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PubMed2000

Quantitative trait loci that control vector competence for dengue-2 virus in the mosquito Aedes aegypti.

Quantitative trait loci (QTL) affecting the ability of the mosquito Aedes aegypti to become infected with dengue-2 virus were mapped in an F(1) intercross. Dengue-susceptible A. aegypti aegypti were crossed with dengue refractory A. aegypti formosus. F(2) offspring were analyzed for midgut infection and escape barriers. In P(1) and F(1) parents and in 207 F(2) individuals, regions of 14 cDNA loci were analyzed with single-strand conformation polymorphism analysis to identify and orient linkage groups with respect to chromosomes I-III. Genotypes were also scored at 57 RAPD-SSCP loci, 5 (TAG)(n) microsatellite loci, and 6 sequence-tagged RAPD loci. Dengue infection phenotypes were scored in 86 F(2) females. Two QTL for a midgut infection barrier were detected with standard and composite interval mapping on chromosomes II and III that accounted for approximately 30% of the phenotypic variance (sigma(2)(p)) in dengue infection and these accounted for 44 and 56%, respectively, of the overall genetic variance (sigma(2)(g)). QTL of minor effect were detected on chromosomes I and III, but these were not detected with composite interval mapping. Evidence for a QTL for midgut escape barrier was detected with standard interval mapping but not with composite interval mapping on chromosome III.

Aedes↗
PubMed2001

Organization of genes controlling disease resistance in the potato genome.

Nineteen single dominant genes (R genes) for resistance to viruses, nematodes, and fungi have been positioned on the molecular map of potato using DNA markers. Fourteen of those genes are located in five "hotspots" for resistance in the potato genome. Quantitative trait loci (QTL) for resistance to late blight caused by the oomycete Phytophthora infestans, to tuber rot caused by the bacterium Erwinia carotovora ssp. atroseptica, and to root cyst nematodes have been identified on all 12 potato chromosomes. Some QTL for resistance to different pathogens are linked to each other and/or to resistance hotspots. Based on the genetic clustering with R genes, we propose that some QTL for resistance have a molecular basis similar to single R genes. Mapping potato genes with sequence similarity to cloned R genes of other plants and other defense-related genes reveals linkage between candidate genes, R genes, and resistance QTL. To explain the molecular basis of polygenic resistance in potato we propose (a) genes having structural similarity with cloned R genes and (b) genes involved in the defense response. The "candidate gene approach" enables the identification of markers highly useful for marker-assisted selection in potato breeding.

Animals↗
PubMed2005

[QTL analysis for traits associated with photosynthetic functions in rice (Oryza sativa L.)].

A mapping population of 81 F11 lines (Recombinant Inbred Lines, RILs), derived from a cross between a japonica variety Kinmaze and an indica variety DV85 by single-seed descent method, was used to detect quantitative trait loci (QTL) for traits associated with photosynthetic functions. Total leaf nitrogen content (TLN), chlorophyll a/b ratio (Chl. a:b) and chlorophyll content (Chl) were measured in leaves of rice (Oryza sativa L.) at the 7th day after heading. A total of six putative QTLs were detected with percentage of variance explained (PVE) ranging between 11.2% -29.6%, and LOD of QTLs 2.66-4.81. Of those putative QTLs, three for TLN were detected on chromosomes 1,2 and 11, with PVE of 17.3%, 15.3% and 13.7%, respectively;Two controlling Chl. a:b on chromosomes 3 and 4, PVE of 13.8% and 29.6%, one for Chl on chromosome 1, PVE of 11.2%. Four of those detected QTLs were newly reported in this study. Interestingly, the QTL controlling chlorophyll content,namely qCC-1 reported here,was detected in the region of the RFLP marker C122 on chromosome 1, where harbored NADH-glutamate synthase structure gene according to a previous study. Because the biosynthesis of chlorophyll begins with glutamate, qCC-1 would play a vital role in photosynthetic functions. Whereas,no QTL controlling chlorophyll content were detected at the 30th day after heading, suggesting that the effect of the QTL controlling chlorophyll content decreased during leaf senescence.

Chlorophyll↗
PubMed2005

A hyperspace model to decipher the genetic architecture of developmental processes: allometry meets ontogeny.

To better utilize limited resources for their survival and reproduction, all organisms undergo developmental changes in both body size and shape during ontogeny. The genetic analysis of size change with increasing age, i.e., growth, has received considerable attention in quantitative developmental genetic studies, but the genetic architecture of ontogenetic changes in body shape and its associated allometry have been poorly understood partly due to the lack of analytical tools. In this article, we attempt to construct a multivariate statistical framework for studying the genetic regulation of ontogenetic growth and shape. We have integrated biologically meaningful mathematical functions of growth curves and developmental allometry into the estimation process of genetic mapping aimed at identifying individual quantitative trait loci (QTL) for phenotypic variation. This model defined with high dimensions can characterize the ontogenetic patterns of genetic effects of QTL over the lifetime of an organism and assess the interplay between genetic actions/interactions and phenotypic integration. The closed forms for the residual covariance matrix and its determinant and inverse were derived to overcome the computational complexity typical of our high-dimensional model. We used a worked example to validate the utility of this model. The implications of this model for genetic research of evo-devo are discussed.

Algorithms↗
PubMed2004

Construction of a linkage map based on a Lathyrus sativus backcross population and preliminary investigation of QTLs associated with resistance to ascochyta blight.

A linkage map of the Lathyrus sativus genome was constructed using 92 backcross individuals derived from a cross between an accession resistant (ATC 80878) to ascochyta blight caused by Mycosphaerella pinodes and a susceptible accession (ATC 80407). A total of 64 markers were mapped on the backcross population, including 47 RAPD, seven sequence-tagged microsatellite site and 13 STS/CAPS markers. The map comprised nine linkage groups, covered a map distance of 803.1 cM, and the average spacing between markers was 15.8 cM. Quantitative trait loci (QTL) associated with ascochyta blight resistance were detected using single-point analysis and simple and composite interval mapping. The backcross population was evaluated for stem resistance in temperature-controlled growth room trials. One significant QTL, QTL1, was located on linkage group 1 and explained 12% of the phenotypic variation in the backcross population. A second suggestive QTL, QTL2, was detected on linkage group 2 and accounted for 9% of the trait variation. The L. sativus R-QTL regions detected may be targeted for future intergenus transfer of the trait into accessions of the closely related species Pisum sativum.

Ascomycota↗
PubMed2005

QTL of three agronomically important traits and their interactions with environment in a European x Chinese rapeseed population.

A rapeseed population consisted of 282 doubled haploid (DH) lines derived from a cross between a European vality "Sallux" and a Chinese inbred line "Gaoyou" was planted in 4 locations, 2 in Xi'an and Hangzhou, China, and 2 in Goettingen, Germany. Field experiments were carried out to obtain agronomically phenotypic data from above four environments. A linkage map including 125 SSR-markers was constructed and QTL analyses was performed using mixed model approach to detect QTLs showing additive (a), epistasis (aa) as well as their interactions with environments (QE) for three important agronomic traits: plant height, flowering time and maturity. The results demonstrated that each trait was controlled by several QTLs with additive effect and a number of QTLs with epistatic and QE interaction effects. Plant height was controlled by many QTLs (12 loci with a or combined ae, 5 loci with ae). Additive effects were predominant,totally explained 75% of the phenotypic variation and often combined with digenic epistasis. Of 12 main QTLs, 9 showed Gaoyou alleles decreasing plant height. Most of QTLs with QE effects showed ecologically favourable alleles in diverse regions. Five of 7 ae loci showed Gaoyou alleles in Hangzhou and all the ae loci but one had Sollux alleles in two locations of Germany increasing plant height. The digenic epistatic main effect accounted for one third of total additive main effects. In this study,we discovered 7 and 8 loci having significant additive main effects upon flowering time and maturity, respectively. Of them, early flowering and maturity alleles were respectively 6 and 5 derived from Chinese parent Gaoyou. All these QTLs together accounted for around 60% of the phenotypic variation for each trait. Significant ae interactions were detected for flowering time and maturity and parental alleles showed almost evenly dispersal at all environments. Three of 8 main QTLs for maturity were located at similar or identical positions as QTLs for flowering time, which confirmed the close correlation between these two traits. Two QTLs for plant height on linkage groups N14-1 and 19 were located at similar positions as QTL for flowering time and as already known QTLs for oil content. Selection for reduced plant height and early flowering might reduce oil content. Digenic epistatic QTLs both for flowering time and maturity were detected but much less important than QTLs with additive effects.

Brassica rapa↗
PubMed1998

Empirical nonparametric bootstrap strategies in quantitative trait loci mapping: conditioning on the genetic model.

Several nonparametric bootstrap methods are tested to obtain better confidence intervals for the quantitative trait loci (QTL) positions, i.e., with minimal width and unbiased coverage probability. Two selective resampling schemes are proposed as a means of conditioning the bootstrap on the number of genetic factors in our model inferred from the original data. The selection is based on criteria related to the estimated number of genetic factors, and only the retained bootstrapped samples will contribute a value to the empirically estimated distribution of the QTL position estimate. These schemes are compared with a nonselective scheme across a range of simple configurations of one QTL on a one-chromosome genome. In particular, the effect of the chromosome length and the relative position of the QTL are examined for a given experimental power, which determines the confidence interval size. With the test protocol used, it appears that the selective resampling schemes are either unbiased or least biased when the QTL is situated near the middle of the chromosome. When the QTL is closer to one end, the likelihood curve of its position along the chromosome becomes truncated, and the nonselective scheme then performs better inasmuch as the percentage of estimated confidence intervals that actually contain the real QTL's position is closer to expectation. The nonselective method, however, produces larger confidence intervals. Hence, we advocate use of the selective methods, regardless of the QTL position along the chromosome (to reduce confidence interval sizes), but we leave the problem open as to how the method should be altered to take into account the bias of the original estimate of the QTL's position.

Chromosome Mapping↗
PubMed1997

Location of the first genetic locus, PKDr1, controlling autosomal dominant polycystic kidney disease in Han:SPRD cy/+ rat.

The Han:SPRD cy/+ strain develops a form of slowly progressive disease that appears similar in many respects to that seen in the autosomal dominant polycystic kidney disease (ADPKD) in humans. We have performed a total genome scan in an experimental backcross population derived from affected Han:SPRD cy/+ rat (PKD) and non-affected Wistar Ottawa Karlsburg rat (WOK) using 117 microsatellite markers. The genetic dissection of PKD allowed us to map on rat chromosome 5, a quantitative trait locus (QTL) controlling PKD, kidney mass and plasma urea concentration. The homology region is likely to reside on human chromosome 8. The gene responsible for PKD in Han:SPRD cy/+ rat is neither PKD1, localised on human chromosome 16, nor PKD2, localised on human chromosome 4. Therefore, we propose that this new locus be denoted PKDr1. The detection of the PKDr1 locus and associated QTL should accelerate research into the genetic causes of ADPKD.

Animals↗
PubMed2002

Isolate-specific QTLs of resistance to leaf stripe (Pyrenophora graminea) in the 'Steptoe' x 'Morex' spring barley cross.

Leaf stripe caused by the fungus Pyrenophora graminea represents a serious threat to grain yield in organically grown barley and in conventional Nordic and Mediterranean districts, for which resistant cultivars are necessary. A medium-density, molecular marker map derived from a 'Steptoe' (partially resistant) x 'Morex' (susceptible) spring barley cross and its derived doubled-haploid mapping population inoculated with the fungus made it possible to identify QTLs of resistance to leaf stripe. In order to investigate isolate-specificity of partial resistance, the 'Steptoe' x 'Morex' segregating population was inoculated with two highly virulent P. graminea isolates, Dg2 and Dg5. The present study demonstrates that partial resistance to leaf stripe of cv 'Steptoe' is governed in part by shared loci and in part by isolate-specific ones. One QTL is common to the resistance for the two isolates, on the long arm of chromosome 2 (2H), two QTLs are linked on chromosome 3 (3H), and the remaining two are isolate-specific, respectively for isolate Dg2 on chromosome 2 (2H) and for isolate Dg5 on chromosome 7 (5H). The QTL in common is that with the major effect on the resistance for each isolate, explaining 18.3% and 30.9% R(2) respectively for Dg2 and Dg5. The isolate-specific QTLs mapped in the 'Steptoe' x 'Morex' barley reference map support the assumption of Parlevliet and Zadoks (1977) that partial resistance may be due to minor gene-for-minor-gene interactions. Map comparisons of the QTLs with the known qualitative resistance genes to leaf stripe, Rdg1 (2H) and Rdg2 (7H), as well as with other QTLs of partial resistance in barley, show that the QTL for resistance to both isolates mapped on the long arm of chromosome 2 (2H) does not coincide with the qualitative Rdg1 gene but is linked to it at about 30 cM. One isolate-specific QTL of resistance to P. graminea, mapped on the short arm of chromosome 2 (2H), is coincident with a QTL for resistance to Pyrenophora teres previously mapped in the 'Steptoe' x 'Morex' cross.

Chromosome Mapping↗
PubMed2002

Comparative genetic analysis of quantitative traits in sunflower ( Helianthus annuus L.) 1. QTL involved in resistance to Sclerotinia sclerotiorum and Diaporthe helianthi.

Sclerotinia sclerotiorum and Diaporthe helianthi are important pathogens of sunflower ( Helianthus annuus L.). Two hundred and twenty F2-F3 families were developed from an intraspecific cross between two inbred sunflower lines XRQ and PSC8. Using this segregating population a genetic map of 19 linkage groups with 290 molecular markers covering 2,318 cM was constructed. Disease resistances were measured in field experiments during 3 years (1998, 1999 and 2000) for phomopsis and 2 years for S. sclerotiorum (1997 and 1999). QTL were detected using the interval mapping method at a LOD threshold of 3. A total of 15 QTL for each pathogen resistance were detected across several linkage groups, confirming the polygenic nature of the resistances. These QTL explained from 7 to 41% of the phenotypic variability. The QTL for phomopsis resistance, in the 3 years of tests, mapped in the same region, and this was also true for some forms of S. sclerotiorum resistance in the 2 years of tests. On linkage group 8, QTL affecting resistance to both S. sclerotiorum and D. helianthi mycelium extension on leaves colocalised, suggesting a common component in the mechanism of resistance for these two pathogens. The colocalisation of QTL and breeding for resistance to S. sclerotiorum and to D. helianthi by pyramiding QTL in sunflower are discussed.

Journal Article↗
PubMed1997

Blood pressure and survival of a chromosome 7 congenic strain bred from Dahl rats.

11 beta-hydroxylase (Cyp11b1) mutations were previously linked to altered steroid biosynthesis and blood pressure in Dahl salt-resistant (R) and Dahl salt-sensitive (S) rats. In the present work, interval mapping identified a putative blood pressure quantitative trait locus (QTL) near Cyp11b1 in an F1(SxR)xS population (LOD = 2.0). Congenic rats (Designated S.R-Cyp11b) were constructed by introgressing the R-rat Cyp11b1 allele into the S strain. S.R-Cyp11b rats had significantly lower blood pressure and heart weight compared with S rats, proving the existence of a blood pressure QTL on Chromosome (Chr) 7 despite the fact that QTL linkage analysis of blood pressure never achieved stringent statistical criteria for significance. To test the effects of the introgressed region on blood pressure and survival, S.R.-Cyp11b and S rats were maintained on a 4% NaCl diet until they died or became moribund. Analysis of variance (ANOVA) indicated significant strain differences in blood pressure and days survived (P < 0.0001 for both) as well as gender differences in days survived (P = 0.0003). Kaplan-Meier survival analysis also found significant strain (P < 0.0001) and gender (P = 0.007) differences in days survived. However, when the effects of blood pressure were removed, significant strain differences in survival essentially disappeared. This suggests that the increased survival of S.R-Cyp11b rats was largely due to their decreased blood pressure and thus strongly corroborates the existence of a blood pressure QTL on Chr 7 near or at Cyp11b1.

Adrenal Hyperplasia, Congenital↗
PubMed2004

Identification of drought-inducible genes and differentially expressed sequence tags in barley.

Drought limits cereal yields in several regions of the world and plant water status plays an important role in tolerance to drought. To investigate and understand the genetic and physiological basis of drought tolerance in barley, differentially expressed sequence tags (dESTs) and candidate genes for the drought response were mapped in a population of 167 F8 recombinant inbred lines derived from a cross between "Tadmor" (drought tolerant) and "Er/Apm" (adapted only to specific dry environments). One hundred sequenced probes from two cDNA libraries previously constructed from drought-stressed barley (Hordeum vulgare L., var. Tokak) plants and 12 candidate genes were surveyed for polymorphism, and 33 loci were added to a previously published map. Composite interval mapping was used to identify quantitative trait loci (QTL) associated with drought tolerance including leaf relative water content, leaf osmotic potential, osmotic potential at full turgor, water-soluble carbohydrate concentration, osmotic adjustment, and carbon isotope discrimination. A total of 68 QTLs with a limit of detection score > or =2.5 were detected for the traits evaluated under two water treatments and the two traits calculated from both treatments. The number of QTLs identified for each trait varied from one to 12, indicating that the genome contains multiple genes affecting different traits. Two candidate genes and ten differentially expressed sequences were associated with QTLs for drought tolerance traits.

Chromosome Mapping↗
PubMed1994

Chromosomal mapping of two loci affecting filarial worm susceptibility in Aedes aegypti.

Two quantitative trait loci (QTL) affecting susceptibility of the mosquito Aedes aegypti to the filarial worm parasite Brugia malayi were identified using restriction fragment length polymorphism (RFLP) markers. The first locus, fsb[1,LF178], resides within a 10 cM interval on chromosome 1 and exhibits a recessive effect with respect to susceptibility. The second locus, fsb[2,LF98], resides within a 9 cM interval on chromosome 2 and exhibits an additive effect on susceptibility. Significant epistasis was detected between these loci, although the effect of fsb[2,LF98] was dependent on the genetic background of the mosquito strains. Suggestions for a standard QTL nomenclature are included.

Aedes↗
PubMed1995

Comparing power of different methods for QTL detection.

We compared the powers of two methods for detection of quantitative trait loci (QTL) using genetic markers, in the simple case of an interval between two codominant markers and a backcross population. The first method is the interval mapping approach, based on the use of likelihood ratio tests performed in many positions within the interval considered and the second is the classical analysis of variance (ANOVA) testing only on the positions of the two markers. For both approaches we took into account the correlation between tests performed at different markers or positions in the interval. Appropriate thresholds and powers of tests were then calculated using analytical formulations. Simulations were also done to check the validity of the approximations used to calculate the power of the interval mapping test. Results show that the interval mapping test is slightly more powerful (about 5%) than ANOVA for small intervals (less than 20 cM) and that, for quite large effects of the QTL, the advantage of interval mapping increases as the distance between markers increases. It is more than 30% for intervals of about 70 cM.

Analysis of Variance↗
PubMed2001

Genetic analysis of cholesterol accumulation in inbred mice.

Genetic linkage analysis in the laboratory mouse identified chromosomal regions containing genes that contribute to cholesterol accumulation in the liver and plasma. Comparisons between five inbred strains of mice obtained from the Jackson Laboratory (DBA/2, AKR, C57BL/6, SJL, and 129P3) revealed a direct correlation between intestinal cholesterol absorption and susceptibility to diet-induced hypercholesterolemia. This correlation was lost in the F1 generation arising from crosses between high- and low-absorbing strains. Linkage analyses in AKxD recombinant inbred strains and 129xSJL129F1 N2 backcross mice identified four quantitative trait loci (QTL) that influenced Liver cholesterol accumulation (Lcho1-4) and one locus that affected Plasma cholesterol accumulation (Pcho1). These loci map to five chromosomes and, with one exception, are different from the seven QTL identified previously that influence intestinal cholesterol absorption. We conclude that a large number of genes affects the amount of cholesterol absorbed in the small intestine and its accumulation in the liver and plasma of inbred mice.

Animals↗
PubMed2006

Genetical metabolomics of flavonoid biosynthesis in Populus: a case study.

Genetical metabolomics [metabolite profiling combined with quantitative trait locus (QTL) analysis] has been proposed as a new tool to identify loci that control metabolite abundances. This concept was evaluated in a case study with the model tree Populus. Using HPLC, the peak abundances were analyzed of 15 closely related flavonoids present in apical tissues of two full-sib poplar families, Populus deltoides cv. S9-2 x P. nigra cv. Ghoy and P. deltoides cv. S9-2 x P. trichocarpa cv. V24, and correlation and QTL analysis were used to detect flux control points in flavonoid biosynthesis. Four robust metabolite quantitative trait loci (mQTL), associated with rate-limiting steps in flavonoid biosynthesis, were mapped. Each mQTL was involved in the flux control to one or two flavonoids. Based on the identities of the affected metabolites and the flavonoid pathway structure, a tentative function was assigned to three of these mQTL, and the corresponding candidate genes were mapped. The data indicate that the combination of metabolite profiling with QTL analysis is a valuable tool to identify control points in a complex metabolic pathway of closely related compounds.

Chromatography, High Pressure Liquid↗
PubMed2005

QTL analysis of fruit components in the progeny of a Rennell Island Tall coconut (Cocos nucifera L.) individual.

We investigated the genetic factors controlling fruit components in coconut by performing QTL analyses for fruit component weights and ratios in a segregating progeny of a Rennell Island Tall genotype. The underlying linkage map of this population was already established in a previous study, as well as QTL analyses for fruit production, which were used to complement our results. The addition of 53 new markers (mainly SSRs) led to minor amendments in the map. A total of 52 putative QTLs were identified for the 11 traits under study. Thirty-four of them were grouped in six small clusters, which probably correspond to single pleiotropic genes. Some additional QTLs located apart from these clusters also had relatively large effects on the individual traits. The QTLs for fruit component weight, endosperm humidity and fruit production were found at different locations in the genome, suggesting that efficient marker-assisted selection for yield can be achieved by selecting QTLs for the individual components. The detected QTLs descend from a genotype belonging to the "Pacific" coconut group. Based on the known molecular and phenotypic differences between "Pacific" and "Indo-Atlantic" coconuts, we suggest that a large fraction of coconut genetic diversity is still to be investigated by studying populations derived from crosses between these groups.

Chromosome Mapping↗
PubMedDate not supplied

Composite interval mapping reveals a major locus influencing embryonic development rate in rainbow trout (Oncorhynchus mykiss).

Little is known about the genetics controlling the rate of embryonic development in salmonids, despite the fact that this trait plays an important role in the life history of wild and cultured stocks. We investigated the genetics of embryonic development rate by performing an analysis of quantitative trait loci (QTL) on two families of androgenetically derived doubled haploid rainbow trout produced from a hybrid of two clonal lines with divergent embryonic development rates. A total of 170 doubled haploid individuals were genotyped at 222 marker loci [219 amplified fragment length polymorphism (AFLP) markers, 2 microsatellites, and p53]. A genetic linkage analysis resulted in a map consisting of 27 linkage groups with 21 of the markers remaining unlinked at a minimum LOD of 3.0 and maximum theta of 0.40. Eight of these linkage groups were matched to published rainbow trout linkage groups. Composite interval mapping (CIM) revealed evidence for two QTL influencing time to hatch, and suggestive evidence for a third. These QTL accounted for a total of 24.6% of the variation in time to hatch. One of these QTL had a large effect on development rate, especially in one family of doubled haploids, in which it explained 25.6% of the variance in time to hatch. QTL influencing embryonic length and weight at the commencement of exogenous feeding were also identified. The QTL with the strongest effect on embryonic length (lenR13) mapped to the same position as the QTL with the strongest effect on time to hatch (tthR13), suggesting a single QTL may have a pleiotropic effect on both these traits. These results suggest that the use of clonal lines with a doubled haploid crossing design is an effective way of analyzing the genetic basis of complex traits in salmonids.

Animals↗