Genetic resistance to transmissible spongiform encephalopathies (TSE) in goats

Abstract

Breeding programmes to promote resistance to classical scrapie, similar to those for sheep in existing transmissible spongiform encephalopathies (TSE) regulations, have not been established in goats. The European Commission requested a scientific opinion from EFSA on the current knowledge of genetic resistance to TSE in goats. An evaluation tool, which considers both the weight of evidence and strength of resistance to classical scrapie of alleles in the goat PRNP gene, was developed and applied to nine selected alleles of interest. Using the tool, the quality and certainty of the field and experimental data are considered robust enough to conclude that the K222, D146 and S146 alleles both confer genetic resistance against classical scrapie strains known to occur naturally in the EU goat population, with which they have been challenged both experimentally and under field conditions. The weight of evidence for K222 is greater than that currently available for the D146 and S146 alleles and for the ARR allele in sheep in 2001. Breeding for resistance can be an effective tool for controlling classical scrapie in goats and it could be an option available to member states, both at herd and population levels. There is insufficient evidence to assess the impact of K222, D146 and S146 alleles on susceptibility to atypical scrapie and bovine spongiform encephalopathy (BSE), or on health and production traits. These alleles are heterogeneously distributed across the EU Member States and goat breeds, but often at low frequencies (< 10%). Given these low frequencies, high selection pressure may have an adverse effect on genetic diversity so any breeding for resistance programmes should be developed at Member States, rather than EU level and their impact monitored, with particular attention to the potential for any negative impact in rare or small population breeds.

Keywords: TSE; classical; genetics; goats; resistance; scrapie.

Figure 1

Number of goats (head) in the EU in 2013. No data from SE

Figure 2

Number of goat holdings in the EU in 2013. No data from SE

Figure 3

Geographical distribution of caprine classical scrapie (CS) and atypical scrapie (AS) within EU28 based on surveillance carried out between 2002 and 2015

1. Green: MS that reported both CS and AS. Blue: MS that reported only CS. Yellow: MS that reported only AS. White: MS that have not reported caprine scrapie.

Figure 4

Stream‐adjusted prevalence of classical scrapie (CS) in goats within EU28 and based on active surveillance data

1. Number of cases/10,000 rapid tests standardised by stream, i.e., SHC vs. NSHC during the period 2002–2015. The proportion of tests carried out in all the 28 MSs in the NSHC vs SHC in goats has been used to define the baseline population for the direct standardisation. The sizes of the blue dots are proportional to the prevalence.

Figure 5

Temporal trend of CS in goats in EU MS where the disease was reported over at least 3 years during the period 2002–2015

1. Crosses (+) indicate the annual stream‐adjusted prevalence (cases per 10,000 rapid tests). Lines show the linear trend (black line) and the bounds of the 95% CI (grey lines).

Figure 6

Temporal trends of AS in goats in ES, FR, IT and PT, during the period 2002–2015

1. Crosses (+) indicate the annual stream‐adjusted prevalence (cases per 10,000 rapid tests). Lines show the linear trend (black line) and the bounds of the 95% CI (grey lines).

Figure 7

PrP^res analysis of scrapie strains by triplex‐Western blotting On the same blot, three antibodies were applied that have different epitopes on the PrP sequence: 12B2 for N‐terminus, Sha31 for the core sequence, and SAF84 somewhat more C terminal from Sha31 (Biacabe et al., 2007). By calculating ratios between epitope signals, specific properties of PrP^{R es} appear that discriminate between the TSE types classical scrapie, BSE and CH1641. Each dot represents a separate goat TSE isolate. The IT scrapie cases exhibit a reduced N terminus epitope presence intermediate between BSE/CH1641 and the remaining classical scrapie samples (vertical axis). CH1641 can be distinguished from BSE due to the presence of a dual PrP^{R es} triple band population (horizontal axis), only one goat isolate in the geographical study occurred clearly in the CH1641 area where also an experimental goat CH1641 isolate was located. Sheep scrapie cases from the NL (orange filled squares), experimental caprine CH1641, experimental caprine BSE, experimental caprine scrapie (Lacroux et al., 2014), and bovine classical and atypical BSE samples were used as controls. Source: data from the GoatBSE consortium study. Graph prepared by Jan Langeveld.

Figure 8

Scale of the weight of evidence on genetic resistance of the caprine and ovine PRNP genes

Figure 9

Scale of the weight of evidence on genetic resistance of the caprine PRNP gene and strength of resistance of selected alleles according to the two‐tier tool Definitions of the two tiers are given in Sections 3.3.5.1 and 3.3.5.2. For comparison, the evidence of resistance with the ARR allele in sheep between 2001 and 2017 (see Section 3.4.3) has been added. Note: the G‐STOP has not been included in the tool.

Figure 10

Frequency of goats with alleles of interest included in surveys across EU (GoatBSE deliverable D1.2) (http://www.goattse.eu/site/files/goatBSE_Deliverable_D1-2_21sep2011.pdf)

Figure 11

Distribution of the codon 146 genotypes in the goat population of Cyprus for the period 2010–2016 (Veterinary Services. Ministry of Agriculture, Rural Development and Environment. Cyprus)

Figure 12

Scheme for a breeding programme for resistance to scrapie in goats, based on sheep breeds

1. *The selection regime is based on allele frequency and population size (lower right corner), whereby under mild selection heterozygous and homozygous bucks are used indiscriminately, under moderate selection homozygous rams are used preferably but supplemented with heterozygous bucks, and under strong selection homozygous rams are used exclusively. Limits for classifying populations as large, medium or small have not been determined in goat breeds, but were < 750 for small breeds and > 3,750 for large breeds in sheep. Scheme designed by Jack J. Windig.

Figure E.1

Discriminatory western blot of the 12 isolates that were used in the homogenate for the oral and intracerebral challenges

Figure E.2

Lesion profiles from Tg338 and tgShpXl mice challenged with the homogenate that was used to challenge the goats

1. Only clinically positive mice contributed to the lesion profiles. Ten mice of each mouse line were challenged. Numbers in brackets indicate the average IP of the mice which contributed to the profile. n = number of mice which contributed to the profile.

Figure E.3

Distribution of the codon 146 genotypes in the goat population of Cyprus for the period 2010–2016

Figure E.4

Survival curves of NN146 and ND146 groups

Figure E.5

Survival curves of NN146 and NS146 groups

Figure E.6

Survival curves of NN146 and DD146 groups

Figure E.7

Survival curves of NN146 and SS146 groups

Figure E.8

Annual number of TSE index cases per category of farm in CY