Identification of quantitative trait loci influencing wood specific gravity in an outbred pedigree of loblolly pine

We report the identification of quantitative trait loci (QTL) influencing wood specific gravity (WSG) in an outbred pedigree of loblolly pine (Pinus taeda L.). QTL mapping in an outcrossing species is complicated by the presence of multiple alleles (> 2) at QTL and marker loci. Multiple alleles at QTL allow the examination of interaction among alleles at QTL (deviation from additive gene action). Restriction fragment length polymorphism (RFLP) marker genotypes and wood specific gravity phenotypes were determined for 177 progeny. Two RFLP linkage maps were constructed, representing maternal and paternal parent gamete segregations as inferred from diploid progeny RFLP genotypes. RFLP loci segregating for multiple alleles were vital for aligning the two maps. Each RFLP locus was assayed for cosegregation with WSG QTL using analysis of variance (ANOVA). Five regions of the genome contained one or more RFLP loci showing differences in mean WSG at or below the P = 0.05 level for progeny as grouped by RFLP genotype. One region contained a marker locus (S6a) whose QTL-associated effects were highly significant (P > 0.0002). Marker S6a segregated for multiple alleles, a prerequisite for determining the number of alleles segregating at the linked QTL and analyzing the interactions among QTL alleles. The QTL associated with marker S6a appeared to be segregating for multiple alleles which interacted with each other and with environments. No evidence for digenic epistasis was found among the five QTL.     

A two-stage half-sib design for mapping quantitative trait loci in food animals

Daughter and granddaughter half-sib designs for mapping quantitative trait loci were modified to increase experimental power. This new design includes a two-stage procedure, in contrast to conventional one-step half-sib designs. In stage 1, a few progeny of each sire are genotyped for marker loci. Based on the analyses of stage 1 data, some sires are chosen to continue genotyping more progeny for stage 2. When multiple chromosomes are under investigation, chromosomes and sires for stage 2 are selected based on the analysis of stage 1 data. Sire selection results in increased frequency of heterozygous genotypes of interest in stage 2 if the markers are linked to those genes. Chromosome selection can increase the proportion of chromosomes with segregating quantitative trait loci in stage 2 if not all of the chromosomes evaluated in stage 1 have segregating quantitative trait loci. Numerical results indicated that two-stage half-sib designs are generally more powerful than conventional designs when 1) the noncentrality parameter is moderate or larger, 2) larger quantitative trait loci are mapped using tightly linked markers in larger families, and 3) variation is large in numbers and sizes of segregating quantitative trait loci among the chromosomes evaluated in stage 1.     

Estimation of effects of quantitative trait loci in large complex pedigrees

A method was derived to estimate effects of quantitative trait loci (QTL) using incomplete genotype information in large outbreeding populations with complex pedigrees. The method accounts for background genes by estimating polygenic effects. The basic equations used are very similar to the usual linear mixed model equations for polygenic models, and segregation analysis was used to estimate the probabilities of the QTL genotypes for each animal. Method R was used to estimate the polygenic heritability simultaneously with the QTL effects. Also, initial allele frequencies were estimated. The method was tested in a simulated data set of 10,000 animals evenly distributed over 10 generations, where 0, 400 or 10,000 animals were genotyped for a candidate gene. In the absence of selection, the bias of the QTL estimates was < 2%. Selection biased the estimate of the Aa genotype slightly, when zero animals were genotyped. Estimates of the polygenic heritability were 0.251 and 0.257, in absence and presence of selection, respectively, while the simulated value was 0.25. Although not tested in this study, marker information could be accommodated by adjusting the transmission probabilities of the genotypes from parent to offspring according to the marker information. This renders a QTL mapping study in large multi-generation pedigrees possible.     

Quantitative trait loci (QTL) analyses and alcohol-related behaviors

Recombinant inbred (RI) strains can make an important contribution toward the merger of molecular genetics and quantitative genetics in the quest for quantitative trait loci (QTL). We present preliminary analyses of alcohol-related processes from our ongoing research using the BXD RI series. Issues concerning reliability, genetic correlations, and RI QTL analysis are discussed. Several strategies for replication and extension of QTL candidate regions are considered: F1 crosses between RI strains, F2 crosses, heterogeneous stock, interspecific backcrosses, QTL selection, and the use of murine QTL in chromosomal regions syntenic to human chromosomes as candidate chromosomal regions for human QTL.     

Analytical and clinical performance of an automated immunoassay system (Immulite) for estradiol in serum

Mouse strains congenic for individual quantitative trait loci (QTLs) conferring hypnotic sensitivity to ethanol were constructed by backcrossing genotypically selected ILS x ISS N2 individuals to either inbred Long Sleep (ILS) or inbred Short Sleep (ISS) mice. We used a novel "speed congenic" approach in which N2 mice were genotyped for markers flanking each of the five originally identified QTLs. Genotypic selection for ISS regions at four of the five QTLs, and for ILS/ISS at the fifth QTL, allowed rapid fixation of the genetic background. We call this strategy "QTL-Marker-Assisted Counter Selection" or QMACS. By the N4 generation, phenotypic assessments showed that in some sublines the QTL had not been captured; these sublines were discarded and positive lines split to create new replicate sublines. One QTL, on Chromosome (Chr) 8, was not confirmed. At the N8, virtually all sublines on the remaining QTLs retained the phenotypic difference between heterozygotes and ISS homozygotes. Small numbers of interim congenics were produced at the N6 and later generations in which the ILS QTL was made homozygous on the ISS background; as expected, these congenic mice showed an increased sleep time. For later backcrosses (after the N4), the parents were selected on the basis of phenotype as well as genotype. The parent-offspring correlation over all QTLs was significant, supporting the use of phenotypic selection in congenic construction.     

Genetic response from marker assisted selection in an outbred population for differing marker bracket sizes and with two identified quantitative trait loci

Effect of flanking quantitative trait loci (QTL)-marker bracket size on genetic response to marker assisted selection in an outbred population was studied by simulation of a nucleus breeding scheme. In addition, genetic response with marker assisted selection (MAS) from two quantitative trait loci on the same and different chromosome(s) was investigated. QTL that explained either 5% or 10% of phenotypic variance were simulated. A polygenic component was simulated in addition to the quantitative trait loci. In total, 35% of the phenotypic variance was due to genetic factors. The trait was measured on females only. Having smaller marker brackets flanking the QTL increased the genetic response from MAS selection. This was due to the greater ability to trace the QTL transmission from one generation to the next with the smaller flanking QTL-marker bracket, which increased the accuracy of estimation of the QTL allelic effects. Greater negative covariance between effects at both QTL was observed when two QTL were located on the same chromosome compared to different chromosomes. Genetic response with MAS was greater when the QTL were on the same chromosome in the early generations and greater when they were on different chromosomes in the later generations of MAS.     

Negative regulation of transcription by anti-sigma factors

The identification, mapping and eventual cloning of genes which determine or influence important epidemiological traits in parasites can have great benefits for the control of parasitic disease. In this review, strategies are outlined for identifying genetic markers for complex, quantitative traits. A genetic marker is a variable DNA sequence which co-occurs with a variable quantitative trait. Candidate markers are chosen because they are thought to directly influence the trait whereas random markers are expected to be linked to another DNA sequence which influences the trait. Association studies compare the value of a quantitative trait between different marker genotype classes in a population, without regard to family structure. Linkage studies compare the value of a quantitative trait between marker genotype classes within families or within a population (usually derived from a cross between inbred lines) which is segregating for both marker and quantitative trait loci. The most commonly used analytical methods for determining the significance of association or linkage between marker and quantitative trait loci, and for estimating parameters such as recombination rate and quantitative gene action, are least-squares and maximum likelihood. Both methods may be used to test either single markers or the interval between flanking markers, and both suffer from the need to minimize type I and type II error rates with multiple tests.     

Molecular dissection of developmental behavior of plant height in rice (Oryza sativa L.)

A doubled haploid population of 123 lines from IR64/Azucena was used to dissect the developmental behavior and genotype by environment interaction for plant height by conditional and unconditional quantitative trait loci (QTL) mapping methods in rice. It was shown that the number of QTL detected was different at various measuring stages. Some QTL could be detected at all stages and some only at one or several stages. More QTL could be found on the basis of time-dependent measures of different stages. By conditional QTL mapping of time-dependent measures, it is possible to reveal dynamic gene expression for quantitative traits. Mapping QTL for genetic main effects and GE interaction effects could help us in understanding the nature of QTL x environment interaction for the development of quantitative traits.     

Quantitative trait loci affecting differences in floral morphology between two species of monkeyflower (Mimulus)

Conspicuous differences in floral morphology are partly responsible for reproductive isolation between two sympatric species of monkeyflower because of their effect on visitation of the flowers by different pollinators. Mimulus lewisii flowers are visited primarily by bumblebees, whereas M. cardinalis flowers are visited mostly by hummingbirds. The genetic control of 12 morphological differences between the flowers of M. lewisii and M. cardinalis was explored in a large linkage mapping population of F2 plants n = 465 to provide an accurate estimate of the number and magnitude of effect of quantitative trait loci (QTLs) governing each character. Between one and six QTLs were identified for each trait. Most (9/12) traits appear to be controlled in part by at least one major QTL explaining >/=25% of the total phenotypic variance. This implies that either single genes of individually large effect or linked clusters of genes with a large cumulative effect can play a role in the evolution of reproductive isolation and speciation.     

Social relations and extent and severity of coronary artery disease. The Stockholm Female Coronary Risk Study

Peak bone mass is a major determinant of risk of osteoporotic fracture. Family and twin studies have found a strong genetic component to the determination of bone mineral density (BMD). However, BMD is a complex trait whose expression is confounded by environmental influences and polygenic inheritance. The number, locations, and effects of the individual genes contributing to natural variation in this trait are all unknown. Experimental animal models provide a means to circumvent complicating environmental factors, and the development of dense genetic maps based on molecular markers now provides opportunities to resolve quantitative genetic variation into individual regions of the genome influencing a given trait (quantitative trait loci, QTL). To begin to identify the heritable determinants of BMD, we have examined genetically distinct laboratory mouse strains raised under strict environmental control. Mouse whole-body bone mineral content by dual-energy X-ray absorptiometry (DXA) correlated strongly with skeletal calcium content by ashing, and peak whole-body BMD by DXA in female mice occurred at approximately 80-90 days of age. We therefore determined mean body weight and peak whole body BMD values in 12-week-old female mice from a panel of 24 recombinant inbred (RI) BXD strains, derived from a cross between C57BL/6 and DBA/2 progenitors. The distribution of body weight and BMD values among the strains clearly indicated the presence of strong genetic influences on both of these traits, with an estimated narrow sense heritability of 60% and 35%, respectively. The patterns of differences in body weight and peak whole body BMD in the BXD strains were then integrated with a large database of genetic markers previously defined in the RI BXD strains to generate chromosome map sites for QTL. After correction for redundancy among the significant correlations, QTL analysis of the BXD RI strain series provisionally identified 10 chromosomal sites linked to peak bone mass development in the female. Several of the identified sites map near genes encoding hormones, structural proteins, and cell surface receptors that are intricately involved in skeletal homeostasis. Four QTL for body weight were also identified. One of these loci was also strongly linked to inherited variation in BMD. This finding suggests that body weight and peak BMD may be influenced by linked genes or perhaps by common genes with pleiotropic effects. Our phenotyping in the RI BXD strains has allowed us to map a number of specific genetic loci strongly related to the acquisition of peak BMD. Confirmation of these findings will likely result in the understanding of which genes control skeletal health.     

A second-generation linkage map of the bovine genome

We report a bovine linkage map constructed with 1236 polymorphic DNA markers and 14 erythrocyte antigens and serum proteins. The 2990-cM map consists of a sex-specific, X chromosome linkage group and 29 sex-averaged, autosomal linkage groups with an average interval size of 2.5 cM. The map contains 627 new markers and 623 previously linked markers, providing a basis for integrating the four published bovine maps. Orientation and chromosomal assignment of all the linkage groups, except BTA20 and BTA22, was provided by 88 markers that were assigned previously to chromosomes. This map provides sufficient marker density for genomic scans of populations segregating quantitative trait loci (QTL) and subsequent implementation of marker-assisted selection (MAS) mating schemes.     

Polygenic mutation in Drosophila melanogaster: genetic interactions between selection lines and candidate quantitative trait loci

We have investigated genetic interactions between spontaneous mutations affecting abdominal and sternopleural bristle number that have accumulated in 12 long-term selection lines derived from an inbred strain, and mutations at 14 candidate bristle number quantitative trait loci. The quantitative test for complementation was to cross the selection lines to an inbred wild-type strain (the control cross) and to a derivative of the control strain into which the mutant allele at the candidate locus to be tested was substituted (the tester strain). Genetic interactions between spontaneous mutations affecting bristle number and the candidate locus mutations were common, and in several cases the interaction effects were different in males and females. Analyses of variance of the (tester- control) differences among and within groups of replicate lines selected in the same direction for the same trait showed significant group effects for several candidate loci. Genetically, the interactions could be caused by allelism of, and/ or epistasis between, spontaneous mutations in the selection lines and the candidate locus mutations. It is possible that much of the response to selection was from new mutations at candidate bristle number quantitative trait loci, and that for some of these loci, mutation rates were high.     

Detection and positional cloning of blood pressure quantitative trait loci: is it possible? Identifying the genes for genetic hypertension

Identification of the quantitative trait loci that influence blood pressure and cause genetic hypertension is a major challenge. Several genetically hypertensive rat strains exist and can be used to locate by linkage analysis broad chromosomal regions containing blood pressure quantitative trait loci. Such broad chromosomal regions, and the narrower subregions, can be moved among strains (ie, production of congenic strains and congenic substrains) to identify small chromosomal regions containing the blood pressure quantitative trait loci. However, ultimate positional cloning of the quantitative trait loci presents a major difficulty because the genetic variants involved are likely to result in subtle changes in function rather than the blatant loss of function characteristic of all mendelian disease genes discovered so far by positional cloning.     

Detection of putative loci affecting conformational type traits in an elite population of United States Holsteins using microsatellite markers

Quantitative trait loci affecting conformational type traits were studied in seven large grandsire families of US Holsteins using the granddaughter design and 16 microsatellite markers on 10 chromosomes. The most significant marker effect was marker BM203 (chromosome 27) for dairy form in a single grandsire family. A multivariate analysis for dairy form and milk yield was also conducted, and the result was highly significant, indicating that a segregating quantitative trait locus or loci affecting dairy form and milk yield could exist near BM203 on chromosome 27. Marker BM1258 (chromosome 23) had a significant effect on udder depth. A multivariate analysis on udder depth and somatic cell score was conducted for markers 513 and BM1258, and both markers showed significant effects on these two traits, indicating that one or several quantitative trait loci affecting udder depth and mastitis might exist on chromosome 23. Marker BM4204 (chromosome 9) had a significant effect on foot angle and on the composite index of traits pertaining to feet and legs, indicating that one or several quantitative trait loci affecting traits pertaining to feet and legs might exist on chromosome 9. Selection on these markers could increase genetic progress within these families.     

Effect of inaccurate parameter estimates on genetic response to marker-assisted selection in an outbred population

The effect of inaccurate estimates of variance and of the location of the quantitative trait locus on the genetic response to marker-assisted selection was studied by simulation of an adult multiple ovulation and embryo transfer nucleus breeding scheme. Two genetic models were simulated for the quantitative trait locus: a total of 10 alleles or 2 distinct alleles per base parent. For both models, the locus explained either 5 or 10% of phenotypic variance. A polygenic component was simulated, and the two genetic components were summed to 35% heritability for a trait measured on females. Overestimation of variance of the quantitative trait locus had minimal effect on genetic gain for marker-assisted selection over the short term, but decreased long-term response. The long-term loss was reduced when variance of the quantitative trait locus was reestimated after four generations of marker-assisted selection. Selection for favorable alleles at a nonexistent quantitative trait locus resulted in first generation losses of 3 and 7% for postulated quantitative trait loci, explaining 5 and 10% of variance, respectively. The larger the degree of error in location, the larger was the genetic loss compared with the correct location scenario. For the largest simulated location error of 15 cM, genetic superiority of marker-assisted selection was reduced by 80% in the first generation. We concluded that studies should be undertaken to verify estimates of quantitative trait locus and location to make optimal use of marker-assisted selection.     

Quantitative trait loci and metabolic pathways

The interpretation of quantitative trait locus (QTL) studies is limited by the lack of information on metabolic pathways leading to most economic traits. Inferences about the roles of the underlying genes with a pathway or the nature of their interaction with other loci are generally not possible. An exception is resistance to the corn earworm Helicoverpa zea (Boddie) in maize (Zea mays L.) because of maysin, a C-glycosyl flavone synthesized in silks via a branch of the well characterized flavonoid pathway. Our results using flavone synthesis as a model QTL system indicate: (i) the importance of regulatory loci as QTLs, (ii) the importance of interconnecting biochemical pathways on product levels, (iii) evidence for "channeling" of intermediates, allowing independent synthesis of related compounds, (iv) the utility of QTL analysis in clarifying the role of specific genes in a biochemical pathway, and (v) identification of a previously unknown locus on chromosome 9S affecting flavone level. A greater understanding of the genetic basis of maysin synthesis and associated corn earworm resistance should lead to improved breeding strategies. More broadly, the insights gained in relating a defined genetic and biochemical pathway affecting a quantitative trait should enhance interpretation of the biological basis of variation for other quantitative traits.     

Developmental loss of effect of a Chromosome 15 QTL on alcohol acceptance

Human alcohol abuse and alcoholism have clear developmental features, suggesting the possibility of changes over time in heritability and in quantitative genetic architecture, and raising prospects of identifying individual genes or quantitative trait loci (QTLs) that display different influence on alcohol-related phenotypes at different ages. The identification of specific loci showing such age-related changes will open up opportunities of focused association studies and of genotype manipulation by various mating procedures. Most animal model research in alcohol assesses the phenotypes of the animals at an early age; developmental studies are rare. Here we report on a QTL on Chromosome (Chr) 15 of the mouse that has been shown in several populations, including BXD recombinant inbred strains, an F2, and genotypically selected lines, to affect a measure of alcohol consumption. In the present study, we measured alcohol acceptance in the genotypically selected animals and in an F4 sample at about 100 days and again at about 300 days of age. In both groups, and in both sexes, significant differences were observed at 100 days between animals that were homozygous for the "increasing" haplotype defining the QTL region and those homozygous for the "decreasing" haplotype. At 300 days of age, the effect is absent in females and has diminished or disappeared in males. The results provide a further confirmation of the Chr 15 QTL in young mice, offer a new perspective on the development of alcohol-related phenotypes, and have strong implications for research design.     

Genetic analysis of susceptibility to dextran sulfate sodium-induced colitis in mice

The genetic basis for differential sensitivity of inbred mice to inflammatory bowel disease induced by dextran sulfate sodium (DSS) is unknown. Susceptible C3H/HeJ were outcrossed to partially resistant C57BL/6J mice. F2 and N2 progeny were phenotyped by evaluating histopathologic lesions in large intestine detected 16 days after a 5-day period of feeding 3.5% DSS. Screening for DSS colitis (Dssc) loci revealed quantitative trait loci (QTL) on Chr 5 (Dssc1) and Chr 2 (Dssc2). These traits contributed additively, explaining 17.5% of the variation in total colonic lesions. Additional QTL on Chr 18 and 1 that collectively explained 11% of the variation in total colon lesions were indicated. In the cecum, only a putative QTL on Chr 11 was associated with pathology (lesion severity) in the cecum. Reduced DSS susceptibility was observed in congenic stocks in which the highly susceptible NOD/Lt strain carried putative resistance alleles from either B6 on Chr 2 or from the highly resistant NON/Lt strain on Chr 9. We conclude that multiple genes control susceptibility to DSS colitis in mice. Possible Dssc candidate genes are discussed in terms of current knowledge of inflammatory bowel disease susceptibility loci in humans.     

The molecular basis of quantitative genetic variation in central and secondary metabolism in Arabidopsis

To find the genes controlling quantitative variation, we need model systems where functional information on physiology, development, and gene regulation can guide evolutionary inferences. We mapped quantitative trait loci (QTLs) influencing quantitative levels of enzyme activity in primary and secondary metabolism in Arabidopsis. All 10 enzymes showed highly significant quantitative genetic variation. Strong positive genetic correlations were found among activity levels of 5 glycolytic enzymes, PGI, PGM, GPD, FBP, and G6P, suggesting that enzymes with closely related metabolic functions are coregulated. Significant QTLs were found influencing activity of most enzymes. Some enzyme activity QTLs mapped very close to known enzyme-encoding loci (e.g., hexokinase, PGI, and PGM). A hexokinase QTL is attributable to cis-acting regulatory variation at the AtHXK1 locus or a closely linked regulatory locus, rather than polypeptide sequence differences. We also found a QTL on chromosome IV that may be a joint regulator of GPD, PGI, and G6P activity. In addition, a QTL affecting PGM activity maps within 700 kb of the PGM-encoding locus. This QTL is predicted to alter starch biosynthesis by 3.4%, corresponding with theoretical models, suggesting that QTLs reflect pleiotropic effects of mutant alleles.