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Genome-wide association analysis and genomic prediction of Mycobacterium avium subspecies paratuberculosis infection in US Jersey cattle.

Zare Y, Shook GE, Collins MT, Kirkpatrick BW - PLoS ONE (2014)

Bottom Line: Correspondence between results of GRAMMAR-GC and Bayes C was high (70-80% of most significant SNPs in common).These SNPs could potentially be associated with causal variants underlying susceptibility to MAP infection in Jersey cattle.Predictive performance of the model developed by Bayes C for prediction of infection status of animals in validation set was low (55% probability of correct ranking of paired case and control samples).

View Article: PubMed Central - PubMed

Affiliation: College of Agricultural and Life Sciences, Department of Animal Sciences, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.

ABSTRACT
Paratuberculosis (Johne's disease), an enteric disorder in ruminants caused by Mycobacterium avium subspecies paratuberculosis (MAP), causes economic losses in excess of $200 million annually to the US dairy industry. To identify genomic regions underlying susceptibility to MAP infection in Jersey cattle, a case-control genome-wide association study (GWAS) was performed. Blood and fecal samples were collected from ∼ 5,000 mature cows in 30 commercial Jersey herds from across the US. Discovery data consisted of 450 cases and 439 controls genotyped with the Illumina BovineSNP50 BeadChip. Cases were animals with positive ELISA and fecal culture (FC) results. Controls were animals negative to both ELISA and FC tests that matched cases on birth date and herd. Validation data consisted of 180 animals including 90 cases (positive to FC) and 90 controls (negative to ELISA and FC), selected from discovery herds and genotyped by Illumina BovineLD BeadChip (∼ 7K SNPs). Two analytical approaches were used: single-marker GWAS using the GRAMMAR-GC method and Bayesian variable selection (Bayes C) using GenSel software. GRAMMAR-GC identified one SNP on BTA7 at 68 megabases (Mb) surpassing a significance threshold of 5 × 10(-5). ARS-BFGL-NGS-11887 on BTA23 (27.7 Mb) accounted for the highest percentage of genetic variance (3.3%) in the Bayes C analysis. SNPs identified in common by GRAMMAR-GC and Bayes C in both discovery and combined data were mapped to BTA23 (27, 29 and 44 Mb), 3 (100, 101, 106 and 107 Mb) and 17 (57 Mb). Correspondence between results of GRAMMAR-GC and Bayes C was high (70-80% of most significant SNPs in common). These SNPs could potentially be associated with causal variants underlying susceptibility to MAP infection in Jersey cattle. Predictive performance of the model developed by Bayes C for prediction of infection status of animals in validation set was low (55% probability of correct ranking of paired case and control samples).

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Manhattan plots displaying the results of single-marker genome-wide association analysis (GRAMMAR-GC) for susceptibility to MAP infection.A) Discovery data (32,587 SNPs) B) Validation data (31,065 SNPs) C) Combined data (32,375 SNPs). Y-axis represents –log10 of P-values corrected by genomic control (GC) and X-axis represents chromosomes. Thresholds represent P-values of 10−4 and 5×10−4 for moderate and suggestive associations, respectively.
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pone-0088380-g001: Manhattan plots displaying the results of single-marker genome-wide association analysis (GRAMMAR-GC) for susceptibility to MAP infection.A) Discovery data (32,587 SNPs) B) Validation data (31,065 SNPs) C) Combined data (32,375 SNPs). Y-axis represents –log10 of P-values corrected by genomic control (GC) and X-axis represents chromosomes. Thresholds represent P-values of 10−4 and 5×10−4 for moderate and suggestive associations, respectively.

Mentions: Appearance of a single cluster in the MDS plot suggested the absence of population substructure in the discovery data (Figure S1-A). The deflation factor () was estimated to be 0.96 (SE = 9×10−5). The GC-corrected P-values for the majority of SNPs corresponded well to the expected P-values under H0 of no association, with a few departures indicating association with the trait under study (Figure S2-A). No SNP passed the threshold of strong association (Figure 1-A). The most significant SNP was identified on BTA7 position 68 Mb (P = 4.9×10−5) surpassing the threshold for moderate association (Table 2). The second most significant SNP (P = 5.9×10−5) was located on BTA3 (107 Mb) and failed to pass the moderate threshold (Figure 1-A, Table 2). The 20 most significant SNPs (P<5×10−4) were located on 8 chromosomes including BTA7, 3, 23, 17, 6, 1, 5 and 13 (in order of significance) (Table 2). On BTA3 a total of six SNPs covering 101 to 107 Mb were identified (Table 2). These six SNPs represented four distinct genomic regions based on LD between pairs of SNPs; three SNPs (at 100.9 Mb, 101 Mb and 102.2 Mb) were in high LD (average pair wise r2 = 0.67) representing one genomic region and the other three SNPs each represented one region. Also, six SNPs were identified on BTA23 representing a total of four regions including 27.7 Mb, 29.3–32.6 Mb (r2 = 0.63), 44.4 Mb and one region at 7.8 Mb (r2 = 0.54 for SNPs at 7.84 and 7.87 Mb) (Table 2). BTA1 contained three SNPs located at positions 125.6, 135.3 and 141.9 Mb (P<5×10−4) representing three genomic regions based on a relatively low average pair wise r2 (0.25) (Table 2).


Genome-wide association analysis and genomic prediction of Mycobacterium avium subspecies paratuberculosis infection in US Jersey cattle.

Zare Y, Shook GE, Collins MT, Kirkpatrick BW - PLoS ONE (2014)

Manhattan plots displaying the results of single-marker genome-wide association analysis (GRAMMAR-GC) for susceptibility to MAP infection.A) Discovery data (32,587 SNPs) B) Validation data (31,065 SNPs) C) Combined data (32,375 SNPs). Y-axis represents –log10 of P-values corrected by genomic control (GC) and X-axis represents chromosomes. Thresholds represent P-values of 10−4 and 5×10−4 for moderate and suggestive associations, respectively.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3921184&req=5

pone-0088380-g001: Manhattan plots displaying the results of single-marker genome-wide association analysis (GRAMMAR-GC) for susceptibility to MAP infection.A) Discovery data (32,587 SNPs) B) Validation data (31,065 SNPs) C) Combined data (32,375 SNPs). Y-axis represents –log10 of P-values corrected by genomic control (GC) and X-axis represents chromosomes. Thresholds represent P-values of 10−4 and 5×10−4 for moderate and suggestive associations, respectively.
Mentions: Appearance of a single cluster in the MDS plot suggested the absence of population substructure in the discovery data (Figure S1-A). The deflation factor () was estimated to be 0.96 (SE = 9×10−5). The GC-corrected P-values for the majority of SNPs corresponded well to the expected P-values under H0 of no association, with a few departures indicating association with the trait under study (Figure S2-A). No SNP passed the threshold of strong association (Figure 1-A). The most significant SNP was identified on BTA7 position 68 Mb (P = 4.9×10−5) surpassing the threshold for moderate association (Table 2). The second most significant SNP (P = 5.9×10−5) was located on BTA3 (107 Mb) and failed to pass the moderate threshold (Figure 1-A, Table 2). The 20 most significant SNPs (P<5×10−4) were located on 8 chromosomes including BTA7, 3, 23, 17, 6, 1, 5 and 13 (in order of significance) (Table 2). On BTA3 a total of six SNPs covering 101 to 107 Mb were identified (Table 2). These six SNPs represented four distinct genomic regions based on LD between pairs of SNPs; three SNPs (at 100.9 Mb, 101 Mb and 102.2 Mb) were in high LD (average pair wise r2 = 0.67) representing one genomic region and the other three SNPs each represented one region. Also, six SNPs were identified on BTA23 representing a total of four regions including 27.7 Mb, 29.3–32.6 Mb (r2 = 0.63), 44.4 Mb and one region at 7.8 Mb (r2 = 0.54 for SNPs at 7.84 and 7.87 Mb) (Table 2). BTA1 contained three SNPs located at positions 125.6, 135.3 and 141.9 Mb (P<5×10−4) representing three genomic regions based on a relatively low average pair wise r2 (0.25) (Table 2).

Bottom Line: Correspondence between results of GRAMMAR-GC and Bayes C was high (70-80% of most significant SNPs in common).These SNPs could potentially be associated with causal variants underlying susceptibility to MAP infection in Jersey cattle.Predictive performance of the model developed by Bayes C for prediction of infection status of animals in validation set was low (55% probability of correct ranking of paired case and control samples).

View Article: PubMed Central - PubMed

Affiliation: College of Agricultural and Life Sciences, Department of Animal Sciences, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.

ABSTRACT
Paratuberculosis (Johne's disease), an enteric disorder in ruminants caused by Mycobacterium avium subspecies paratuberculosis (MAP), causes economic losses in excess of $200 million annually to the US dairy industry. To identify genomic regions underlying susceptibility to MAP infection in Jersey cattle, a case-control genome-wide association study (GWAS) was performed. Blood and fecal samples were collected from ∼ 5,000 mature cows in 30 commercial Jersey herds from across the US. Discovery data consisted of 450 cases and 439 controls genotyped with the Illumina BovineSNP50 BeadChip. Cases were animals with positive ELISA and fecal culture (FC) results. Controls were animals negative to both ELISA and FC tests that matched cases on birth date and herd. Validation data consisted of 180 animals including 90 cases (positive to FC) and 90 controls (negative to ELISA and FC), selected from discovery herds and genotyped by Illumina BovineLD BeadChip (∼ 7K SNPs). Two analytical approaches were used: single-marker GWAS using the GRAMMAR-GC method and Bayesian variable selection (Bayes C) using GenSel software. GRAMMAR-GC identified one SNP on BTA7 at 68 megabases (Mb) surpassing a significance threshold of 5 × 10(-5). ARS-BFGL-NGS-11887 on BTA23 (27.7 Mb) accounted for the highest percentage of genetic variance (3.3%) in the Bayes C analysis. SNPs identified in common by GRAMMAR-GC and Bayes C in both discovery and combined data were mapped to BTA23 (27, 29 and 44 Mb), 3 (100, 101, 106 and 107 Mb) and 17 (57 Mb). Correspondence between results of GRAMMAR-GC and Bayes C was high (70-80% of most significant SNPs in common). These SNPs could potentially be associated with causal variants underlying susceptibility to MAP infection in Jersey cattle. Predictive performance of the model developed by Bayes C for prediction of infection status of animals in validation set was low (55% probability of correct ranking of paired case and control samples).

Show MeSH
Related in: MedlinePlus