Quantitative Trait Loci Genotypes Research Articles

A Two-Stage Approximation for Analysis of Mixture Genetic Models in Large Pedigrees

Information from cosegregation of marker and QTL alleles, in addition to linkage disequilibrium (LD), can improve genomic selection. Variance components linear models have been proposed for this purpose, but accommodating dominance and epistasis is not straightforward with them. A full-Bayesian analysis of a mixture genetic model is favorable in this respect, but is computationally infeasible for whole-genome analyses. Thus, we propose an approximate two-step approach that neglects information from trait phenotypes in inferring ordered genotypes and segregation indicators of markers. Quantitative trait loci (QTL) fine-mapping scenarios, using high-density markers and pedigrees of five generations without genotyped females, were simulated to test this strategy against an exact full-Bayesian approach. The latter performed better in estimating QTL genotypes, but precision of QTL location and accuracy of genomic breeding values (GEBVs) did not differ for the two methods at realistically low LD. If, however, LD was higher, the exact approach resulted in a slightly higher accuracy of GEBVs. In conclusion, the two-step approach makes mixture genetic models computationally feasible for high-density markers and large pedigrees. Furthermore, markers need to be sampled only once and results can be used for the analysis of all traits. Further research is needed to evaluate the two-step approach for complex pedigrees and to analyze alternative strategies for modeling LD between QTL and markers.

Transcriptome Profiling of Embryonic Development Rate in Rainbow Trout Advanced Backcross Introgression Lines

In rainbow trout (Oncorhynchus mykiss) and other fishes, embryonic development rate is an ecologically and evolutionarily important trait that is closely associated with survival and physiological performance later in life. To identify genes differentially regulated in fast and slow-developing embryos of rainbow trout, we examined gene expression across developmental time points in rainbow trout embryos possessing alleles linked to a major quantitative trait loci (QTL) for fast versus slow embryonic development rate. Whole genome expression microarray analyses were conducted using embryos from a fourth generation backcross family, whereby each backcross generation involved the introgression of the fast-developing alleles for a major development rate QTL into a slow-developing clonal line of rainbow trout. Embryos were collected at 15, 19, and 28days post-fertilization; sex and QTL genotype were determined using molecular markers, and cDNA from 48 embryos were used for microarray analysis. A total of 183 features were identified with significant differences between embryonic development rate genotypes. Genes associated with cell cycle growth, muscle contraction and protein synthesis were expressed significantly higher in embryos with the fast-developing allele (Clearwater) than those with the slow-developing allele (Oregon State University), which may associate with fast growth and early body mass construction in embryo development. Across time points, individuals with the fast-developing QTL allele appeared to have earlier onset of these developmental processes when compared to individuals with the slow development alleles, even as early as 15days post-fertilization. Differentially expressed candidate genes chosen for linkage mapping were localized primarily to regions outside of the major embryonic development rate QTL, with the exception of a single gene (very low-density lipoprotein receptor precursor).

Using molecular classification to predict gains in maximal aerobic capacity following endurance exercise training in humans

A low maximal oxygen consumption (VO2max) is a strong risk factor for premature mortality. Supervised endurance exercise training increases VO2max with a very wide range of effectiveness in humans. Discovering the DNA variants that contribute to this heterogeneity typically requires substantial sample sizes. In the present study, we first use RNA expression profiling to produce a molecular classifier that predicts VO2max training response. We then hypothesized that the classifier genes would harbor DNA variants that contributed to the heterogeneous VO2max response. Two independent preintervention RNA expression data sets were generated (n=41 gene chips) from subjects that underwent supervised endurance training: one identified and the second blindly validated an RNA expression signature that predicted change in VO2max ("predictor" genes). The HERITAGE Family Study (n=473) was used for genotyping. We discovered a 29-RNA signature that predicted VO2max training response on a continuous scale; these genes contained approximately 6 new single-nucleotide polymorphisms associated with gains in VO2max in the HERITAGE Family Study. Three of four novel candidate genes from the HERITAGE Family Study were confirmed as RNA predictor genes (i.e., "reciprocal" RNA validation of a quantitative trait locus genotype), enhancing the performance of the 29-RNA-based predictor. Notably, RNA abundance for the predictor genes was unchanged by exercise training, supporting the idea that expression was preset by genetic variation. Regression analysis yielded a model where 11 single-nucleotide polymorphisms explained 23% of the variance in gains in VO2max, corresponding to approximately 50% of the estimated genetic variance for VO2max. In conclusion, combining RNA profiling with single-gene DNA marker association analysis yields a strongly validated molecular predictor with meaningful explanatory power. VO2max responses to endurance training can be predicted by measuring a approximately 30-gene RNA expression signature in muscle prior to training. The general approach taken could accelerate the discovery of genetic biomarkers, sufficiently discrete for diagnostic purposes, for a range of physiological and pharmacological phenotypes in humans.

Altered placental expression of PAPPA2 does not affect birth weight in mice

BackgroundPregnancy-associated plasma protein A2 (PAPPA2) is an insulin-like growth factor binding protein (IGFBP) protease expressed in the placenta and upregulated in pregnancies complicated by pre-eclampsia. The mechanism linking PAPPA2 expression and pre-eclampsia and the consequences of altered PAPPA2 expression remain unknown. We previously identified PAPPA2 as a candidate gene for a quantitative trait locus (QTL) affecting growth in mice and in the present study examined whether this QTL affects placental PAPPA2 expression and, in turn, placental or embryonic growth.MethodsUsing a line of mice that are genetically homogenous apart from a 1 megabase QTL region containing the PAPPA2 gene, we bred mice homozygous for alternate QTL genotypes and collected and weighed placentae and embryos at E12.5. We used quantitative RT-PCR to measure the mRNA levels of PAPPA2, as well as mRNA levels of IGFBP-5 (PAPPA2's substrate), and PAPPA (a closely related IGFBP protease) to examine potential feedback and compensation effects. Western blotting was used to quantify PAPPA2 protein. Birth weight was measured in pregnancies allowed to proceed to parturition.ResultsPAPPA2 mRNA and protein expression levels in the placenta differed by a factor of 2.5 between genotypes, but we did not find a significant difference between genotypes in embryonic PAPPA2 mRNA levels. Placental IGFBP-5 and PAPPA mRNA expression levels were not altered in response to PAPPA2 levels, and we could not detect IGFBP-5 protein in the placenta by Western blotting. The observed difference in placental PAPPA2 expression had no significant effect on placental or embryonic mass at mid-gestation, birth weight or litter size.ConclusionsDespite a significant difference between genotypes in placental PAPPA2 expression similar in magnitude to the difference between pre-eclamptic and normal placentae previously reported, we observed no difference in embryonic, placental or birth weight. Our results suggest that elevated PAPPA2 levels are a consequence, rather than a cause, of pregnancy complications.

Combined expression patterns of QTL-linked candidate genes best predict thermotolerance in Drosophila melanogaster

Knockdown resistance to high temperature (KRHT) is a thermal adaptation trait in Drosophila melanogaster. Here we used quantitative real-time PCR (qRT-PCR) to test for possible associations between KRHT and the expression of candidate genes within quantitative trait loci (QTL) in eight recombinant inbred lines (RIL). hsp60 and hsc70-3 map within an X-linked QTL, while CG10383, catsup, ddc, trap1, and cyp6a13 are linked in a KRHT-QTL on chromosome 2. hsc70-3 expression increased by heat-hardening. Principal Components analysis revealed that catsup, ddc and trap1 were either co-expressed or combined in their expression levels. This composite expression variable (e-PC1) was positively associated to KRHT in non-hardened RIL. In heat-hardened flies, hsp60 was negatively related to hsc70-3 on e-PC2, with effects on KRHT. These results are consistent with the notion that QTL can be shaped by expression variation in combined candidate loci. We found composite variables of gene expression (e-PCs) that best correlated to KRHT. Network effects with other untested linked loci are apparent because, in spite of their associations with KRHT phenotypes, e-PCs were sometimes uncorrelated with their QTL genotype.

A comprehensive analysis of QTL for abdominal fat and breast muscle weights on chicken chromosome 5 using a multivariate approach

Quantitative trait loci (QTL) influencing the weight of abdominal fat (AF) and of breast muscle (BM) were detected on chicken chromosome 5 (GGA5) using two successive F(2) crosses between two divergently selected 'Fat' and 'Lean' INRA broiler lines. Based on these results, the aim of the present study was to identify the number, location and effects of these putative QTL by performing multitrait and multi-QTL analyses of the whole available data set. Data concerned 1186 F(2) offspring produced by 10 F(1) sires and 85 F(1) dams. AF and BM traits were measured on F(2) animals at slaughter, at 8 (first cross) or 9 (second cross) weeks of age. The F(0), F(1) and F(2) birds were genotyped for 11 microsatellite markers evenly spaced along GGA5. Before QTL detection, phenotypes were adjusted for the fixed effects of sex, F(2) design, hatching group within the design, and for body weight as a covariable. Univariate analyses confirmed the QTL segregation for AF and BM on GGA5 in male offspring, but not in female offspring. Analyses of male offspring data using multitrait and linked-QTL models led us to conclude the presence of two QTL on the distal part of GGA5, each controlling one trait. Linked QTL models were applied after correction of phenotypic values for the effects of these distal QTL. Several QTL for AF and BM were then discovered in the central region of GGA5, splitting one large QTL region for AF into several distinct QTL. Neither the 'Fat' nor the 'Lean' line appeared to be fixed for any QTL genotype. These results have important implications for prospective fine mapping studies and for the identification of underlying genes and causal mutations.

Confirmation and fine-mapping of a major QTL for resistance to infectious pancreatic necrosis in Atlantic salmon (Salmo salar): population-level associations between markers and trait.

BackgroundInfectious pancreatic necrosis (IPN) is one of the most prevalent and economically devastating diseases in Atlantic salmon (Salmo salar) farming worldwide. The disease causes large mortalities at both the fry- and post-smolt stages. Family selection for increased IPN resistance is performed through the use of controlled challenge tests, where survival rates of sib-groups are recorded. However, since challenge-tested animals cannot be used as breeding candidates, within-family selection is not performed and only half of the genetic variation for IPN resistance is being exploited. DNA markers linked to quantitative trait loci (QTL) affecting IPN resistance would therefore be a powerful selection tool. The aim of this study was to identify and fine-map QTL for IPN-resistance in Atlantic salmon, for use in marker-assisted selection to increase the rate of genetic improvement for this trait.ResultsA genome scan was carried out using 10 large full-sib families of challenge-tested Atlantic salmon post-smolts and microsatellite markers distributed across the genome. One major QTL for IPN-resistance was detected, explaining 29% and 83% of the phenotypic and genetic variances, respectively. This QTL mapped to the same location as a QTL recently detected in a Scottish Atlantic salmon population. The QTL was found to be segregating in 10 out of 20 mapping parents, and subsequent fine-mapping with additional markers narrowed the QTL peak to a 4 cM region on linkage group 21. Challenge-tested fry were used to show that the QTL had the same effect on fry as on post-smolt, with the confidence interval for QTL position in fry overlapping the confidence interval found in post-smolts. A total of 178 parents were tested for segregation of the QTL, identifying 72 QTL-heterozygous parents. Genotypes at QTL-heterozygous parents were used to determine linkage phases between alleles at the underlying DNA polymorphism and alleles at single markers or multi-marker haplotypes. One four-marker haplotype was found to be the best predictor of QTL alleles, and was successfully used to deduce genotypes of the underlying polymorphism in 72% of the parents of the next generation within a breeding nucleus. A highly significant population-level correlation was found between deduced alleles at the underlying polymorphism and survival of offspring groups in the fry challenge test, parents with the three deduced genotypes (QQ, Qq, qq) having mean offspring mortality rates of 0.13, 0.32, and 0.49, respectively. The frequency of the high-resistance allele (Q) in the population was estimated to be 0.30. Apart from this major QTL, one other experiment-wise significant QTL for IPN-resistance was detected, located on linkage group 4.ConclusionThe QTL confirmed in this study represents a case of a major gene explaining the bulk of genetic variation for a presumed complex trait. QTL genotypes were deduced within most parents of the 2005 generation of a major breeding company, providing a solid framework for linkage-based MAS within the whole population in subsequent generations. Since haplotype-trait associations valid at the population level were found, there is also a potential for MAS based on linkage disequilibrium (LD). However, in order to use MAS across many generations without reassessment of linkage phases between markers and the underlying polymorphism, the QTL needs to be positioned with even greater accuracy. This will require higher marker densities than are currently available.

Searching for interacting QTL in related populations of an outbreeding species

Many important crop species are outbreeding. In outbreeding species the search for genes affecting traits is complicated by the fact that in a single cross up to four alleles may be present at each locus. This paper is concerned with the search for interacting quantitative trait loci (QTL) in populations which have been obtained by crossing a number of parents. It will be assumed that the parents are unrelated, but the methods can be extended easily to allow a pedigree structure. The approach has two goals: (1) finding QTL that are interacting with other loci and also loci which behave additively; (2) finding parents which segregate at two or more interacting QTL. Large populations obtained by crossing these parents can be used to study interactions in detail. QTL analysis is carried out by means of regression on predictions of QTL genotypes.

Incorporation of Discrete Genotype Effects for Multiple Genes into Animal Model Evaluations when only a Small Fraction of the Population Has Been Genotyped

An efficient algorithm is described for marker-assisted selection appropriate for large populations, even though only a small fraction of the population is genotyped. Genotype probabilities for specific loci are computed for all animals without genotypes. Effects of the quantitative trait loci (QTL) are then estimated by a “cow model” and the appropriate effects are subtracted from the cows’ records. Selection is based on genetic evaluations computed from the adjusted records after addition of each animal's QTL genotype effect. The proposed scheme was applied to 10 simulated populations of 37,000 cows generated over 30 yr and compared with a selection scheme based on a standard animal model. Two diallelic QTL with substitution effects of 0.5 and 0.32 phenotypic standard deviations were simulated with initial frequencies of 0.5 for both alleles. Means and standard errors of estimates of the QTL effects at yr 30 were 0.498±0.011 and 0.347±0.008. Thus, estimation of the larger QTL was nearly exact, whereas the smaller QTL was slightly overestimated. At yr 9 through 12 after the beginning of the breeding program, genetic gain in the marker-assisted selection scheme was 0.17 standard deviations greater than the standard scheme. This corresponds to nearly 2 yr of genetic progress relative to the standard scheme, or more than 40% of the total genetic gain obtained by the standard scheme at yr 9. Although genetic gain of the 2 schemes was nearly equal by yr 30, the Gibson effect of eventual greater progress by trait-based selection was not observed. Extension of the methods proposed in the current study could be applied to rank sires accurately including both marker and pedigree information for the large number of segregating QTL that will be detected by whole-genome single nucleotide polymorphism scans.

On the detection of imprinted quantitative trait loci in line crosses: effect of linkage disequilibrium.

Imprinted quantitative trait loci (QTL) are commonly reported in studies using line-cross designs, especially in livestock species. It was previously shown that such parent-of-origin effects might result from the nonfixation of QTL alleles in one or both parental lines, rather than from genuine molecular parental imprinting. We herein demonstrate that if linkage disequilibrium exists between marker loci and nonfixed QTL, spurious detection of pseudo-imprinting is increased by an additional 40-80% in scenarios mimicking typical livestock situations. This is due to the fact that imprinting can be tested only in F(2) offspring whose sire and dam have distinct marker genotypes. In the case of linkage disequilibrium between markers and QTL, such parents have a higher chance to have distinct QTL genotypes as well, thus resulting in distinct padumnal and madumnal allele substitution effects, i.e., QTL pseudo-imprinting.

Selection on multiple QTL with control of gene diversity and inbreeding for long‐term benefit

The purpose of this study was to develop and investigate selection strategies that aim at maximizing long-term genetic response while conserving gene diversity and controlling inbreeding in populations of limited effective size, assuming complete knowledge of all genes affecting a quantitative trait. Three selection strategies were proposed to select on 100 quantitative trait loci (QTL) and compared with truncation selection on breeding value. Alternative selection strategies aimed at maximizing the average breeding value of parents with a penalty on (1) the number of unfavourable QTL genotypes among parents (OS-I), (2) the negative of the logarithm of the frequency of the favourable allele at each QTL among parents (OS-II), and (3) the average pedigree relationship among parents (OS-III). When all QTL and their effects were known, the strategies examined were able to obtain extra long-term responses, conserve QTL diversity and reduce inbreeding, compared with truncation selection. Strategy OS-II was the most effective in conserving QTL diversity and OS-III in reducing inbreeding. By changing the magnitude of the penalties applied, the impact on long-term response, inbreeding and diversity can be controlled. Extra long-term responses over truncation selection of OS-I and OS-II were even greater when effects of QTL were estimated rather than assumed known, indicating the applicability of results to practical strategies for marker-assisted selection. Extra responses are expected to be reduced for larger population sizes.

A statistical model for the identification of genes governing the incidence of cancer with age

The cancer incidence increases with age. This epidemiological pattern of cancer incidence can be attributed to molecular and cellular processes of individual subjects. Also, the incidence of cancer with ages can be controlled by genes. Here we present a dynamic statistical model for explaining the epidemiological pattern of cancer incidence based on individual genes that regulate cancer formation and progression. We incorporate the mathematical equations of age-specific cancer incidence into a framework for functional mapping aimed at identifying quantitative trait loci (QTLs) for dynamic changes of a complex trait. The mathematical parameters that specify differences in the curve of cancer incidence among QTL genotypes are estimated within the context of maximum likelihood. The model provides testable quantitative hypotheses about the initiation and duration of genetic expression for QTLs involved in cancer progression. Computer simulation was used to examine the statistical behavior of the model. The model can be used as a tool for explaining the epidemiological pattern of cancer incidence.

Combining classical trait and microarray data to dissect transcriptional regulation: a case study

The selective transcriptional profiling approach involves selecting an optimal subset of individuals to microarray from a larger set of individuals for which relatively inexpensive quantitative trait and molecular marker data are available. The goal of the selection and subsequent analyses is to identify genes whose expression is associated with a quantitative trait or quantitative trait locus (QTL). In this paper, we applied the selective transcriptional profiling approach to data sets concerning flowering time and gene transcription levels of Arabidopsis recombinant inbred lines. Our results confirm that the selective transcriptional profiling approach can achieve much greater power for uncovering associations than standard approaches that ignore information from classical traits. In addition, we show that selective transcriptional profiling can achieve power similar to standard approaches at a fraction of the cost and effort. We also identified three groups of genes which show distinctive patterns with regard to gene expression levels, QTL genotype, and a classical trait. This study represents the first application of selective transcriptional profiling to real data and serves as a template for dissecting gene regulation networks related to a classical trait using the selective transcriptional profiling approach.

Genomic selection

SummaryGenomic selection is a form of marker‐assisted selection in which genetic markers covering the whole genome are used so that all quantitative trait loci (QTL) are in linkage disequilibrium with at least one marker. This approach has become feasible thanks to the large number of single nucleotide polymorphisms (SNP) discovered by genome sequencing and new methods to efficiently genotype large number of SNP. Simulation results and limited experimental results suggest that breeding values can be predicted with high accuracy using genetic markers alone but more validation is required especially in samples of the population different from that in which the effect of the markers was estimated. The ideal method to estimate the breeding value from genomic data is to calculate the conditional mean of the breeding value given the genotype of the animal at each QTL. This conditional mean can only be calculated by using a prior distribution of QTL effects so this should be part of the research carried out to implement genomic selection. In practice, this method of estimating breeding values is approximated by using the marker genotypes instead of the QTL genotypes but the ideal method is likely to be approached more closely as more sequence and SNP data is obtained. Implementation of genomic selection is likely to have major implications for genetic evaluation systems and for genetic improvement programmes generally and these are discussed.

Reciprocal Congenic Lines of Mice Capture the Aliq1 Effect on Acute Lung Injury Survival Time

Acute lung injury (ALI) is a devastating condition resulting from diverse causes. Genetic studies of human populations indicate that ALI is a complex disease with substantial phenotypic variance, incomplete penetrance, and gene-environment interactions. To identify genes controlling ALI mortality, we previously investigated mean survival time (MST) differences between sensitive A/J (A) and resistant C57BL/6J (B) mice in ozone using quantitative trait locus (QTL) analysis. MST was significantly linked to QTLs (Aliq1-3) on chromosomes 11, 13, and 17, respectively. Additional QTL analyses of separate and combined backcross and F(2) populations supported linkage to Aliq1 and Aliq2, and established significance for previously suggestive QTLs on chromosomes 7 and 12 (named Aliq5 and Aliq6, respectively). Decreased MSTs of corresponding chromosome substitution strains (CSSs) verified the contribution of most QTL-containing chromosomes to ALI survival. Multilocus models demonstrated that three QTLs could explain the MST difference between progenitor strains, agreeing with calculated estimates for number of genes involved. Based on results of QTL genotype analysis, a double CSS (B.A-6,11) was generated that contained Aliq1 and Aliq4 chromosomes. Surprisingly, MST and pulmonary edema after exposure of B.A-6,11 mice were comparable to B mice, revealing an unpredicted loss of sensitivity compared with separate CSSs. Reciprocal congenic lines for Aliq1 captured the corresponding phenotype in both background strains and further refined the QTL interval. Together, these findings support most of the previously identified QTLs linked to ALI survival and established lines of mice to further resolve Aliq1.

Educational Software for Mapping Quantitative Trait Loci (QTL)

This educational software was developed to aid teachers and students in their understanding of how the process of identifying the most likely quantitative trait loci (QTL) position is determined between two flanking DNA markers. The objective of the software that we developed was to: (1) show how a QTL is mapped to a position on a chromosome using a hands-on approach; (2) show how varying the guessed position of the QTL changes the mixture of QTL genotypes within each marker class. A least squares approach was used to determine the F statistic associated with each guessed QTL position between the flanking DNA markers. When the F statistic reaches a maximum value, the correct position of the QTL has been identified. The instructor identifies the true position of the QTL, while the students enter a guess as to the QTL position between flanking markers. The histograms generated by the software show the discrepancy between the true and guessed mixture of QTL genotypes within each of the nine marker classes. The output also shows how the design matrix and test statistic change as the guessed QTL position is altered. This software will aid the instructor in explaining how a QTL is mapped. Students will learn to associate the degree of recombination between markers and the QTL with resulting magnitude of the F statistic.

Semiparametric Methods for Mapping Quantitative Trait Loci with Censored Data

Statistical methods for the detection of genes influencing quantitative traits with the aid of genetic markers are well developed for normally distributed, fully observed phenotypes. Many experiments are concerned with failure-time phenotypes, which have skewed distributions and which are usually subject to censoring because of random loss to follow-up, failures from competing causes, or limited duration of the experiment. In this article, we develop semiparametric statistical methods for mapping quantitative trait loci (QTLs) based on censored failure-time phenotypes. We formulate the effects of the QTL genotype on the failure time through the Cox (1972, Journal of the Royal Statistical Society, Series B 34, 187-220) proportional hazards model and derive efficient likelihood-based inference procedures. In addition, we show how to assess statistical significance when searching several regions or the entire genome for QTLs. Extensive simulation studies demonstrate that the proposed methods perform well in practical situations. Applications to two animal studies are provided.

Mixture model equations for marker‐assisted genetic evaluation

Marker-assisted genetic evaluation needs to infer genotypes at quantitative trait loci (QTL) based on the information of linked markers. As the inference usually provides the probability distribution of QTL genotypes rather than a specific genotype, marker-assisted genetic evaluation is characterized by the mixture model because of the uncertainty of QTL genotypes. It is, therefore, necessary to develop a statistical procedure useful for mixture model analyses. In this study, a set of mixture model equations was derived based on the normal mixture model and the EM algorithm for evaluating linear models with uncertain independent variables. The derived equations can be seen as an extension of Henderson's mixed model equations to mixture models and provide a general framework to deal with the issues of uncertain incidence matrices in linear models. The mixture model equations were applied to marker-assisted genetic evaluation with different parameterizations of QTL effects. A sire-QTL-effect model and a founder-QTL-effect model were used to illustrate the application of the mixture model equations. The potential advantages of the mixture model equations for marker-assisted genetic evaluation were discussed. The mixed-effect mixture model equations are flexible in modelling QTL effects and show desirable properties in estimating QTL effects, compared with Henderson's mixed model equations.

Fine-mapping milk production quantitative trait loci on BTA6: analysis of the bovine osteopontin gene.

Bovine chromosome six (BTA6) harbors up to six quantitative trait loci (QTL) influencing the milk production of dairy cattle. In stark contrast to human, there is long-range linkage disequilibrium in dairy cattle, which has previously made it difficult to identify the mutations underlying these QTL. Using 38 microsatellite markers in a pedigree of 3,147 Holstein bulls, we fine mapped regions of BTA6 that had previously been shown to harbor QTL. Next, we sequenced a 12.3-kb region harboring Osteopontin, a positional candidate for the statistically most significant of the identified QTL. Nine mutations were identified, and only genotypes for the OPN3907 indel were concordant with the QTL genotypes of eight bulls that were established by segregation analysis. Four of these mutations were genotyped, and a joint linkage/linkage disequilibrium mapping analysis was used to demonstrate the existence of only two functionally distinct clusters of haplotypes within the QTL region, which were uniquely defined by OPN3907 alleles. We estimate a probability of 0.40 that no other mutation within this region is concordant with the QTL genotypes of these eight bulls. Finally, we demonstrate that the motif harboring OPN3907, which is upstream of the promoter and within a region known to harbor tissue-specific osteopontin regulatory elements, is moderately conserved among mammals. The motif was not retrieved from database queries and may be a novel regulatory element.

QTL-based analysis of leaf senescence in an indica/japonica hybrid in rice (Oryza sativa L.)

In order to identify quantitative trait loci (QTLs) for leaf senescence and related traits in rice (Oryza sativa L.), we developed two backcross populations, indica/japonica// japonica and indica/japonica//indica, using IR36 as the indica parent and Nekken-2 as the japonica parent. The QTLs were mapped using a set of simple sequence-repeat markers (SSRs) in the BC(1)F(1) population. Senescence was characterized in these plants by measuring the leaf chlorophyll content 25 days after flowering (DAF), the reduction in chlorophyll content (the difference between the chlorophyll content at flowering and at 25 DAF), and the number of late-discoloring leaves per panicle at 25 DAF in five plants from each BC(1)F(2) line. These plants were moved into a temperature-controlled growth cabinet at the time of flowering and allowed to mature under identical conditions. Eleven QTLs were detected in the two populations. The major of QTLs for senescence were found on the short arm of chromosome 6 and on the long arm of chromosome 9. Of these, one QTL on chromosome 6 and two on chromosome 9 were verified by confirming the effects of the genotypes on the phenotypes of the BC(1)F(3) lines. The japonica parent was found to contribute to late senescence at all but one QTL. Based on a comparison of the effects of heterozygotes and homozygotes on the phenotypic values of each QTL genotype, we concluded that the differential senescence observed in the indica-japonica hybrid was not due to over-dominance; rather, it was the result of partial-dominance genes that were donated from either of the parents.