Genetic Variation In Quantitative Traits Research Articles

Drift on holey landscapes as a dominant evolutionary process.

An organism's phenotype has been shaped by evolution but the specific processes have to be indirectly inferred for most species. For example, correlations among traits imply the historical action of correlated selection and, more generally, the expression and distribution of traits is expected to be reflective of the adaptive landscapes that have shaped a population. However, our expectations about how quantitative traits-like most behaviors, physiological processes, and life-history traits-should be distributed under different evolutionary processes are not clear. Here, we show that genetic variation in quantitative traits is not distributed as would be expected under dominant evolutionary models. Instead, we found that genetic variation in quantitative traits across six phyla and 60 species (including both Plantae and Animalia) is consistent with evolution across high-dimensional "holey landscapes." This suggests that the leading conceptualizations and modeling of the evolution of trait integration fail to capture how phenotypes are shaped and that traits are integrated in a manner contrary to predictions of dominant evolutionary theory. Our results demonstrate that our understanding of how evolution has shaped phenotypes remains incomplete and these results provide a starting point for reassessing the relevance of existing evolutionary models.

A demo-genetic model shows how silviculture reduces natural density-dependent selection in tree populations.

Biological production systems and conservation programs benefit from and should care for evolutionary processes. Developing evolution-oriented strategies requires knowledge of the evolutionary consequences of management across timescales. Here, we used an individual-based demo-genetic modelling approach to study the interactions and feedback between tree thinning, genetic evolution, and forest stand dynamics. The model combines processes that jointly drive survival and mating success-tree growth, competition and regeneration-with genetic variation of quantitative traits related to these processes. In various management and disturbance scenarios, the evolutionary rates predicted by the coupled demo-genetic model for a growth-related trait, vigor, fit within the range of empirical estimates found in the literature for wild plant and animal populations. We used this model to simulate non-selective silviculture and disturbance scenarios over four generations of trees. We characterized and quantified the effect of thinning frequencies and intensities and length of the management cycle on viability selection driven by competition and fecundity selection. The thinning regimes had a drastic long-term effect on the evolutionary rate of vigor over generations, potentially reaching 84% reduction, depending on management intensity, cycle length and disturbance regime. The reduction of genetic variance by viability selection within each generation was driven by changes in genotypic frequencies rather than by gene diversity, resulting in low-long-term erosion of the variance across generations, despite short-term fluctuations within generations. The comparison among silviculture and disturbance scenarios was qualitatively robust to assumptions on the genetic architecture of the trait. Thus, the evolutionary consequences of management result from the interference between human interventions and natural evolutionary processes. Non-selective thinning, as considered here, reduces the intensity of natural selection, while selective thinning (on tree size or other criteria) might reduce or reinforce it depending on the forester's tree choice and thinning intensity.

Assessment of genetic diversity for seed vigor traits in rice (Oryza sativa L.) through principal component and cluster analysis

Seed vigor, an important characteristic of seed quality attributes, determines the rate of early, rapid, uniform germination, emergenceand growth of strong seedling in any environmental condition. In the present set of experiment, 44 rice (Oryza sativa L.) varieties wereassessed for different seed vigor component traits. For evaluation of these traits, basic statistics, correlation, principal component (PC) andcluster analysis were carried out to obtain genetic diversity for seed vigor traits and early seedling vigor among rice varieties specifically to select the best varieties and important seed vigor traits for its possible use in future rice breeding programme. The estimation of descriptive statistics of 20 quantitative seed vigor-related traits indicated existence of variability among the varieties. The 44 varieties were grouped into five clusters on the basis of average linkage and dendogram. Varieties in Cluster I are considered to possess very high vigor traits and cluster IV with least seed vigor traits. Principal component (PC) analysis showed first 5 PCs having Eigen value >1 explaining 77.01% of the total variation with different seed vigor traits. In the biplot analysis between PCs 1 and 2, the varieties remained scattered in all four quadrants, showing large genetic variation in quantitative traits. Seed vigor index-I, seed vigor index-II, seed dry weight, shoot length, reserve mobilization, germination percentage, dehydrogenase, mean germination rate, germination speed, and mean germination time contributed to high variability among the varieties. The seed vigor traits were positively correlated with germination percentage, shoot length, seedling dry weight, speed of germination, mean germination rate, reserve mobilization, superoxide dismutase, dehydrogenase and alpha-amylase. The positive correlation among these seed vigor-contributing traits suggested that these characteristics are important for direct selection of high seed vigor varieties and early emergence.

Evaluation of genetic variation of morphological and clubroot-resistance traits of radish and metabonomic analysis of clubroot-resistant cultivar

Global commercial production of radish (Raphanus sativus) is highly threatened by Plamodiophora brassicae. Germplasm evaluation and the deep analysis of variants with clubroot-resistant trait are needed to produce quality cultivars. The genetic diversity was analyzed for 97 radish germplasms based on 20 agronomic traits and the response to clubroot. Additionally, differentially regulated metabolites (DRMs) between healthy and P. brassicae-infected resistant cultivars were measured. The genetic diversity index values of quality traits varied from 0.396 to 1.350, and that of quantitative traits varied from 1.65–2.15. The variation of radish quantitative traits ranged from 19.18% to 54.44%. The principal component analysis indicated 8 comprehensive indicators, allowing classification of germplasms into 4 classes, with 71 in class I, 20 in class II, 4 in class III, and 2 in class IV. The results of classification of germplasms by the response to clubroot infection only or by comprehensive agronomic traits including response of plants to clubroot disease infection were similar. Among all traits assessed in the present study, the clubroot severity and the depth of in-soil root were closely linked. Metabolomic analysis revealed that the metabolites changes of clubroot resistant cultivar “DHBC” pre- and post- P. brassicae infection was relatively stable. P. brassicae infection resulted in limited DRMs, significant down-regulation was identified on ginsenoside, dihydro-2(3H)-thiophenone, proline, 1-pyrroline, while apiosylglucosyl 4-hydroxybenzoate, chrycolide, glucomalcomiin, and phosphocholine were significantly up-regulated. We revealed more extensive genetic variation in quantitative traits than in quality indexes in radish and we summarized that the response of radish to clubroot disease may be a dominate indicator in evaluation of radish varieties. Finally, untargeted metabolomic study confirmed the clubroot resistance of “DHBC” and revealed a sophisticated metabolites (including some precious pharmaceutical ingredients) variation in response to clubroot infection, offers new directions in the studies of clubroot resistance mechanism of radish.

Environmental contributions to the evolution of trait differences in Geum triflorum: Implications for restoration.

How the environment influences the distribution of trait variation across a species' range has important implications for seed transfer during restoration. Evolution across environments could influence fitness when individuals are transferred into new environments. Here, we evaluate the role the environment has had on the distribution of genetic variance for traits important to adaptation. In a common garden experiment, we quantified trait differentiation for populations of Geum triflorum sourced from three distinct ecoregions and evaluated the ability of climate to predict trait variation. Populations were sourced from the Manitoba and Great Lake alvar ecoregions that experience predictable extremes in seasonal water availability and the prairie ecoregion which exhibits unpredictable changes in water availability. Plants sourced from alvar ecoregions exhibited smaller but more stomata and greater intrinsic water-use efficiency relative to prairie plant populations, supporting the evolution of ecotypic differences. Estimates of standing genetic variance and heritable genetic variation for quantitative traits suggest alvar populations have greater adaptive potential. However, low evolvability suggests all populations likely have limited capacity to evolve in response to environmental change. These results highlight the importance of the environment in influencing the evolution and distribution of genetic differences across populations used as seed sources for restoration. Additionally, these data may inform recommendations for seed transfer across novel environments and our expectations of populations' adaptive potential.

Maintenance of quantitative genetic variance in complex, multitrait phenotypes: the contribution of rare, large effect variants in 2 Drosophila species.

The interaction of evolutionary processes to determine quantitative genetic variation has implications for contemporary and future phenotypic evolution, as well as for our ability to detect causal genetic variants. While theoretical studies have provided robust predictions to discriminate among competing models, empirical assessment of these has been limited. In particular, theory highlights the importance of pleiotropy in resolving observations of selection and mutation, but empirical investigations have typically been limited to few traits. Here, we applied high-dimensional Bayesian Sparse Factor Genetic modeling to gene expression datasets in 2 species, Drosophila melanogaster and Drosophila serrata, to explore the distributions of genetic variance across high-dimensional phenotypic space. Surprisingly, most of the heritable trait covariation was due to few lines (genotypes) with extreme [>3 interquartile ranges (IQR) from the median] values. Intriguingly, while genotypes extreme for a multivariate factor also tended to have a higher proportion of individual traits that were extreme, we also observed genotypes that were extreme for multivariate factors but not for any individual trait. We observed other consistent differences between heritable multivariate factors with outlier lines vs those factors without extreme values, including differences in gene functions. We use these observations to identify further data required to advance our understanding of the evolutionary dynamics and nature of standing genetic variation for quantitative traits.

Induced variability and assessment of mutagenic effectiveness and efficiency in sorghum genotypes [Sorghum bicolor (L.) Moench

Purpose Sorghum is an important cereal crop, cultivated for food, fodder and biofuel. Mutation breeding techniques are used to create genetic variability for qualitative and quantitative traits in crop plants. The purpose of this study was to create induced variability and estimate mutagenic effectiveness and efficiency of physical and chemical mutagens in two sorghum cultivars. Materials and methods Gamma rays (100, 200, 300 and 400 Gy, Co60 source, Bhabha Atomic Research Center, Mumbai, India), ethyl methane sulfonate (0.1%, 0.2%, 0.3%, and 0.4% EMS, Sigma-Aldrich, Bangalore, India) and their combinations were used to mutagenize 296B (rainy season) and Parbhani moti (post-rainy) cultivars. Morphological and yield traits were analyzed for enhanced variability in qualitative and quantitative traits across M2 and M3 generations. Results Based on the mutagenic sensitivity, lethal dose at 50% survivability (LD50) for both the genotypes was found to be 269–281 Gy in case of gamma rays and 0.32–0.33% for EMS. Based on reduced germination and survivability, mutagenic sensitivity was dose dependent and genotype independent. High frequency of chlorophyll mutations (albino, xantha, viridis, variegated and chlorina) was linearly correlated with dose in both the genotypes. Among the favorable mutants, dwarf and brown midrib were isolated from Parbhani moti population, which could be used in the cross breeding programs. A combined treatment, 100 Gy + 0.1% EMS showed high mutagenic effectiveness and efficiency. Enhanced genetic variation for quantitative traits as measured by wide range values and coefficient of variation was attributed to the effect of physical and chemical mutagens. Early flowering and high grain yield (24–49% increase over control) mutants were identified in M2 and validated in M3 generation in both genotypes. Conclusions This study has revealed wide genetic variability and better effectiveness and efficiency of the physical (300 Gy) and chemical mutagens (0.2%) and their combination (200 Gy + 0.2%) across two sorghum genotypes. Significant correlations identified between quantitative traits will help in better selection in the segregating generations.

Absence of genetic differentiation in performance traits of Sinapis arvensis populations from crop and non‐crop habitats across Northern Algeria: Implications for management

AbstractWeeds can originate from adjacent habitats, dispersing naturally from non‐crop habitats as well as brought in from other crop fields by machinery or as contaminants of crop seeds. This constant dispersal may homogenise populations and transmit resistance genes. In this study, we examined (a) the genetic variation in quantitative traits and (b) the level of resistance to two widely used herbicides, amidosulfuron + iodosulfuron‐methyl‐sodium and florasulam + 2,4‐D, in eight population pairs of Sinapis arvensis from crop and adjacent non‐crop habitats across eight regions in Northern Algeria. Our quantitative genetic approach on phenotypic and phenological data of plants grown under controlled conditions from seeds of these populations showed similar levels of within‐population genetic variation and no genetic differentiation in quantitative traits between the two habitat types. This points to an important exchange of S. arvensis seeds and/or pollen between the two habitat types, but not among crop fields at the regional scale, as we found a strong regional effect for most of the plant traits for both habitat types that correlated with longitudinal temperature and precipitation gradients. We also found an absence of resistance against the two herbicides at a detection level of 10%. Florasulam + 2,4‐D showed a higher level and speed of phytotoxicity compared to amidosulfuron + iodosulfuron‐methyl‐sodium. Given our findings, we propose measures for more efficient management of S. arvensis, including minimisation of seed dispersal during transport of straw balls, crop rotation to avoid the build‐up of herbicide resistance, and management of populations in the close vicinity of crop fields.

Variance Components of Some Quantitative Characters in 16 Varieties of Rice (Oryza sativa L.) influenced by Different Nitrogen Fertilizer Levels

Heritability and phenotypic estimates of some quantitative traits and its influence on different nitrogen fertilizer levels give the room for recombinants which become a prerequisite for any breeding study. Genetic variation in quantitative traits for the development of a new variety of crop plant with different nitrogen fertilizer levels. Based on this background, the study was conducted in order to evaluate the quantitative traits from advanced blast-resistant rice varieties in order to establish relationship between yield and yield components using genetic variances. To achieve this objective, two field studies were carried out in Malaysia during the cropping season 2017/2018. Sixteen advanced blast-resistant rice genotypes were studied in order to find out phenotypic correlation and heritability in some quantitative characters to determine the effect of various levels of Nitrogen fertilizer. The field experiment was conducted in a split-plot design replicated three times in a plot of 35 × 28.5 m2. The planting distance was 25 × 25 cm and the plot size was 2 × 1.5 m2 unit for genotype in each replication. There was a highly significant variation among the genotypes in response to nitrogen levels, high PCV, GCV, heritability, relative distance and genetic advance which indicated that different quantitative traits especially tonnes per hectare (Tha), grain weight per plot (GWTPP) and kilogram per plot (kgplot) significantly influence the yield trait. Similarly, high heritability (>60%) was observed indicating the substantial effect of additive genes more than the environmental effect. Yield per plant showed strong to low positive correlations (𝑟 = 0.99 - 0.09) at phenotypic level for grain weight per plot (GWTPP), number of tillers per hill (NTH), number of panicle per hill (NPH) and kilogram per plot (kg/plot).

Genetic variation and early selection in Larix decidua Mill. from progeny test in Romania

High genetic variation and determinism for quantitative traits of Larix decidua Mill. were found in a progeny test established at its south-eastern limit of distribution area. The top range families are from both native populations and artificial stands of unknown origin. Recurrent selection at the nursery stage based on total height can reduce the generation time and increase the genetic gain. Despite the economic and ecological importance of Larix decidua in Europe, little information is available regarding its genetic variation and genetic parameters, particularly in the south-eastern part of its distribution area. The objectives of this study were to investigate genetic variation, to estimate genetic parameters and to predict genetic gain in three alternative selection strategies for quantitative traits of L. decidua in a progeny experiment at the nursery stage. Genetic variation of growth, branch traits and bud flushing were assessed in an open-pollinated progenies from 56 plus trees of L. decidua. Plus trees were selected from two natural populations (native to the Romanian Carpathians) and four artificial stands of unknown origin (most likely from the Austrian Alps). Analysis of variance was performed at three levels: provenance region, family and within family. The variance components, coefficients of heritability, genetic and phenotypic correlations, and genetic gain were also determined. Large genetic variation in quantitative traits was found among L. decidua open-pollination families. Results highlight high genetic control for growth traits and bud flushing and support the premise that the strategy based on recurrent selection will bring the greatest genetic gain in the next breeding generation. Results complete the knowledge concerning genetic parameters of some traits important for L. decidua breeding programmes in Europe. Further analysis is necessary in order to determine the origin of the genitors involved in the next breeding cycle, given that the best families come from both natural populations and artificial stands, which are very most likely from the Tyrolean Alps.

Inferring the distribution of fitness effects of spontaneous mutations in Chlamydomonas reinhardtii.

Spontaneous mutations are the source of new genetic variation and are thus central to the evolutionary process. In molecular evolution and quantitative genetics, the nature of genetic variation depends critically on the distribution of effects of mutations on fitness and other quantitative traits. Spontaneous mutation accumulation (MA) experiments have been the principal approach for investigating the overall rate of occurrence and cumulative effect of mutations but have not allowed the phenotypic effects of individual mutations to be studied directly. Here, we crossed MA lines of the green alga Chlamydomonas reinhardtii with its unmutated ancestral strain to create haploid recombinant lines, each carrying an average of 50% of the accumulated mutations in a large number of combinations. With the aid of the genome sequences of the MA lines, we inferred the genotypes of the mutations, assayed their growth rate as a measure of fitness, and inferred the distribution of fitness effects (DFE) using a Bayesian mixture model. We infer that the DFE is highly leptokurtic (L-shaped). Of mutations with absolute fitness effects exceeding 1%, about one-sixth increase fitness in the laboratory environment. The inferred distribution of effects for deleterious mutations is consistent with a strong role for nearly neutral evolution. Specifically, such a distribution predicts that nucleotide variation and genetic variation for quantitative traits will be insensitive to change in the effective population size.

Maintenance of genetic variation in quantitative traits of a woodland rodent during generations of captive breeding

Breeding programs to conserve diversity are predicated on the assumption that genetic variation in adaptively important traits will be lost in parallel to the loss of variation at neutral loci. To test this assumption, we monitored quantitative traits across 18 generations of Peromyscus leucopus mice propagated with protocols that mirror breeding programs for threatened species. Ears, hind feet, and tails became shorter, but changes were reversible by outcrossing and therefore were due to accumulated inbreeding. Heritability of ear length decreased, because of an increase in phenotypic variance rather than the expected decrease in additive genetic variance. Additive genetic variance in hind foot length increased. This trait initially had low heritability but large dominance or common environmental variance contributing to resemblance among full-sibs. The increase in the additive component indicates that there was conversion of interaction variances to additive variance. For no trait did additive genetic variation decrease significantly across generations. These findings indicate that the restructuring of genetic variance that occurs with genetic drift and novel selection in captivity can prevent or delay the loss of phenotypic and heritable variation, providing variation on which selection can act to adapt populations to captivity and perhaps later to readapt to more natural habitats after release. Therefore, the importance of minimizing loss of gene diversity from conservation breeding programs for threatened wildlife species might lie in preventing immediate reduction in individual fitness due to inbreeding and protecting allelic diversity for long-term evolutionary change, more so than in protecting variation in quantitative traits for rapid re-adaptation to wild environments.

What can genome-wide association studies tell us about the evolutionary forces maintaining genetic variation for quantitative traits?

Contents 21 I. 21 II. 22 III. 24 IV. 25 V. 29 30 References 30 SUMMARY: Understanding the evolutionary forces that shape genetic variation within species has long been a goal of evolutionary biology. Integrating data for the genetic architecture of traits from genome-wide association mapping studies (GWAS) along with the development of new population genetic methods for identifying selection in sequence data may allow us to evaluate the roles of mutation-selection balance and balancing selection in shaping genetic variation at various scales. Here, we review the theoretical predictions for genetic architecture and additional signals of selection on genomic sequence for the loci that affect traits. Next, we review how plant GWAS have tested for the signatures of various selective scenarios. Limited evidence to date suggests that within-population variation is maintained primarily by mutation-selection balance while variation across the landscape is the result of local adaptation. However, there are a number of inherent biases in these interpretations. We highlight these challenges and suggest ways forward to further understanding of the maintenance of variation.

A Model of Compound Heterozygous, Loss-of-Function Alleles Is Broadly Consistent with Observations from Complex-Disease GWAS Datasets.

The genetic component of complex disease risk in humans remains largely unexplained. A corollary is that the allelic spectrum of genetic variants contributing to complex disease risk is unknown. Theoretical models that relate population genetic processes to the maintenance of genetic variation for quantitative traits may suggest profitable avenues for future experimental design. Here we use forward simulation to model a genomic region evolving under a balance between recurrent deleterious mutation and Gaussian stabilizing selection. We consider multiple genetic and demographic models, and several different methods for identifying genomic regions harboring variants associated with complex disease risk. We demonstrate that the model of gene action, relating genotype to phenotype, has a qualitative effect on several relevant aspects of the population genetic architecture of a complex trait. In particular, the genetic model impacts genetic variance component partitioning across the allele frequency spectrum and the power of statistical tests. Models with partial recessivity closely match the minor allele frequency distribution of significant hits from empirical genome-wide association studies without requiring homozygous effect sizes to be small. We highlight a particular gene-based model of incomplete recessivity that is appealing from first principles. Under that model, deleterious mutations in a genomic region partially fail to complement one another. This model of gene-based recessivity predicts the empirically observed inconsistency between twin and SNP based estimated of dominance heritability. Furthermore, this model predicts considerable levels of unexplained variance associated with intralocus epistasis. Our results suggest a need for improved statistical tools for region based genetic association and heritability estimation.

Genes that affect Atlantic salmon growth in hatchery do not have the same effect in the wild

Summary Dissecting the genetic mechanisms of phenotypic traits that influence fitness in diverse environments provides the important first step towards understanding the robustness of the observed genotype–phenotype associations, the role of genotype‐by‐environment interaction (GEI) shaping fitness trade‐offs and maintaining genetic variation of quantitative traits. However, the molecular basis of complex traits in vertebrates has rarely, if ever, been studied simultaneously in natural and controlled laboratory environments. To evaluate whether the same genomic regions affect the growth of juvenile Atlantic salmon in wild and hatchery conditions, we mapped QTLs affecting the size‐at‐age of juvenile parr after the first summer utilizing the same mapping (family) material to avoid confounding effects of different genetic background. We identified three significant QTLs for fork length in the hatchery that were undetectable in the natural environment, while two QTLs detected in the wild were not observed when fish were reared in hatchery conditions. Altogether, four individual markers showed significant (P < 0·05) genotype‐by‐environment interactions. The allelic effects for three QTLs observed in the hatchery were in the same direction in both environments, while for two QTLs the alleles associated with a larger body size in the wild showed the opposite (albeit non‐significant) trend in the hatchery environment. Our results indicate that the growth of juvenile salmon in two contrasting environments is controlled by different genetic mechanisms that are most likely influenced by multiple processes, including food availability, inter‐ and intraspecific competition, and trade‐offs between the costs and benefits of individual movement in the wild. Furthermore, the findings of the study imply that a substantial proportion of growth‐related QTLs reported by earlier studies in a hatchery environment may represent QTLs specific to farmed conditions and hence have no effect on fish growth in the wild. For comprehensive understanding of the molecular, physiological and ecological mechanisms influencing complex traits, it is therefore crucial to evaluate the genotype–phenotype relationships under natural conditions, rather than relying solely on laboratory experiments.

Association mapping reveals the role of purifying selection in the maintenance of genomic variation in gene expression

The evolutionary forces that maintain genetic variation in quantitative traits within populations remain poorly understood. One hypothesis suggests that variation is under purifying selection, resulting in an excess of low-frequency variants and a negative correlation between minor allele frequency and selection coefficients. Here, we test these predictions using the genetic loci associated with total expression variation (eQTLs) and allele-specific expression variation (aseQTLs) mapped within a single population of the plant Capsella grandiflora. In addition to finding eQTLs and aseQTLs for a large fraction of genes, we show that alleles at these loci are rarer than expected and exhibit a negative correlation between phenotypic effect size and frequency. Overall, our results show that the distribution of frequencies and effect sizes of the loci responsible for local expression variation within a single outcrossing population are consistent with the effects of purifying selection.

The Nature of Genetic Variation for Complex Traits Revealed by GWAS and Regional Heritability Mapping Analyses.

We use computer simulations to investigate the amount of genetic variation for complex traits that can be revealed by single-SNP genome-wide association studies (GWAS) or regional heritability mapping (RHM) analyses based on full genome sequence data or SNP chips. We model a large population subject to mutation, recombination, selection, and drift, assuming a pleiotropic model of mutations sampled from a bivariate distribution of effects of mutations on a quantitative trait and fitness. The pleiotropic model investigated, in contrast to previous models, implies that common mutations of large effect are responsible for most of the genetic variation for quantitative traits, except when the trait is fitness itself. We show that GWAS applied to the full sequence increases the number of QTL detected by as much as 50% compared to the number found with SNP chips but only modestly increases the amount of additive genetic variance explained. Even with full sequence data, the total amount of additive variance explained is generally below 50%. Using RHM on the full sequence data, a slightly larger number of QTL are detected than by GWAS if the same probability threshold is assumed, but these QTL explain a slightly smaller amount of genetic variance. Our results also suggest that most of the missing heritability is due to the inability to detect variants of moderate effect (∼0.03-0.3 phenotypic SDs) segregating at substantial frequencies. Very rare variants, which are more difficult to detect by GWAS, are expected to contribute little genetic variation, so their eventual detection is less relevant for resolving the missing heritability problem.

From genotypes to phenotypes: expression levels of genes encompassing adaptive SNPs in black spruce.

Measuring transcript levels for adaptive genes revealed polymorphisms having cis -effect upon gene expression levels related to phenotype variation in a black spruce natural population. Trees growing in temperate and boreal regions must acclimate to changes in climatic factors such as low winter temperatures to survive to seasonal variations. Common garden studies have shown that genetic variation in quantitative traits helps species to survive and adapt to environmental changes and local conditions. Twenty-four genes carrying SNPs were previously associated with genetic adaptation in black spruce (Picea mariana [Mill.] BSP). The objectives of this study were to investigate the potential role of these genes in regulation of winter acclimation and adaptation by studying their patterns of expression as a function of the physiological stage during the annual growth cycle, tissue type, and their SNP genotypic class. Considerable variability in gene expression was observed between different vegetative tissues or organs, and between physiological stages. The genes were expressed predominantly in tissues that could be linked more directly to winter acclimation and adaptation. The expression levels of several of the genes were significantly related to variation in tree height growth or budset timing and expression level variation related to SNP genotypic classes was observed in four of the genes. An interaction between genotypic classes and physiological stages was also observed for some genes, indicating genotypes with different reaction norms in terms of gene expression.

Targeted Recombinant Progeny: a design for ultra-high resolution mapping of Quantitative Trait Loci in crosses between inbred or pure lines.

BackgroundHigh-resolution mapping of the loci (QTN) responsible for genetic variation in quantitative traits is essential for positional cloning of candidate genes, and for effective marker assisted selection. The confidence interval (QTL) flanking the point estimate of QTN-location is proportional to the number of individuals in the mapping population carrying chromosomes recombinant in the given interval. Consequently, many designs for high resolution QTN mapping are based on increasing the proportion of recombinants in the mapping population.The "Targeted Recombinant Progeny" (TRP) design is a new design for high resolution mapping of a target QTN in crosses between pure, or inbred lines. It is a three-generation procedure generating a large number of recombinant individuals within a QTL previously shown to contain a QTN. This is achieved by having individuals that carry chromosomes recombinant across the target QTL interval as parents of a large mapping population; most of whom will therefore carry recombinant chromosomes targeted to the given QTL. The TRP design is particularly useful for high resolution mapping of QTN that differentiate inbred or pure lines, and hence are not amenable to high resolution mapping by genome-wide association tests.ResultsIn the absence of residual polygenic variation, population sizes required for achieving given mapping resolution by the TRP-F2 design relative to a standard F2 design ranged from 0.289 for a QTN with standardized allele substitution effect = 0.2, mapped to an initial QTL of 0.2 Morgan to 0.041 for equivalent QTN mapped to an initial QTL of 0.02 M. In the presence of residual polygenic variation, the relative effectiveness of the TRP design ranges from 1.068 to 0.151 for the same initial QTL intervals and QTN effect. Thus even in the presence of polygenic variation, the TRP can still provide major savings. Simulation showed that mapping by TRP should be based on 30-50 markers spanning the initial interval; and on at least 50 or more G2 families representing this number of recombination points,.ConclusionsThe TRP design can be an effective procedure for achieving high and ultra-high mapping resolution of a target QTN previously mapped to a known confidence interval (QTL).

How old are quantitative trait loci and how widely do they segregate?

The mutations that cause genetic variation in quantitative traits could be old and segregate across many breeds or they could be young and segregate only within one breed. This has implications for our understanding of the evolution of quantitative traits and for genomic prediction to improve livestock. We investigated the age of quantitative trait loci (QTL) for milk production traits identified as segregating in Holstein dairy cattle. We use a multitrait method and found that six of 11 QTL also segregate in Jerseys. Variants identified as Holstein-only QTL were fixed or rare [minor allele frequency (MAF) < 0.05] in Jersey. The age of the QTL mutations appears to vary from perhaps 2000 to 50,000 generations old. The older QTL tend to have high derived allele frequencies and often segregate across both breeds. Holstein-only QTL were often embedded within longer haplotypes, supporting the conclusion that they are typically younger mutations that have occurred more recently than QTL that segregate in both breeds. A reference population for genomic prediction using both Holsteins and Jersey cattle incorrectly predicted a QTL in Jersey cattle when the QTL only segregates in Holsteins. Overcoming this error should help to make genomic prediction more accurate in smaller breeds.