Mapping genetic loci that regulate lipid levels in a NZB/B1NJxRF/J intercross and a combined intercross involving NZB/B1NJ, RF/J, MRL/MpJ, and SJL/J mouse strains

The NZB/B1NJ (NZB) mouse strain exhibits high cholesterol and HDL levels in blood compared with several other strains of mice. To study the genetic regulation of blood lipid levels, we performed a genome-wide linkage analysis in 542 chow-fed F2 female mice from an NZBxRF/J (RF) intercross and in a combined data set that included NZBxRF and MRL/MpJxSJL/J intercrosses. In the NZBxRF F2 mice, the cholesterol and HDL concentrations were influenced by quantitative trait loci (QTL) on chromosome (Chr) 5 [logarithm of odds (LOD) 17-19; D5Mit10] that was in the region identified earlier in crosses involving NZB mice, but two QTLs on Chr 12 (LOD 4.7; D12Mit182) and Chr 19 (LOD 5.7; D19Mit1) were specific to the NZBxRF intercross. Triglyceride levels were affected by two novel QTLs at D12Mit182 (LOD 8.7) and D15Mit13 (LOD 3.5). The combined-cross linkage analysis (1,054 mice, 231 markers) 1) identified four shared QTLs (Chrs 5, 7, 14, and 17) that were not detected in one of the parental crosses and 2) improved the resolution of two shared QTLs. In summary, we report additional loci regulating lipid levels in NZB mice that had not been identified earlier in crosses involving the NZB strain of mice. The identification of shared loci from multiple crosses increases confidence toward finding the QTL gene.     

Mapping Quantitative Trait Loci in Crosses between Outbred Lines Using Least Squares

The use of genetic maps based upon molecular markers has allowed the dissection of some of the factors underlying quantitative variation in crosses between inbred lines. For many species crossing inbred lines is not a practical proposition, although crosses between genetically very different outbred lines are possible. Here we develop a least squares method for the analysis of crosses between outbred lines which simultaneously uses information from multiple linked markers. The method is suitable for crosses where the lines may be segregating at marker loci but can be assumed to be fixed for alternative alleles at the major quantitative trait loci (QTLs) affecting the traits under analysis (e.g., crosses between divergent selection lines or breeds with different selection histories). The simultaneous use of multiple markers from a linkage group increases the sensitivity of the test statistic, and thus the power for the detection of QTLs, compared to the use of single markers or markers flanking an interval. The gain is greater for more closely spaced markers and for markers of lower information content. Use of multiple markers can also remove the bias in the estimated position and effect of a QTL which may result when different markers in a linkage group vary in their heterozygosity in the F(1) (and thus in their information content) and are considered only singly or a pair at a time. The method is relatively simple to apply so that more complex models can be fitted than is currently possible by maximum likelihood. Thus fixed effects and effects of background genotype can be fitted simultaneously with the exploration of a single linkage group which will increase the power to detect QTLs by reducing the residual variance. More complex models with several QTLs in the same linkage group and two-locus interactions between QTLs can similarly be examined. Thus least squares provides a powerful tool to extend the range of crosses from which QTLs can be dissected whilst at the same time allowing flexible and realistic models to be explored.     

Combining data from multiple inbred line crosses improves the power and resolution of quantitative trait loci mapping

Rodent inbred line crosses are widely used to map genetic loci associated with complex traits. This approach has proven to be powerful for detecting quantitative trait loci (QTL); however, the resolution of QTL locations, typically approximately 20 cM, means that hundreds of genes are implicated as potential candidates. We describe analytical methods based on linear models to combine information available in two or more inbred line crosses. Our strategy is motivated by the hypothesis that common inbred strains of the laboratory mouse are derived from a limited ancestral gene pool and thus QTL detected in multiple crosses are likely to represent shared ancestral polymorphisms. We demonstrate that the combined-cross analysis can improve the power to detect weak QTL, can narrow support intervals for QTL regions, and can be used to separate multiple QTL that colocalize by chance. Moreover, combined-cross analysis can establish the allelic states of a QTL among a set of parental lines, thus providing critical information for narrowing QTL regions by haplotype analysis.     

Genetic dissection of ``OLETF', a rat model for non-insulin-dependent diabetes mellitus

To elucidate the genetic factors underlying non-insulin-dependent diabetes mellitus (NIDDM), we performed genome-wide quantitative trait locus (QTL) analysis, using the Otsuka Long-Evans Tokushima Fatty (OLETF) rat. The OLETF rat is an excellent animal model of NIDDM because the features of the disease closely resemble human NIDDM. Genetic dissection with two kinds of F2 intercross progeny, from matings between the OLETF rat and non-diabetic control rats F344 or BN, allowed us to identify on Chromosome (Chr) 1 a major QTL associated with features of NIDDM that was common to both crosses. We also mapped two additional significant loci, on Chrs 7 and 14, in the (OLETF × F344)F₂ cross alone, and designated these three loci as Diabetes mellitus, OLETF type Dmo 1, Dmo2 and Dmo3 respectively. With regard to suggestive QTLs, we found loci on Chrs 10, 11, and 16 that were common to both crosses, as well as loci on Chrs 5 and 12 in the (OLETF × F344)F₂ cross and on Chrs 4 and 13 in the (OLETF × BN)F₂ cross. Our results showed that NIDDM in the OLETF rat is polygenic and demonstrated that different genetic backgrounds could affect ``fitness' for QTLs and produce different phenotypic effects from the same locus. Received: 9 October 1997 / Accepted: 29 January 1998     

Healing quantitative trait loci in a combined cross analysis using related mouse strain crosses

Inbred mouse strains MRL and LG share the ability to fully heal ear hole punches with the full range of appropriate tissues without scarring. They also share a common ancestry, MRL being formed from a multi-strain cross with two final backcrosses to LG before being inbred by brother-sister mating. Many gene-mapping studies for healing ability have been performed using these two strains, resulting in the location of about 20 quantitative trait loci (QTLs). Here, we combine two of these crosses (N = 638), MRL/lpr × C57BL/6NTac and LG/J × SM/J, in a single combined cross analysis to increase the mapping power, decrease QTL support intervals, separate multiple QTLs and establish allelic states at individual QTL. The combined cross analysis located 11 QTLs, 6 affecting only one cross (5 LG × SM and 1 MRL × B6) and 5 affecting both crosses, approximately the number of common QTLs expected given strain SNP similarity. Amongst the five QTLs mapped in both crosses, three had significantly different genetic effects, additive in one cross and over or underdominant in the other. It is possible that allelic states at these three loci are different in SM and B6 because they lead to differences in dominance interactions with the LG and MRL alleles. QTL support intervals are 40% smaller in the combined cross analysis than in either of the single crosses. Combined cross analysis was successful in enhancing the interpretation of earlier QTL results for these strains.     

Using the mixed model for interval mapping of quantitative trait loci in outbred line crosses

Interval mapping by simple regression is a powerful method for the detection of quantitative trait loci (QTLs) in line crosses such as F2 populations. Due to the ease of computation of the regression approach, relatively complex models with multiple fixed effects, interactions between QTLs or between QTLs and fixed effects can easily be accommodated. However, polygenic effects, which are not targeted in QTL analysis, cannot be treated as random effects in a least squares analysis. In a cross between true inbred lines this is of no consequence, as the polygenic effect contributes just to the residual variance. In a cross between outbred lines, however, if a trait has high polygenic heritability, the additive polygenic effect has a large influence on variation in the population. Here we extend the fixed model for the regression interval mapping method to a mixed model using an animal model. This makes it possible to use not only the observations from progeny (e.g. F2), but also those from the parents (F1) to evaluate QTLs and polygenic effects. We show how the animal model using parental observations can be applied to an outbred cross and so increase the power and accuracy of QTL analysis. Three estimation methods, i.e. regression and an animal model either with or without parental observations, are applied to simulated data. The animal model using parental observations is shown to have advantages in estimating QTL position and additive genotypic value, especially when the polygenic heritability is large and the number of progeny per parent is small.     

Mapping of quantitative trait loci for a new source of resistance to bruchids in the wild species Vigna nepalensis Tateishi & Maxted (Vigna subgenus Ceratotropis)

Azuki bean breeders have long been interested in producing azuki bean [Vigna angularis (Willd.) Ohwi & Ohashi] varieties with bruchid resistance. A new bruchid (Callosobruchus spp.) resistance source was found in V. nepalensis Tateishi & Maxted, a species that is cross compatible with azuki bean. Quantitative trait loci (QTLs) analysis for resistance to C. chinensis (L.) and C. maculatus (F.) was conducted using F(2) (V. nepalensis x V. angularis) and BC(1)F(1) [(V. nepalensis x V. angularis) x V. angularis] populations derived from crosses between the bruchid resistant species V. nepalensis and bruchid susceptible species V. angularis. Resistance was measured using two traits, percentage of seeds damaged by bruchids and the time taken for adult bruchids to emerge from seeds. Based on the results from both populations seven QTLs were detected for bruchid resistance; five QTLs for resistance to C. chinensis and two QTLs for resistance to C. maculatus. The different locations found for some resistance QTL to the two bruchid species suggests different resistance mechanisms. QTLs on linkage group (LG) 1 and LG2 for bruchid resistance to C. chinensis co-localized with seed size QTLs suggesting that incremental increase in seed size accompanied susceptibility to C. chinensis. Based on linked markers the QTL on these two linkage groups appear to be the same as previously reported in other Asian Vigna. However, several other QTLs were newly detected including one on LG4 that appears unrelated to seed size. Transfer of these new sources of bruchid resistance from V. nepalensis to azuki bean will be aided by the progress being made in azuki genome mapping.     

QTL analysis of intraspecific differences between two Silene vulgaris ecotypes

BACKGROUND AND AIMS: Serpentine soils provide a highly selective substrate for plant colonization and growth and represent an ideal system for studying the evolution of plant-ecotypes. In the present study the aim was to identify the genetic architecture of morphological traits distinguishing serpentine and non-serpentine ecotypes of Silene vulgaris. METHODS: Using an F(2) mapping population derived from an intraspecific cross between a serpentine and a non-serpentine ecotype of S. vulgaris, the genetic architecture of 12 morphological traits was explored using a quantitative trait locus (QTL) analysis. KEY RESULTS: The QTL analysis identified a total of 49 QTLs, of which 24 were classified as major QTLs. The mean number of QTLs per trait category was found to correspond well with numbers reported in the literature for similar crosses. Clustering of QTLs for different traits was found on several linkage groups. CONCLUSIONS: Morphological traits that differentiate the two ecotypes are strongly correlated, presumably as a consequence of the joint effects of extensive linkage of QTLs for different traits and directional selection. The signature of consistent directional selection was found for leaf and shoot trait divergence. Intraspecific ecotype differences in S. vulgaris were found to be distributed across the entire genome. The study shows that QTL analyses on non-model organisms can provide novel insights into the genetic basis of plant diversification.     

Identification of candidate gene regions in the rat by co-localization of QTLs for bone density, size, structure and strength

Susceptibility to osteoporotic fracture is influenced by genetic factors that can be dissected by whole-genome linkage analysis in experimental animal crosses. The aim of this study was to characterize quantitative trait loci (QTLs) for biomechanical and two-dimensional dual-energy X-ray absorptiometry (DXA) phenotypes in reciprocal F2 crosses between diabetic GK and normo-glycemic F344 rat strains and to identify possible co-localization with previously reported QTLs for bone size and structure. The biomechanical measurements of rat tibia included ultimate force, stiffness and work to failure while DXA was used to characterize tibial area, bone mineral content (BMC) and areal bone mineral density (aBMD). F2 progeny (108 males, 98 females) were genotyped with 192 genome-wide markers followed by sex- and reciprocal cross-separated whole-genome QTL analyses. Significant QTLs were identified on chromosome 8 (tibial area; logarithm of odds (LOD) = 4.7 and BMC; LOD = 4.1) in males and on chromosome 1 (stiffness; LOD = 5.5) in females. No QTLs showed significant sex-specific interactions. In contrast, significant cross-specific interactions were identified on chromosome 2 (aBMD; LOD = 4.7) and chromosome 6 (BMC; LOD = 4.8) for males carrying F344mtDNA, and on chromosome 15 (ultimate force; LOD = 3.9) for males carrying GKmtDNA, confirming the effect of reciprocal cross on osteoporosis-related phenotypes. By combining identified QTLs for biomechanical-, size- and qualitative phenotypes (pQCT and 3D CT) from the same population, overlapping regions were detected on chromosomes 1, 3, 4, 6, 8 and 10. These are strong candidate regions in the search for genetic risk factors for osteoporosis.     

Genetic resolution and verification of quantitative trait loci for flowering and plant height with recombinant inbred lines of maize.

Recombinant inbred (RI) lines offer several advantages for detecting quantitative trait loci (QTLs), including increased precision of trait measurements, power for detection of additive effects, and resolution of linked QTLs. This study was conducted to detect and characterize QTLs in maize for flowering and plant height and to compare QTL detection in an early (F2:3) generation of the same population. One hundred and eighty-six RIs from a cross between inbred lines Mo17 and H99 were evaluated in a replicated field experiment and analyzed at 101 loci detected by restriction fragment length polymorphisms. QTLs were identified by single-factor analysis of variance. A total of 59 QTLs were detected for plant height, ear height, top height, anthesis, silk emergence, and anthesis to silk interval. Individual QTLs explained 2.2-15.4% of trait variation, and multiple models including all QTLs detected for a trait explained up to 52.5% of the phenotypic variation. Comparison of QTLs detected with 150 F2:3 lines from the same population indicated that 16 (70%) of the 23 F2:3 QTLs were also observed in the F6:7 generation. Parental effects were consistent across generations. At 14 of the 16 QTLs detected in both generations, genetic effects were smaller in the F6:7. Also, some QTLs detected in the F2:3 were resolved into multiple linked QTLs in the F6:7, indicating the additional power of RI populations for mapping, with important implications for marker-assisted selection as well as map-based cloning of QTLs. Key words : Zea mays, RFLP, plant breeding, genetics, recombination.     

Nuclear-cytoplasmic interactions reduce male fertility in hybrids of Arabidopsis lyrata subspecies

We examined the level of postzygotic reproductive isolation in F(1) and F(2) hybrids of reciprocal crosses between the Arabidopsis lyrata subspecies lyrata (North American) and petraea (European). Our main results are: first, the percentage of fertile pollen was significantly reduced in the F(1) and F(2) compared to the parental populations. Second, mean pollen fertility differed markedly between reciprocal crosses: 84% in the F(2) with ssp. lyrata cytoplasm and 61% in the F(2) with ssp. petraea cytoplasm. Third, 17% of the F(2) with ssp. petraea cytoplasm showed male sterility (produced less than 30 pollen grains in our subsample). The hybrids were female fertile. We used QTL mapping to find the genomic regions that determine pollen fertility and that restore cytoplasmic male sterility (CMS). In the F(2) with ssp. lyrata cytoplasm, an epistatic pair of QTLs was detected. In the reciprocal F(2) progeny, four QTLs demonstrated within-population polymorphism for hybrid male sterility. In addition, in the F(2) with ssp. petraea cytoplasm, there was a strong male fertility restorer locus on chromosome 2 where a cluster of CMS restorer gene-related PPR genes have been found in A. lyrata. Our results underline the importance of cytonuclear interactions in understanding genetics of the early stages of speciation.     

Additive and additive × additive interaction make important contributions to spikelets per panicle in rice near isogenic (Oryza sativa L.) lines

Epistasis plays an important role in the genetic basis of rice yield traits. Taking interactions into account in breeding programs will help the development of high-yielding rice varieties. In this study, three sets of near isogenic lines (NILs) targeting three QTLs for spikelets per panicle (SPP), namely qSPP1, qSPP2 and qSPP7, which share the same Zhenshan 97 genetic background, were used to produce an F 2 population in which the three QTLs segregated simultaneously. The genotypes of the individual F 2 plants at the three QTLs were replaced with three markers that are closely linked to the corresponding QTLs. These QTLs were validated in the F 2 and F 3 popula- tions at the single marker level. qSPP7 exhibited major pleiotropic effects on SPP, plant height and heading date. Multifactor analysis of variance was performed for the F 2 population and its progeny. Additive × additive interaction between qSPP2 and qSPP7 had significant effects on SPP in both the F 2 population and its progeny. Both additive and additive × additive interactions could explain about 73% of the total SPP phenotypic variance. The SPP performance of 27 three-locus combinations was ranked and favorable combinations were rec- ommended for rice breeding in different ecosystems.     

High Resolution of Quantitative Traits into Multiple Loci via Interval Mapping

A very general method is described for multiple linear regression of a quantitative phenotype on genotype [putative quantitative trait loci (QTLs) and markers] in segregating generations obtained from line crosses. The method exploits two features, (a) the use of additional parental and F(1) data, which fixes the joint QTL effects and the environmental error, and (b) the use of markers as cofactors, which reduces the genetic background noise. As a result, a significant increase of QTL detection power is achieved in comparison with conventional QTL mapping. The core of the method is the completion of any missing genotypic (QTL and marker) observations, which is embedded in a general and simple expectation maximization (EM) algorithm to obtain maximum likelihood estimates of the model parameters. The method is described in detail for the analysis of an F(2) generation. Because of the generality of the approach, it is easily applicable to other generations, such as backcross progenies and recombinant inbred lines. An example is presented in which multiple QTLs for plant height in tomato are mapped in an F(2) progeny, using additional data from the parents and their F(1) progeny.     

Fine mapping of collagen-induced arthritis quantitative trait loci in an advanced intercross line

The generation of advanced intercross lines (AIL) is a powerful approach for high-resolution fine mapping of quantitative trait loci (QTLs), because they accumulate much more recombination events compared with conventional F2 intercross and N2 backcross. However, the application of this approach is severely hampered by the requirements of excessive resources to maintain such crosses, i.e., in terms of animal care, space, and time. Therefore, in this study, we produced an AIL to fine map collagen-induced arthritis (CIA) QTLs using comparatively limited resources. We used only 308 (DBA/1 x FVB/N)F11/12 AIL mice to refine QTLs controlling the severity and onset of arthritis as well as the Ab response and T cell subset in CIA, namely Cia2, Cia27, and Trmq3. These QTLs were originally identified in (DBA/1 x FVB/N)F2 progeny. The confidence intervals of the three QTLs were refined from 40, 43, and 48 Mb to 12, 4.1, and 12 Mb, respectively. The data were complemented by the use of another QTL fine-mapping approach, haplotype analysis, to further refine Cia2 into a 2-Mb genomic region. To aid in the search for candidate genes for the QTLs, genome-wide expression profiling was performed to identify strain-specific differentially expressed genes within the confidence intervals. Of the 1396 strain-specific differentially expressed genes, 3, 3, and 12 genes were within the support intervals of the Cia2, Cia27, and Trmq3, respectively. In addition, this study revealed that Cia27 and Trmq3 controlling anti-CII IgG2a Ab and CD4:CD8 T cell ratio, respectively, also regulated CIA clinical phenotypes.     

Isolation of a major genetic interaction associated with an extreme phenotype using assorted F2 populations in rice

Detection of quantitative trait loci (QTLs) is dependent on the materials used in the analysis, as different combinations of parental materials may lead to different outcomes in QTLs for the same trait. On the other hand, an extreme phenotype associated with a given trait implies the potential involvement of a particular allele in various allelic interactions. A genetic factor associated with such an extreme phenotype may frequently be identified from various genetic populations consisting of different parental combinations. In this study, we attempted to uncover the genetic factor associated with extremely early heading date in rice, using various F2 populations. Heading date in rice has been characterized by at least 19 QTLs, from which 12 genes have been identified. A58, a rice strain with an extremely early heading date, is adapted to Hokkaido, the northernmost limit of rice cultivation. Six F2 populations derived from crosses of A58 with six other strains displayed a range of heading dates. Genotyping using 19 QTL markers indicated that the A58 allele of the Ghd7 locus was present in most F2 individuals exhibiting extremely early heading dates. This analysis also demonstrated that when the wild-type Ehd1 allele was present, the Ghd7 allele from A58 accelerated floral induction. The results of this study demonstrate that assorted F2 populations are valuable materials for comprehensive genotyping to explore major genetic factors for extreme phenotypes, and that this methodology is broadly applicable to other unknown traits.     

Identification of cotton fiber quality quantitative trait loci using intraspecific crosses derived from two near-isogenic lines differing in fiber bundle strength

Cotton fiber properties are very important to the yarn quality. Modern high-speed textile operations around the world require long, strong and fine cotton fibers. The objective of this research was to identify stable fiber quantitative trait loci (QTLs) that could be used in cotton breeding through marker-assisted selection (MAS). Two cotton lines, MD90ne and MD52ne, are near-isogenic with significant differences in fiber properties, especially strength. Fiber samples from 734 progeny plants of two F2 populations (A and B) derived from crosses between MD90ne and MD52ne were collected at Stoneville, MS, USA in 2012. Fiber quality attributes were measured using a High Volume Instrument 1000. A simple sequence repeat (SSR) genetic linkage map with 165 loci covering 632.53 cM was constructed using population A, consisting of 356 F2 individuals and used for identifying QTLs related to fiber bundle strength (FBS), short fiber index (SFI) and upper-half mean fiber length (UHML). One QTL for FBS originating from the stronger fiber parent MD52ne was identified on chromosome (Chr.) 3. Three QTLs each for SFI and UHML were identified on Chrs. 3, 4 and 14 and Chrs. 3, 11 and 24, respectively. Population B, consisting of 378 F2 progeny, was used to confirm these QTLs by analyzing 57 SSR markers mapped on Chrs. 3, 14 and 24. Three QTLs—qFBS-c3, qSFI-c14 and qUHML-c24—were confirmed and appeared stable. These three QTLs could potentially be used in breeding to improve cotton fiber quality through a MAS strategy.     

Genome-wide association for methamphetamine sensitivity in an advanced intercross mouse line

Sensitivity to the locomotor stimulant effects of methamphetamine (MA) is a heritable trait that utilizes neurocircuitry also associated with the rewarding effects of drugs. We used the power of a C57BL/6J × DBA/2J F(2) intercross (n = 676) and the precision of a C57BL/6J × DBA/2J F(8) advanced intercross line (Aap: B6, D2-G8; or F(8) AIL; n = 552) to identify and narrow quantitative trait loci (QTLs) associated with sensitivity to the locomotor stimulant effects of MA. We used the program QTLRel to simultaneously map QTL in the F(2) and F(8) AIL mice. We identified six genome-wide significant QTLs associated with locomotor activity at baseline and seven genome-wide significant QTLs associated with MA-induced locomotor activation. The average per cent decrease in QTL width between the F(2) and the integrated analysis was 65%. Additionally, these QTLs showed a distinct temporal specificity within each session that allowed us to further refine their locations, and identify one QTL with a 1.8-LOD support interval of 1.47 Mb. Next, we utilized publicly available bioinformatics resources to exploit strain-specific sequence data and strain- and region-specific expression data to identify candidate genes. These results illustrate the power of AILs in conjunction with sequence and gene expression data to investigate the genetic underpinnings of behavioral and other traits.     

QTL analysis of fertility-restoration against cytoplasmic male sterility in wheat

The cytoplasm of Triticum timopheevi causes cytoplasmic male sterility (CMS) in common wheat (T. aestivum) cv. 'Chinese Spring' (CS), and that of Aegilops kotschyi causes CMS in spelt wheat (T. spelta) var. duhamelianum (Sp). CS has fertility-restoring (Rf) genes against the latter cytoplasm and Sp has the ones against the former. To know the genetic system concerning to CMS, we crossed 66 F8 recombinant inbred lines (RILs) derived from a cross between CS and Sp as males to the alloplasmic lines of CS and Sp having the cytoplasms of T. timopheevi and Ae. kotschyi, respectively. The fertilities of respective F1 plants derived from the crosses were examined for QTL analysis. The major QTLs detected in both systems were located on the short arm of chromosome 1B. One minor QTL on chromosome 2B was also commonly detected in both of the systems, while other minor QTLs against T timopheevi cytoplasm were distributed on the chromosomes 2A, 4B, and 6A.     

Approaches to interval mapping of QTL in a multigeneration pedigree: the example of porcine chromosome 4

Quantitative trait loci (QTLs) have been mapped in many studies of F2 populations derived from crosses between diverse lines. One approach to confirming these effects and improving the mapping resolution is genetic chromosome dissection through a backcrossing programme. Analysis by interval mapping of the data generated is likely to provide additional power and resolution compared with treating data marker by marker. However, interval mapping approaches for such a programme are not well developed, especially where the founder lines were outbred. We explore alternative approaches to analysis using, as an example, data from chromosome 4 in an intercross between wild boar and Large White pigs where QTLs have been previously identified. A least squares interval mapping procedure was used to study growth rate and carcass traits in a subsequent second backcross generation (BC2). This procedure requires the probability of inheriting a wild boar allele for each BC2 animal for locations throughout the chromosome. Two methods for obtaining these probabilities were compared: stochastic or deterministic. The two methods gave similar probabilities for inheriting wild boar alleles and, hence, gave very similar results from the QTL analysis. The deterministic approach has the advantage of being much faster to run but requires specialized software. A QTL for fatness and for growth were confirmed and, in addition, a QTL for piglet growth from weaning at 5 weeks up to 7 weeks of age and another for carcass length were detected.     

Chromosomal mapping of host resistance loci to Trichinella spiralis nematode infection in rats

The differences in host response among strains of rats to intestinal nematode parasite Trichinella spiralis infection could provide a powerful benefit for further elucidation of molecular interactions between the host and the parasite. Using several strains of rats, we previously observed that DA strain is a strong responder and F344 strain is a weak responder with respect to expulsion of the adult worm. To identify the host resistance loci, quantitative trait loci (QTLs) analysis in F2 population from crosses between DA and F344 strains was performed. One significant QTL (designated as Tspe) was mapped to the middle region of chromosome 9. In addition, the effect of DA allele at Tspe locus could act recessively and lead to the rejection of more adult worms from the gut. The results from the present study provide more insights on host–parasite interactions, which may be useful in facilitating the development of novel approaches for treatment and control of intestinal parasites in human and domestic livestock.