Optimal sampling of a population to determine QTL location, variance, and allelic number

In a population intended for breeding and selection, questions of interest relative to a specific segregating QTL are the variance it generates in the population, and the number and effects of its alleles. One approach to address these questions is to extract several inbreds from the population and use them to generate multiple mapping families. Given random sampling of parents, sampling strategy may be an important factor determining the power of the analysis and its accuracy in estimating QTL variance and allelic number. We describe appropriate multiple-family QTL mapping methodology and apply it to simulated data sets to determine optimal sampling strategies in terms of family number versus family size. Genomes were simulated with seven chromosomes, on which 107 markers and six QTL were distributed. The total heritability was 0.60. Two to ten alleles were segregating at each QTL. Sampling strategies ranged from sampling two inbreds and generating a single family of 600 progeny to sampling 40 inbreds and generating 40 families of 15 progeny each. Strategies involving only one to five families were subject to variation due to the sampling of inbred parents. For QTL where more than two alleles were segregating, these strategies did not sample QTL alleles representative of the original population. Conversely, strategies involving 30 or more parents were subject to variation due to sampling of QTL genotypes within the small families obtained. Given these constraints, greatest QTL detection power was obtained for strategies involving five to ten mapping families. The most accurate estimation of the variance generated by the QTL, however, was obtained with strategies involving 20 or more families. Finally, strategies with an intermediate number of families best estimated the number of QTL alleles. We conclude that no overall optimal sampling strategy exists but that the strategy adopted must depend on the objective.Communicated by P. Langridge     

Fruit size QTL analysis of an F<Subscript>1</Subscript> population derived from a cross between a domesticated sweet cherry cultivar and a wild forest sweet cherry

Maximizing fruit size is critical for profitable sweet cherry (Prunus avium L.) production. Yet, despite its importance, little is known about the genetic control of fruit size. The objective of this study was to identify quantitative trait loci (QTLs) for fruit size and two essential components of fruit size, mesocarp cell number and size. This study utilized a double pseudo-testcross population derived from reciprocal crosses between a sweet cherry cultivar with ~8 g fruit, “Emperor Francis” (EF), and a wild forest sweet cherry selection with ~2 g fruit, “New York 54” (NY). A total of 190 F₁ progeny previously utilized for the construction of the linkage maps were evaluated in 2006 and 2007 for fruit weight, length, and diameter; mesocarp cell number and length; and pit length and diameter. In 2008, a subset of this population was again evaluated for fruit weight. Correlation analysis revealed that the three fruit size traits were highly correlated with each other, and mesocarp cell number, not cell length, was correlated with fruit size. Three QTLs were identified for each fruit size trait, and one QTL was identified for mesocarp cell number. Fruit size QTLs were found on linkage group 2 on the EF map (EF 2) and linkage groups 2 and 6 on the NY map (NY 2 and NY 6). On EF 2, the cell number QTL clustered with the fruit size QTL, suggesting that the underlying basis of the fruit size increase associated with this QTL was an increase in mesocarp cell number. On NY 6, pit length and diameter QTLs clustered with those for fruit size, suggesting that the underlying morphological basis of this fruit size QTL is the difference in pit size.     

QTL analysis of flower and fruit traits in sour cherry

The map locations and effects of quantitative trait loci (QTLs) were estimated for eight flower and fruit traits in sour cherry (Prunus cerasus L.) using a restriction fragment length polymorphism (RFLP) genetic linkage map constructed from a double pseudo-testcross. The mapping population consisted of 86 progeny from the cross between two sour cherry cultivars, Rheinische Schattenmorelle (RS)×Erdi Botermo (EB). The genetic linkage maps for RS and EB were 398.2 cM and 222.2 cM, respectively, with an average interval length of 9.8 cM. The RS/EB linkage map that was generated with shared segregating markers consisted of 17 linkage groups covering 272.9 cM with an average interval length of 4.8 cM. Eleven putatively significant QTLs (LOD >2.4) were detected for six characters (bloom time, ripening time, % pistil death, % pollen germination, fruit weight, and soluble solids concentration). The percentage of phenotypic variation explained by a single QTL ranged from 12.9% to 25.9%. Of the QTLs identified for the traits in which the two parents differed significantly, 50% had allelic effects opposite to those predicted from the parental phenotype. Three QTLs affecting flower traits (bloom time, % pistil death, and % pollen germination) mapped to a single linkage group, EB 1. The RFLP closest to the bloom time QTL on EB 1 was detected by a sweet cherry cDNA clone pS141 whose partial amino acid sequence was 81% identical to that of a Japanese pear stylar RNase. Received: 4 March 1999 / Accepted: 27 August 1999     

Genetic structure of a QTL hotspot on chromosome 2 in sweet cherry indicates positive selection for favorable haplotypes

A genomic region of particular interest for sweet cherry (Prunus avium L.) breeding is a quantitative trait locus (QTL) “hotspot” on chromosome 2. QTLs for fruit size, firmness, sweetness, and flowering time are reported to map to this region. An understanding of genetic diversity, allele sources, linkage relationships, and historical recombinations is critical to enable the combining of favorable alleles at multiple loci. The objectives of this study were to characterize, visualize, and interpret the genetic structure of this previously identified QTL hotspot within North American sweet cherry breeding germplasm, using a pedigree-based haploblocking approach. Across the 29.4 cM (6.3 Mbp) region defined by single nucleotide polymorphism (SNP) information from the RosBREED cherry 6K SNP array v1, a total of 12 recombination events falling into six inter-marker regions were traced within the pedigree of elite and wild germplasm (n = 55). These recombinations defined five haploblocks containing 5–15 markers and exhibiting 7–11 haplotypes each. Over the entire QTL hotspot, 30 extended haplotypes were identified for which parental gametes could be determined. When the haploblocks and their haplotypes were used to explore genetic diversity, ancestry, and recombination patterns, and then integrated with previous QTL results for fruit size, the results indicated that favorable alleles at this QTL hotspot are under positive selection in breeding. The genetic framework provided by a haploblock approach and knowledge of haplotype-level diversity sets the stage for assigning breeding utility to these haplotypes.     

Efficient Method for Analysis of QTL Using F1 Progenies in an Outcrossing Species

In the present paper, we proposed a statistical procedure based on composite interval mapping for accurate analysis of quantitative trait loci (QTL) for individuals sampled from an outcrossing population with two-generation families consisting of the sampled individuals and F1 progenies obtained by crossing them as parental individuals. In the proposed procedure, haplotypes of markers of parental individuals were reconstructed based on the genotypes of F1 progenies and QTL analyses with composite interval mapping were conducted separately for each of parents as well as jointly for both parents. A least squares method was applied to the composite interval mapping, where some of markers were selected as cofactors to absorb the variation induced by QTL located elsewhere in the genome. The procedure was evaluated for the efficiency in detecting QTL and the precision of estimates of locations and effects of QTL using simulations. It was shown that QTL with interaction between paternal and maternal alleles was effectively detected by joint analysis of both parents, while a QTL segregating only in one parent, closely linked to a QTL segregating only in the other parent, was successfully detected by analyzing separately each of the parents with inclusion of markers of both parents. The proposed procedure can provide detailed genetic information useful for marker assisted breeding in an outcrossing species such as forest trees.     

QTL analysis and candidate gene mapping for skin and flesh color in sweet cherry fruit (<Emphasis Type="Italic">Prunus avium</Emphasis> L.)

Sweet cherry (Prunus avium L.) skin and fruit colors vary widely due to differences in red and yellow pigment profiles. The two major market classes of sweet cherry represent the two color extremes, i.e., yellow skin with red blush and yellow flesh and dark mahogany skin with mahogany flesh. Yet, within these extremes, there is a continuum of skin and flesh color types. The genetic control of skin and flesh color in sweet cherry was investigated using a quantitative trait locus (QTL) approach with progeny derived from a cross between cherry parents representing the two color extremes. Skin and flesh colors were measured using a qualitative color-card rating over three consecutive years and also evaluated quantitatively for darkness/lightness (L*), red/green (a*), and yellow/blue (b*). Segregations for the color measurements (card, L*, a*, and b*) did not fit normal distributions; instead, the distributions were skewed towards the color of the dark-fruited parent. A major QTL for skin and flesh color was identified on linkage group (LG) 3. Two QTLs for skin and flesh color were also identified on LG 6 and LG 8, respectively, indicating segregation for minor genes. The significance and magnitude of the QTL identified on LG 3 suggests the presence of a major regulatory gene within this QTL interval. A candidate gene PavMYB10, homologous to apple MdMYB10 and Arabidopsis AtPAP1, is within the interval of the major QTL on LG 3, suggesting that PavMYB10 could be the major determinant of fruit skin and flesh coloration in sweet cherry.     

Bayesian QTL analyses using pedigreed families of an outcrossing species,with application to fruit firmness in apple

Key message

Proof of concept of Bayesian integrated QTL analyses across pedigree-related families from breeding programs of an outbreeding species. Results include QTL confidence intervals, individuals’ genotype probabilities and genomic breeding values.

Abstract

Bayesian QTL linkage mapping approaches offer the flexibility to study multiple full sib families with known pedigrees simultaneously. Such a joint analysis increases the probability of detecting these quantitative trait loci (QTL) and provide insight of the magnitude of QTL across different genetic backgrounds. Here, we present an improved Bayesian multi-QTL pedigree-based approach on an outcrossing species using progenies with different (complex) genetic relationships. Different modeling assumptions were studied in the QTL analyses, i.e., the a priori expected number of QTL varied and polygenic effects were considered. The inferences include number of QTL, additive QTL effect sizes and supporting credible intervals, posterior probabilities of QTL genotypes for all individuals in the dataset, and QTL-based as well as genome-wide breeding values. All these features have been implemented in the FlexQTL^? software. We analyzed fruit firmness in a large apple dataset that comprised 1,347 individuals forming 27 full sib families and their known ancestral pedigrees, with genotypes for 87 SSR markers on 17 chromosomes. We report strong or positive evidence for 14 QTL for fruit firmness on eight chromosomes, validating our approach as several of these QTL were reported previously, though dispersed over a series of studies based on single mapping populations. Interpretation of linked QTL was possible via individuals’ QTL genotypes. The correlation between the genomic breeding values and phenotypes was on average 90 %, but varied with the number of detected QTL in a family. The detailed posterior knowledge on QTL of potential parents is critical for the efficiency of marker-assisted breeding.     

QTL detection with bidirectional and unidirectional selective genotyping: marker-based and trait-based analyses

Selective genotyping of one or both phenotypic extremes of a population can be used to detect linkage between markers and quantitative trait loci (QTL) in situations in which full-population genotyping is too costly or not feasible, or where the objective is to rapidly screen large numbers of potential donors for useful alleles with large effects. Data may be subjected to 'trait-based' analysis, in which marker allele frequencies are compared between classes of progeny defined based on trait values, or to 'marker-based' analysis, in which trait means are compared between progeny classes defined based on marker genotypes. Here, bidirectional and unidirectional selective genotyping were simulated, using population sizes and selection intensities relevant to cereal breeding. Control of Type I error was usually adequate with marker-based analysis of variance or trait-based testing using the normal approximation of the binomial distribution. Bidirectional selective genotyping was more powerful than unidirectional. Trait-based analysis and marker-based analysis of variance were about equally powerful. With genotyping of the best 30 out of 500 lines (6%), a QTL explaining 15% of the phenotypic variance could be detected with a power of 0.8 when tests were conducted at a marker 10 cM from the QTL. With bidirectional selective genotyping, QTL with smaller effects and (or) QTL farther from the nearest marker could be detected. Similar QTL detection approaches were applied to data from a population of 436 recombinant inbred rice lines segregating for a large-effect QTL affecting grain yield under drought stress. That QTL was reliably detected by genotyping as few as 20 selected lines (4.5%). In experimental populations, selective genotyping can reduce costs of QTL detection, allowing larger numbers of potential donors to be screened for useful alleles with effects across different backgrounds. In plant breeding programs, selective genotyping can make it possible to detect QTL using even a limited number of progeny that have been retained after selection.     

QTL detection by multi-parent linkage mapping in oil palm (Elaeis guineensis Jacq.)

A quantitative trait locus (QTL) analysis designed for a multi-parent population was carried out and tested in oil palm (Elaeis guineensis Jacq.), which is a diploid cross-fertilising perennial species. A new extension of the MCQTL package was especially designed for crosses between heterozygous parents. The algorithm, which is now available for any allogamous species, was used to perform and compare two types of QTL search for small size families, within-family analysis and across-family analysis, using data from a 2 × 2 complete factorial mating experiment involving four parents from three selected gene pools. A consensus genetic map of the factorial design was produced using 251 microsatellite loci, the locus of the Sh major gene controlling fruit shell presence, and an AFLP marker of that gene. A set of 76 QTLs involved in 24 quantitative phenotypic traits was identified. A comparison of the QTL detection results showed that the across-family analysis proved to be efficient due to the interconnected families, but the family size issue is just partially solved. The identification of QTL markers for small progeny numbers and for marker-assisted selection strategies is discussed.     

Identification and mapping of fruit rot resistance QTL in American cranberry using GBS

Sustainability of the cranberry industry is threatened by widespread and increasing losses due to fruit rot in the field as well as increasing restrictions on fungicide inputs. Breeding for resistance offers a partial solution but is challenging because fruit rot is caused by a complex of pathogenic fungi that can vary by location and from year to year. We identified four genetically diverse germplasm accessions that exhibit broad-spectrum fruit rot resistance under field conditions. Three of these accessions were used in biparental crosses to develop four populations segregating for resistance. Genotyping by sequencing was used to generate single-nucleotide polymorphism (SNP) markers for development of high-density genetic maps and quantitative trait locus (QTL) analyses. Nineteen QTL associated with fruit rot resistance, distributed on nine linkage groups, were discovered in our populations. Three of these QTL matched previously reported fruit rot resistance QTL. Four newly reported QTL found on linkage group 8 (Vm8), which explain between 21 and 33% of the phenotypic variance for fruit rot, are of particular interest to our breeding program. The populations described herein were also phenotyped for other horticulturally important traits, and QTL associated with yield and berry weight were identified. These QTL provide markers for candidate gene discovery and for future breeding efforts to enhance and pyramid disease resistance and other traits into elite horticultural backgrounds.     

A strategy for developing representative germplasm sets for systematic QTL validation,demonstrated for apple,peach, and sweet cherry

Horticultural crop improvement would benefit from a standardized, systematic, and statistically robust procedure for validating quantitative trait loci (QTLs) in germplasm relevant to breeding programs. Here, we describe and demonstrate a strategy for developing reference germplasm sets of perennial, clonally propagated crops, especially those with long juvenile periods. Germplasm is chosen to efficiently represent important members of larger pedigree-connected genepools. To facilitate validation of multiple QTLs, genome-wide representation of alleles is optimized for designated important breeding parents (IBPs) by estimating average allelic representation in relatives. The strategy and arising principles were demonstrated in a simulated germplasm set. Strong statistical power can be achieved with a carefully chosen germplasm set composed of IBPs, their numerous unselected progenies and close relatives, and all available founders and intermediate ancestors. Crop Reference Sets were developed in the marker-assisted breeding (MAB)-enabling “RosBREED” project as a base resource for QTL validation in US breeding germplasm of apple (Malus × domestica), peach (Prunus persica), and sweet cherry (Prunus avium) consisting of 467, 452, and 268 individuals, respectively. These sets adequately represent the most designated IBPs, have distinct advantages for QTL validation over other germplasm arrangements of equal size, and are recommended as a base resource for QTL validation by breeders of these US crops. The strategy described here can be used to develop efficient reference germplasm sets suiting other breeding genepools or to calculate the statistical power for QTL validation of germplasm sets already established.     

Bayesian QTL mapping using genome-wide SSR markers and segregating population derived from a cross of two commercial F<Subscript>1</Subscript> hybrids of tomato

Key message

Using newly developed euchromatin-derived genomic SSR markers and a flexible Bayesian mapping method, 13 significant agricultural QTLs were identified in a segregating population derived from a four-way cross of tomato.

Abstract

So far, many QTL mapping studies in tomato have been performed for progeny obtained from crosses between two genetically distant parents, e.g., domesticated tomatoes and wild relatives. However, QTL information of quantitative traits related to yield (e.g., flower or fruit number, and total or average weight of fruits) in such intercross populations would be of limited use for breeding commercial tomato cultivars because individuals in the populations have specific genetic backgrounds underlying extremely different phenotypes between the parents such as large fruit in domesticated tomatoes and small fruit in wild relatives, which may not be reflective of the genetic variation in tomato breeding populations. In this study, we constructed F₂ population derived from a cross between two commercial F₁ cultivars in tomato to extract QTL information practical for tomato breeding. This cross corresponded to a four-way cross, because the four parental lines of the two F₁ cultivars were considered to be the founders. We developed 2510 new expressed sequence tag (EST)-based (euchromatin-derived) genomic SSR markers and selected 262 markers from these new SSR markers and publicly available SSR markers to construct a linkage map. QTL analysis for ten agricultural traits of tomato was performed based on the phenotypes and marker genotypes of F₂ plants using a flexible Bayesian method. As results, 13 QTL regions were detected for six traits by the Bayesian method developed in this study.

     

Assessment of cultivated cherry germplasm in Iran by multivariate analysis

Key message

This work is an important step in the conservation of genetic cherry resources, which showed distinctive and interesting agronomical characters. Also it introduces suitable genotypes for cultivation and breeding studies.

Abstract

The purpose of this study was to characterize cherry germplasm that is cultivated in Iran. Thirty-three morphopomological parameters were studied in this germplasm, consisting of 70 cherry genotypes (41 sweet cherry, 24 sour cherry and 5 duke cherry genotypes). A wide variation was found in blooming time, ripening time, fruit weight, fruit color, anthocyanin, total soluble solids (TSS), titratable acidity (TA), fruit dimensions and flesh firmness and stone size. There were close positive correlations between fruit weight and fruit dimensions, and between fruit weight and fruit stalk weight, fruit flesh firmness and cracking and also a negative correlation between pH and TA. Dendrogram gave a clear separation between the sour, duke and sweet cherry species and also showed existing intraspecific morphological variation. Based on fruit size and organoleptic properties, the sweet cherry genotypes ‘Siah-Mashhad’, ‘Takdaneh-Mashhad’, ‘Shabestar’, ‘Siah-Daneshkade’, ‘Ghazvin’ and ‘Droongezna’ are recommended for fresh consumption. Good fruit chemical composition and late-ripening time stands out genotypes ‘Dirres-Italia’, ‘Dirres-Pardis’, ‘Maremoot’, ‘Abardeh’ and ‘Rorshon’ and make them suitable for processing. Also, ‘Gilas46’ and ‘Gilas49’ were substantially late-ripening, a characteristic that makes these genotypes highly suitable for breeding studies in case of ripening time. Furthermore, sour cherries ‘Hashtgerd2’ and ‘Hashtgerd3’ and duke cherries ‘Pardis1’ and ‘Pardis3’ were the best genotypes. This work is an important step in the conservation of genetic cherry resources in Iran, which showed distinctive and interesting agronomical characters such as low susceptibility to fruit cracking, high levels of total soluble solids, early fruit maturity and high fruit quality.     

Using mating designs to uncover QTL and the genetic architecture of complex traits

Analysis of quantitative trait loci (QTL) affecting complex traits is often pursued in single-cross experiments. For most purposes, including breeding, some assessment is desired of the generalizability of the QTL findings and of the overall genetic architecture of the trait. Single-cross experiments provide a poor basis for these purposes, as comparison across experiments is hampered by segregation of different allelic combinations among different parents and by context-dependent effects of QTL. To overcome this problem, we combined the benefits of QTL analysis (to identify genomic regions affecting trait variation) and classic diallel analysis (to obtain insight into the general inheritance of the trait) by analyzing multiple mapping families that are connected via shared parents. We first provide a theoretical derivation of main (general combining ability (GCA)) and interaction (specific combining ability (SCA)) effects on F(2) family means relative to variance components in a randomly mating reference population. Then, using computer simulations to generate F(2) families derived from 10 inbred parents in different partial-diallel designs, we show that QTL can be detected and that the residual among-family variance can be analyzed. Standard diallel analysis methods are applied in order to reveal the presence and mode of action (in terms of GCA and SCA) of undetected polygenes. Given a fixed experiment size (total number of individuals), we demonstrate that QTL detection and estimation of the genetic architecture of polygenic effects are competing goals, which should be explicitly accounted for in the experimental design. Our approach provides a general strategy for exploring the genetic architecture, as well as the QTL underlying variation in quantitative traits.     

QTL analysis of yield and seed number in Citrus

Amount, regularity and low seed content of the crop are important properties of scion citrus cultivars. The genetic control of these traits was studied in a progeny derived from the cross Citrus volkameriana×Poncirus trifoliata using molecular marker analysis. Since the traits were not normally distributed, the Kruskal-Wallis non-parametric test was used for quantitative trait loci (QTLs) detection. Most of the QTLs detected correspond to the trait ”number of fruits per tree”, in agreement with its known physiological complexity. Related traits (fruit number, fruit size and seed number) are controlled by QTLs some of which are located in the same genomic regions, suggesting that undesired associations could be broken to some degree by recombination. QTL analysis over years revealed important effects of genotype-by-environment interaction on QTL detection. This result agrees with the differences found for the trait means among years, which was found to be related, among other causes, to the alternate bearing of some genotypes and the amount of rain before harvest. Received: 1 October 1999 / Accepted: 2 December 1999     

High-density linkage maps constructed in sweet cherry (<Emphasis Type="Italic">Prunus avium</Emphasis> L.) using cross- and self-pollination populations reveal chromosomal homozygosity in inbred families and non-syntenic regions with the peach genome

The landrace sweet cherry (Prunus avium L.) cultivar ‘Cristobalina’ is a useful resource for sweet cherry breeding due to several important traits, including low chilling requirement, early maturity date, and self-compatibility. In this work, three families (N?=?325), derived from ‘Cristobalina’, were used to develop high-density genetic maps using the RosBREED 6K Illumina Infinium® cherry SNP array. Two of the families were derived from self-pollination, which allowed construction of the first F₂ genetic maps in the species. The other map developed was from an interspecific cross of cultivars ‘Vic’?×?‘Cristobalina’. The maps developed include 511 to 816 mapped SNPs covering 622.4 to 726.0 cM. Mapped SNP marker order and position were compared to the sweet cherry and peach genome sequences, and a high degree of synteny was observed. However, inverted and small translocated regions between peach and sweet cherry genomes were observed with the most noticeable inversion at the top of LG5. The progeny resulting from self-pollination also revealed a high level of homozygosity, as large presumably homozygous regions as well as entire homozygous LGs were observed. These maps will be used for genetic analysis of relevant traits in sweet cherry breeding by QTL analysis, and self-pollination populations will be useful for investigating inbreeding depression in a naturally outbreeding species.     

Differences in body size and egg loads of Rhagoletis indifferens (Diptera: Tephritidae) from introduced and native cherries

The western cherry fruit fly, Rhagoletis indifferens Curran, infests introduced, domesticated sweet [Prunus avium (L.) L.], and tart cherries (Prunus cerasus L.) as well as native bitter cherry, Prunus emarginata (Douglas) Eaton. Bitter cherries are smaller than sweet and tart cherries and this could affect various life history traits of flies. The objectives of the current study were to determine 1) if body size and egg loads of flies infesting sweet, tart, and bitter cherries differ from one another; and 2) if any observed body size differences are genetically based or caused by the host fruit environment. Pupae and adults of both sexes reared from larval-infested sweet and tart cherries collected in Washington and Montana were larger than those reared from bitter cherries. In addition, flies of both sexes caught on traps in sweet and tart cherry trees were larger than those caught in bitter cherry trees and females trapped from sweet and tart cherry trees had 54.0-98.8% more eggs. The progeny of flies from naturally-infested sweet and bitter cherries reared for one generation in the laboratory on sweet cherry did not differ in size. The same also was true for progeny of sweet and bitter cherry flies reared in the field on bitter cherry. The results suggest that the larger body sizes of flies from sweet and tart cherries than bitter cherries in the field are caused by host fruit and not genetic factors.     

Genome‐wide association studies based on sequence‐derived genotypes reveal new QTL associated with conformation and performance traits in the Franches–Montagnes horse breed

To identify novel quantitative trait loci (QTL) within horses, we performed genome‐wide association studies (GWAS) based on sequence‐level genotypes for conformation and performance traits in the Franches–Montagnes (FM) horse breed. Sequence‐level genotypes of FM horses were derived by re‐sequencing 30 key founders and imputing 50K data of genotyped horses. In total, we included 1077 FM horses genotyped for ~4 million SNPs and their respective de‐regressed breeding values of the traits in the analysis. Based on this dataset, we identified a total of 14 QTL associated with 18 conformation traits and one performance trait. Therefore, our results suggest that the application of sequence‐derived genotypes increases the power to identify novel QTL which were not identified previously based on 50K SNP chip data.     

Application of a new IBD-based QTL mapping method to common wheat breeding population: analysis of kernel hardness and dough strength

Mapping quantitative trait loci (QTL) in plants is usually conducted using a population derived from a cross between two inbred lines. The power of such QTL detection and the estimation of the effects highly depend on the choice of the two parental lines. Thus, the QTL found represent only a small part of the genetic architecture and can be of limited economical interest in marker-assisted selection. On the other hand, applied breeding programmes evaluate large numbers of progeny derived from multiple-related crosses for a wide range of agronomic traits. It is assumed that the development of statistical techniques to deal with pedigrees in existing plant populations would increase the relevance and cost effectiveness of QTL mapping in a breeding context. In this study, we applied a two-step IBD-based-variance component method to a real wheat breeding population, composed of 374 F₆ lines derived from 80 different parents. Two bread wheat quality related traits were analysed by the method. Results obtained show very close agreement with major genes and QTL already known for those two traits. With this new QTL mapping strategy, inferences about QTL can be drawn across the breeding programme rather than being limited to the sample of progeny from a single cross and thus the use of the detected QTL in assisting breeding would be facilitated.     

Mapping of quantitative trait loci (QTLs) for oil yield using SSRs and gene-based markers in African oil palm (<Emphasis Type="Italic">Elaeis guineensis</Emphasis> Jacq.)

The identification of quantitative trait loci (QTLs) based on anchor markers, especially candidate genes that control a trait of interest, has been noted to increase the power of QTL detection. Since these markers can be scored as co-dominant data, they are also valuable for comparing and integrating the QTL linkage maps from diverse mapping populations. To estimate the position and effects of QTLs linked to oil yield traits in African oil palm, co-dominant microsatellites (SSR) and candidate gene-based sequence polymorphisms were applied to construct a linkage map for a progeny showing large differences in oil yield components. The progeny was genotyped for 97 SSR markers, 93 gene-linked markers, and 12 non-gene-linked SNP markers. From these, 190 segregating loci could be arranged into 31 linkage groups while 12 markers remained unmapped. Using the single marker linkage, interval mapping and multiple QTL methods, 16 putative QTLs on seven linkage groups affecting important oil yield related traits such as fresh fruit bunch yield (FFB), ratio of oil per fruit (OF), oil per bunch (OB), fruit per bunch (FB) and wet mesocarp per fruit (WMF) could be identified in the segregating population with estimated values for explained variance ranging from 12.4 % to 54.5 %. Markers designed from some candidate genes involved in lipid biosynthesis were found to be mapped near significant QTLs for various economic yield traits. Associations between QTLs and potential candidate genes are discussed.