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Validation of test-statistics: QQ-plot
Figure 1 gives the QQ plots for four mastitis-related traits obtained in both GWAS and Haplotype-based association. The four plots from haplotype-based association were all based on haplotype reconstruction with phasing parameter “scale” =4.0. The QQ plot of phasing with scale=2.0 showed severe false positives in markers’ distribution (Figure 6 in discussion), whose mapping result was discarded in this study in order to maintain the accuracy of association. Therfore, “scale”=4.0 was regarded as a better setting of parameter in this study, and the followed results from haplotype-based association were all based on scale=4.0.
Figure 1. QQ plots of –log10P resulting from GWAS (first line) and Haplotype-based Association (second line) for traits: Abscess(case-control), Abscess(category), Infect status, LSCS, from left to right within each line. The red diagonal line is the standard y=x, representing Observed p-values = Expected p-values following null hypothesis. Dots on this line or very close to it represent SNPs that follow null hypothesis with no significant association with the trait. Dots obviously deviated from this line correspond to SNPs that disobey null hypothesis and were significant SNPs.
According to Figure 1, all plots gave reasonable distributions of p-values of markers, with major SNPs following null hypothesis and only a few deviated SNPs indicating significant SNPs. This result indicated a good correction of population stratification in our model-based association.
However, false positives may still exist in our analysis: In both GWAS and Haplotype-based association, plots of abscess traits (Abscess(case-control), Abscess(category)) show slight over-estimation of p-values of a few markers, which may lead to presence of false positives in the test-statistics. This infers a certain degree of fitting problem of our model, which may come from the definition of the model itself, or due to the limited number of animals and cases in abscess traits.
QTL mapping and potential QTL regions
The result of QTL mapping was summarized in Table 3. In GWAS, 14 chromosome-wise significant SNPs over 11 chromosomes were detected, within which 3 are genome-wise significant SNPs separately distributed on OAR5, OAR21, OAR24. In haplotype-based association, 24 chromosome-wise significant SNPs over 13 chromosomes were detected, with 1 genome-wise significant SNP on OAR25. Among all these regions, 4 regions were found significant in both association methods (Table 3). These 4 regions shared by both methods were thought to be candidate QTLs for their respective traits. The details of these 4 interesting regions were described below trait by trait. Manhattan plots of all traits for both association methods are shown in Figure 2.
For Abscess(case-control), region 95.9-96.7 Mb on OAR5 was detected in both methods significantly associated with mammary abscess in Lacaune sheep (Table 4). In addition, there are also 5 regions on OAR2, 4, 8, 20 which showed significance in one method and moderate p-values in the other method. Since Bonferroni correction is generally a serious method in significance testing, these 5 regions may also be interesting in affecting mammary abscess but need further validation.
The line in bold shows the region significant in both association methods.
1: The intervals of the QTLs were defined based on the QTL regions found in two association methods.
For trait Abscess(category), region 14.5-16.6 Mb on OAR8 was detected in both methods significantly associated with mammary abscess (Table 5). Other 2 regions on OAR5 and OAR8 are also interesting for abscess since they were detected significant in GWAS and showed moderate p-values in Haplotype association.
Table 5. Potential QTL regions in Abscess(category) from GWAS and Haplotype association. The line in bold shows the region significant in two association methods.
By horizontally comparing the results from Abscess(case-control) and Abscess(category) (Table 4 & Table 5), it is interesting to find that the two regions, 95.9-96.7 Mb on OAR5 and 14.5-16.6 Mb on OAR8, were shared by both these two abscess traits as significant regions for QTLs. This may infer a general relationship between these two regions and mammary abscess in Lacaune sheep. Figure 3 and Figure 4 show the Manhattan plots of these two candidate regions on their chromosomes, respectively.
Figure 3. Manhattan plots on OAR5 for Trait Abscess(case-control): Region 95.9-96.7Mb showed significant association with Abscess(case-control) in both GWAS and Haplotype association. The black line indicates the genome-wise significance threshold, and the red line indicates the chromosome-wise significance threshold.
Figure 4. Manhattan plots on OAR8 for Trait Abscess(category): Region 14.5-16.6 Mb showed potential association with Abscess(category) in both GWAS and Haplotype-based association. The black line indicates the genome-wise significance threshold, and the red line indicates the chromosome-wise significance threshold.
Apart from the shared regions by the two association methods, haplotype-based association detected two other regions that had been validated by previous QTL detection projects on LSCS trait in Lacaune sheep (Rupp et al., 2011; unpublished paper, 2013). These two regions were detected associated with two mammary abscess traits (from haplotype-based association) and LSCS trait, which infer themselves as general QTLs underlying mastitis infection. Table 6 gives the information of these two QTLs detected in this study and in previous study.
Complexity of genetic determinism of mastitis and fine-phenotyping of mastitis-related traits
n summary, five interesting regions were detected in this study to be significantly associated with mastitis-related traits (Table 9).
Among these five regions, the region on OAR16 (around 30Mb) is shared by three mastitis-related traits detected from this study and previous study both on Lacaune sheep. This result indicated a big possibility of existence of a candidate QTL around 30Mb on OAR16 highly related to general mastitis infection. In addition, the region on OAR20 is also very interesting since it has been detected both related to SCC-based trait and mammary abscess trait, which also infers a general association with the mastitis. Moreover, sheep MHC Class I and Class II genes are reported partly located around 25Mb – 27Mb on OAR20 (Sheep Genome Browser; http://www.livestockgenomics.csiro.au/cgi-bin/gbrowse/oarv3.1/). Since loci on the same chromosome are generally in different extents of linkage, further study can be carried out to explore the genetic linkage between MHC loci and the regions detected in this study on OAR20 (49.1 – 49.5Mb). In addition, two regions on OAR5 and OAR8 were detected specifically related to mammary abscess. This may infer a specific immune pathway of forming mammary abscess in response to chronic mastitis. However, due to the limited number of cases in abscess traits in our dataset (20 cases in Ascess (case-control) and 41 cases in abscess (category)), the power of QTL mapping may be not high enough to detect medium and small QTLs for abscess in this study. More animals and cases are needed in order to detect more QTLs for abscess and at the same time check the obained two regions on OAR5 and OAR8.
Table of contents :
INTRODUCTION
MATERIAL AND METHODS
ANIMALS
PHENOTYPES
GENOTYPES AND QUALITY CONTROL
STATISTICAL ANALYSIS
Genome-wide association study (GWAS)
Haplotype-based Association Study
RESULTS
VALIDATION OF TEST-STATISTICS: QQ-PLOT
QTL MAPPING AND POTENTIAL QTL REGIONS
Mammary abscess traits: Abscess(case-control) and Abscess(category)
Somatic Cell Count traits: Infect status and LSCS
DISCUSSION
COMPLEXITY OF GENETIC DETERMINISM OF MASTITIS AND FINE-PHENOTYPING OFMASTITIS-RELATED TRAITS
GWAS AND HAPLOTYPE-BASED ASSOCIATION
HAPLOTYPE RECONSTRUCTION
CONCLUSION
ACKNOWLEDGEMENT
REFERENCES
