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Identification of quantitative trait loci controlling acute virulence in Toxoplasma gondii.

ABSTRACT: Strains of Toxoplasma gondii can be grouped into three predominant clonal lineages with members of the type I group being uniformly lethal in mice. To elucidate the basis of this extreme virulence, a genetic cross was performed between a highly virulent type I strain (GT-1) and a less-virulent type III strain (CTG), and the phenotypes of resulting progeny were analyzed by genetic linkage mapping. Analysis of independent recombinant progeny identified several quantitative trait loci that contributed to acute virulence. A major quantitative trait locus located on chromosome VII accounted for approximately 50% of the virulence phenotype, whereas a minor locus on chromosome IV, linked to the ROP1 gene, accounted for approximately 10%. These loci are conserved in other type I strains, indicating that acute virulence is controlled by discrete genes common to the type I lineage.

SUBMITTER: Su C

PROVIDER: S-EPMC125035 | biostudies-literature | 2002 Aug

REPOSITORIES: biostudies-literature

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Identification of quantitative trait loci controlling acute virulence in Toxoplasma gondii.

Su Chunlei C Howe Daniel K DK Dubey J P JP Ajioka James W JW Sibley L David LD

Proceedings of the National Academy of Sciences of the United States of America 20020729 16

Strains of Toxoplasma gondii can be grouped into three predominant clonal lineages with members of the type I group being uniformly lethal in mice. To elucidate the basis of this extreme virulence, a genetic cross was performed between a highly virulent type I strain (GT-1) and a less-virulent type III strain (CTG), and the phenotypes of resulting progeny were analyzed by genetic linkage mapping. Analysis of independent recombinant progeny identified several quantitative trait loci that contribu ...[more]

PMID: 12149482

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Project description:A new mixed-model method was developed for mapping quantitative trait loci (QTL) by incorporating multiple polygenic covariance structures. First, we used genome-wide markers to calculate six different kinship matrices. We then partitioned the total genetic variance into six variance components, one corresponding to each kinship matrix, including the additive, dominance, additive × additive, dominance × dominance, additive × dominance, and dominance × additive variances. The six different kinship matrices along with the six estimated polygenic variances were used to control the genetic background of a QTL mapping model. Simulation studies showed that incorporating epistatic polygenic covariance structure can improve QTL mapping resolution. The method was applied to yield component traits of rice. We analyzed four traits (yield, tiller number, grain number, and grain weight) using 278 immortal F2 crosses (crosses between recombinant inbred lines) and 1619 markers. We found that the relative importance of each type of genetic variance varies across different traits. The total genetic variance of yield is contributed by additive × additive (18%), dominance × dominance (14%), additive × dominance (48%), and dominance × additive (15%) variances. Tiller number is contributed by additive (17%), additive × additive (22%), and dominance × additive (43%) variances. Grain number is mainly contributed by additive (42%), additive × additive (19%), and additive × dominance (31%) variances. Grain weight is almost exclusively contributed by the additive (73%) variance plus a small contribution from the additive × additive (10%) variance. Using the estimated genetic variance components to capture the polygenic covariance structure, we detected 39 effects for yield, 39 effects for tiller number, 24 for grain number, and 15 for grain weight. The new method can be directly applied to polygenic-effect-adjusted genome-wide association studies (GWAS) in human and other species.

Project description:Blue mold caused by Penicillium expansum is the most important postharvest disease of apple worldwide and results in significant financial losses. There are no defined sources of resistance to blue mold in domesticated apple. However, resistance has been described in wild Malus sieversii accessions, including plant introduction (PI)613981. The objective of the present study was to identify the genetic loci controlling resistance to blue mold in this accession. We describe the first quantitative trait loci (QTL) reported in the Rosaceae tribe Maleae conditioning resistance to P. expansum on genetic linkage group 3 (qM-Pe3.1) and linkage group 10 (qM-Pe10.1). These loci were identified in a M.× domestica 'Royal Gala' X M. sieversii PI613981 family (GMAL4593) based on blue mold lesion diameter seven days post-inoculation in mature, wounded apple fruit inoculated with P. expansum. Phenotypic analyses were conducted in 169 progeny over a four year period. PI613981 was the source of the resistance allele for qM-Pe3.1, a QTL with a major effect on blue mold resistance, accounting for 27.5% of the experimental variability. The QTL mapped from 67.3 to 74 cM on linkage group 3 of the GMAL4593 genetic linkage map. qM-Pe10.1 mapped from 73.6 to 81.8 cM on linkage group 10. It had less of an effect on resistance, accounting for 14% of the experimental variation. 'Royal Gala' was the primary contributor to the resistance effect of this QTL. However, resistance-associated alleles in both parents appeared to contribute to the least square mean blue mold lesion diameter in an additive manner at qM-Pe10.1. A GMAL4593 genetic linkage map composed of simple sequence repeats and 'Golden Delicious' single nucleotide polymorphism markers was able to detect qM-Pe10.1, but failed to detect qM-Pe3.1. The subsequent addition of genotyping-by-sequencing markers to the linkage map provided better coverage of the PI613981 genome on linkage group 3 and facilitated discovery of qM-Pe3.1. A DNA test for qM-Pe3.1 has been developed and is currently being evaluated for its ability to predict blue mold resistance in progeny segregating for qM-Pe3.1. Due to the long juvenility of apple, the availability of a DNA test to screen for the presence of qM-Pe3.1 at the seedling stage will greatly improve efficiency of breeding apple for blue mold resistance.

Dataset Information

Identification of quantitative trait loci controlling acute virulence in Toxoplasma gondii.

Publications

Identification of quantitative trait loci controlling acute virulence in Toxoplasma gondii.

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