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Virulence attributes and hyphal growth of C. neoformans are quantitative traits and the MATalpha allele enhances filamentation.

Lin X, Huang JC, Mitchell TG, Heitman J - PLoS Genet. (2006)

Bottom Line: We discovered that variation in hyphal length produced during fruiting is a quantitative trait resulting from the combined effects of multiple genetic loci, including the mating type (MAT) locus.Importantly, the alpha allele of the MAT locus enhanced hyphal growth compared with the a allele.MAC1 allelic differences contribute to phenotypic variation, and mac1Delta mutants exhibit defects in filamentation, melanin production, and high temperature growth.

View Article: PubMed Central - PubMed

Affiliation: Department of Molecular Genetics and Microbiology, Duke University Medical Center, Durham, North Carolina, United States of America.

ABSTRACT
Cryptococcus neoformans is a fungal human pathogen with a bipolar mating system. It undergoes a dimorphic transition from a unicellular yeast to hyphal filamentous growth during mating and monokaryotic fruiting. The traditional sexual cycle that leads to the production of infectious basidiospores involves cells of both alpha and a mating type. Monokaryotic fruiting is a modified form of sexual reproduction that involves cells of the same mating type, most commonly alpha, which is the predominant mating type in both the environment and clinical isolates. However, some a isolates can also undergo monokaryotic fruiting. To determine whether mating type and other genetic loci contribute to the differences in fruiting observed between alpha and a cells, we applied quantitative trait loci (QTL) mapping to an inbred population of F2 progeny. We discovered that variation in hyphal length produced during fruiting is a quantitative trait resulting from the combined effects of multiple genetic loci, including the mating type (MAT) locus. Importantly, the alpha allele of the MAT locus enhanced hyphal growth compared with the a allele. Other virulence traits, including melanization and growth at 39 degrees C, also are quantitative traits that share a common QTL with hyphal growth. The Mac1 transcription factor, encoded in this common QTL, regulates copper homeostasis. MAC1 allelic differences contribute to phenotypic variation, and mac1Delta mutants exhibit defects in filamentation, melanin production, and high temperature growth. Further characterization of these QTL regions will reveal additional quantitative trait genes controlling biological processes central to fungal development and pathogenicity.

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Five Significant QTLs Influence the Variation of Hyphal ElongationAnalysis by WinQTL using the CIM method is shown. The y-axis shows the LOD score and the x-axis shows the marker location on each chromosome. Five QTLs with a LOD score greater than the threshold 3.2 are labeled. Chromosome 14 is not depicted, as no QTL was identified on this chromosome.
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pgen-0020187-g005: Five Significant QTLs Influence the Variation of Hyphal ElongationAnalysis by WinQTL using the CIM method is shown. The y-axis shows the LOD score and the x-axis shows the marker location on each chromosome. Five QTLs with a LOD score greater than the threshold 3.2 are labeled. Chromosome 14 is not depicted, as no QTL was identified on this chromosome.

Mentions: To obtain the most robust prediction of QTLs, several mapping methods were applied to search for QTLs, including single marker analysis [36], interval mapping (IM) [37], composite interval mapping (CIM) [38,39], and multiple interval mapping (MIM) [40]. Single marker analysis is based on the association between a marker genotype and trait value. IM uses two observable flanking markers to construct an interval within which to search for QTLs. CIM fits background markers to account for variance caused by nontarget QTLs. MIM uses multiple marker intervals simultaneously to fit multiple putative QTLs. Because each method yielded a similar prediction of the number and location of QTLs, only the results obtained using CIM are shown (Figure 5). In Figure 5, the y-axis shows the log of the odds index (LOD) of a particular QTL, indicating the strength of statistical support. The x-axis shows the marker distribution along each chromosome. As depicted in Figure 5, there are 5 QTLs with a LOD score above 3.2, the threshold generated through permutation tests, indicating that these QTLs contribute significantly to the genetic variation in hyphal growth observed in this inbred population. Based on the estimation from the CIM analysis, these five QTLs account for 17.1%, 4.4%, 4.6%, 18.8%, and 6.9% of the genetic variance with a cumulative effect of 52%. QTL1 and QTL4 are the two most significant loci accounting for the variation in hyphal growth in this inbred population (17.1% and 18.8%, respectively) and each of the other three QTLs accounts for less than 10% of the effect.


Virulence attributes and hyphal growth of C. neoformans are quantitative traits and the MATalpha allele enhances filamentation.

Lin X, Huang JC, Mitchell TG, Heitman J - PLoS Genet. (2006)

Five Significant QTLs Influence the Variation of Hyphal ElongationAnalysis by WinQTL using the CIM method is shown. The y-axis shows the LOD score and the x-axis shows the marker location on each chromosome. Five QTLs with a LOD score greater than the threshold 3.2 are labeled. Chromosome 14 is not depicted, as no QTL was identified on this chromosome.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC1636697&req=5

pgen-0020187-g005: Five Significant QTLs Influence the Variation of Hyphal ElongationAnalysis by WinQTL using the CIM method is shown. The y-axis shows the LOD score and the x-axis shows the marker location on each chromosome. Five QTLs with a LOD score greater than the threshold 3.2 are labeled. Chromosome 14 is not depicted, as no QTL was identified on this chromosome.
Mentions: To obtain the most robust prediction of QTLs, several mapping methods were applied to search for QTLs, including single marker analysis [36], interval mapping (IM) [37], composite interval mapping (CIM) [38,39], and multiple interval mapping (MIM) [40]. Single marker analysis is based on the association between a marker genotype and trait value. IM uses two observable flanking markers to construct an interval within which to search for QTLs. CIM fits background markers to account for variance caused by nontarget QTLs. MIM uses multiple marker intervals simultaneously to fit multiple putative QTLs. Because each method yielded a similar prediction of the number and location of QTLs, only the results obtained using CIM are shown (Figure 5). In Figure 5, the y-axis shows the log of the odds index (LOD) of a particular QTL, indicating the strength of statistical support. The x-axis shows the marker distribution along each chromosome. As depicted in Figure 5, there are 5 QTLs with a LOD score above 3.2, the threshold generated through permutation tests, indicating that these QTLs contribute significantly to the genetic variation in hyphal growth observed in this inbred population. Based on the estimation from the CIM analysis, these five QTLs account for 17.1%, 4.4%, 4.6%, 18.8%, and 6.9% of the genetic variance with a cumulative effect of 52%. QTL1 and QTL4 are the two most significant loci accounting for the variation in hyphal growth in this inbred population (17.1% and 18.8%, respectively) and each of the other three QTLs accounts for less than 10% of the effect.

Bottom Line: We discovered that variation in hyphal length produced during fruiting is a quantitative trait resulting from the combined effects of multiple genetic loci, including the mating type (MAT) locus.Importantly, the alpha allele of the MAT locus enhanced hyphal growth compared with the a allele.MAC1 allelic differences contribute to phenotypic variation, and mac1Delta mutants exhibit defects in filamentation, melanin production, and high temperature growth.

View Article: PubMed Central - PubMed

Affiliation: Department of Molecular Genetics and Microbiology, Duke University Medical Center, Durham, North Carolina, United States of America.

ABSTRACT
Cryptococcus neoformans is a fungal human pathogen with a bipolar mating system. It undergoes a dimorphic transition from a unicellular yeast to hyphal filamentous growth during mating and monokaryotic fruiting. The traditional sexual cycle that leads to the production of infectious basidiospores involves cells of both alpha and a mating type. Monokaryotic fruiting is a modified form of sexual reproduction that involves cells of the same mating type, most commonly alpha, which is the predominant mating type in both the environment and clinical isolates. However, some a isolates can also undergo monokaryotic fruiting. To determine whether mating type and other genetic loci contribute to the differences in fruiting observed between alpha and a cells, we applied quantitative trait loci (QTL) mapping to an inbred population of F2 progeny. We discovered that variation in hyphal length produced during fruiting is a quantitative trait resulting from the combined effects of multiple genetic loci, including the mating type (MAT) locus. Importantly, the alpha allele of the MAT locus enhanced hyphal growth compared with the a allele. Other virulence traits, including melanization and growth at 39 degrees C, also are quantitative traits that share a common QTL with hyphal growth. The Mac1 transcription factor, encoded in this common QTL, regulates copper homeostasis. MAC1 allelic differences contribute to phenotypic variation, and mac1Delta mutants exhibit defects in filamentation, melanin production, and high temperature growth. Further characterization of these QTL regions will reveal additional quantitative trait genes controlling biological processes central to fungal development and pathogenicity.

Show MeSH
Related in: MedlinePlus