Small-effect Quantitative Trait Loci Research Articles

Quantitative trait locus mapping reveals complex genetic architecture of quantitative virulence in the wheat pathogen Zymoseptoria tritici.

We conducted a comprehensive analysis of virulence in the fungal wheat pathogen Zymoseptoria tritici using quantitative trait locus (QTL) mapping. High-throughput phenotyping based on automated image analysis allowed the measurement of pathogen virulence on a scale and with a precision that was not previously possible. Across two mapping populations encompassing more than 520 progeny, 540 710 pycnidia were counted and their sizes and grey values were measured. A significant correlation was found between pycnidia size and both spore size and number. Precise measurements of percentage leaf area covered by lesions provided a quantitative measure of host damage. Combining these large and accurate phenotypic datasets with a dense panel of restriction site-associated DNA sequencing (RADseq) genetic markers enabled us to genetically dissect pathogen virulence into components related to host damage and those related to pathogen reproduction. We showed that different components of virulence can be under separate genetic control. Large- and small-effect QTLs were identified for all traits, with some QTLs specific to mapping populations, cultivars and traits and other QTLs shared among traits within the same mapping population. We associated the presence of four accessory chromosomes with small, but significant, increases in several virulence traits, providing the first evidence for a meaningful function associated with accessory chromosomes in this organism. A large-effect QTL involved in host specialization was identified on chromosome 7, leading to the identification of candidate genes having a large effect on virulence.

Molecular Dissection of Seedling Salinity Tolerance in Rice (Oryza sativa L.) Using a High-Density GBS-Based SNP Linkage Map.

BackgroundSalinity is one of the many abiotic stresses limiting rice production worldwide. Several studies were conducted to identify quantitative trait loci (QTLs) for traits associated to salinity tolerance. However, due to large confidence interval for the position of QTLs, utility of reported QTLs and the associated markers has been limited in rice breeding programs. The main objective of this study is to construct a high-density rice genetic map for identification QTLs and candidate genes for salinity tolerance at seedling stage.ResultsWe evaluated a population of 187 recombinant inbred lines (RILs) developed from a cross between Bengal and Pokkali for nine traits related to salinity tolerance. A total of 9303 SNP markers generated by genotyping-by-sequencing (GBS) were mapped to 2817 recombination points. The genetic map had a total map length of 1650 cM with an average resolution of 0.59 cM between markers. For nine traits, a total of 85 additive QTLs were identified, of which, 16 were large-effect QTLs and the rest were small-effect QTLs. The average interval size of QTL was about 132 kilo base pairs (Kb). Eleven of the 85 additive QTLs validated 14 reported QTLs for shoot potassium concentration, sodium-potassium ratio, salt injury score, plant height, and shoot dry weight. Epistatic QTL mapping identified several pairs of QTLs that significantly contributed to the variation of traits. The QTL for high shoot K+ concentration was mapped near the qSKC1 region. However, candidate genes within the QTL interval were a CC-NBS-LRR protein, three uncharacterized genes, and transposable elements. Additionally, many QTLs flanked small chromosomal intervals containing few candidate genes. Annotation of the genes located within QTL intervals indicated that ion transporters, osmotic regulators, transcription factors, and protein kinases may play essential role in various salt tolerance mechanisms.ConclusionThe saturation of SNP markers in our linkage map increased the resolution of QTL mapping. Our study offers new insights on salinity tolerance and presents useful candidate genes that will help in marker-assisted gene pyramiding to develop salt tolerant rice varieties.Electronic supplementary materialThe online version of this article (doi:10.1186/s12284-016-0125-2) contains supplementary material, which is available to authorized users.

Identification of additional QTLs for flowering time by removing the effect of the maturity gene E1 in soybean

The adaptability of soybean to be grown at a wide range of latitudes is attributed to natural variation in the major genes and quantitative trait loci (QTLs) that control flowering time and maturity. Thus, the identification of genes controlling flowering time and maturity and the understanding of their molecular basis are critical for improving soybean productivity. However, due to the great effect of the major maturity gene E1 on flowering time, it is difficult to detect other small-effect QTLs. In this study, aiming to reduce the effect of the QTL, associated with the E1 gene, on the detection of other QTLs, we divided a population of 96 recombinant inbred lines (RILs) into two sub-populations: one with the E1 allele and another with the e1nl allele. Compared with the results of using all 96 recombinant inbred lines, additional QTLs for flowering time were identified in the sub-populations, two (qFT-B1 and qFT-H) in RILs with the E1 allele and one (qFT-J-2) in the RILs with the e1nl allele, respectively. The three QTLs, qFT-B1, qFT-H and qFT-J-2 were true QTLs and played an important role in the regulation of growth period. Our data provides valuable information for the genetic mapping and gene cloning of traits controlling flowering time and maturity and will help a better understanding of the mechanism of photoperiod-regulated flowering and molecular breeding in soybean.

Identification and fine mapping of quantitative trait loci for the number of vascular bundle in maize stem.

Studies that investigated the genetic basis of source and sink related traits have been widely conducted. However, the vascular system that links source and sink received much less attention. When maize was domesticated from its wild ancestor, teosinte, the external morphology has changed dramatically; however, less is known for the internal anatomy changes. In this study, using a large maize‐teosinte experimental population, we performed a high‐resolution quantitative trait locus (QTL) mapping for the number of vascular bundle in the uppermost internode of maize stem. The results showed that vascular bundle number is dominated by a large number of small‐effect QTLs, in which a total of 16 QTLs that jointly accounts for 52.2% of phenotypic variation were detected, with no single QTL explaining more than 6% of variation. Different from QTLs for typical domestication traits, QTLs for vascular bundle number might not be under directional selection following domestication. Using Near Isogenic Lines (NILs) developed from heterogeneous inbred family (HIF), we further validated the effect of one QTL qVb9‐2 on chromosome 9 and fine mapped the QTL to a 1.8‐Mb physical region. This study provides important insights for the genetic architecture of vascular bundle number in maize stem and sets basis for cloning of qVb9‐2.

A Chromosome Segment Substitution Library of Weedy Rice for Genetic Dissection of Complex Agronomic and Domestication Traits.

Chromosome segment substitution lines (CSSLs) are a powerful alternative for locating quantitative trait loci (QTL), analyzing gene interactions, and providing starting materials for map-based cloning projects. We report the development and characterization of a CSSL library of a U.S. weedy rice accession ‘PSRR-1’ with genome-wide coverage in an adapted rice cultivar ‘Bengal’ background. The majority of the CSSLs carried a single defined weedy rice segment with an average introgression segment of 2.8 % of the donor genome. QTL mapping results for several agronomic and domestication traits from the CSSL population were compared with those obtained from two recombinant inbred line (RIL) populations involving the same weedy rice accession. There was congruence of major effect QTLs between both types of populations, but new and additional QTLs were detected in the CSSL population. Although, three major effect QTLs for plant height were detected on chromosomes 1, 4, and 8 in the CSSL population, the latter two escaped detection in both RIL populations. Since this was observed for many traits, epistasis may play a major role for the phenotypic variation observed in weedy rice. High levels of shattering and seed dormancy in weedy rice might result from an accumulation of many small effect QTLs. Several CSSLs with desirable agronomic traits (e.g. longer panicles, longer grains, and higher seed weight) identified in this study could be useful for rice breeding. Since weedy rice is a reservoir of genes for many weedy and agronomic attributes, the CSSL library will serve as a valuable resource to discover latent genetic diversity for improving crop productivity and understanding the plant domestication process through cloning and characterization of the underlying genes.

Genetic Basis Underlying Behavioral Correlation Between Fugu Takifugu rubripes and a Closely Related Species, Takifugu niphobles.

Correlated suits of behaviors (behavioral syndrome) are commonly observed in both inter- and intraspecific studies. In order to understand the genetic basis of such a correlation between species, we compared ten behaviors classified into five categories (acclimation, feeding, normal swimming, reaction to a novel object and activity in a novel environment) between two pufferfish species, Takifugu rubripes and T. niphobles. The two species showed consistent differences in nine behaviors with a significant correlation among behaviors. Quantitative trait locus (QTL) analysis using second generation hybrids revealed that different sets of small effect QTL are associated with the observed interspecific behavioral disparity. This indicates that correlations in temperament traits between them are governed by many genes with small effects, and each behavior has been selected to form particular combination patterns. One of the QTL showing small pleiotropic effect includes the Drd4 gene known for its association with behavioral traits in some animal taxa including mammals.

Identification of quantitative trait loci for yield and yield related traits in groundnut (Arachis hypogaea L.) under different water regimes in Niger and Senegal.

Yield under drought stress is a highly complex trait with large influence to even a minor fluctuation in the environmental conditions. Genomics-assisted breeding holds great promise for improving such complex traits more efficiently in less time, but requires markers associated with the trait of interest. In this context, a recombinant inbred line mapping population (TAG 24 × ICGV 86031) was used to identify markers associated with quantitative trait loci (QTLs) for yield and yield related traits at two important locations of West Africa under well watered and water stress conditions. Among the traits analyzed under WS condition, the harvest index (HI) and the haulm yield (HYLD) were positively correlated with the pod yield (PYLD) and showed intermediate broad sense heritability. QTL analysis using phenotyping and genotyping data resulted in identification of 52 QTLs. These QTLs had low phenotypic variance (<12 %) for all the nine traits namely plant height, primary branching, SPAD chlorophyll meter reading, percentage of sound mature kernels, 100 kernel weight, shelling percentage, HI, HYLD and PYLD. Interestingly, few QTLs identified in this study were also overlapped with previously reported QTLs detected for drought tolerance related traits identified earlier in Indian environmental conditions using the same mapping population. Accumulating these many small-effect QTLs into a single genetic background is nearly impossible through marker-assisted backcrossing and even marker-assisted recurrent selection. Under such circumstances, the deployment of genomic selection is the most appropriate approach for improving such complex traits with more precision and in less time.Electronic supplementary materialThe online version of this article (doi:10.1007/s10681-015-1472-6) contains supplementary material, which is available to authorized users.

Genetic architecture of variation in heading date among Asian rice accessions.

BackgroundHeading date, a crucial factor determining regional and seasonal adaptation in rice (Oryza sativa L.), has been a major selection target in breeding programs. Although considerable progress has been made in our understanding of the molecular regulation of heading date in rice during last two decades, the previously isolated genes and identified quantitative trait loci (QTLs) cannot fully explain the natural variation for heading date in diverse rice accessions.ResultsTo genetically dissect naturally occurring variation in rice heading date, we collected QTLs in advanced-backcross populations derived from multiple crosses of the japonica rice accession Koshihikari (as a common parental line) with 11 diverse rice accessions (5 indica, 3 aus, and 3 japonica) that originate from various regions of Asia. QTL analyses of over 14,000 backcrossed individuals revealed 255 QTLs distributed widely across the rice genome. Among the detected QTLs, 128 QTLs corresponded to genomic positions of heading date genes identified by previous studies, such as Hd1, Hd6, Hd3a, Ghd7, DTH8, and RFT1. The other 127 QTLs were detected in different chromosomal regions than heading date genes.ConclusionsOur results indicate that advanced-backcross progeny allowed us to detect and confirm QTLs with relatively small additive effects, and the natural variation in rice heading date could result from combinations of large- and small-effect QTLs. We also found differences in the genetic architecture of heading date (flowering time) among maize, Arabidopsis, and rice.Electronic supplementary materialThe online version of this article (doi:10.1186/s12870-015-0501-x) contains supplementary material, which is available to authorized users.

Detection of quantitative trait loci for mineral content of Nelore longissimus dorsi muscle.

BackgroundBeef cattle require dietary minerals for optimal health, production and reproduction. Concentrations of minerals in tissues are at least partly genetically determined. Mapping genomic regions that affect the mineral content of bovine longissimus dorsi muscle can contribute to the identification of genes that control mineral balance, transportation, absorption and excretion and that could be associated to metabolic disorders.MethodsWe applied a genome-wide association strategy and genotyped 373 Nelore steers from 34 half-sib families with the Illumina BovineHD BeadChip. Genome-wide association analysis was performed for mineral content of longissimus dorsi muscle using a Bayesian approach implemented in the GenSel software.ResultsMuscle mineral content in Bos indicus cattle was moderately heritable, with estimates ranging from 0.29 to 0.36. Our results suggest that variation in mineral content is influenced by numerous small-effect QTL (quantitative trait loci) but a large-effect QTL that explained 6.5% of the additive genetic variance in iron content was detected at 72 Mb on bovine chromosome 12. Most of the candidate genes present in the QTL regions for mineral content were involved in signal transduction, signaling pathways via integral (also called intrinsic) membrane proteins, transcription regulation or metal ion binding.ConclusionsThis study identified QTL and candidate genes that affect the mineral content of skeletal muscle. Our findings provide the first step towards understanding the molecular basis of mineral balance in bovine muscle and can also serve as a basis for the study of mineral balance in other organisms.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-014-0083-3) contains supplementary material, which is available to authorized users.

Two quantitative trait loci, Dw1 and Dw2, are primarily responsible for rootstock-induced dwarfing in apple.

The apple dwarfing rootstock ‘Malling9’ (‘M9’) has been used worldwide both to reduce scion vigour and as a genetic source for breeding new rootstocks. Progeny of ‘M9’ segregate for rootstock-induced dwarfing of the scion, indicating that this trait is controlled by one or more genetic factors. A quantitative trait locus (QTL) analysis of a rootstock population derived from the cross between ‘M9’ × ‘Robusta5’ (non-dwarfing) and grafted with ‘Braeburn’ scions identified a major QTL (Dw1) on linkage group (LG) 5, which exhibits a significant influence on dwarfing of the scion. A smaller-effect QTL affecting dwarfing (Dw2) was identified on LG11, and four minor-effect QTLs were found on LG6, LG9, LG10 and LG12. Phenotypic analysis indicates that the combination of Dw1 and Dw2 has the strongest influence on rootstock-induced dwarfing, and that Dw1 has a stronger effect than Dw2. Genetic markers linked to Dw1 and Dw2 were screened over 41 rootstock accessions that confer a range of effects on scion growth. The majority of the dwarfing and semi-dwarfing rootstock accessions screened carried marker alleles linked to Dw1 and Dw2. This suggests that most apple dwarfing rootstocks have been derived from the same genetic source.

Joint-multiple family linkage analysis predicts within-family variation better than single-family analysis of the maize nested association mapping population

Quantitative trait locus (QTL) mapping has been used to dissect the genetic architecture of complex traits and predict phenotypes for marker-assisted selection. Many QTL mapping studies in plants have been limited to one biparental family population. Joint analysis of multiple biparental families offers an alternative approach to QTL mapping with a wider scope of inference. Joint-multiple population analysis should have higher power to detect QTL shared among multiple families, but may have lower power to detect rare QTL. We compared prediction ability of single-family and joint-family QTL analysis methods with fivefold cross-validation for 6 diverse traits using the maize nested association mapping population, which comprises 25 biparental recombinant inbred families. Joint-family QTL analysis had higher mean prediction abilities than single-family QTL analysis for all traits at most significance thresholds, and was always better at more stringent significance thresholds. Most robust QTL (detected in >50% of data samples) were restricted to one family and were often not detected at high frequency by joint-family analysis, implying substantial genetic heterogeneity among families for complex traits in maize. The superior predictive ability of joint-family QTL models despite important genetic differences among families suggests that joint-family models capture sufficient smaller effect QTL that are shared across families to compensate for missing some rare large-effect QTL.

Mapping of Yr62 and a small-effect QTL for high-temperature adult-plant resistance to stripe rust in spring wheat PI 192252.

This manuscript reports a new gene (Yr62) and a small-effect QTL for potentially durable resistance to stripe rust and usefulness of Yr62 markers for marker-assisted selection. Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is a devastating disease of wheat worldwide. Spring wheat germplasm PI 192252 showed a high level of high-temperature adult-plant (HTAP) resistance to stripe rust in germplasm evaluation over 8years in the State of Washington. To elucidate the genetic basis of resistance, PI 192252 was crossed with 'Avocet susceptible'. A mapping population of 150 F5 recombinant inbred lines was developed using single-seed descent. Stripe rust tests were conducted with selected Pst races in a greenhouse and in field conditions under natural infections. The relative area under the disease progress curve (rAUDPC) data showed continuous distributions, indicating that HTAP resistance of PI 192252 was controlled by quantitative trait loci (QTL). Two QTL were identified in PI 192252, explaining 74.2% of the total phenotypic variation for rAUDPC. These two QTL were mapped to chromosomes 4BL (QYrPI192252.wgp-4BL) and 5BS (QYrPI192252.wgp-5BS) with SSR and SNP markers and explained 40-60 and 22-27%, respectively, of the phenotypic variation across the four environments. Because the major-effect QTL on 4BL is different from previously named Yr genes and inherited as a single gene, it is named Yr62. The SSR marker alleles Xgwm192 222 and Xgwm251 133 flanking Yr62 were different from the alleles in various wheat varieties, suggesting that these markers could be useful in marker-assisted selection for incorporating Yr62 into commercial cultivars.

High-Resolution Inflorescence Phenotyping Using a Novel Image-Analysis Pipeline, PANorama

Variation in inflorescence development is an important target of selection for numerous crop species, including many members of the Poaceae (grasses). In Asian rice (Oryza sativa), inflorescence (panicle) architecture is correlated with yield and grain-quality traits. However, many rice breeders continue to use composite phenotypes in selection pipelines, because measuring complex, branched panicles requires a significant investment of resources. We developed an open-source phenotyping platform, PANorama, which measures multiple architectural and branching phenotypes from images simultaneously. PANorama automatically extracts skeletons from images, allows users to subdivide axes into individual internodes, and thresholds away structures, such as awns, that normally interfere with accurate panicle phenotyping. PANorama represents an improvement in both efficiency and accuracy over existing panicle imaging platforms, and flexible implementation makes PANorama capable of measuring a range of organs from other plant species. Using high-resolution phenotypes, a mapping population of recombinant inbred lines, and a dense single-nucleotide polymorphism data set, we identify, to our knowledge, the largest number of quantitative trait loci (QTLs) for panicle traits ever reported in a single study. Several areas of the genome show pleiotropic clusters of panicle QTLs, including a region near the rice Green Revolution gene SEMIDWARF1. We also confirm that multiple panicle phenotypes are distinctly different among a small collection of diverse rice varieties. Taken together, these results suggest that clusters of small-effect QTLs may be responsible for varietal or subpopulation-specific panicle traits, representing a significant opportunity for rice breeders selecting for yield performance across different genetic backgrounds.

Introgression of homeologous quantitative trait loci (QTLs) for resistance to the root-knot nematode [Meloidogyne arenaria (Neal) Chitwood] in an advanced backcross-QTL population of peanut (Arachis hypogaea L.)

Resistance to root-knot nematodes [Meloidogyne arenaria (Neal) Chitwood] is needed for cultivation of peanut in major peanut-growing areas, but significant resistance is lacking in the cultivated species (Arachis hypogaea L.). Markers to two closely-linked genes introgressed from wild relatives of peanut have been identified previously, but phenotypic evidence for the presence of additional genes in wild species and introgression lines has eluded quantitative trait locus (QTL) identification. Here, to improve sensitivity to small-effect QTLs, an advanced backcross population from a cross between a Florunner component line and the synthetic amphidiploid TxAG-6 [Arachis batizocoi × (A. cardenasii × A. diogoi)]4× was screened for response to root-knot nematode infection. Composite interval mapping results suggested a total of seven QTLs plus three putative QTLs. These included the known major resistance gene plus a second QTL on LG1, and a potentially homeologous B-genome QTL on LG11. Additional potential homeologs were identified on linkage group (LG) 8 and LG18, plus a QTL on LG9.2 and putative QTLs on LG9.1 and 19. A QTL on LG15 had no inferred resistance-associated homeolog. Contrary to expectation, two introgressed QTLs were associated with susceptibility, and QTLs at some homeologous loci were found to confer opposite phenotypic responses. Long-term functional conservation accompanied by rapid generation of functionally divergent alleles may be a singular feature of NBS-LRR resistance gene clusters, contributing to the richness of resistance alleles available in wild relatives of crops. The significance for peanut evolution and breeding is discussed.

Genome scan for meat quality traits in Nelore beef cattle

Meat quality traits are economically important because they affect consumers' acceptance, which, in turn, influences the demand for beef. However, selection to improve meat quality is limited by the small numbers of animals on which meat tenderness can be evaluated due to the cost of performing shear force analysis and the resultant damage to the carcass. Genome wide-association studies for Warner-Bratzler shear force measured at different times of meat aging, backfat thickness, ribeye muscle area, scanning parameters [lightness, redness (a*), and yellowness] to ascertain color characteristics of meat and fat, water-holding capacity, cooking loss (CL), and muscle pH were conducted using genotype data from the Illumina BovineHD BeadChip array to identify quantitative trait loci (QTL) in all phenotyped Nelore cattle. Phenotype count for these animals ranged from 430 to 536 across traits. Meat quality traits in Nelore are controlled by numerous QTL of small effect, except for a small number of large-effect QTL identified for a*fat, CL, and pH. Genomic regions harboring these QTL and the pathways in which the genes from these regions act appear to differ from those identified in taurine cattle for meat quality traits. These results will guide future QTL mapping studies and the development of models for the prediction of genetic merit to implement genomic selection for meat quality in Nelore cattle.

QTL analysis of canning quality and color retention in black beans (Phaseolus vulgaris L.)

Black bean (Phaseolus vulgaris L.) consumption is increasing in the USA. One of the major challenges faced by breeders is to develop superior black bean cultivars to meet the demands of the canning industry. Processors require beans that take up water quickly during pre-canning soak and beans that retain their black color after canning. To properly assess canning quality requires expensive and detailed measurements of the canned product, often not possible for bean breeders. The objective of this research was identify quantitative trait loci (QTL) in a black bean recombinant inbred line (RIL) population for canning quality traits related to water uptake, color retention, and anthocyanin concentration. The parental lines from which the population was developed, Black Magic and Shiny Crow, contrasted in water uptake and color retention. These cultivars also differed in seed coat luster, controlled by a single gene, Asp. A medium-density linkage map of 1,449 markers and a distance of 1,660 cM was developed from this RIL population. The map was aligned to the bean genome sequence V1.0 by using sequence information associated with the Diversity Arrays Technology markers. QTL analysis revealed that the region near the Asp gene on chromosome Pv 07 is the major determinant of water uptake, explaining up to 49 % of the phenotypic variation. A group of QTL for color retention-related traits was found at the upper region of Pv 11, explaining up to 30 % of the phenotypic variation. A smaller effect QTL clustered on Pv 5 co-localized with a QTL for canned bean anthocyanin concentration and explained less than 10 % of the phenotypic variation. These color-related QTL have marker-assisted selection potential for bean breeders interested in enhancing color retention and anthocyanin concentration of processed black beans.

Rufy1 or Hnrnph1 is a likely quantitative trait gene for methamphetamine sensitivity

Sensitivity to the locomotor stimulant properties of drugs of abuse is a heritable trait and its genetic basis may be shared with alleles that modulate activation of the mesolimbic reward pathway. We previously used mouse lines derived from C57BL/6J and DBA/2J alleles that were selected for high and low methamphetamine (MA) sensitivity and identified a genome‐wide significant quantitative trait locus (QTL) on chromosome 11. In order to further pursue this QTL, we utilized the power of an F2 cross and the iterative nature of interval‐specific congenic lines in an effort to identify the causal gene(s) underlying this QTL. The results of F2 mice and the larger congenic lines revealed two large‐effect QTLs for MA‐induced locomotor activity; however, the phenotypic results of the smaller subcongenic lines revealed additional smaller effect QTLs with different modes of inheritance. One subcongenic locus converged remarkably well with the QTL peak in the F2 cross and altered methamphetamine sensitivity in a time‐dependent manner. We generated eight sub‐subcongenic lines derived from this subcongenic line (17 congenic lines total). Owing to a fortuitous recombination event, we identified and replicated a 0.23 Mb region spanning 50.17–50.40 Mb that was critical for MA sensitivity. This region contains only three genes (Rufy1, Hnrnph1, and Cby3) and only two of these genes are expressed in the brain (Rufy1 and Hnrnph1). This study exemplifies how a careful and detailed use of congenic lines can yield narrow QTL intervals and a tractable number of genes for quantitative trait gene identification.

Coding Gene SNP Mapping Reveals QTL Linked to Growth and Stress Response in Brook Charr (Salvelinus fontinalis)

Growth performance and reduced stress response are traits of major interest in fish production. Growth and stress-related quantitative trait loci (QTL) have been already identified in several salmonid species, but little effort has been devoted to charrs (genus Salvelinus). Moreover, most QTL studies to date focused on one or very few traits, and little investigation has been devoted to QTL identification for gene expression. Here, our objective was to identify QTL for 27 phenotypes related to growth and stress responses in brook charr (Salvelinus fontinalis), which is one of the most economically important freshwater aquaculture species in Canada. Phenotypes included 12 growth parameters, six blood and plasma variables, three hepatic variables, and one plasma hormone level as well as the relative expression measurements of five genes of interest linked to growth regulation. QTL analysis relied on a linkage map recently built from S. fontinalis consisting of both single-nucleotide polymorphism (SNP, n = 266) and microsatellite (n =81) markers in an F2 interstrain hybrid population (n = 171). We identified 63 growth-related QTL and four stress-related QTL across 18 of the 40 linkage groups of the brook charr linkage map. Percent variance explained, confidence interval, and allelic QTL effects also were investigated to provide insight into the genetic architecture of growth- and stress-related QTL. QTL related to growth performance and stress response that were identified could be classified into two groups: (1) a group composed of the numerous, small-effect QTL associated with some traits related to growth (i.e., weight) that may be under the control of a large number of genes or pleiotropic genes, and (2) a group of less numerous QTL associated with growth (i.e., gene expression) and with stress-related QTL that display a larger effect, suggesting that these QTL are under the control of a limited number of genes of major effect. This study represents a first step toward the identification of genes potentially linked to phenotypic variation of growth and stress response in brook charr. The ultimate goal is to provide new tools for developing Molecular Assisted Selection for this species.

Will genomic selection be a practical method for plant breeding?

BackgroundGenomic selection or genome-wide selection (GS) has been highlighted as a new approach for marker-assisted selection (MAS) in recent years. GS is a form of MAS that selects favourable individuals based on genomic estimated breeding values. Previous studies have suggested the utility of GS, especially for capturing small-effect quantitative trait loci, but GS has not become a popular methodology in the field of plant breeding, possibly because there is insufficient information available on GS for practical use.ScopeIn this review, GS is discussed from a practical breeding viewpoint. Statistical approaches employed in GS are briefly described, before the recent progress in GS studies is surveyed. GS practices in plant breeding are then reviewed before future prospects are discussed.ConclusionsStatistical concepts used in GS are discussed with genetic models and variance decomposition, heritability, breeding value and linear model. Recent progress in GS studies is reviewed with a focus on empirical studies. For the practice of GS in plant breeding, several specific points are discussed including linkage disequilibrium, feature of populations and genotyped markers and breeding scheme. Currently, GS is not perfect, but it is a potent, attractive and valuable approach for plant breeding. This method will be integrated into many practical breeding programmes in the near future with further advances and the maturing of its theory.

New Insights into the Genetics ofin VivoInduction of Maternal Haploids, the Backbone of Doubled Haploid Technology in Maize

Haploids and doubled haploid (DH) inbred lines have become an invaluable tool for maize genetic research and hybrid breeding, but the genetic basis of in vivo induction of maternal haploids is still unknown. This is the first study reporting comparative quantitative trait locus (QTL) analyses of this trait in maize. We determined haploid induction rates (HIR) in testcrosses of a total of 1061 progenies of four segregating populations involving two temperate haploid inducers, UH400 (HIR = 8%) and CAUHOI (HIR = 2%), one temperate and two tropical inbreds with HIR = 0%, and up to three generations per population. Mean HIR of the populations ranged from 0.6 to 5.2% and strongly deviated from the midparent values. One QTL (qhir1) explaining up to p = 66% of the genetic variance was detected in bin 1.04 in the three populations involving a noninducer parent and the HIR-enhancing allele was contributed by UH400. Segregation ratios of loci in bin 1.04 were highly distorted against the UH400 allele in these three populations, suggesting that transmission failure of the inducer gamete and haploid induction ability are related phenomena. In the CAUHOI × UH400 population, seven QTL were identified on five chromosomes, with qhir8 on chromosome 9 having p > 20% in three generations of this cross. The large-effect QTL qhir1 and qhir8 will likely become fixed quickly during inducer development due to strong selection pressure applied for high HIR. Hence, marker-based pyramiding of small-effect and/or modifier QTL influencing qhir1 and qhir8 may help to further increase HIR in maize. We propose a conceptual genetic framework for inheritance of haploid induction ability, which is also applicable to other dichotomous traits requiring progeny testing, and discuss the implications of our results for haploid inducer development.