Genomics and Applied Biology 2016, Vol.7, No.4, 1-8
4
where δ
2
IC is the variance among IC and δ
2
e is the residual variance.
3 Result
3.1 Presence and variation of natural antibodies against KLH titres in Serum of IC
Natural antibodies binding KLH were detected for all IgA, IgG and IgM isotypes in IC serum. The analysis of
variance showed significant difference (p˂0.0001) with time of sampling being the main source of variation. IgM
concentration/titre value had the highest means but with minimum variance and standard error of the mean. The
IgG had the highest variance and standard error of the mean with moderate means (Table 1)
Table 1 The Means and standard deviations of Isotype on the levels of Nabs titres of IC against KLH antigens. The IgM had higher
Nabs titres with lower standard error (SE)
Isotype
Range
Mean
SE
Variance
Minimum
Maximum
IgM
3.045
0.031
0.0234
2.59
3.46
IgG
1.575
0.110
0.2916
0.37
2.94
IgA
1.013
0.039
0.0369
0.63
1.53
3.2 Repeatability of natural antibodies titers
Natural antibodies (IgA, IgG and IgM) titers of IC were determined at 4 points to assess their repeatability. The
estimated repeatability for IgA, IgG and IgM was 0.99, 0.68 and 0.99 respectively with IgG isotype showing
highest variance (Table 2).
Table 2: Natural IgA, IgM and IgG isotypes antibodies titers binding keyhole limpet hemocyanin in blood serum of IC; overall
variance, variance within and among IC, significance of variation and estimates of repeatability
Parameter
IgM
IgG
IgA
Overall variance
0.0180
0.309261
0.03827
Variance among IC
0.0123
0.3007
0.03790
Variance within IC
0.0057
0.000061
0.00037
Variation among IC (p values)
˂0.001
˂0.0001
˂0.605
Repeatability
0.68
0.99
0.99
4 Discussion
The lack of effective control measures for infectious diseases (management, vaccination and prophylaxis) in
livestock not only causes significant economic losses but may also endanger human health through zoonosis,
compromise animal welfare and food security (Stear et al. 2012). The use of genetic selection of animal for traits
of resistance to infection has been presented as the “ultimate tool in sustainable disease control” (Waller, 2006;
Khobondo et al. 2014; Khobondo et al. 15b). Disease resistance and immune response is a complex trait
polygenically expressed with several immune proteins. Due to this complexity, the most important and rate
limiting challenge for disease genetic studies is likely to be obtaining suitable phenotypes (immune parameter). In
goats and sheep for example, selection is based on the phenotyping of relevant traits such as zootechnical
performance, Fecal Egg Count (FEC), and measures of anaemia and blood eosinophilia under conditions of either
natural or experimental nematode infection (Mandonnet et al. 2014). In cattle, several immune parameters have
been reported to be potentially related to susceptibility or resistance to various diseases (Thompson-Csrispi et al.
2013). These include soluble mediators like Nabs, cytokines, antimicrobial peptides and complement proteins, and
cellular components like B, T and NK cells, y-T cells and granulocytes (Ploegaert et al. 2008). Therefore, choice
of immune parameter for disease resistance study is critical (Biochard and Brochard, 2012). For example,
specificity of acquired immunity is limiting to other pathogen except the one the animal has been primed with
before. Therefore, natural antibodies could be promising since it is polyreactive and non specific despite being
slow to combat pathogens.
