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PubMed1997

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.

Animals↗
PubMed2005

Mapping QTLs for grain dormancy on wheat chromosome 3A and the group 4 chromosomes, and their combined effect.

A major QTL for grain dormancy, QPhs.ocs-3A.1, derived from the highly dormant wheat Zenkoujikomugi (Zen), has been identified in a study made under a controlled environment. Further investigations were needed to dissect the precise position and expression of QPhs.ocs-3A.1 under different field conditions because the ability to detect genetic loci for grain dormancy traits is compromised by environmental effects and genotype/environment interactions. Group 4 chromosomes have also been shown to be possible sites of QTLs for grain dormancy. The objectives of this study were (1) to locate additional molecular markers in the QPhs.ocs-3A.1 region, (2) to identify QTLs on the group 4 chromosomes and (3) to elucidate their combined effects. We examined the recombinant inbred lines (RILs) from a cross between Chinese Spring (CS) and Zen over a 3-year period in one location and 1 year in a different location. In an interval mapping study QPhs.ocs-3A.1 was mapped to within the 4.6 cM region flanked by Xbarc310 and Xbcd907 at the proximal end of the short arm of chromosome 3A. QPhs.ocs-3A.1 was confirmed to be the predominant dormancy QTL since it explained a large portion (11.6-44.8%) of the phenotypic variation, and was strongly displayed under dormancy-breaking conditions or at low germination temperatures. For QPhs.ocs-4A.1, identified on the long arm of chromosome 4A, and QPhs.ocs-4B.1, on the centromeric region of the long arm of Chr 4B, the LOD peak positions and the desirable allele were consistent between the trials, while the LOD scores and contribution to the phenotypic variation varied. Transgressive segregants were observed among the 125 RILs and most of them had a combination of the three alleles conferring a higher dormancy: the Zen alleles at QPhs.ocs-3A.1 and QPhs.ocs-4A.1 and the CS allele at QPhs.ocs-4B1. This demonstrated a combined effect of the desirable alleles on accelerating grain dormancy, with their total effect being superior to that of Zen.

Chromosome Mapping↗
PubMed2000

Genetic linkage analysis of X-ray hypersensitivity in the LEC mutant rat.

The LEC rat has been reported to exhibit X-ray hypersensitivity and deficiency in DNA double-strand break (DSB) repair. The present study was performed to map the locus responsible for this phenotype, the xhs (X-ray hypersensitivity), as the first step in identifying the responsible gene. Analysis of the progeny of (BN x LEC)F(1) x LEC backcrosses indicated that the X-ray hypersensitive phenotype was controlled by multiple genetic loci in contrast to the results reported previously. Quantitative trait loci (QTL) linkage analysis revealed two responsible loci located on Chromosomes (Chr) 4 and 1. QTL on Chr 4 exhibited very strong linkage to the X-ray hypersensitive phenotype, while QTL on Chr 1 showed weak linkage. The Rad52 locus, mutation of which results in hypersensitivity to ionizing radiation and impairment of DNA DSB repair in yeast, was reported to be located on the synteneic regions of mouse Chr 6 and human Chr 12. However, mapping of the rat Rad52 locus indicated that it was located 23 cM distal to the QTL on Chr 4. Furthermore, none of the radio-sensitivity-related loci mapped previously in the rat chromosome were identical to the QTL on Chrs 4 and 1 in the LEC rat. Thus, it seems that X-ray hypersensitivity in the LEC rat is caused by mutation(s) in as-yet-undefined genes.

Animals↗
PubMed2003

Rearranged gene order between pig and human in a QTL region on SSC 7.

On porcine Chromosome 7, the region surrounding the MHC region contains QTL influencing many traits including growth, back fat thickness, and carcass composition. Towards the identification of the responsible gene(s), this article describes an increase of density of the radiated hybrid map of SSC 7 in the q11-q14 region and the comparative analysis of gene order on the porcine RH map and human genome assembly. Adding 24 new genes in this region, we were able to build a framework map that fills in gaps on the previous maps. The new software Carthagene was used to build a robust framework in this region. Comparative analysis of human and porcine maps revealed a global conservation of gene order and of distances between genes. A rearranged fragment of around 3.7 Mb was, however, found in the pig approximately 20 Mb upstream from the expected location on the basis of the human map. This rearrangement, found by RH mapping on the IMpRH 7.000 rads panel, has been confirmed by two-color FISH and by mapping on the high resolution IMNpRH2 12.000 rads panel. The rearranged fragment contains two microsatellites found at the most likely QTL location in the INRA QTL experiment. It also contains the BMP5 gene, which, together with CLPS, could be considered as a possible candidate.

Animals↗
PubMed1996

Quantitative trait loci contributing to phencyclidine-induced and amphetamine-induced locomotor behavior in inbred mice.

Phencyclidine (PCP) and amphetamine (AMP) can induce psychotic syndromes in humans, whereas administration of these drugs to mice results in behavioral activation that is influenced by genetic factors. Quantitative trait loci (QTL) underlying genetic differences in response to PCP and AMP in mice were provisionally identified by correlating allelic variation at known marker loci in the BXD series of recombinant inbred (RI) mice and its progenitors (C57BL/6J and DBA/2J inbred strains) with the locomotor response of each strain to PCP and AMP. Total distance traveled for individual mice from each of the 26 BXD RI and two progenitor strains was measured after injections of normal saline and 7.5 mg/kg i.p. injection of PCP. This procedure was repeated after 1 week, using 5.0 mg/kg of AMP, instead of PCP. Markers significantly (p < .01) correlated with response to PCP map to murine chromosomes 1, 14, and 15. Response to amphetamine was correlated with markers mapping to chromosomes 4, 5, 6, 8, 14, and 18. Identification of the QTL underlying PCP-induced and AMP-induced behavior in mice may provide clues into the complicated genetics of psychosis in humans.

Amphetamine↗
PubMed1999

Temporal and multiple quantitative trait loci analyses of resistance to bacterial wilt in tomato permit the resolution of linked loci.

Ralstonia solanacearum is a soil-borne bacterium that causes the serious disease known as bacterial wilt in many plant species. In tomato, several QTL controlling resistance have been found, but in different studies, markers spanning a large region of chromosome 6 showed strong association with the resistance. By using two different approaches to analyze the data from a field test F3 population, we show that at least two separate loci approximately 30 cM apart on this chromosome are most likely involved in the resistance. First, a temporal analysis of the progression of symptoms reveals a distal locus early in the development of the disease. As the disease progresses, the maximum LOD peak observed shifts toward the proximal end of the chromosome, obscuring the distal locus. Second, although classical interval mapping could only detect the presence of one locus, a statistical "two-QTL model" test, specifically adapted for the resolution of linked QTL, strongly supported the hypothesis for the presence of two loci. These results are discussed in the context of current molecular knowledge about disease resistance genes on chromosome 6 and observations made by tomato breeders during the production of bacterial wilt-resistant varieties.

Bacterial Infections↗
PubMed2003

Limits of fine-mapping a quantitative trait.

Once a significant linkage is found, an important goal is reducing the error in the estimated location of the linked locus. A common approach to reducing location error, called fine-mapping, is the genotyping of additional markers in the linked region to increase the genetic information. The utility of fine-mapping for quantitative trait linkage analysis is largely unknown. To explore this issue, we performed a fine-mapping simulation in which the region containing a significant linkage at a 10-centiMorgan (cM) resolution was fine-mapped at 2, 1, and 0.5 cM. We simulated six quantitative trait models in which the proportion of variation due to the quantitative trait locus (QTL) ranged from 0.20-0.90. We used four sampling designs that were all combinations of 100 and 200 families of sizes 5 and 7. Variance components linkage analysis (Genehunter) was performed until 1,000 replicates were found with a maximum lodscore greater than 3.0. For each of these 1,000 replications, we repeated the linkage analysis three times: once for each of the fine-map resolutions. For the most realistic model, reduction in the average location error ranged from 3-15% for 2-cM fine-mapping and from 3-18% for 1-cM fine-mapping, depending on the number of families and family size. Fine-mapping at 0.5 cM did not differ from the 1-cM results. Thus, if the QTL accounts for a small proportion of the variation, as is the case for realistic traits, fine-mapping has little value.

Chromosome Mapping↗
PubMed2003

The human gene map for performance and health-related fitness phenotypes: the 2002 update.

This review presents the 2002 update of the human gene map for physical performance and health-related phenotypes. It is based on peer-reviewed papers published by the end of 2002 and includes association studies with candidate genes, genome-wide scans with polymorphic markers, and single gene defects causing exercise intolerance to variable degrees. The genes and markers with evidence of association or linkage with a performance or fitness phenotype in sedentary or active people, in adaptation to acute exercise, or for training-induced changes are positioned on the genetic map of all autosomes and the X chromosome. Negative studies are reviewed, but a gene or locus must be supported by at least one positive study before being inserted on the map. By the end of 2000, 29 loci were depicted on the map. The 2001 map includes 71 loci on the autosomes and two on the X chromosome. In contrast, the 2002 human gene map for physical performance and health-related phenotypes includes 90 gene entries and QTL, plus two on the X chromosome. To all these loci, one must add 14 mitochondrial genes in which sequence variants have been shown to influence relevant fitness and performance phenotypes.

Anthropometry↗
PubMed2001

Evidence for a language quantitative trait locus on chromosome 7q in multiplex autism families.

Autism is a syndrome characterized by deficits in language and social skills and by repetitive behaviors. We hypothesized that potential quantitative trait loci (QTLs) related to component autism endophenotypes might underlie putative or significant regions of autism linkage. We performed nonparametric multipoint linkage analyses, in 152 families from the Autism Genetic Resource Exchange, focusing on three traits derived from the Autism Diagnostic Interview: "age at first word," "age at first phrase," and a composite measure of "repetitive and stereotyped behavior." Families were genotyped for 335 markers, and multipoint sib pair linkage analyses were conducted. Using nonparametric multipoint linkage analysis, we found the strongest QTL evidence for age at first word on chromosome 7q (nonparametric test statistic [Z] 2.98; P=.001), and subsequent linkage analyses of additional markers and association analyses in the same region supported the initial result (Z=2.85, P=.002; chi(2)=18.84, df 8, P=.016). Moreover, the peak fine-mapping result for repetitive behavior (Z=2.48; P=.007) localized to a region overlapping this language QTL. The putative autism-susceptibility locus on chromosome 7 may be the result of separate QTLs for the language and repetitive or stereotyped behavior deficits that are associated with the disorder.

Autistic Disorder↗
PubMed2004

Seed quality QTL in a prominent soybean population.

Soybean [Glycine max (L.) Merr.] is a versatile crop due to its multitude of uses as a high protein meal and vegetable oil. Soybean seed traits such as seed protein and oil concentration and seed size are important quantitative traits. The objective of this study was to identify representative protein, oil, and seed size quantitative trait loci (QTL) in soybean. A recombinant inbred line (RIL) population consisting of 131 F6-derived lines was created from two prominent ancestors of North American soybeans ('Essex' and 'Williams') and the RILs were grown in six environments. One hundred simple sequence repeat (SSR) markers spaced throughout the genome were mapped in this population. There were a total of four protein, six oil, and seven seed size QTL found in this population. The QTL found in this study may assist breeders in marker-assisted selection (MAS) to retain current positive QTL in modern soybeans while simultaneously pyramiding additional QTL from new germplasm.

Agriculture↗
PubMed2006

Identification of quantitative trait loci (QTL) for oil and protein contents and their relationships with other seed quality traits in Brassica juncea.

A detailed RFLP-genomic map was used to study the genetics of oil, seed and meal protein and sum of oil and seed/meal protein contents in a recombinant doubled-haploid population developed by crossing black- and yellow-seeded Brassica juncea lines. Two yellow seed color genes (SC-B4, SC-A6) and one QTL for erucic acid content (E(1b)) showed pleiotropic effect for oil, protein and sum of oil and seed/meal protein contents. Six (O-A1, O-A6, O-A9, O-B3, O-B4, O-B5) and five (SP-A1, SP-A9, SP-B4, SP-B6, SP-C) QTLs were significant for oil and seed protein contents, respectively. Tight linkage of three of these QTLs (SP-A1, SP-A9, SP-B4, O-A1, O-A9, O-B4), with opposite effects, poses challenge to the plant breeders for simultaneous improvement of negatively correlated (r = -0.7**) oil and seed protein contents. However, one QTL for oil content (O-B3) and two for seed protein content (SP-B6, SP-C) were found to be unlinked, which offer the possibility for simultaneous improvement of these two traits. QTLs significant for meal protein (MP-A1, MP-A6, MP-A9, MP-B5, MP-B6) were significant at least for oil, seed protein or sum of oil and seed/meal protein contents (T-A6, T-A7, T-B4, T-B5). Sum of oil and seed protein contents and sum of oil and meal protein contents had a perfect correlation, as well as same epistatic interactions and QTLs with similar additive effect. This indicates that protein in seed or meal has practically the same meaning for breeding purposes. Epistatic interactions were significant for the quality traits, and their linkage reflected association among the traits.

Agriculture↗
PubMed2000

Some properties of a variance components model for fine-mapping quantitative trait loci.

Identifying etiological variants for multifactorial traits by allelic association holds promise when many markers are available in close proximity. However, evidence for or against association at any particular marker does not provide any direct information about the influence of causal variants or the frequency of the etiologic allele(s). Recently, a variance components model of linkage and association was developed for quantitative traits which is sufficiently flexible to provide some insights into these issues. We show that this combined linkage/association model provides an estimate of the additive genetic variance of a trait that is attributable to disequilibrium between the marker and QTL. We use this estimate to construct approximate boundaries of the minimum level of disequilibrium between an observed marker and unobserved QTL and to delimit the permissible range of allele frequencies at the QTL based on available data at nearby markers. This information may facilitate fine-mapping studies of complex traits that aim to localize QTLs by assessment of association with many markers in a candidate region of interest.

Alleles↗
PubMed2006

QTL analysis for capsaicinoid content in Capsicum.

Pungency or "heat" found in Capsicum fruit results from the biosynthesis and accumulation of alkaloid compounds known as capsaicinoids in the dissepiment, placental tissue adjacent to the seeds. Pepper cultivars differ with respect to their level of pungency because of quantitative and qualitative variation in capsaicinoid content. We analyzed the segregation of three capsaicinoids: capsaicin, dihydrocapsaicin and nordihydrocapsaicin in an inter-specific cross between a mildly pungent Capsicum annuum 'NuMex RNaky' and the wild, highly pungent C. frutescens accession BG2814-6. F(3) families were analyzed in three trials in California and in Israel and a dense molecular map was constructed comprised mostly of loci defined by simple sequence repeat (SSR) markers. Six QTL controlling capsaicinoid content were detected on three chromosomes. One gene from the capsaicinoid biosynthetic pathway, BCAT, and one random fruit EST, 3A2, co-localized with QTL detected in this study on chromosomes 3 and 4. Because one confounding factor in quantitative determination of capsaicinoid is fruit size, fruit weight measurements were taken in two trials. Two QTL controlling fruit weight were detected, however, they did not co-localize with QTL detected for capsaicinoid content. The major contribution to the phenotypic variation of capsaicinoid content (24-42% of the total variation) was attributed to a digenic interaction between a main-effect QTL, cap7.1, and a marker located on chromosome 2 that did not have a main effect on the trait. A second QTL, cap7.2 is likely to correspond to the QTL, cap, identified in a previous study as having pronounced influence on capsaicinoid content.

Capsaicin↗
PubMed2006

Functional mapping - how to map and study the genetic architecture of dynamic complex traits.

The development of any organism is a complex dynamic process that is controlled by a network of genes as well as by environmental factors. Traditional mapping approaches for analysing phenotypic data measured at a single time point are too simple to reveal the genetic control of developmental processes. A general statistical mapping framework, called functional mapping, has been proposed to characterize, in a single step, the quantitative trait loci (QTLs) or nucleotides (QTNs) that underlie a complex dynamic trait. Functional mapping estimates mathematical parameters that describe the developmental mechanisms of trait formation and expression for each QTL or QTN. The approach provides a useful quantitative and testable framework for assessing the interplay between gene actions or interactions and developmental changes.

Animals↗
PubMed2006

A joint model for nonparametric functional mapping of longitudinal trajectory and time-to-event.

BACKGROUND: The characterization of the relationship between a longitudinal response process and a time-to-event has been a pressing challenge in biostatistical research. This has emerged as an important issue in genetic studies when one attempts to detect the common genes or quantitative trait loci (QTL) that govern both a longitudinal trajectory and developmental event. RESULTS: We present a joint statistical model for functional mapping of dynamic traits in which the event times and longitudinal traits are taken to depend on a common set of genetic mechanisms. By fitting the Legendre polynomial of orthogonal properties for the time-dependent mean vector, our model does not rely on any curve, which is different from earlier parametric models of functional mapping. This newly developed nonparametric model is demonstrated and validated by an example for a forest tree in which stemwood growth and the time to first flower are jointly modelled. CONCLUSION: Our model allows for the detection of specific QTL that govern both longitudinal traits and developmental processes through either pleiotropic effects or close linkage, or both. This model will have great implications for integrating longitudinal and event data to gain better insights into comprehensive biology and biomedicine.

Algorithms↗
PubMed2002

Plant defense genes associated with quantitative resistance to potato late blight in Solanum phureja x dihaploid S. tuberosum hybrids.

Markers corresponding to 27 plant defense genes were tested for linkage disequilibrium with quantitative resistance to late blight in a diploid potato population that had been used for mapping quantitative trait loci (QTLs) for late blight resistance. Markers were detected by using (i) hybridization probes for plant defense genes, (ii) primer pairs amplifying conserved domains of resistance (R) genes, (iii) primers for defense genes and genes encoding transcriptional regulatory factors, and (iv) primers allowing amplification of sequences flanking plant defense genes by the ligation-mediated polymerase chain reaction. Markers were initially screened by using the most resistant and susceptible individuals of the population, and those markers showing different allele frequencies between the two groups were mapped. Among the 308 segregating bands detected, 24 loci (8%) corresponding to six defense gene families were associated with resistance at chi2 > or = 13, the threshold established using the permutation test at P = 0.05. Loci corresponding to genes related to the phenylpropanoid pathway (phenylalanine ammonium lyase [PAL], chalcone isomerase [CHI], and chalcone synthase [CHS]), loci related to WRKY regulatory genes, and other -defense genes (osmotin and a Phytophthora infestans-induced cytochrome P450) were significantly associated with quantitative disease resistance. A subset of markers was tested on the mapping population of 94 individuals. Ten defense-related markers were clustered at a QTL on chromosome III, and three defense-related markers were located at a broad QTL on chromosome XII. The association of candidate genes with QTLs is a step toward understanding the molecular basis of quantitative resistance to an important plant disease.

Acyltransferases↗
PubMed2002

A resistance gene analog useful for targeting disease resistance genes against different pathogens on group 1S chromosomes of barley, wheat and rye.

Comparative sequence analysis of the resistance gene analog (RGA) marker locus aACT/CAA (originally found to be tightly linked to the multiallelic barley Mla cluster) from genomes of barley, wheat and rye revealed a high level of relatedness among one another and showed high similarity to a various number of NBS-LRR disease resistance proteins. Using the sequence-specific polymerase chain reaction (PCR), RGA marker aACT/CAA was mapped on group 1S chromosomes of the Triticeae and was associated with disease resistance loci. In barley and rye, the marker showed linkage to orthologous powdery mildew resistance genes Mla1 and Pm17, respectively, while in wheat linkage with a QTL against fusarium head blight (FHB) disease was determined. The use of RGA clones for R gene mapping and their role in the expression of qualitative and quantitative resistance is discussed.

Journal Article↗
PubMed1996

Quantitative trait loci for murine growth.

Body size is an archetypal quantitative trait with variation due to the segregation of many gene loci, each of relatively minor effect, and the environment. We examine the effects of quantitative trait loci (QTLs) on age-specific body weights and growth in the F2 intercross of the LG/J and SM/J strains of inbred mice. Weekly weights (1-10 wk) and 75 microsatellite genotypes were obtained for 535 mice. Interval mapping was used to locate and measure the genotypic effects of QTLs on body weight and growth. QTL effects were detected on 16 of the 19 autosomes with several chromosomes carrying more than one QTL. The number of QTLs for age-specific weights varied from seven at 1 week to 17 at 10 wk. The QTLs were each of relatively minor, subequal effect. QTLs affecting early and late growth were generally distinct, mapping to different chromosomal locations indicating separate genetic and physiological systems for early and later murine growth.

Age Factors↗

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