Polymorphism analysis of prion protein gene in 11 Pakistani goat breeds

ABSTRACT

The association between caprine PrP gene polymorphisms and its susceptibility to scrapie has been investigated in current years. As the ORF of the PrP gene is extremely erratic in different breeds of goats, we studied the PrP gene polymorphisms in 80 goats which belong to 11 Pakistani indigenous goat breeds from all provinces of Pakistan. A total of 6 distinct polymorphic sites (one novel) with amino acid substitutions were identified in the PrP gene which includes 126 (A -> G), 304 (G -> T), 379 (A -> G), 414 (C -> T), 428 (A -> G) and 718 (C -> T). The locus c.428 was found highly polymorphic in all breeds as compare to other loci. On the basis of these PrP variants NJ phylogenetic tree was constructed through MEGA6.1 which showed that all goat breeds along with domestic sheep and Mauflon sheep appeared as in one clade and sharing its most recent common ancestors (MRCA) with deer species while Protein analysis has shown that these polymorphisms can lead to varied primary, secondary and tertiary structure of protein. Based on these polymorphic variants, genetic distance, multidimensional scaling plot and principal component analyses revealed the clear picture regarding greater number of substitutions in cattle PrP regions as compared to the small ruminant species. In particular these findings may pinpoint the fundamental control over the scrapie in Capra hircus on genetic basis.

KEYWORDS:

• Goat
• neurodegenerative
• PrP
• PrP^C
• PrP^Sc
• Prion protein
• scrapie
• TSEs

INTRODUCTION

The accumulation of protein aggregates is an amalgamating feature of a large class protein conformational disorders that ultimately target the central nervous system and lead to progressive neurodegeneration e.g. Alzheimer disease and Prion diseases.¹ The prion theory forecasts that certain mutations in PrP gene may result in unstable PrP molecules with transitional conformations, thus initiating the disease process² and are accountable for much of the disparity in pathology and disease transmission. Transmissible spongiform encephalopathies (TSEs), or prion diseases, have cases that arise sporadically (Creutzfeldt-Jakob disease [CJD]) or are inherited (fatal familial insomnia).³ Transmission mechanism of prion diseases across the mammalian species is not as such effective as within species⁴ but being a zoonotic and fatal potential, scrapie prions indicated transmission efficacy comparable to BSE causing CJD.⁵

Scrapie is a mortal, incurable and transmissible neurodegenerative disease of sheep and goats which occur due to the conversion of normal cell surface glycoprotein (PrP^C) into conformationally altered isoform (PrP^Sc) in the absence of nucleic acids.⁶ The key difference flanked by the 2 forms is that PrP^C is entirely sensitive to proteases, while PrP^Sc is only degraded in part and its amino-terminal end removed.⁷ As a natural host of scrapie both in sheep and goats showed analogous incubation period while the clinical manifestation perhaps slightly different. Moreover, the supplementary transmissible spongiform encephalopathies (TSEs) which comprise of bovine spongiform encephalopathy (BSE), Creutzfeldt–Jakob disease (CJD) and transmissible mink encephalopathy (TME), usually portrayed by accretion of an anomalous and disease specific isoform (PrP^Sc) of an usual host-encoded cellular prion protein (PrP^C) in the central nervous system. PrP^C is also found in number of peripheral cell types along with glial cells of the CNS but in low level.^8,9,10 Scrapie research has centered, for many years on developing more realistic live animal tests to make a diagnosis of infected animals; the identification of the genetic basis; and its probable application in breeding plans. Previously, it has been reported in Pakistan that caprine PrP polymorphisms was present in different breeds of sheep and goats such as in Beetal, Tedy and Pak Angora and it was associated with resistance to some important zoonotic and fatal group of diseases which may cross species barrier.^8,11 Monitoring and investigation about the transmission of these agents via blood play vital role and has substantial concern regarding the safety of blood and its products.¹²

In Pakistan goats are kept mainly for milk and meat purpose and play a critical role in the economy of country as well as farmers (Table 1). Presently there are about 58.3 million heads of goats in Pakistan and their population is increasing at rate of 3% per annum.¹³ As small ruminants are the only animals which are migrating in industrialized and developing countries, different zoonotic diseases spotted in small ruminants are mainly transmitted to human beings as occupational infections which badly affect the breeders and veterinarians. Therefore, the investigation of biological activity of PrP^C remained crucial to understand the pathogenesis of prion associated diseases through contaminated food.^7,14,15 Though no scrapie case has been documented yet in any of Pakistani goats, identifying the PrP gene polymorphism spectrum in these species may be useful for future breeding plans in terms of scrapie resistance.

TABLE 1. Phenotypic characteristics of goat breeds in Pakistan under study.

Breed	Type	Body Color	Size	Average body weight (kg)	General Description
Barbari	Milk	White with small light brown patches	Large	Male(40)/female(24)	Short size, tubular and erract ears which mainly found in Gujrat, Jhelum and Sargodha districts in Punjab Province.
Beetal	Milk/Meat	Golden	Large	Male(55)/female(45)	Massive head, Roman nose, long broad and pendulous ears; spiraled horns, longer in males; long stout legs; short tail; udder well-developed and long teats, milk yield 190 liters in a 150 days lactation; more than 50% twin or triplet births and Found in Punjab, Pakistan and India.
Bari	Meat	White with tan or black patches	Medium	Male(30)/female(24)	Long haired, all males and small number of females are bearded
Damani	Milk	black hair coat with tan head and legs	Medium	Male(35)/female(30)	a long hair coat and well developed udders mainly found in the Bannu and Dera Ismail Khan districts in NWF Province, Pakistan.
Jattal	Milk/Meat	White and black or white with gray, red or black spots	Small	Male(23)/female(19)	mainly found in AJK
Kaghani	Meat	a white, gray, brown or black body coat	Large	Male(37)/female(32)	used for the production of cashmere fiber and meat
Khurasani	Milk/Meat	black long hair coat	Medium	Male(30)/female(25)	turned back horns and fine second hair coat in winter while Khurasan, Toba Kakari, Suleiman mountains region of Zhob and Sherani districts, Loralai, Ziarat, Chaghai and Pishin districts are its main niche
Labri	Milk/Meat	White long hairy coat on body	Large	Male(45)/female(35)	Chilas valley in Diamir district in Northern Areas
Lehri	Meat	Brown and white spots on body	Large	Male(43)/female(39)	Found in Balochistan province and in Kachi area of Sibi
Pahari	Milk/Meat	White long hairy body	Large	Male(50)/female(43)	Found in Punjab and Balochistan provinces
Tapri	Milk/Meat	White coated body	Medium	Male(33)/female(25)	Found in Sindh province

MATERIALS AND METHODS

Study Animals and Management Practices

Pakistan is located in South Asia possessing tropical and subtropical environment that is known to be hot (35 + 13°C) and humid (45.38% ± 13.11%) in some areas.¹³ During summer in Punjab the temperature may go up to 48°C with humidity level (39%). The goats and other livestock animals in Pakistan are kept under similar natural climatic conditions. Adequate feed and water are bequeathed for their maintenance and production. To protect animals from harsh climatic conditions and predators semi closed traditional shelters system were employed where routine vaccination and de-worming were routinely carried out.

Sample Collection

A total of 80 blood samples (3ml from each), having specific phenotypic characteristics were cautiously collected from 11 Pakistani goat breeds as of Jattal (11), Barbari (07), Lebri (09), Tapri (03), Kaghani (05), Khurasani (08), Beetal (11), Bari (03), Lehri (10), Pahari (07) and Damani (06) from all 4 provinces of Pakistan along with Azad Jammu & Kashmir region (AJK) and stored at −20°C till further processing. All the selected goat breeds were identified by an expert and their history about the age; breed and sex were also obtained from the farmers.

Genetic Analysis

Genomic DNA was extracted from EDTA-treated blood buffy coat using a standard DNA isolation protocol as previously described.¹⁶ A PCR was standardized for the specific amplification of 876 bp of exon 3 of the PrP gene and for this, a reaction mixture of a total volume of 30 µl was prepared containing nuclease free water, 1x PCR buffer (NH₄)₂ SO₄, 50 mM MgCl₂, 10 mM dNTPs mix, 20 pmol each of the forward (5′-1CTTTAAGTGATTTTTACGTGG21-3′) and reverse primers (5′-854TGGCAAAGATTAAGAAGATAATG876-3′), 0.2 unit of Taq DNA Polymerase (Fermentas, Cat #EP0402) and 1µl of DNA as template. The standard amount of PCR reaction mixture, DNA samples, Primers and water was used for amplification of PrP gene. Amplification reactions were performed with a Thermal Cycler (iCycler BioRad, USA) conditions comprised of initial denaturation at 94°C for 05 minutes, followed by denaturation at 94°C for 45 sec, annealing at 60°C for 02 min and extension was at 72°C for 45 sec. Final extension was maintained at 72°C for 10 minutes and storage at 4°C. All amplicons were visualized by staining with ethidium bromide through the electrophoresis of a 05 µl reaction mixture on 2% agarose gels.

Sequence Analysis

Prior to Sanger sequencing, amplicons were cleaned using TIANquick Midi Purification Kit (Tiangen Biotech Beijing Co., Ltd.) while both sense and antisense strands of the amplified DNA were sequenced by using Big Dye terminator cycle sequencing chemistry v 3.1 (Applied Biosystems, USA) and electrophoresis was done by an automated DNA sequencer (ABI Prism 3130xL Genetic Analyzer, Applied Biosystems, USA) from 1st Base Laboratories Singapore. Sequences were analyzed through Codon Code aligner manually followed by the identification of novel SNPs detection.

Bioinformatics Tools

Codon Code aligner software was used to edit and align the PrP sequences while MEGAv.6 software¹⁷ was used to construct the phylogenetic trees and have insight of phylogeny of Pakistani goat breeds with other mammalian species (Fig. 1). We used homologous PrP sequences ranging from primate members to jawless vertebrate sequences. Moreover, the PrP gene coding sequence of all animals was sequenced and analyzed to identify polymorphisms in selected individuals. Single nucleotide polymorphism distributions were tabulated according to every nucleotide site (Table 2). Furthermore, variation profile was summarized in Table 3 where percentages with respect to being a breed a heterozygous, homozygous, or cumulative variation were calculated. Previously at the protein level, 40 6 amino acid polymorphisms have been described (Table 4).

FIGURE 1. Variation plot based on polymorphic contents taken from Table 5.

TABLE 2. Polymorphism observed in PrP gene in Pakistani goat breeds of meat and milk potential.

Breed	Sample ID	c.126	c.304	c.379	c.414	c.428	c.718
Barbari	B- 32	A			C		T
	B-30					G
	B-36	A/G			C/T	A/G	C/T
	B-56	A/G			C/T	A/G
	B-57					G
	B-58			A	C		T
	B- 61					A/G
Lebri,	L- 08	A/G			C/T	A/G	C/T
	L- 09	A/G			C/T		C/T
	L- 02	A/G	G/T		C/T	A/G	C/T
	L- 01					G
	L- 06					G
	L- 07					A/G
	L- 11					A/G
	L-12					A/G
	L-13					G
Tapri	T-53	A/G			C/T		C/T
	T-70					A/G
	T-51					G
Bari	Br-07					A/G
	Br-02					A/G
	Br-01					G
Khurasani	K-42	A/G			C/T		C/T
	K-33					A/G
	K-34					A/G
	K-27					G
	K-48	A/G			C/T	A/G	C/T
	K-31	A/G			C/T		C/T
	K-36					C/G
	K-45	A/G			C/T
Beetal	B-41	A/G			C/T	A/G	C/T
	B-03					A/G
	B-04				C/T	A/G
	B-04	A/G				A/G	C/T
	B-14					A/G
	B-20					A/G
	B-28					A/G
	B-46					G
	B-73	A/G		A/G	C/T	A/G
	B-26	A/G			C/T	A/G	C/T
	B-49	A/G			C/T	A/G	C/T
Jattal	J-38					A/G
	J-39	A/G			C/T	A/G	C/T
	J-43					A/G
	J-47					G
	J-49	A/G	G/T		C/T		C/T
	J-48					A/G
	J-46					G
	J-41					A/G
	J-50
	J-51					A/G
	J-11	A/G	G/T		C/T	A/G	C/T
Kaghani	Kg-06	A/G			C/T		C/T
	Kg-04					G
	Kg-07					A/G
	Kg-02					A/G
	Kg-03					A/G
Lehri	Lehri 20	A/G			C/T	A/G	C/T
	Lh-43	A		A/G	C
	Lh-36					G
	Lh-33					A/G
	Lh-30					A/G
	Lh-35					G
	Lh-40					A/G
	Lh-41					A/G
	Lh-37	A			C		C/T
	Lh-38	A			C
Pahari	P-01	A/G			C/T	A/G
	P-08	A/G	G/T		C/T		C/T
	P-03	A	G		C		T
	P-12	A/G	G/T		C/T	A/G	C/T
	P-09					G
	P-04					A/G
	P-06					G
Damani	D-03					G
	D-09					A/G
	D-11					G
	D-12					G
	D-13					A/G
	D-16					A/G

TABLE 3. Level of polymorphism summarized according to percentage observed at each nucleotide position.

Sample ID	c.126	c.304	c.379	c.414	c.428	c.718
Homozygous (%)	17.85714	16.66667	33.33333	20.68966	29.23077	13.04348
Heterozygous (%)	82.14286	83.33333	66.66667	79.31034	70.76923	86.95652
Polymorphic (%)	35	7.5	3.75	36.25	81.25	28.75

TABLE 4. Single nucleotide polymorphisms identified in the PrP region of animals all over the world.

SNPs Reported in literature	SNPs Reported in literature
W18R^32	R151H^35
V21A^33	R154H^33
L23P^33	P168Q^33
G37V^34	V179V^35
S39R^8	D181O^35
P42P^36	I185F^8
G49S^33	T194P^37
Q101R^32	F201F^32
Q101Q^32	T202T^38
G102W^25	K207K^5
K107K^33	R211Q^39
T110P^34	R211G^40
V125V^40	I218L^26
S127G^23,26	T219I^40
L133Q^38	T219T^41
M137I^38	Q220H^33
S138S^36	Q222K^34
I142M^36	Q222Q^32
I142T^37	K231R^26
I421I^32	G232W^32
H143R^36	G232G^41
N146D^39	L237L^8
N146S^26	S240P^36,42

TABLE 5. Comparison between studied PrP sequences of animals all over the world with indeginous genotypes of goat breeds of Pakistan. Entries in bold and underlined format in the reported column were also determined as amino acid polymorphisms in studied breeds. Similarly, one entry placed the 3^rd spot in the right most column was the novel polymorphism detected in indigenous goat population.

Residual Polymorphism
Reported		Reported in Pakistan	In our Breeds
W18R	R151H	S39R^8	G102W
V21A	R154H
L23P	P168Q
G37V	V179V	I142M^13
S39R	D181O		S127G
P42P	I185F
G49S	T194P	H143R^13
Q101R	F201F
Q101Q	T202T		N135S
G102W	K207K	N146S/D^13
K107K	R211Q
T110P	R211G
V125V	I218L	R154H^13	H143R
S127G	T219I
L133Q	T219T
M137I	Q220H	I185F^8
S138S	Q222K		K231R
I142M	Q222Q
I142T	K231R	R211Q^13
I421I	G232W
H143R	G232G		S240P
N146D	L237L	Q222K^13
N146S	S240P

Genetic Distance

Genetic distances between populations were calculated using Barry and Hartigan evolutionary model called ‘BH87’, asynchronous distance between homologous DNA sequences based on the observed proportions of changes among the 4 bases whereas “Bioconductor” statistical package in R was used to generate genetic distance matrix for selected species.

Multidimensional Scaling Plot

Multidimensional scaling method convert the structure in the similarity matrix to a simple geometrical picture: the larger the dissimilarity between 2 samples (evaluated through genetic distance profiling), the further apart the points representing the experiments in the picture may be. Furthermore, genetic relationship between groups were examined using an MDS plot of the genetic distance matrix in R.

Principal Component Analysis

Principal component analysis (PCA), a powerful multivariate investigative tool to identify patterns in specifically many dimensions, interrelated data sets and express the data sets by pinpointing their similarities and differences which is based on Eigen analysis. Therefore, PCA used here as a means of constructing an informative graphical representation of the data set by projecting the data onto a lower dimensional space. In the study, control and training data was presented in a 2 dimensions (2D) subspace of the first 2 PCs. The PCs derived by the Eigen analysis of correlation matrix (R = [r_ij]) was a linear combination of the original p variables (the species) and each PC uncorrelated with the other, meaning these were the new transformed data expressed in terms of the patterns existing in the original data set. The total PCs derived were equal to the number of original variables present in the dataset. The PCs formed were with decreasing order of magnitude of variance of the total variation in the data sets. Thus the first 2 PCs capturing most of the variation in the data set is visualized in a 2D representation. The coefficient of the variables in each of the linear combination, i.e. the PC was defined as loadings. The magnitude of these loadings represented the importance of each variable present. Thus a 2D representation of the loadings of the first 2 PCs were identified as any cluster structure present in the variables (80 PrP homologs), exhibiting the co-occurring pattern of individuals in the control and training data sets.

RESULTS

Observed SNP Profiles

Total six polymorphic sites (at positions 126, 304, 379, 414, 428 and 718) were observed in 80 individuals of 11 breeds which were most notably raised for meat and milk production in Pakistan. In general, c.428 position was found highly polymorphic in all breeds with homozygous G, A and A/G heterozygous genotypes (Table 2). In total, 81.25% of individuals were found polymorphic out of them 71.01% individuals were heterozygous for this particular site. Lowest percentage of polymorphism was achieved at c.379 as 3.75%. Similarly, significant percentage of polymorphisms were obtained at c.126, c.304, c.414 and c.718 sites as 35%, 7.5%, 36.25% and 28.75% respectively (Fig. 2). Heterozygous sites were also evaluated in proportion to their relative cumulative polymorphic variation. All individuals showed their preference for being highly heterozygous as compared to be homozygous (Table 3).

FIGURE 2. NJ Phylogenetic tree constructed using maximum likelihood method between 11 Pakistani goat breeds and 40 other mammalian species. Bootstrap value was kept 1000.

Furthermore, distance analyses (Fig. 3), MDS (Fig. 4), PCA (Fig. 5) and phylogenetic tree (Fig. 1) was re-constructed with the help of these PrP variables to have an insight of Pakistani goat breeds phylogeny to deepen our understanding in this field of great concern. The results showed that our local goat breeds were in the clade suggesting their genetic relatedness depending on PrP gene. However, deer and antelope were closer relative of Capra hircus on the basis of PrP gene as compared to buffalo, while domestic yak, European bison, gazelles and cattle comes after these species. Similarly, dromedary camel, llama and Bactrian camel from UK, China, Germany, Iran and Pakistan appeared as in a separate clade (Fig. 1).

FIGURE 3. Barry and Hartigan's relative rate test for the comparison of evolutionary distance between PrP homologs in different breeds/species.

FIGURE 4. Multidimensional Scaling plot of genetic distance between populations (Basques – closed circles, Iberia – open circles, Europe – closed squares, Middle East – cross, Caucasus – closed triangles, North Africa – open triangles). The first 2 axes account for highest genetic variation present in the sample and can be demonstrated that the plot is an accurate representation of the genetic distance matrix. The small ruminant group cluster together on the bottom-left side of the plot, near their bigger ruminant neighbors represented on the upper left place. The canine populations are found near the bottom-right of plot, differentiated from the other 2 ruminant groups.

FIGURE 5. Principal component analyses resolve the genetic distance matrix of selected species into PC1, PC2, and PC3 and so on. Out of these, PC1 and PC2 represents large proportion of variation in the dataset and are plotted. PCA results enhanced consistency in our data set as all 3 groups make their spots according to their phylogenetic links. Here PC1 is quoting largest variation in the dataset as compared to PC2. So neighborhood has been revealed between cattle and goat. In that study central nervous system specific human enhancers exhibit 3 distinctive and internally compact clusters exposing the interactive pattern of TFBSs. The control data set of human non-conserved and non-coding elements do not present any vivid cluster structure for the 14 TFBSs that formed internally closely packed clusters in CNS specific enhancers, thus elucidating the significance of clusters in panel A. TFBSs are color coded.

Variations at Protein Sequence Level

Different softwares were used to check out the effect of nucleotide change on primary and secondary structures of protein.¹¹ (Baber et al., 2009;⁵) The sequence having nucleotide changes at all 6 positions was selected as representative sequence and translated by Expasy Translate tool. As the individuals in this study showed close relatedness with Capra hericus (Fig. 1) so the predicted ORF was then aligned with reference prion protein of Capra hircus by using Clustal Omega which resulted in 2 conservative, 2 semi-conservatives and 1 non-conservative variation (Figure S1).

Secondary structure of reference caprine prion protein (Figure S2), as well as altered prion protein was predicted by Phyre2 software which has shown absence of alpha helix at 113-117 and break down of single alpha halix (147-159) of PrP^C into 2 (150-152 and 155-159) in major prion protein (Figure S3). These variations may cause change in folding pattern of protein which may convert PrP^C to PrP^SC.⁶ This shift could be a major cause of scrapie in goats.

Genetic Distance Evaluation

Distance profiling in biological sciences is an important technique to reveal the level of diversity among individuals of a population/community. Several algorithms were available in form of software packages as well as others have been implemented in Bioconductor. In this study, we used BH87 computational model to generate distance profile against the selected individuals of different breeds/species (Fig. 3). The outcome of this model was a table containing pair wise distance values in it. Diversity pattern, constructed using these computed distance values, is shown in Figure 3 (Distance Plot).¹⁸

MDS Plot

Multidimensional scaling (MDS) is a tool by which researchers can obtain quantitative estimates of similarity/dissimilarity among groups of items. We provided input in the form of pair wise distance matrix generated for all species mentioned above using BH87 statistical model (Fig. 3). The outcome of MDS, conveyed us the relationships among member sequences. Similar items wherein were seemed to be located proximal to one another, and more diverse items were found proportionately further apart. For example, 3 clusters were uniquely located at variable spots in the MDS diagram (Fig. 4). Member species of each cluster were more related to each other as compared to the individuals of a different cluster as shown in MDS plot. N-1 dimensions (N for number of sequences) were implicitly computed for our total sequence data set. We screened out 1st 2 dimensions only to observe variation pattern in the current data set.¹⁹ In this analysis, slightly scattered pattern of large ruminant cluster suggests greater substitution rates in their PrP region as compared to goat and canine species.

2D Loading PCA

Principal components analysis can be used to explore a large data matrix for the direction of largest variation. The whole idea of principal components analysis was to find new directions in the data along with maximal variation. A direction was defined as a linear combination Zk of the data Z by a vector k with weights. So, we employed bioconductor implementation to achieve linear combinations with the help of 2 implicitly calculated Eigen values. These Eigen values provided transformations of our genetic dataset in order to give direction of maximum source variation in the distance profile.

PrP gene along with its homologs was the targeted genomic regions of the selected species. For this purpose, previously calculated genetic distance profile using BH87 computational model (Fig. 3), was used to generate initially 2 linear combinations such as PC1 and PC2 residing in the Figure 5 as vertical and horizontal axis. In total, 70 homologous genes from different organisms were included in our data set. According to PCA, it revealed that highest variation may be due to the presence of top most cluster which were resident very far from 2 other clusters. In a group, the members were less variable with respect to each other.²⁰

Final identification of the cluster structures in the binding site preferences of the training and control data set was achieved with the application of Principal Component Analysis (PCA). The first 2 PCs explained maximum of the total variation present in the patterned correlated data set. The 2D loading plot of the first 2 PCs derived from PCA on control data exposed a scenario of interactive pattern of prions across the species in the training data set. The 2D loading plot exhibits clarity of 3 distinct sets of closely packed prions, i.e., 3 cluster configurations of species. The cluster configurations presented coincide with the cluster configuration perceived in R_X = [r²_ij]. The species which co-occurring with the PrPs packed in cluster-3 were also merged in it.

Phylogenetic Tree Reconstruction

A NJ phylogenetic tree was reconstructed using PrP sequences of 50 individuals including 10 sample sequences. Rest of other homologs was retrieved from GenBank. The rectangular view showed that all our local goat breeds placed themselves in one clade indicating their genetic relatedness based on PrP gene. In the tree diagram (Fig. 1), our breeds can be observed as the closest relative of Capra hircus, then domestic yak, European bison, gazelles and cattle comes after these species. Killer whale, dolphin appeared in a separate clade. Wild ass, horse and zebra came as close relative in another separate clade. Similarly, alpaca, llama and Bactrian camel from Pakistan appeared as in a separate clade. In the last clade fox, wolf, canada lynx, bobcat, cheetah, puma, mongoose, walrus, sea lions, seal, skunk bear and lesser panda appeared.

As far as the first clade was concerned, regular trend of all goats were observed in which all breeds showed close relatedness with each other. Another important thing was also observed that domestic sheep placed itself into goat clade. Barbari-58, Khurasani-36, Lehri-43, Kaghani-03, Beetal-26 and Mouflon sheep place themselves closer to other mammals.

DISCUSSION

Ovine and caprine management has endured huge economic losses due to scrapie epidemics in Europe. In the majority of countries, the prevalence of natural scrapie in goats remained underrated as compared to sheep. Studies to produce information on PrP gene polymorphisms and their distribution in goat breeds domesticated in diverse countries have become progressively more important, especially after the discovery of BSE or prions in goats in the 1990s.²¹ Surely, identification of candidate PrP gene polymorphic alleles that may confer susceptibility or resistance to goat scrapie, was a beginning step in understanding the likelihood of any selection program. Modern gene sequence technologies have now paved the path for breeders to make sheep and goats resistant against distressing disorders including scrapie by helping them in determining the allele frequencies, which is a prerequisite to devise an appropriate breeding plan for reasons of animal welfare as well as human food safety and food security.

This study provides new evidence in Pakistani goats for an association of PrP gene polymorphisms with resistance to classical scrapie. In contrast there is no indication for gene variants studied in an association with increased susceptibility to classical scrapie, such as the one found for codon 136 valine polymorphism of European ovine PrP.²² Of the 6 PrP coding region polymorphisms that were observed in investigated herds (G102W, S127G, N135S, H143R, K231R and S240P), one N135S was described for the first time in the Pakistani goat population. In conformity with previous association studies, we found that the goat PrP gene was highly variable in all the 11 breeds studied with majority of animals showing H143R polymorphism. Among caprine PrP polymorphisms I142M, H143R, N146S/D, R154H, R211Q and Q222K which has been reported both in European²³ and Asian sheep breeds²⁴ in association to scrapie resistance, only H143R was detected for the studied goats.¹³ This polymorphism has also been identified in other Pakistani goat breeds like Pak Angora, Teddy and Beetal⁸ along with G102W²⁵ and K231R²⁶ in European caprine (Table 5). Moreover, F141L and R154H that were risk factors for typical scrapie and has been reported in some European^27,28,29,30 and Asiatic³¹ breeds, were not detected in the populations of Pakistani studied goats. Our genetic analysis also revealed an association of S127G with a decreased probability to develop clinical scrapie in agreement to European breeds.²² It appears that domestic goat populations maintain a number of PrP polymorphisms as might be expected from balancing selection and the majority of these polymorphisms were associated with a degree of protection against prions compared to the wild type. We were interested to see if a goat population from a region which had never any confirmed scrapie outbreaks would show equally diverse PrP genetics as the UK or other scrapie affected countries (Table 5). A comprehensive list of already reported polymorphisms as well as published from Pakistani biologists was generated. Out of 6 variants, 5 named G102W, S127G, H143R, K231R and S240P were in correspondence with the variant list from all over the world. Here we reported a novel genotype N135S identified in Pakistani goats would of great interest for future correspondence. In general, c.428 position was observed as highly polymorphic in all breeds with homozygous G, A and A/G heterozygous genotypes (Table 2). With respect to that site, approximately 81.25% of individuals were found polymorphic (Fig. 2). Out of them, 71.01% individuals were heterozygous for this particular site. Lowest percentage of polymorphism was achieved at c.379 as 3.75%. Similarly, significant percentage of polymorphisms were obtained at c.126, c.304, c.414 and c.718 sites as 35%, 7.5%, 36.25% and 28.75% respectively (Fig. 2). Whereas, heterozygous sites were evaluated as proportion to the cumulative polymorphic variation. Surprisingly, all species had adopted the heterozygous trend as compared to be homozygous (Table 3) which might had made them less susceptible to scrapie.

This important PrP sequences with important variation profiles from scrapie resistant individuals were further exploited to discover its evolutionary mechanism. In distance plot, MDS, PCA and phylogenetic analysis, these species/breeds had shown their origin were of great interest. Analyzing all sequences with respect to multiple angles generated their origin association with other species/breeds and on the basis of this gene deer and antelope species were clustered with Capra hircus. Through sequence analyses we came up with an important finding that killer whale has the lowest rate of variation while mongoose seemed to possess the largest rate of substitutions (Fig. 1). Similarly, MDS and PCA (Figs. 4 and 5) diagrams elucidated that all canine sequences had observed the highest level of variations described by PC1 (representing 75% of variation alone).

ABBREVIATIONS

MRCA	=	Most Recent Common Ancestors
TSEs	=	Transmissible Spongiform Encephalopathies
CJD	=	Creutzfeldt-Jakob disease
TME	=	Transmissible mink encephalopathy
GPI	=	Glycosyl-phosphatidyl inositol
CDS	=	Coding DNA sequence
ORF	=	Open Reading Frame
MDS	=	Multidimensional scaling
EDTA	=	Ethylenediamine tetra-acetic acid
SNPs	=	Single Nucleotide Polymorphism
PrPc	=	Cellular prion protein
PrPsc	=	Scrapie prion protein

DISCLOSURE OF POTENTIAL CONFLICTS OF INTEREST

We have no conflicts of interest to disclose; all authors approved the manuscript and this submission.

Funding

This work was supported by the Natural Science Foundation of China (Project No. 31472166).