A quantitative trait locus for oleic fatty acid content on Sus scrofa chromosome 7

A partial genome scan using microsatellite markers was conducted to detect quantitative trait loci (QTLs) for 10 fatty acid contents of backfat on 15 chromosomes in a porcine resource population. Two QTLs were discovered on Sus scrofa chromosome 4 (SSC4) and SSC7. The QTL on SSC4 was located between marker loci sw1336 and sw512, and this QTL was detected (P < 0.05) only for linoleic acid. Its position was in proximity of those mapped for linoleic acid content in previous studies. The QTL on SSC7 was mapped between markers swr1343 and sw2155, and it was significant (P < 0.05) only for oleic acid. A novelty of the QTL for oleic acid was suggested because the QTL was located far from any other QTLs previously mapped for fatness traits. The QTL on SSC7 explained 19% of phenotypic variation for oleic acid content. Further studies on fine mapping and positional comparative candidate gene analysis would be the next step toward better understanding of the genetic architecture of fatty acid contents.     

Quantitative trait loci mapping for fatty acid contents in the backfat on porcine chromosomes 1, 13, and 18

A partial genome scan using microsatellite markers was conducted in order to detect quantitative trait loci (QTLs) for 10 fatty acid contents of the backfat in a pig reference population. Two QTLs were found by studying SSC1, SSC13, and SSC18, where QTLs had already been identified for backfat thickness. A QTL was located between marker loci S0113 and SW974 on chromosome 1; this QTL was only significantly detected (P < 0.05) for linoleic acid. The other QTL was discovered between markers S0062 and S0120 on chromosome 18, and its significance only showed (P < 0.05) for myristic acid. The two QTLs mapped to the same location as the backfat thickness QTL. A third of the phenotypic variation was explained for linoleic acid by the QTL on chromosome 1, and a quarter for myristic acid by the QTL on chromosome 18. Further studies on fine mapping and positional comparative candidate gene analyses will be the next step toward a better understanding of the genetic architecture of fatty acid contents.     

Comparative analysis and development of microsatellite markers on swine (Sus scrofa) chromosome 1qter

Several quantitative trait loci (QTL) have been detected on SSC1qter (Sus scrofa chromosome 1qter), including QTL for the number of vertebrae, as reported in our previous study. To provide the tools for analysis of QTLs on SSC1qter, we constructed a comparative map of swine and human. In addition, we identified 26 swine STSs and mapped 16 of them on SSC1qter using the INRA - University of Minnesota porcine radiation hybrid (IMpRH) panel. We screened a BAC library using these swine STSs and developed 35 new polymorphic microsatellite markers from the BAC clones, of which 26 were informative in our reference family. We also mapped nine microsatellite markers we had isolated previously. Consequently a total of 44 new polymorphic microsatellite markers were located within a 60-cM region of SSC1qter, spanning from SW1092 to the telomere.     

Fine mapping of quantitative trait loci for mastitis resistance on bovine chromosome 11

Quantitative trait loci (QTL) affecting clinical mastitis (CM) and somatic cell score (SCS) were mapped on bovine chromosome 11. The mapping population consisted of 14 grandsire families belonging to three Nordic red cattle breeds: Finnish Ayrshire (FA), Swedish Red and White (SRB) and Danish Red. The families had previously been shown to segregate for udder health QTL. A total of 524 progeny tested bulls were included in the analysis. A linkage map including 33 microsatellite and five SNP markers was constructed. We performed combined linkage disequilibrium and linkage analysis (LDLA) using the whole data set. Further analyses were performed for FA and SRB separately to study the origin of the identified QTL/haplotype and to examine if it was common in both populations. Finally, different two-trait models were fitted. These postulated either a pleiotropic QTL affecting both traits; two linked QTL, each affecting one trait; or one QTL affecting a single trait. A QTL affecting CM was fine-mapped. In FA, a haplotype having a strong association with a high negative effect on mastitis resistance was identified. The mapping precision of an earlier detected SCS-QTL was not improved by the LDLA analysis because of lack of linkage disequilibrium between the markers used and the QTL in the region.     

Association mapping of quantitative resistance for <Emphasis Type="Italic">Leptosphaeria maculans</Emphasis> in oilseed rape (<Emphasis Type="Italic">Brassica napus</Emphasis> L.)

Stem canker caused by the fungus Leptosphaeria maculans is a major disease of Brassica napus. Quantitative resistance factors appear to be important components for effective and durable control of this pathogen. Quantitative trait loci (QTL) for stem canker resistance have previously been identified in the Darmor variety. However, before these QTL can be used in marker-assisted selection (MAS) to breed resistant varieties, they must be validated in a wide range of genetic backgrounds. We used an association mapping approach to confirm the markers located within the QTL previously identified in Darmor and establish their usefulness in MAS. For this, we characterized the molecular diversity of an oilseed rape collection of 128 lines showing a large spectrum of responses to infection by L. maculans, using 72 pairs of primers for simple sequence repeat and other markers. We used different association mapping models which either do or do not take into account the population structure and/or family relatedness. In all, 61 marker alleles were found to be associated with resistance to stem canker. Some of these markers were associated with previously identified QTL, which confirms their usefulness in MAS. Markers located in regions not harbouring previously identified QTL were also associated with resistance, suggesting that new QTL or allelic variants are present in the collection. All of these markers associated with stem canker resistance will help identify accessions carrying desirable alleles and facilitate QTL introgression.     

Fine mapping and imprinting analysis for fatness trait QTLs in pigs

Quantitative trait loci (QTL) for fatness traits were reported recently in an experimental Meishan × Large White and Landrace F₂ cross. To further investigate the regions on pig Chr 2 (SSC2), SSC4, and SSC7, 25 additional markers from these regions were typed on 800 animals (619 F₂ animals, their F₁ parents, and F₀ grandfathers). Compared with the published maps, a modified order of markers was observed for SSC4 and SSC7. QTL analyses were performed both within the half-sib families as well as across families (line cross). Furthermore, a QTL model accounting for imprinting effects was tested. Information content could be increased considerably on all three chromosomes. Evidence for the backfat thickness QTL on SSC7 was increased, and the location could be reduced to a 33-cM confidence interval. The QTL for intramuscular fat on SSC4 could not be detected in this half-sib analysis, whereas under the line cross model a suggestive QTL on a different position on SSC4 was detected. For SSC2, in the half-sib analysis, a suggestive QTL for backfat thickness was detected with the best position at 26 cM. Imprinting analysis, however, revealed a genome-wise, significant, paternally expressed QTL on SSC2 with the best position at 63 cM. Our results suggest that this QTL is different from the previously reported paternally expressed QTL for muscle mass and fat deposition on the distal tip of SSC2p. Received: 15 October 1999 / Accepted: 21 February 2000     

Quantitative trait loci for chemical body composition traits in pigs and their positional associations with body tissues, growth and feed intake

In this study, quantitative trait loci (QTL) for chemical and physical body composition, growth and feed intake in pigs were identified in a three-generation full-sib population, developed by crossing Pietrain sires with a commercial dam line. Phenotypic data from 315 F₂ animals were available for protein and lipid deposition measured in live animals by the deuterium dilution technique at 30-, 60-, 90-, 120- and 140-kg body weight. At 140-kg body weight, carcass characteristics were measured by the AutoFOM grading system and after dissection. Three hundred and eighty-six animals from 49 families were genotyped for 51 molecular markers covering chromosomes SSC2, SSC4, SSC8, SSC9, SSC10 and SSC14. Novel QTL for protein (lipid) content at 60-kg body weight and protein (lipid) accretion from 120 to 140 kg were detected on SSC9 near several previously detected QTL for lean and fat tissue in neck, shoulder and ham cuts. Another QTL for lipid accretion was found on SSC8, closely associated with a QTL for intramuscular fat content. QTL for daily feed intake were detected on SSC2 and SSC10. The favourable allele of a QTL for food conversion ratio (FCR) on SSC2 was associated with alleles for increased lean tissue and decreased fat tissue. Because no QTL for growth rate were found in the region, the QTL for FCR is most likely due to a change in body composition. These QTL provide insights into the genomic regulation of chemical or physical body composition and its association with feed intake, feed efficiency and growth.     

A whole genome scan to detect quantitative trait loci for gestation length and sow maternal ability related traits in a White Duroc × Erhualian F2 resource population

Gestation length and maternal ability are important to improve the sow reproduction efficiency and their offspring survival. To map quantitative trait loci (QTL) for gestation length and maternal ability related traits including piglet survival rate and average body weight of piglets at weaning, more than 200 F2 sows from a White Duroc × Erhualian resource population were phenotyped. A genome-wide scan was performed with 194 microsatellite markers covering the whole pig genome. QTL analysis was carried out using a composite regression interval mapping method via QTL express. The results showed that total number of born piglets was significantly correlated with gestation length (r = -0.13, P < 0.05). Three QTL were detected on pig chromosome (SSC)2, 8 and 12 for gestation length. The QTL on SSC2 achieved the 5% genome-wide significant level and the QTL on SSC8 was consistent with previous reports. Four suggestive QTL were identified for maternal ability related traits including 1 QTL for survival rate of piglets at weaning on SSC8, 3 QTL for average body weight of piglet at weaning on SSC3, 11 and 13.     

Identification of Quantitative Trait Loci for Resistance to RSIVD in Red Sea Bream (<Emphasis Type="Italic">Pagrus major</Emphasis>)

Red sea bream iridoviral disease (RSIVD) is a major viral disease in red sea bream farming in Japan. Previously, we identified one candidate male individual of red sea bream that was significantly associated with convalescent individuals after RSIVD. The purpose of this study is to identify the quantitative trait loci (QTL) linked to the RSIVD-resistant trait for future marker-assisted selection (MAS). Two test families were developed using the candidate male in 2014 (Fam-2014) and 2015 (Fam-2015). These test families were challenged with RSIV, and phenotypes were evaluated. Then, de novo genome sequences of red sea bream were obtained through next-generation sequencing, and microsatellite markers were searched and selected for linkage map construction. One immune-related gene, MHC class IIβ, was also used for linkage map construction. Of the microsatellite markers searched, 148 and 197 were mapped on 23 and 27 linkage groups in the female and male linkage maps, respectively, covering approximately 65% of genomes in both sexes. One QTL linked to an RSIVD-resistant trait was found in linkage group 2 of the candidate male in Fam-2014, and the phenotypic variance of the QTL was 31.1%. The QTL was closely linked to MHC class IIβ. Moreover, the QTL observed in Fam-2014 was also significantly linked to an RSIVD-resistant trait in the candidate male of Fam-2015. Our results suggest that the RSIVD-resistant trait in the candidate male was controlled by one major QTL closely linked to the MHC class IIβ gene and could be useful for MAS of red sea bream.     

Detection of loci affecting milk production and health traits in an elite US Holstein population using microsatellite markers

Quantitative trait loci (QTL) affecting health and milk production traits were studied in seven large half-sib US Holstein families by using the granddaughter design. Genotyping for 16 markers was completed and marker allele differences within and pooled-across families were analysed. Potential QTL were identified for somatic cell score (SCS), fat yield, fat percentage, protein yield and protein percentage. Three markers (BM203, BM4505 and BM2078) were associated with significant effects for different traits and, after further analysis, may be useful in marker-assisted selection in specific families. Comparisons between these data and previously identified QTL support the location of a QTL for milk yield and protein yield on chromosome 21.     

Mapping of QTLs for lycopene and other fruit traits in a Lycopersicon esculentum × L. pimpinellifolium cross and comparison of QTLs across tomato species

Quantitative trait loci (QTLs) for several fruit traits in tomato were mapped and characterized in a backcross population of an interspecific cross between Lycopersicon esculentum fresh-marker breeding line NC84173 and L. pimpinellifolium accession LA722. A molecular linkage map of this cross that was previously constructed based on 119 BC1 individuals and 151 RFLP markers was used for the QTL mapping. The parental lines and 119 BC1S1 families (self-pollinated progeny of BC1 individuals) were grown under field conditions at two locations, Rock Spring, PA, and Davis, CA, and fruits were scored for weight (FW), polar (PD) and equatorial diameters (ED), shape (FS), total soluble solids content (SSC), pH and lycopene content (LYC). For each trait, between 4 and 10 QTLs were identified with individual effects ranging between 4.4% and 32.9% and multilocus QTL effects ranging between 39% and 75% of the total phenotypic variation. Most QTL effects were predictable from the parental phenotypes, and several QTLs were identified that affected more than one trait. A few pairwise epistatic interactions were detected between QTL-linked and QTL-unlinked markers. Despite great differences between PA and CA growing conditions, the majority of FW QTLs (78%) and SSC QTLs (75%) in the two locations shared similar genomic positions. Almost all of the QTLs that were identified in the present study for FW and SSC were previously identified in six other studies that used different interspecific crosses of tomato; this indicates conservation of QTLs for fruit traits across tomato species. Altogether, the seven studies identified at least 28 QTLs for FW and 32 QTLs for SSC on the 12 tomato chromosomes. However, for each trait a few major QTLs were commonly identified in 4 or more studies; such ‘popular’ QTLs should be of considerable interest for breeding purposes as well as basic research towards cloning of QTLs. Notably, a majority of QTLs for increased SSC also contributed to decreased fruit size. Therefore, to significantly increase SSC of the cultivated tomato, some compromise in fruit size may be unavoidable. This revised version was published online in June 2006 with corrections to the Cover Date.     

Confirmation of QTL on porcine chromosomes 1 and 8 influencing leukocyte numbers, haematological parameters and leukocyte function

A genome wide search in European Wild Boar x Swedish Yorkshire (W x Y) inter-cross pigs has earlier identified quantitative trait loci (QTL) for leucocyte number and function on porcine chromosomes 1 and 8 (SSC 1 and 8). To verify the involvement of these chromosomal regions in the regulation of haematocrit (Hem) and haemoglobin (Hb) levels, leucocyte numbers and in vitro leukocyte functions (mitogen induced proliferation and IL-2 production, virus induced interferon-alpha production and neutrophil phagocytosis), animals of different genetic backgrounds were analysed. The animals comprised a back-cross sire family (n=47) of W x Y pigs and six crossbred [Y x Landrace (L)] sire families (n=191). They were genotyped for 16 genetic markers and an interval analysis was performed. On SSC1, a QTL close to S0082 on the q-arm that influenced numbers of white blood cells in L x Y pigs and numbers of band neutrophils and CD8(+) cells in W x Y pigs was identified (P相似文献   

猪重要胴体性状的遗传定位

为了寻找影响猪重要胴体性状主基因在染色体的位置,我们以大白猪和梅山猪为父母本建立了F2资源家系。随机选留81头F2代个体,经屠宰获得猪胴体性状数据。结合家系个体的48个微卫星标记基因型,用线性模型最小二乘法对各胴体性状进行数量性状基因座（QTL）的区间定位。定位结果表明位于猪染色体（SSC）4号的瘦肉率和瘦肉量QTL达到基因组极显著水平;SSC1、2和4上眼肌面积QTL达到染色体显著水平;位于SSC1和4上的眼肌高度QTL与眼肌面积QTL在同一染色体区域;而眼肌宽度QTL位于SSC6;位于SSC7同一标记区间的皮重、皮率、骨重和骨率QTL表现出很好的一致性,均达到染色体显著水平。SSC6和7的体长QTL达到染色体显著水平。 Abstract: To detect quantitative trait loci (QTL) for body composition traits in pigs, a resource family with three-generation was developed by using Large White grand sires and Meishan grand dams. A total of 81 F2 progenies were phenotyped for body composition. All animals were genotyped for microsatellite markers. The main results are as follows:, the strongest linkages at genome-wise level of lean meat percentage and total meat content were detected on SSC1 and 4. QTLs for loin eye area were located on SSC1, 2 and 4, QTLs for loin eye height on SSC 1 and 4, and QTLs for loin eye width on SSC 6. The best positions estimated for QTLs of skin percentage and of skin weight were in the same marker interval. Two QTLs significant at genome-wise level or highly significant at chromosome-wide level for carcass length were located on SSC6 and 7.     

Quantitative trait loci associated with AutoFOM grading characteristics, carcass cuts and chemical body composition during growth of Sus scrofa

A three-generation full-sib resource family was constructed by crossing two commercial pig lines. Genotypes for 37 molecular markers covering chromosomes SSC1, SSC6, SSC7 and SSC13 were obtained for 315 F2 animals of 49 families and their parents and grandparents. Phenotypic records of traits including carcass characteristics measured by the AutoFOM grading system, dissected carcass cuts and meat quality characteristics were recorded at 140 kg slaughter weight. Furthermore, phenotypic records on live animals were obtained for chemical composition of the empty body, protein and lipid accretion (determined by the deuterium dilution technique), daily gain and feed intake during the course of growth from 30 to 140 kg body weight. Quantitative trait loci (QTL) detection was conducted using least-squares regression interval mapping. Highest significance at the 0.1% chromosome-wise level was obtained for five QTL: AutoFOM belly weight on SSC1; ham lean-meat weight, percentage of fat of primal cuts and daily feed intake between 60 and 90 kg live weight on SSC6; and loin lean-meat weight on SSC13. QTL affecting daily gain and protein accretion were found on SSC1 in the same region. QTL for protein and lipid content of empty body at 60 kg liveweight were located close to the ryanodine receptor 1 (RYR1) locus on SSC6. On SSC13, significant QTL for protein accretion and feed conversion ratio were detected during growth from 60 to 90 kg. In general, additive genetic effects of alleles originating from the Piétrain line were associated with lower fatness and larger muscularity as well as lower daily gain and lower protein accretion rates. Most of the QTL for carcass characteristics were found on SSC6 and were estimated after adjustment for the RYR1 gene. QTL for carcass traits, fatness and growth on SSC7 reported in the literature, mainly detected in crosses of commercial lines x obese breeds, were not obtained in the present study using crosses of only commercial lines, suggesting that these QTL are not segregating in the analysed commercial lines.     

QTL analysis of white blood cell, platelet and red blood cell-related traits in an F2 intercross between Landrace and Korean native pigs

Haematological traits play important roles in disease resistance and defence functions. The objective of this study was to locate quantitative trait loci (QTL) and the associated positional candidate genes influencing haematological traits in an F₂ intercross between Landrace and Korean native pigs. Eight blood‐related traits (six erythrocyte traits, one leucocyte trait and one platelet trait) were measured in 816 F₂ progeny. All experimental animals were genotyped with 173 informative microsatellite markers located throughout the pig genome. We report that nine chromosomes harboured QTL for the baseline blood parameters: genomic regions on SSC 1, 4, 5, 6, 8, 9, 11, 13 and 17. Eight of twenty identified QTL reached genome‐wide significance. In addition, we evaluated the KIT locus, an obvious candidate gene locus affecting variation in blood‐related traits. Using dense single nucleotide polymorphism marker data on SSC 8 and the marker‐assisted association test, the strong association of the KIT locus with blood phenotypes was confirmed. In conclusion, our study identified both previously reported and novel QTL affecting baseline haematological parameters in pigs. Additionally, the positional candidate genes identified here could play an important role in elucidating the genetic architecture of haematological phenotype variation in swine and in humans.     

QTL analysis of clinical-chemical traits in an F₂ intercross between Landrace and Korean native pigs

Clinical-chemical traits are essential when examining the health status of individuals. The aim of this study was to identify quantitative trait loci (QTL) and the associated positional candidate genes affecting clinical-chemical traits in a reciprocal F(2) intercross between Landrace and Korean native pigs. Following an overnight fast, 25 serum phenotypes related to clinical-chemical traits (e.g., hepatic function parameters, renal function parameters, electrolyte, lipids) were measured in >970 F(2) progeny. All experimental samples were subjected to genotyping analysis using 165 microsatellite markers located across the genome. We identified eleven genome-wide significant QTL in six chromosomal regions (SSC 2, 7, 8, 13, 14, and 15) and 59 suggestive QTL in 17 chromosomal regions (SSC 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 16, 17, and 18). We also observed significant effects of reciprocal crosses on some of the traits, which would seem to result from maternal effect, QTL on sex chromosomes, imprinted genes, or genetic difference in mitochondrial DNA. The role of genomic imprinting in clinical-chemical traits also was investigated. Genome-wide analysis revealed a significant evidence for an imprinted QTL in SSC4 affecting serum amylase levels. Additionally, a series of bivariate linkage analysis provided strong evidence that QTL in SSC 2, 13, 15, and 18 have a pleiotropic effect on clinical-chemical traits. In conclusion, our study detected both novel and previously reported QTL influencing clinical-chemical traits in pigs. The identified QTL together with the positional candidate genes identified here could play an important role in elucidating the genetic structure of clinical-chemical phenotype variation in humans and swine.     

QTL analysis of back fat thickness and carcass pH in an F2 intercross between Landrace and Korean native pigs

In this study, we conducted a genome-wide linkage analysis to identify the quantitative trait loci (QTL) that influence back fat thickness and carcass pH in an F(2) intercross between Landrace and Korean native pigs. Eight phenotypes related with back fat thickness and carcass pH were measured in more than 960 F(2) progeny. All experimental animals were subjected to genotypic analysis using 173 microsatellite markers located throughout the pig genome. The GridQTL program, based on the least squares regression model, was used to perform the QTL analysis. We identified 22 genome-wide significant QTL in 9 chromosomal regions (SSC1, 2, 5, 6, 7, 8, 12, 15, and 16) and 29 suggestive QTL in 16 chromosomal regions (SSC2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 14, 15, 16, 17, 18, and X). On SSC5, we detected a QTL affecting back fat thickness that accounted for 4.8 % of the phenotypic variance, which was the highest test statistic (F-ratio = 50.3 under the additive model, nominal P value = 2.5 × 10(-12)) observed in this study. Additionally, we showed that there were significant QTL on SSC16 affecting carcass pH traits. In conclusion, the QTL identified in this study together with associated positional candidate genes could play an important role in determining the genetic structure underlying the variation of back fat thickness and carcass pH in pigs.     

Usefulness of marker‐assisted selection to improve maize for increased resistance to Sesamia nonagrioides attack with no detrimental effect on yield

Two decades of investigations on maize resistance to Mediterranean corn borer (Sesamia nonagrioides Lefebvre; MCB) have shown that breeding for increased resistance to stem tunnelling by MCB often resulted in reduced yield because significant genetic correlation between both traits exists in some backgrounds. Unlike phenotypic selection, marker‐assisted selection (MAS) could differentiate markers linked only to one trait from those linked simultaneously to yield potential and susceptibility to the pest. In the current study, the suitability of MAS for improving resistance to stem tunnelling without adverse effects on yield has been tested. The unfavourable genetic relationship between yield potential and susceptibility could be overcome using MAS. Gains obtained using MAS were weak, because genetic variance explained by the quantitative trait loci (QTL) was low but results encourage us to persevere in using marker information for simultaneous improvement of resistance and yield especially if genome‐wide approaches are applied. Approaches to detect QTL are widely used, but studies on the suitability of markers linked to QTL for performing MAS have been mostly neglected.     

Polymorphisms on SSC15q21-q26 Containing QTL for reproduction in Swine and its association with litter size

Several quantitative trait loci (QTL) for important reproductive traits (ovulation rate) have been identified on the porcine chromosome 15 (SSC15). To assist in the selection of positional candidate swine genes for these QTL on SSC15, twenty-one genes had already been assigned to SSC15 in a previous study in our lab, by using the radiation hybrid panel IMpRH. Further polymorphism studies were carried out on these positional candidate genes with four breeds of pigs (Duroc, Erhualian, Dahuabai and Landrace) harboring significant differences in reproduction traits. A total of nineteen polymorphisms were found in 21 genes. Among these, seven in six genes were used for association studies, whereby NRP2 polymorphism was found to be significantly (p < 0.05) associated with litter-size traits. NRP2 might be a candidate gene for pig-litter size based on its chromosome location (Du et al., 2006), significant association with litter-size traits and relationships with Sema and the VEGF super families.     

Family-based mapping of quantitative trait loci in plant breeding populations with resistance to Fusarium head blight in wheat as an illustration

Traditional quantitative trait loci (QTL) mapping approaches are typically based on early or advanced generation analysis of bi-parental populations. A limitation associated with this methodology is the fact that mapping populations rarely give rise to new cultivars. Additionally, markers linked to the QTL of interest are often not immediately available for use in breeding and they may not be useful within diverse genetic backgrounds. Use of breeding populations for simultaneous QTL mapping, marker validation, marker assisted selection (MAS), and cultivar release has recently caught the attention of plant breeders to circumvent the weaknesses of conventional QTL mapping. The first objective of this study was to test the feasibility of using family-pedigree based QTL mapping techniques generally used with humans and animals within plant breeding populations (PBPs). The second objective was to evaluate two methods (linkage and association) to detect marker-QTL associations. The techniques described in this study were applied to map the well characterized QTL, Fhb1 for Fusarium head blight resistance in wheat (Triticum aestivum L.). The experimental populations consisted of 82 families and 793 individuals. The QTL was mapped using both linkage (variance component and pedigree-wide regression) and association (using quantitative transmission disequilibrium test, QTDT) approaches developed for extended family-pedigrees. Each approach successfully identified the known QTL location with a high probability value. Markers linked to the QTL explained 40–50% of the phenotypic variation. These results show the usefulness of a human genetics approach to detect QTL in PBPs and subsequent use in MAS.