Evaluation of Chilling Tolerance in Hokkaido Rice Varieties and Detection of Quantitative Trait Loci for Chilling Tolerance after Acclimation

Plant height (PH) and ear height (EH) are important agronomic traits in maize (Zea mays L.) breeding. To investigate the influence of the genetic background on the detection of quantitative trait locus (QTL) conferring PH and EH, related mapping populations were developed from a near isogenic line (NIL) and its recurrent parent. Through joint-environment analyses, a total of four QTLs for PH were identified within the introgressed regions of the used NIL. Compared with the mapping results of RILs, extra PH QTLs could be detected within the target region of the used NIL on chromosome 4, but a previous PH QTL within this region was lost. The missed detection of a previous PH QTL also occurred on chromosome 6. As such, the genetic background of the recurrent parent exerted its influence on the detection of height QTL in this study. Meanwhile, according to the analyses of recombination events, qPEH6, a major height QTL on chromosome 6, was narrowed down to a region of approximately 1 Mb. Sequence analysis revealed that GRMZM2G014119, which encodes an ubiquitin-like protein related to the auxin response, was roughly assumed to be the candidate gene responsible for qPEH6.

Quantitative trait loci (QTL) detection experiments have often been restricted to large biallelic populations. Use of connected multiparental crosses has been proposed to increase the genetic variability addressed and to test for epistatic interactions between QTL and the genetic background. We present here the results of a QTL detection performed on six connected F(2) populations of 150 F(2:3) families each, derived from four maize inbreds and evaluated for three traits of agronomic interest. The QTL detection was carried out by composite interval mapping on each population separately, then on the global design either by taking into account the connections between populations or not. Epistatic interactions between loci and with the genetic background were tested. Taking into account the connections between populations increased the number of QTL detected and the accuracy of QTL position estimates. We detected many epistatic interactions, particularly for grain yield QTL (R(2) increase of 9.6%). Use of connections for the QTL detection also allowed a global ranking of alleles at each QTL. Allelic relationships and epistasis both contribute to the lack of consistency for QTL positions observed among populations, in addition to the limited power of the tests. The potential benefit of assembling favorable alleles by marker-assisted selection are discussed.

Viticulture has to cope with climate change and to decrease pesticide inputs, while maintaining yield and wine quality. Breeding is a key lever to meet this challenge, and genomic prediction a promising tool to accelerate breeding programs. Multivariate methods are potentially more accurate than univariate ones. Moreover, some prediction methods also provide marker selection, thus allowing quantitative trait loci (QTLs) detection and the identification of positional candidate genes. To study both genomic prediction and QTL detection for drought-related traits in grapevine, we applied several methods, interval mapping (IM) as well as univariate and multivariate penalized regression, in a bi-parental progeny. With a dense genetic map, we simulated two traits under four QTL configurations. The penalized regression method Elastic Net (EN) for genomic prediction, and controlling the marginal False Discovery Rate on EN selected markers to prioritize the QTLs. Indeed, penalized methods were more powerful than IM for QTL detection across various genetic architectures. Multivariate prediction did not perform better than its univariate counterpart, despite strong genetic correlation between traits. Using 14 traits measured in semi-controlled conditions under different watering conditions, penalized regression methods proved very efficient for intra-population prediction whatever the genetic architecture of the trait, with predictive abilities reaching 0.68. Compared to a previous study on the same traits, these methods applied on a denser map found new QTLs controlling traits linked to drought tolerance and provided relevant candidate genes. Overall, these findings provide a strong evidence base for implementing genomic prediction in grapevine breeding.

Population size and phenotypic measurement are two key factors determining the detection power of quantitative trait loci (QTL) mapping. We evaluated how these two controllable factors quantitatively affect the detection of QTL and their localization using a large F2 murine mapping population and found that three main points emerged from this study. One finding was that the sensitivity of QTL detection significantly decreased as the population size decreased. The decrease in the percentage logarithm of the odd score (LOD score, which is a statistical measure of the likelihood of two loci being lied near each other on a chromosome) can be estimated using the formula 1 - n/N, where n is the smaller and N the larger population size. This empirical formula has several practical implications in QTL mapping. We also found that a population size of 300 seems to be a threshold for the detection of QTL and their localization, which challenges the small population sizes commonly-used in published studies, in excess of 60% of which cite population sizes <300. In addition, it seems that the precision of phenotypic measurement has a limited capacity to affect detection power, which means that quantitative traits that cannot be measured precisely can also be used in QTL mapping for the detection of major QTL.

Construction of a detailed RFLP linkage map of B. rapa (syn. campestris) made it possible, for the first time, to study individual genes controlling quantitative traits in this species. Ninety-five F2 individuals from a cross of Chinese cabbage cv 'Michihili' by Spring broccoli were analyzed for segregation at 220 RFLP loci and for variation in leaf, stem, and flowering characteristics. The number, location, and magnitude of genes underlying 28 traits were determined by using an interval mapping method. Zero to five putative quantitative trait loci (QTL) were detected for each of the traits examined. There were unequal gene effects on the expression of many traits, and the inheritance patterns of traits ranged from those controlled by a single major gene plus minor genes to those controlled by polygenes with small and similar effects. The effect of marker locus density on detection of QTL was analyzed, and the results showed that the number of QTL detected did not change when the number of marker loci used for QTL mapping was decreased from 220 to 126; however, a further reduction from 126 to 56 caused more than 15% loss of the total QTL detected. The detection of putative minor QTL by removing the masking effects of major QTL was explored.

BackgroundThe capacity to maintain internal ion homeostasis amidst changing conditions is particularly important for teleost fishes whose reproductive cycle is dependent upon movement from freshwater to seawater. Although the physiology of seawater osmoregulation in mitochondria-rich cells of fish gill epithelium is well understood, less is known about the underlying causes of inter- and intraspecific variation in salinity tolerance. We used a genome-scan approach in Arctic charr (Salvelinus alpinus) to map quantitative trait loci (QTL) correlated with variation in four salinity tolerance performance traits and six body size traits. Comparative genomics approaches allowed us to infer whether allelic variation at candidate gene loci (e.g., ATP1α1b, NKCC1, CFTR, and cldn10e) could have underlain observed variation.ResultsCombined parental analyses yielded genome-wide significant QTL on linkage groups 8, 14 and 20 for salinity tolerance performance traits, and on 1, 19, 20 and 28 for body size traits. Several QTL exhibited chromosome-wide significance. Among the salinity tolerance performance QTL, trait co-localizations occurred on chromosomes 1, 4, 7, 18 and 20, while the greatest experimental variation was explained by QTL on chromosomes 20 (19.9%), 19 (14.2%), 4 (14.1%) and 12 (13.1%). Several QTL localized to linkage groups exhibiting homeologous affinities, and multiple QTL mapped to regions homologous with the positions of candidate gene loci in other teleosts. There was no gene × environment interaction among body size QTL and ambient salinity.ConclusionsVariation in salinity tolerance capacity can be mapped to a subset of Arctic charr genomic regions that significantly influence performance in a seawater environment. The detection of QTL on linkage group 12 was consistent with the hypothesis that variation in salinity tolerance may be affected by allelic variation at the ATP1α1b locus. IGF2 may also affect salinity tolerance capacity as suggested by a genome-wide QTL on linkage group 19. The detection of salinity tolerance QTL in homeologous regions suggests that candidate loci duplicated from the salmonid-specific whole-genome duplication may have retained their function on both sets of homeologous chromosomes. Homologous affinities suggest that loci affecting salinity tolerance in Arctic charr may coincide with QTL for smoltification and salinity tolerance traits in rainbow trout. The effects of body size QTL appear to be independent of changes in ambient salinity.

Libraries of near-isogenic lines (NILs) were used for quantitative trait locus (QTL) detection in model species and economically important crops. The experimental design and genetic architecture of the considered traits determine the statistical properties of QTL detection. The objectives of our simulation study were to (i) investigate the population sizes required to develop NIL libraries in barley and maize, (ii) compare NIL libraries with nonoverlapping and overlapping donor segments and (iii) study the number of QTLs and the size of their effects with respect to the power and the false-positive rate of QTL detection. In barley, the development of NIL libraries with target segment lengths of 10 c and marker distances of 5 cM was possible using a BC(3)S(2) backcrossing scheme and population sizes of 140. In maize, population sizes larger than 200 were required. Selection for the recipient parent genome at markers flanking the target segments with distances between 5 and 10 cM was required for an efficient control of the false-positive rate. NIL libraries with nonoverlapping donor chromosome segments had a greater power of QTL detection and a smaller false-positive rate than libraries with overlapping segments. Major genes explaining 30% of the genotypic difference between the donor and recipient were successfully detected even with low heritabilities of 0.5, whereas for minor genes explaining 5 !or 10%, high heritabilities of 0.8 or 0.9 were required. The presented results can assist geneticists and breeders in the efficient development of NIL libraries for QTL detection.

Summary — Factors influencing the detection of quantitative trait loci (QTLs) via molecular markers are discussed in the case of recombinant inbred lines. The importance of the residual genetic variance present is emphasized and an expression for the minimum detectable effect is presented, which only depends on the design (trait heritability and number of lines studied); for relatively realistic situations, this minimum effect may be as high as 20 to 30% of the genetic SD. Therefore only QTLs with relatively large effects, and that are sufficiently closely linked to the marker, are likely to be detected. Increasing the genetic distance between parents can increase the probability of finding crosses in which significant (ie large-effect) QTLs are found, at the expense of decreasing the probability of detecting existing small-effect QTLs. Epistasis can diminish QTL detectability. Its possible importance has been discussed, and appears to be difficult to demonstrate. It has been shown that for a complex character, detected QTLs can at most only constitute a small subset of the existing QTLs. Furthermore, the occurrence of numerous small-effect QTLs regularly distributed over a chromosomal fraction in a directional manner has been shown to lead to the artefactual detection of a QTL by a centrally located marker.

BackgroundLinkage maps are an integral resource for dissection of complex genetic traits in plant and animal species. Canonical map construction follows a well-established workflow: an initial discovery phase where genetic markers are mined from a small pool of individuals, followed by genotyping of selected mapping populations using sets of marker panels. A newly developed sequence-based marker technology, Restriction site Associated DNA (RAD), enables synchronous single nucleotide polymorphism (SNP) marker discovery and genotyping using massively parallel sequencing. The objective of this research was to assess the utility of RAD markers for linkage map construction, employing barley as a model system. Using the published high density EST-based SNP map in the Oregon Wolfe Barley (OWB) mapping population as a reference, we created a RAD map using a limited set of prior markers to establish linakge group identity, integrated the RAD and prior data, and used both maps for detection of quantitative trait loci (QTL).ResultsUsing the RAD protocol in tandem with the Illumina sequence by synthesis platform, a total of 530 SNP markers were identified from initial scans of the OWB parental inbred lines - the "dominant" and "recessive" marker stocks - and scored in a 93 member doubled haploid (DH) mapping population. RAD sequence data from the structured population was converted into allele genotypes from which a genetic map was constructed. The assembled RAD-only map consists of 445 markers with an average interval length of 5 cM, while an integrated map includes 463 RAD loci and 2383 prior markers. Sequenced RAD markers are distributed across all seven chromosomes, with polymorphic loci emanating from both coding and noncoding regions in the Hordeum genome. Total map lengths are comparable and the order of common markers is identical in both maps. The same large-effect QTL for reproductive fitness traits were detected with both maps and the majority of these QTL were coincident with a dwarfing gene (ZEO) and the VRS1 gene, which determines the two-row and six-row germplasm groups of barley.ConclusionsWe demonstrate how sequenced RAD markers can be leveraged to produce high quality linkage maps for detection of single gene loci and QTLs. By combining SNP discovery and genotyping into parallel sequencing events, RAD markers should be a useful molecular breeding tool for a range of crop species. Expected improvements in cost and throughput of second and third-generation sequencing technologies will enable more powerful applications of the sequenced RAD marker system, including improvements in de novo genome assembly, development of ultra-high density genetic maps and association mapping.

Quantitative trait loci (QTLs) have been revealed for characters in a segregating population from a spring barley cross between genotypes adapted to North-West Europe. Transgressive segregation was found for all the characters, which was confirmed by the regular detection of positive and negative QTLs from both parents. A QTL for all the agronomic, yield and grain characters measured except thousand grain weight was found in the region of the denso dwarfing gene locus. There were considerable differences between the location of QTLs found in the present study and those found in previous studies of North American germ plasm, revealing the diversity between the two gene pools. Thirty-one QTLs were detected in more than one environment for the 13 characters studied, although many more were detected in just one environment. Whilst biometrical analyses suggested the presence of epistasis in the genetic control of some characters, there was little evidence of interactions between the QTLs apart from those associated with yield. QTLs of large effect sometimes masked the presence of QTLs of smaller effect.

QTL analysis reveals different and independent modes of inheritance for diagnostic achene characters in Microseris (Asteraceae)

Elucidating the genetic components of plant genotype-by-environment interactions is of key importance in the context of increasing climatic instability, diversification of agricultural practices and pest pressure due to phytosanitary treatment limitations. The genotypic response to environmental stresses can be investigated through multi-environment trials (METs). However, genome-wide association studies (GWAS) of MET data are significantly more complex than that of single environments. In this context, we introduce metaGE, a flexible and computationally efficient meta-analysis approach for jointly analyzing single-environment GWAS of any MET experiment. The metaGE procedure accounts for the heterogeneity of quantitative trait loci (QTL) effects across the environmental conditions and allows the detection of QTL whose allelic effect variations are strongly correlated to environmental cofactors. We evaluated the performance of the proposed methodology and compared it to two competing procedures through simulations. We also applied metaGE to two emblematic examples: the detection of flowering QTLs whose effects are modulated by competition in Arabidopsis and the detection of yield QTLs impacted by drought stresses in maize. The procedure identified known and new QTLs, providing valuable insights into the genetic architecture of complex traits and QTL effects dependent on environmental stress conditions. The whole statistical approach is available as an R package.

The focus of the thesis is on the detection of quantitative trait loci (QTL) in dairy cattle and their utilisation in breeding programmes. Analysis of one bovine chromosome for quantitative trait loci for milk production traits is described and a QTL for protein percent was identified that was significant at the 1% level.When analysing the chromosome it was observed that the degree of precision in estimating QTL location and size (or variance) is poor. Through stochastic simulation, the effect of incorrect parameter estimates for quantitative trait locus effect, and position on genetic response from marker assisted selection is investigated.From this study it was concluded that studies should be undertaken to verify estimates of QTL and location to enable optimal use of marker assisted selection. Strategies to confirm the existence and size of quantitative trait loci identified in a genome scan are outlined. Also through stochastic simulation the effect of reducing flanking-marker bracket size was found to increase the genetic response from marker assisted selection.Simulation is used to estimate improvements in rate of genetic gain from marker assisted selection for two scenarios, the current situation and a futuristic setting. The increase in rate of genetic gain with marker assisted selection is some 5% in the current situation with the potential of 30% with improvements in level of genetic variance identified and the identified loci being in disequilibrium with marker alleles.The general discussion of this thesis addresses the use of significance levels in quantitative trait loci detection, experimental designs to identify further quantitative trait loci in the New Zealand dairy industry, and the current and possible future application of marker assisted selection in dairy breeding programmes.

Detection of Quantitative Trait Loci Affecting Milk Production, Health, and Reproductive Traits in Holstein Cattle

Growth is a complex trait determined by the interplay between many genes, some of which play a role at a specific moment during development whereas others play a more general role. To identify the genetic basis of growth, natural variation in Arabidopsis rosette growth was followed in 324 accessions by a combination of top-view imaging, high-throughput image analysis, modelling of growth dynamics, and end-point fresh weight determination. Genome-wide association (GWA) mapping of the temporal growth data resulted in the detection of time-specific quantitative trait loci (QTLs), whereas mapping of model parameters resulted in another set of QTLs related to the whole growth curve. The positive correlation between projected leaf area (PLA) at different time points during the course of the experiment suggested the existence of general growth factors with a function in multiple developmental stages or with prolonged downstream effects. Many QTLs could not be identified when growth was evaluated only at a single time point. Eleven candidate genes were identified, which were annotated to be involved in the determination of cell number and size, seed germination, embryo development, developmental phase transition, or senescence. For eight of these, a mutant or overexpression phenotype related to growth has been reported, supporting the identification of true positives. In addition, the detection of QTLs without obvious candidate genes implies the annotation of novel functions for underlying genes.