Mean Phenotypic Value Research Articles

Transcriptome analysis of inbreeding depression in the Pacific oyster Crassostrea gigas

The Pacific oyster (Crassostrea gigas) is widely cultured worldwide. Because intercrossing inbred strains improves yield (heterosis), development of inbred lines is needed to implement this breeding strategy. However, inbreeding usually reduces the mean phenotypic value shown by characters connected with physiological efficiency or reproductive capacity. The effects of inbreeding on growth and survival of C. gigas have been reported by numerous studies. However, effects of inbreeding on gene expression still remains to be explored in oysters. In this study, the relationship between gene expression and inbreeding depression was investigated in an inbred line of the Pacific oyster. Two inbred groups, an F1 group containing 15 inbreeding families and an F2 group containing 15 families with a presumed relative higher inbreeding level performing worse in growth and survival rate compared to the F1 group, were constituted by using this inbred line. The shell height and survival rate of two inbred groups were compared with those of the wild group including 15 families (CF). A total of 9 RNA-seq libraries were constructed using oyster gills. Based on differential gene analysis, 2430 differentially expressed genes (DEGs) in the F1 group and 3741 in the F2 group were identified respectively compared to the CF group. A total of 1746 common DEGs were counted shared in two inbred groups, of which 911 were up-regulated and 835 were down-regulated. GO and KEGG analysis showed that common DEGs were significantly enriched in the immune response and actin nucleation pathways. Additionally, 695 DEGs were identified between two inbred groups, and GO analysis revealed that these DEGs were significantly in the pathways related to immune and stress response. Our results show the preliminary exploration of the effect of inbreeding on gene expression of C. gigas, which is helpful for us to better understand and manage inbreeding depression of bivalves, and may potentially benefit the breeding of oyster in aquaculture.

Estimating inbreeding depression for growth and reproductive traits using pedigree and genomic methods in Argentinean Brangus cattle.

Inbreeding depression reduces the mean phenotypic value of important traits in livestock populations. The goal of this work was to estimate the level of inbreeding and inbreeding depression for growth and reproductive traits in Argentinean Brangus cattle, in order to obtain a diagnosis and monitor breed management. Data comprised 359,257 (from which 1,990 were genotyped for 40,678 single nucleotide polymorphisms [SNPs]) animals with phenotypic records for at least one of three growth traits: birth weight (BW), weaning weight (WW), and finishing weight (FW). For scrotal circumference (SC), 52,399 phenotypic records (of which 256 had genotype) were available. There were 530,938 animals in pedigree. Three methods to estimate inbreeding coefficients were used. Pedigree-based inbreeding coefficients were estimated accounting for missing parents. Inbreeding coefficients combining genotyped and nongenotyped animal information were also computed from matrix H of the single-step approach. Genomic inbreeding coefficients were estimated using homozygous segments obtained from a Hidden Markov model (HMM) approach. Inbreeding depression was estimated from the regression of the phenotype on inbreeding coefficients in a multiple-trait mixed model framework, either for the whole dataset or for the dataset of genotyped animals. All traits were unfavorably affected by inbreeding depression. A 10% increase in pedigree-based or combined inbreeding would result in a reduction of 0.34 to 0.39 kg in BW, 2.77 to 3.28 kg in WW, and 0.23 cm in SC. For FW, a 10% increase in pedigree-based, genomic, or combined inbreeding would result in a decrease of 8.05 to 11.57 kg. Genomic inbreeding based on the HMM was able to capture inbreeding depression, even in such a compressed genotyped dataset.

Optimum mating designs for exploiting dominance in genomic selection schemes for aquaculture species

BackgroundIn commercial fish, dominance effects could be exploited by predicting production abilities of the offspring that would be generated by different mating pairs and choosing those pairs that maximise the average offspring phenotype. Consequently, matings would be performed to reduce inbreeding depression. This can be achieved by applying mate selection (MS) that combines selection and mating decisions in a single step. An alternative strategy to MS would be to apply minimum coancestry mating (MCM) after selection based on estimated breeding values. The objective of this study was to evaluate, by computer simulations, the potential benefits that can be obtained by implementing MS or MCM based on genomic data for exploiting dominance effects when creating commercial fish populations that are derived from a breeding nucleus.MethodsThe selected trait was determined by a variable number of loci with additive and dominance effects. The population consisted of 50 full-sib families with 30 offspring each. Males and females with the highest estimated genomic breeding values were selected in the nucleus and paired using the MCM strategy. Both MCM and MS were used to create the commercial population.ResultsFor a moderate number of SNPs, equal or even higher mean phenotypic values are obtained by selecting on genomic breeding values and then applying MCM than by using MS when the trait exhibited substantial inbreeding depression. This could be because MCM leads to high levels of heterozygosity across the whole genome, even for loci affecting the trait that are in linkage equilibrium with the SNPs. In contrast, MS specifically promotes heterozygosity for SNPs for which a dominance effect has been detected.ConclusionsIn most scenarios, for the management of aquaculture breeding programs it seems advisable to follow the MCM strategy when creating the commercial population, especially for traits with large inbreeding depression. Moreover, MCM has the appealing property of reducing inbreeding levels, with a corresponding reduction in inbreeding depression for traits beyond those included in the selection objective.

Genetic inbreeding depression load for morphological traits and defects in the Pura Raza Espa\xf1ola horse

BackgroundInbreeding is caused by mating between related individuals and is associated with reduced fitness and performance (inbreeding depression). Several studies have detected heterogeneity in inbreeding depression among founder individuals. Recently, a procedure was developed to predict hidden inbreeding depression load that is associated with founders using the Mendelian sampling of non-founders. The objectives of this study were to: (1) analyse the population structure and general inbreeding, and (2) test this recent approach for predicting hidden inbreeding depression load for four morphological traits and two morphology defects in the Pura Raza Española (PRE) horse breed.ResultsThe regression coefficients that were calculated between trait performances and inbreeding coefficients demonstrated the existence of inbreeding depression. In total, 58,772,533 partial inbreeding coefficients (Fij) were estimated for the whole PRE population (328,706 horses). We selected the descendants of horses with a Fij ≥ 6.25% that contributed to at least four offspring and for which morphological traits were measured for the subsequent analysis of inbreeding depression load (639 horses). A pedigree was generated with the last five generations (5026 animals) used as the reference population (average inbreeding coefficient of 8.39% and average relatedness coefficient of 10.76%). Heritability estimates ranged from 0.08 (cresty neck) to 0.80 (height at withers), whereas inbreeding depression load ratios ranged from 0.01 (knock knee) to 0.40 (length of shoulder), for an inbreeding coefficient of 10%. Most of the correlations between additive and inbreeding depression load genetic values and correlations between inbreeding depression load genetic values for the different traits were positive or near 0.ConclusionsAlthough the average inbreeding depression loads presented negative values, a certain percentage of the animals showed neutral or even positive values. Thus, high levels of inbreeding do not always lead to a decrease in mean phenotypic value or an increase in morphological defects. Hence, individual inbreeding depression loads could be used as a tool to select the most appropriate breeding animals. The possibility of selecting horses that have a high genetic value and are more resistant to the deleterious effects of inbreeding should help improve selection outcomes.

Estimation of genetic and phenotypic trends for wool traits in Kashmir Merino sheep

A study was planned to estimate genetic, heritability and phenotypic trends for Kashmir Merino sheep of J&K. The present study was carried out to study the genetic and phenotypic trends of various wool traits of this breed to understand its progress over the years. Phenotypic, genetic as well as heritability trends were generated for fibre diameter, staple length, greasy fleece weight for clip 1 and greasy fleece weight clip 2 from Government Sheep Breeding Farms Kralpathri (1997–2016) and Goabal (2013–2016). Trend lines were generated as linear regression coefficients of mean breeding values, phenotypic values and heritability for animal’s year of birth. Trends obtained for phenotypic values for fibre diameter and greasy fleece weight at clip one were positive. For staple length and greasy fleece weight at second clip slope was found to be negative. Trends were significant for fibre diameter and staple length and insignificant for all other traits. Slopes for fibre diameter, staple length and greasy fleece weight for first clip and greasy fleece weight for second clip were 0.0126±0.0028, –0.052±0.0203, 0.00228±0.00618, – 0.01945±0.0119 respectively. It may, therefore, be concluded the genetic progress may have more or less stagnated over the years and that an effective selection strategy considering the genetic merit of animals may be adopted to sustain the sheep breeding programs for Kashmir Merino breed.

Genomics-assisted prediction of salt and alkali tolerances and functional marker development in apple rootstocks

BackgroundSaline, alkaline, and saline-alkaline stress severely affect plant growth and development. The tolerance of plants to these stressors has long been important breeding objectives, especially for woody perennials like apple. The aims of this study were to identify quantitative trait loci (QTLs) and to develop genomics-assisted prediction models for salt, alkali, and salt-alkali tolerance in apple rootstock.ResultsA total of 3258 hybrids derived from the apple rootstock cultivars ‘Baleng Crab’ (Malus robusta Rehd., tolerant) × ‘M9’ (M. pumila Mill., sensitive) were used to identify 17, 13, and two QTLs for injury indices of salt, alkali, and salt–alkali stress via bulked segregant analysis. The genotype effects of single nucleotide polymorphism (SNP) markers designed on candidate genes in each QTL interval were estimated. The genomic predicted value of an individual hybrid was calculated by adding the sum of all marker genotype effects to the mean phenotype value of the population. The prediction accuracy was 0.6569, 0.6695, and 0.5834 for injury indices of salt, alkali, and salt–alkali stress, respectively. SNP182G on MdRGLG3, which changes a leucine to an arginine at the vWFA-domain, conferred tolerance to salt, alkali, and salt-alkali stress. SNP761A on MdKCAB, affecting the Kv_beta domain that cooperated with the linked allelic variation SNP11, contributed to salt, alkali, and salt–alkali tolerance in apple rootstock.ConclusionsThe genomics-assisted prediction models can potentially be used in breeding saline, alkaline, and saline-alkaline tolerant apple rootstocks. The QTLs and the functional markers may provide insight for future studies into the genetic variation of plant abiotic stress tolerance.

Population structure, marker-trait association and identification of candidate genes for terminal heat stress relevant traits in bread wheat (Triticum aestivum L. em Thell)

AbstractGenetic improvement along with widened crop base necessitates for the detailed understanding of the genetic diversity and population structure in wheat. The present investigation reports the discovery of a total of 182 alleles by assaying 52 simple sequence repeats (SSRs) on 40 genotypes of bread wheat. Unweighted neighbour-joining method grouped these genotypes into two main clusters. Highly heat tolerant and intermediate tolerant cultivars were grouped in the same cluster, whereas remaining genotypes, particularly sensitive ones, were assigned different cluster. Similarly, the entire population was structured into two sub-populations (K = 2), closely corresponding with the other distance-based clustering patterns. The marker-trait association was discovered for four important physiological parameters, viz. canopy temperature depression, membrane thermostability index (MSI), normalized difference vegetation index and heat susceptibility index, indicating for heat stress (HS) tolerance in wheat. Both general and mixed linear models of association studies during 2017 and 2018, revealed the association of SSR markers, wmc222 (17.60%, PV) and gwm34 (20.70%, PV) with the mean phenotypic value of MSI. Likewise, SSR markers barc183, gwm75, gwm11 and cfd7 revealed a unique relationship with four selected physiological traits. Candidate genes discovered using in silico tools had nine SSR markers within the genic regions reported to play a role in heat and drought stress responses in plants. The information generated about these genic regions may be explored further in expression studies in-vivo to impart HS tolerance in bread wheat.

Contribution of population-level phenotypic plasticity to the invasiveness of Zaprionus indianus (Diptera: Drosophilidae)

Zaprionus indianus is a species of fly native to the Afrotropical biogeographic region, which around twenty years ago invaded the American continent. Several studies have shown that local adaptation and phenotypic plasticity of an invasive species in its native range could favour the colonization of new environments. Zaprionus indianus is a holometabolous generalist polyphagous species that breeds and feeds on the fruits of several different species, which constitute different environments. In this context, we performed a comparative analysis of the phenotypic plasticity of morphological and life history traits in response to seven different breeding environments (i.e. different breeding fruits). The comparison was of native (Africa) vs. invaded range (South America) wild-derived populations. The population-level phenotypic plasticity values related to heterogeneity in different breeding environments for most traits analysed were higher for one of the native range population. This differentiation was also recorded for the ranking across breeding environments of developmental time and wing length mean phenotypic values. In addition, mean phenotypic values pooled across fruit treatments were larger for individuals from the invaded range, which suggests local adaptation. Results define a scenario in which, although not for all the populations analysed, phenotypic plasticity contributes to the invasiveness and local adaptation in native range population of Z. indianus.

Genetic architecture of phenotypic means and plasticities of kernel size and weight in maize.

Genetic relationships between the phenotypic means and plasticities of kernel size and weight revealed the common genetic control of these traits in maize. Kernel size and weight are crucial components of grain yield in maize, and phenotypic plasticity in these traits facilitates adaptations to changing environments. Elucidating the genetic architecture of the mean phenotypic values and plasticities of kernel size and weight may be essential for breeding climate-robust maize varieties. Here, a maize nested association mapping (CN-NAM) population and association panel were grown in different environments. A joint linkage analysis and genome-wide association mapping were performed for five kernel size and weight phenotypic traits and two phenotypic plasticity measures. The mean phenotypes and plasticities were significantly correlated. The overall results of quantitative trait locus (QTL) and candidate gene analyses indicated moderate and high levels of common genetic control for the two traits. Furthermore, the mean phenotypes or plasticities of the hundred-kernel weight and volume were commonly regulated to a high degree. One pleiotropic locus on chromosome 10 simultaneously controlled the mean phenotypic values and plasticities of kernel size and weight. Therefore, the plasticity of kernel size and weight might be indirectly selected during maize breeding; however, selecting for high or low plasticity in combination with high or low mean phenotypic values of kernel size and weight traits may be difficult.

Estimation of genetic, heritability, and phenotypic trends for weight and wool traits in Rambouillet sheep

Genetic and phenotypic trends give an indication of the progress of a breed over the years and help in understanding the effectiveness of selection. Therefore, a study was planned to estimate genetic, heritability and phenotypic trends for Rambouillet breed of sheep. Trends were estimated for birth weight, weaning weight, fibre diameter, greasy fleece weight at clip one and staple length on data collected from 1998 to 2008. Two yearly mean phenotypic values, heritability values, and mean breeding values for birth weight, weaning weight, fibre diameter, greasy fleece weight at clip one and staple length were estimated. These trends were determined as a linear regression coefficient of mean breeding values using BLUP (best linear unbiased prediction) for the animal’s year of birth and a trend line was generated separately for each trait. Trends for phenotypic values were positive for birth weight, staple length and greasy fleece weight whereas for weaning weight and fibre diameter, the trends were negative. The slopes for birth weight and weaning were found to be 0.040 ± 0.0525 and −0.07 ± 0.241 respectively. Slopes for fibre diameter, staple length and greasy fleece weight for first clip were -0.011 ± 0.01, 0.146 ± 0.041 and 0.052 ± 0.029 respectively. The slopes all traits were found to be insignificant except staple length. For heritability, the slopes of birth weight, weaning, fibre diameter, staple length and greasy fleece weight for first clip were 0.0005 ± 0.0048, 0.009 ± 0.0048 0.0058 ± 0.011, 0.0041 ± 0.003, and 0.0061 ± 0.0039 respectively. Trends obtained for breeding values were positive for birthweight, staple length and greasy fleece weight for first clip and negative for weaning weight and fibre diameter. All traits had an insignificant slope for breeding values. The slopes for breeding values for birth weight and weaning were 0.001 ± 0.0004 and −0.0025 ± 0.001 respectively. Slopes for fibre diameter, staple length and greasy fleece weight for first clip were −0.0002 ± 0.0002, 0.0002 ± 0.0001, 0.0001 ± 0.0002 respectively. It is concluded that an optimal selection strategy that considers both genetic merits and coancestry of mates (in order to avoid close breeding and inbreeding depression) should be adopted to sustain the sheep breeding programs in the State.

Inferring the potentially complex genetic architectures of adaptation, sexual dimorphism and genotype by environment interactions by partitioning of mean phenotypes.

Genetic architecture fundamentally affects the way that traits evolve. However, the mapping of genotype to phenotype includes complex interactions with the environment or even the sex of an organism that can modulate the expressed phenotype. Line-cross analysis is a powerful quantitative genetics method to infer genetic architecture by analysing the mean phenotype value of two diverged strains and a series of subsequent crosses and backcrosses. However, it has been difficult to account for complex interactions with the environment or sex within this framework. We have developed extensions to line-cross analysis that allow for gene by environment and gene by sex interactions. Using extensive simulation studies and reanalysis of empirical data, we show that our approach can account for both unintended environmental variation when crosses cannot be reared in a common garden and can be used to test for the presence of gene by environment or gene by sex interactions. In analyses that fail to account for environmental variation between crosses, we find that line-cross analysis has low power and high false-positive rates. However, we illustrate that accounting for environmental variation allows for the inference of adaptive divergence, and that accounting for sex differences in phenotypes allows practitioners to infer the genetic architecture of sexual dimorphism.

Assessment of phenotypic diversity in bitter vetch (Vicia ervilia (L.) Willd.) populations

Knowledge of populations’ diversity contributes to the optimization of their description and conservation. Characterization and estimation of diversity of neglected and underutilized crops would encourage their re-introduction and utilization. Therefore, the aim of this study was to characterize 49 populations of bitter vetch on the basis of 24 agro-morphological traits and estimate phenotypic diversity among and within populations. A wide diversity was present in the collection for the majority of traits analyzed (mean total phenotypic diversity, H T = 0.52). The mean phenotypic diversity among populations studied (G ST ) was 0.31. Most traits related to reproductive phase had G ST ≥ 0.5, while for most traits high intra-population variation (Η S ) was detected. No significant differences among populations’ mean phenotypic diversity values (0.27 ≤ $$\bar{H}p$$ ≤ 0.47) were observed. Principal Component Analysis (PCA) classified the populations into eight distinct groups, mainly due to traits related to reproductive phase and seed yield. The high phenotypic populations’ diversity observed, showed that ex situ conserved populations of bitter vetch constitute an underutilized gene pool that could be re-introduced in cultivated systems and/or utilized by breeding programs and revealed a need for conservation of bitter vetch landraces that are still cultivated.

Predicting rice hybrid performance using univariate and multivariate GBLUP models based on North Carolina mating design II.

Genomic selection (GS) is more efficient than traditional phenotype-based methods in hybrid breeding. The present study investigated the predictive ability of genomic best linear unbiased prediction models for rice hybrids based on the North Carolina mating design II, in which a total of 115 inbred rice lines were crossed with 5 male sterile lines. Using 8 traits of the 575 (115 × 5) hybrids from two environments, both univariate (UV) and multivariate (MV) prediction analyses, including additive and dominance effects, were performed. Using UV models, the prediction results of cross-validation indicated that including dominance effects could improve the predictive ability for some traits in rice hybrids. Additionally, we could take advantage of GS even for a low-heritability trait, such as grain yield per plant (GY), because a modest increase in the number of top selection could generate a higher, more stable mean phenotypic value for rice hybrids. Thus this strategy was used to select superior potential crosses between the 115 inbred lines and those between the 5 male sterile lines and other genotyped varieties. In our MV research, an MV model (MV-ADV) was developed utilizing a MV relationship matrix constructed with auxiliary variates. Based on joint analysis with multi-trait (MT) or with multi-environment, the prediction results confirmed the superiority of MV-ADV over an UV model, particularly in the MT scenario for a low-heritability target trait (such as GY), with highly correlated auxiliary traits. For a high-heritability trait (such as thousand-grain weight), MT prediction is unnecessary, and UV prediction is sufficient.

The evolution of labile traits in sex- and age-structured populations.

Summary Many quantitative traits are labile (e.g. somatic growth rate, reproductive timing and investment), varying over the life cycle as a result of behavioural adaptation, developmental processes and plastic responses to the environment. At the population level, selection can alter the distribution of such traits across age classes and among generations. Despite a growing body of theoretical research exploring the evolutionary dynamics of labile traits, a data‐driven framework for incorporating such traits into demographic models has not yet been developed.Integral projection models (IPMs) are increasingly being used to understand the interplay between changes in labile characters, life histories and population dynamics. One limitation of the IPM approach is that it relies on phenotypic associations between parents and offspring traits to capture inheritance. However, it is well‐established that many different processes may drive these associations, and currently, no clear consensus has emerged on how to model micro‐evolutionary dynamics in an IPM framework.We show how to embed quantitative genetic models of inheritance of labile traits into age‐structured, two‐sex models that resemble standard IPMs. Commonly used statistical tools such as GLMs and their mixed model counterparts can then be used for model parameterization. We illustrate the methodology through development of a simple model of egg‐laying date evolution, parameterized using data from a population of Great tits (Parus major).We demonstrate how our framework can be used to project the joint dynamics of species' traits and population density. We then develop a simple extension of the age‐structured Price equation (ASPE) for two‐sex populations, and apply this to examine the age‐specific contributions of different processes to change in the mean phenotype and breeding value.The data‐driven framework we outline here has the potential to facilitate greater insight into the nature of selection and its consequences in settings where focal traits vary over the lifetime through ontogeny, behavioural adaptation and phenotypic plasticity, as well as providing a potential bridge between theoretical and empirical studies of labile trait variation.

Heterosis for protein, digestibility, fiber, and water soluble carbohydrates in nine sources of orchardgrass germplasm

Orchardgrass, or cocksfoot, (Dactylis glomerata L.) is one of the most important forage grasses used in temperate agriculture. Yet, genetic gains are slow and complicated owing to the perennial and autotetraploid nature of orchardgrass. The development of orchardgrass population hybrids may be a way to more efficiently make genetic gains through heterosis. In the study reported herein, we describe the results of a 3 year study of the effect of heterosis on the forage quality of orchardgrass population hybrids managed with supplemental irrigation at a Cache County, UT, USA field site. The population hybrids derived from the orchardgrass cultivars Latar, Paiute, and Potomac; and from six additional germplasm sources from Asia, Europe, and North America. Data reflected July and August harvests from 2008 to 2010 and included crude protein (CP), in vitro true digestibility (IVTD), neutral detergent fiber (NDF), and water soluble carbohydrates (WSC). There were differences (P < 0.05) among the population hybrids and the included check cultivars for each of the traits at both harvest points. Mid-parent heterosis was relatively common and there were several instances of high-parent heterosis and reciprocal effects. Additionally, the population hybrids possessed better mean phenotypic values than the cultivars for July CP (2 g kg−1), and August CP (4 g kg−1), IVTD (7 g kg−1), NDF (−9 g kg−1), and WSC (4 g kg−1). Overall, the results suggest that population hybrids may prove a feasible approach for orchardgrass forage quality improvement.

Neural networks for predicting breeding values and genetic gains

Analysis using Artificial Neural Networks has been described as an approach in the decision-making process that, although incipient, has been reported as presenting high potential for use in animal and plant breeding. In this study, we introduce the procedure of using the expanded data set for training the network. Wealso proposed using statistical parameters to estimate the breeding value of genotypes in simulated scenarios, in addition to the mean phenotypic value in a feed-forward back propagation multilayer perceptron network. After evaluating artificial neural network configurations, our results showed its superiority to estimates based on linear models, as well as its applicability in the genetic value prediction process. The results further indicated the good generalization performance of the neural network model in several additional validation experiments.

Optimizing the creation of base populations for aquaculture breeding programs using phenotypic and genomic data and its consequences on genetic progress.

The success of an aquaculture breeding program critically depends on the way in which the base population of breeders is constructed since all the genetic variability for the traits included originally in the breeding goal as well as those to be included in the future is contained in the initial founders. Traditionally, base populations were created from a number of wild strains by sampling equal numbers from each strain. However, for some aquaculture species improved strains are already available and, therefore, mean phenotypic values for economically important traits can be used as a criterion to optimize the sampling when creating base populations. Also, the increasing availability of genome-wide genotype information in aquaculture species could help to refine the estimation of relationships within and between candidate strains and, thus, to optimize the percentage of individuals to be sampled from each strain. This study explores the advantages of using phenotypic and genome-wide information when constructing base populations for aquaculture breeding programs in terms of initial and subsequent trait performance and genetic diversity level. Results show that a compromise solution between diversity and performance can be found when creating base populations. Up to 6% higher levels of phenotypic performance can be achieved at the same level of global diversity in the base population by optimizing the selection of breeders instead of sampling equal numbers from each strain. The higher performance observed in the base population persisted during 10 generations of phenotypic selection applied in the subsequent breeding program.

Biometric analysis of protein and oil contents of soybean genotypes in different environments

The objective of this work was to identify by biometric analyses the most stable soybean parents, with higher oil or protein contents, cultivated at different seasons and locations of the state of Minas Gerais, Brazil. Forty-nine genotypes were evaluated in the municipalities of Viçosa, Visconde do Rio Branco, and São Gotardo, in the state of Minas Gerais, from 2009 to 2011. Protein and oil contents were analyzed by infrared spectrometry using a FT-NIR analyzer. The effects of genotype, environment, and genotype x environment interaction were significant. The BARC-8 soybean genotype is the best parent to increase protein contents in the progenies, followed by BR 8014887 and CS 3032PTA276-3-4. Selection for high oil content is more efficient when the crossings involve the Suprema, CD 01RR8384, and A7002 genotypes, which show high mean phenotypic values, wide adaptability, and greater stability to environmental variation.

The role of founder effects on the evolution of reproductive isolation

Several theories argue that large changes in allele frequencies through genetic drift after a small founding population becomes allopatrically isolated can lead to significant changes in reproductive isolation and thus trigger the origin of new species. For this reason, founder speciation has been proposed as a potent force in the generation of new species. Nonetheless, the relative importance of such 'founder effects' remains largely untested. In this report, I used experimental evolution to create one thousand replicates that underwent an extreme bottleneck and to study whether founder effects can lead to an increase in reproductive isolation in Drosophila yakuba. Even though the most common outcome of inbreeding is extinction, founder effects can lead to increased premating reproductive isolation in a very small proportion of cases. Changes in reproductive isolation after a founding population bottleneck are similar to changes in other phenotypic traits, in which inbreeding might displace the mean phenotypic value and substantially increase the phenotypic variance. This increase in phenotypic variance does not confer an increase in the response to selection for reproductive isolation in artificial selection experiments, indicating that the increased phenotypic variance is not caused by increases in additive genetic variance. These results also demonstrate that, similar to morphological and life-history traits, behavioural traits can be affected by inbreeding and genetic drift.

Genetic Architecture of Delayed Senescence, Biomass, and Grain Yield under Drought Stress in Cowpea

The stay-green phenomenon is a key plant trait with wide usage in managing crop production under limited water conditions. This trait enhances delayed senescence, biomass, and grain yield under drought stress. In this study we sought to identify QTLs in cowpea (Vigna unguiculata) consistent across experiments conducted in Burkina Faso, Nigeria, Senegal, and the United States of America under limited water conditions. A panel of 383 diverse cowpea accessions and a recombinant inbred line population (RIL) were SNP genotyped using an Illumina 1536 GoldenGate assay. Phenotypic data from thirteen experiments conducted across the four countries were used to identify SNP-trait associations based on linkage disequilibrium association mapping, with bi-parental QTL mapping as a complementary strategy. We identified seven loci, five of which exhibited evidence suggesting pleiotropic effects (stay-green) between delayed senescence, biomass, and grain yield. Further, we provide evidence suggesting the existence of positive pleiotropy in cowpea based on positively correlated mean phenotypic values (0.34< r <0.87) and allele effects (0.07< r <0.86) for delayed senescence and grain yield across three African environments. Three of the five putative stay-green QTLs, Dro-1, 3, and 7 were identified in both RILs and diverse germplasm with resolutions of 3.2 cM or less for each of the three loci, suggesting that these may be valuable targets for marker-assisted breeding in cowpea. Also, the co-location of early vegetative delayed senescence with biomass and grain yield QTLs suggests the possibility of using delayed senescence at the seedling stage as a rapid screening tool for post-flowering drought tolerance in cowpea breeding. BLAST analysis using EST sequences harboring SNPs with the highest associations provided a genomic context for loci identified in this study in closely related common bean (Phaseolus vulgaris) and soybean (Glycine max) reference genomes.