satisfactory agreement indicates that the new method works as expected.Our extension of the very popular animal model ensures that the upcoming challenges with increasing availability of genomic data for quantitative genetic studies of wild admixed populations can be handled. To make the method widely available to the scientific community, we offer guidance in the form of a tutorial including step-by-step instructions to facilitate implementation.

Dissecting the genetic architecture of quantitative traits using genome-wide identity-by-descent sharing among full-sibs

ABSTRACTAdditive and dominance genetic variances underlying the expression of quantitative traits are important quantities for predicting short-term responses to selection, but they are notoriously challenging to estimate in most wild animal populations. Using estimates of genome-wide identity-by-descent (IBD) sharing from autosomal SNP loci, we estimated quantitative genetic parameters for traits known to be under directional natural selection in nine-spined sticklebacks (Pungitius pungitius) and compared these to traditional pedigree-based estimators. Using four different datasets, with varying sample sizes and pedigree complexity, we further assessed the performance of different Genomic Relationship Matrices (GRM) to estimate additive and dominance variance components. Large variance in IBD relationships allowed accurate estimation of genetic variance components, and revealed significant heritability for all measured traits, with negligible dominance contributions. Genome-partitioning analyses revealed that all traits have a polygenic basis and are controlled by genes at multiple chromosomes. The results demonstrate how large full-sib families of highly fecund vertebrates can be used to obtain accurate estimates quantitative genetic parameters to provide insights on genetic architecture of quantitative traits in non-model organisms from the wild. This approach should be particularly useful for studies requiring estimates of genetic variance components from multiple populations as for instance when aiming to infer the role of natural selection as a cause for population differentiation in quantitative traits.

Heterosis and Combining Abilities in a Diverse Seven-Parent Pearl Millet Population Diallel Tested in West Africa

Pearl millet [Pennisetum glaucum (L.) R. Br.] is an important food-security crop to smallholder farmers in West Africa (WA). Breeding for high yield and stability is a major challenge in the harsh environments of WA but could be tackled by hybrid breeding. Knowledge of combining ability patterns and quantitative-genetic parameters is required for an efficient development of hybrid varieties. Hence, our objectives were to estimate the combining ability of seven genetically diverse Sahelian pearl millet populations from Senegal, Mali, Benin, Burkina Faso, Niger, Sudan and Nigeria and the heterosis and stability of their 42 diallel-derived population hybrids to inform pearl millet hybrid breeding. The genotypes were evaluated in six environments in WA in 2007. Grain yield (GY) exhibited an average panmictic mid-parent heterosis (PMPH) of 24%, ranging from -1.51% to 64.69%. General combining ability (GCA) was significant across test environments as reflected by high heritability estimates and high GCA:SCA variance ratios. Thus, early selection for parental per se performance would be rewarding. The parental population from Sudan (IP8679) had strongly negative GCA for GY. Its lack of adaptation contributed to the predominance of additive effects in the present germplasm set. Parental populations PE02987 (Senegal), PE05344 (Mali) and ICMV IS 92222 (Niger) showed large positive GCA for GY. Their offspring, especially PE02987 × PE05344 and Kapelga × ICMV IS 92222, exhibited a high and stable GY across all test environments. Tapping the regional pearl millet genetic diversity seems therefore beneficial for hybrid breeding to increase pearl millet productivity in WA.

Hybrid Breeding for MLN Resistance: Heterosis, Combining Ability, and Hybrid Prediction

Prior knowledge on heterosis and quantitative genetic parameters on maize lethal necrosis (MLN) can help the breeders to develop numerous resistant or tolerant hybrids with optimum resources. Our objectives were to (1) estimate the quantitative genetic parameters for MLN disease severity, (2) investigate the efficiency of the prediction of hybrid performance based on parental per se and general combining ability (GCA) effects, and (3) examine the potential of hybrid prediction for MLN resistance or tolerance based on markers. Fifty elite maize inbred lines were selected based on their response to MLN under artificial inoculation. Crosses were made in a half diallel mating design to produce 307 F1 hybrids. All hybrids were evaluated in MLN quarantine facility in Naivasha, Kenya for two seasons under artificial inoculation. All 50 inbreds were genotyped with genotyping-by-sequencing (GBS) SNPs. The phenotypic variation was significant for all traits and the heritability was moderate to high. We observed that hybrids were superior to the mean performance of the parents for disease severity (−14.57%) and area under disease progress curve (AUDPC) (14.9%). Correlations were significant and moderate between line per se and GCA; and mean of parental value with hybrid performance for both disease severity and AUDPC value. Very low and negative correlation was observed between parental lines marker based genetic distance and heterosis. Nevertheless, the correlation of GCA effects was very high with hybrid performance which can suggests as a good predictor of MLN resistance. Genomic prediction of hybrid performance for MLN is high for both traits. We therefore conclude that there is potential for prediction of hybrid performance for MLN. Overall, the estimated quantitative genetic parameters suggest that through targeted approach, it is possible to develop outstanding lines and hybrids for MLN resistance.

The evolutionary potential of diet-dependent effects on lifespan and fecundity in a multi-parental population of Drosophila melanogaster

The nutritional conditions experienced by a population play a major role in shaping trait evolution in many taxa. Constraints exerted by nutrient limitation or nutrient imbalance can influence the maximal value that fitness components such as reproduction and lifespan attains, and organisms may shift how resources are allocated to different structures and functions in response to changes in nutrition. Whether the phenotypic changes associated with changes in nutrition represent an adaptive response is largely unknown. Further, it is unclear whether the response of fitness components to diet even has the potential to evolve in most systems. In this study, we use an admixed multiparental population of Drosophila melanogaster reared in three different diet conditions to estimate quantitative genetic parameters for lifespan and fecundity. We find significant genetic variation for both traits in our population and show that lifespan has moderate to high heritabilities within diets. Genetic correlations for lifespan between diets were significantly less than one, demonstrating a strong genotype by diet interaction. These findings demonstrate substantial standing genetic variation in our population that is comparable to natural populations and highlights the potential for adaptation to changing nutritional environments.

Deciphering hybrid larch reaction norms using random regression

ABSTRACTThe link between phenotypic plasticity and heterosis is a broad fundamental question, with stakes in breeding. We report a case-study evaluating temporal series of wood ring traits of hybrid larch (Larix decidua×L. kaempferiand reciprocal) in relation to soil water availability. Growth rings record the tree plastic responses to past environmental conditions, and we used random regressions to estimate the reaction norms of ring width and wood density with respect to water availability. We investigated the role of phenotypic plasticity on the construction of hybrid larch heterosis and on the expression of its quantitative genetic parameters. The data came from an intra-/interspecific diallel mating design between both parental species. Progenies were grown in two environmentally contrasted sites, in France. Ring width plasticity with respect to water availability was confirmed, as all three taxa produced narrower rings under the lowest water availability. Hybrid larch appeared to be the most plastic taxon as its superiority over its parental species increased with increasing water availability. Despite the low heritabilities of the investigated traits, we found that the quantitative genetic parameters varied along the water availability gradient. Finally, by means of a complementary simulation, we demonstrated that random regression can be applied to model the reaction norms of non-repeated records of phenotypic plasticity bound by a family structure. Random regression is a powerful tool for the modeling of reaction norms in various contexts, especially perennial species.