Caprine arthritis-encephalitis and genetic characteristics of small ruminant

Abstract

Caprine arthritis-encephalitis (CAE) is a progressive disease of goats caused by small ruminant lentivirus (SRLV) and is considered as one of the most important threats for goat farming in developed countries. The disease prevalence has never been investigated in the Lithuanian goat population. Therefore, a descriptive cross-sectional study was carried out in 2021–2022 to determine if SRLV infection was present in the Lithuanian goat population and, in the case of a positive result, to estimate the true herd-level prevalence of SRLV infection and specify genotypes and subtypes of SRLV responsible for the infection. Thirty goat herds counting >5 adult goats were randomly selected and, in each herd, a representative sample of adult goats was blood-sampled and tested serologically for SRLV infection using a commercial ELISA. The herd was considered infected if at least one goat tested positive and the true herd-level prevalence of SRLV infection was estimated using the Bayesian approach. Seropositive animals were found in 17 / 30 herds (57 %; 95 % confidence interval: 39 %, 73 %). The true herd-level prevalence was 56 % (95 % credible interval: 36 %, 76 %). In 10 / 17 seropositive herds whose owners consented for resampling of seropositive goats, 1–5 seropositive goats were tested using the nested real-time PCR (nRT-PCR). Goats from 9 seropositive herds tested positive in the nRT-PCR: in 4 herds for genotype A, in 4 herds for genotype B, and in 1 herd – 2 goats for genotype B and 1 goat for genotype A. From each of 9 nRT-PCR-positive herds, 1 PCR product of each genotype was sequenced using Sanger method and the phylogenic tree was constructed using the neighbor-joining method in the Molecular Evolutionary Genetics Analysis software. Four herds turned out to be infected with B1 subtype (91 % identity with the prototypic strain), 3 herds with A2 subtype (90 %-92 % identity), and a herd with mixed infection was infected with B1 (91 % identity) and A2 subtype (90 % identity). In one herd, the only seropositive goat was found to be infected with the strain most closely related to the A1 subtype (80 % identity). This study shows for the first time that SRLV infection is present and widespread in the Lithuanian goat population and both classical SRLV genotypes, represented by quite typical subtypes A2 and B1, appear to be responsible for the infection.

List of abbreviations

α

level of significance

a

b, parameters of the prior Beta distribution

CAE

caprine arthritis-encephalitis

CAEV

caprine arthritis-encephalitis virus

CI 95 %

confidence interval for the level of confidence of 95 %

CrI

credible interval

Ct

RT-PCR cycle threshold

IQR

interquartile range

MEGA

Molecular Evolutionary Genetics Analysis

MVV

maedi-visna virus

NJ

neighbor-joining method

nRT-PCR

nested real-time polymerase chain reaction

Se_H

herd-level diagnostic sensitivity

Sp_H

herd-level diagnostic specificity

Se_I

individual-level diagnostic sensitivity

Sp_I

individual-level diagnostic specificity

S/P%

sample-to-positive control ratio

SRLV

small ruminant lentivirus

TP_H

true herd-level seroprevalence

WAHIS

World Animal Health Information System

Keywords

Bayesian analysis

Between-herd prevalence

Caprine arthritis-encephalitis

MEGA, Nested real-time PCR

Phylogenic analysis

Sanger sequencing

1. Introduction

Caprine arthritis-encephalitis (CAE) is an infectious, chronic, progressive disease of goats caused by small ruminant lentivirus (SRLV). CAE is considered one of the most important threats for goat farming in developed countries due to negative impact on animal welfare (severe clinical signs of arthritis and wasting developing in roughly 20 %-30 % of infected goats and productivity (decreased yield and quality of milk and cheese.

SRLV is a grouping name for five (or four, the issue is still uncertain) genetic types (genotypes: A, B, C, D, and E) and over thirty genetic subtypes.  Genotypes A and B correspond to maedi-visna virus (MVV) and caprine arthritis-encephalitis virus (CAEV), respectively – two classical “ovine” and “caprine” lentiviruses of worldwide distribution whose description dates back to 1960s and 1980s, respectively. Genotypes C, D, and E have only local distribution restricted to Norway, Switzerland and Spain (D), and Sardinia and Northern Italy, although, genotype D may be just a slightly more distinct member of genotype A. Genotypes A and B include many subtypes – A1 to A27 and B1 to B5, respectively. A1 and B1 are prototypic subtypes called, respectively, the Icelandic subtype (after the country where maedi-visna disease was first recognized in 1939; and the Cork subtype (after Professor Linda C. Cork who, among others, provided the first description of CAE in the USA in 1974;. Since their first recognition, the fact of an interspecies transmission of SRLV genotypes and subtypes between sheep, goats, and likely wild ungulates has been well evidenced and the classification into “ovine” and “caprine” genotypes has become purely historical. The most efficient route of CAE dissemination between herds is associated with introducing an infected animal into the herd. Within herds, CAE spreads both vertically via lactogenic route and horizontally through a long-term direct contact between animals.

CAE has been reported from many countries all over the world however no data on SRLV infection in Lithuania are available. Lithuania has a small and quite stable population of goats and sheep counting approximately 14 000 goats and 128 000 sheep, mostly kept on small family farms . In this region of Europe, most reports of the epidemiological situation of CAE come from Lithuanian’s south-western neighbor, Poland. SRLV infection is widespread both in goat and sheep population of Poland with the true herd-level prevalence (TP_H) of roughly 60 % and 30 %, respectively. CAE was likely introduced to Poland in 1980s with goats imported from western European countries and has gradually spread all over the country. It appears to be also present in wild ungulates in Poland. There are no epidemiological surveys on SRLV infection available from other Lithuania’s neighbors such as Belarus, Russia (Kaliningrad Oblast), or Latvia. However, SRLV infection is probably present in Latvia as this country notified CAE to the World Animal Health Organization in 2005 and maedi-visna disease first in 2009–2011 and then in 2015–2017 . According to the World Animal Health Information System (WAHIS), also Russia reported maedi-visna disease in 2012–2019, however given an enormous size of this country and separated nature of the Kaliningrad Oblast, the outbreaks are unlikely to have occurred near the Lithuanian border. SRLV infection has recently been confirmed in goats in the Republic of Tatarstan and Mordovia which are both, however, very distant from the Lithuanian border.

Given a complete lack of information on the epidemiological situation of CAE in Lithuania, we decided to carry out a descriptive cross-sectional study to determine if SRLV infection was present in the Lithuanian goat population and, in the case of a positive result, to estimate TP_H of SRLV infection and specify genotypes and subtypes of SRLV responsible for the infection.

2. Materials and methods

2.1. Sampling and serological testing

The study was carried out in 2021–2022. It was a descriptive cross-sectional study in which a screening diagnostic method was an indirect commercial ELISA coated with the panel of synthetic peptides from SRLV structural proteins – surface glycoprotein (gp135), transmembrane glycoprotein (gp46), and capsid protein (p25/p28) (ID Screen MVV-CAEV Indirect Screening test, ID.vet Innovative Diagnostics, Grabels, France). The ELISA was performed according to the manufacturer’s manual and optical density (OD) was measured at a wavelength of 450 nm in the Epoch Microplate Spectrophotometer (BioTek, USA). At the cut-off value equal to the sample-to-positive control ratio (S/P%) of 50 %, the assay had an individual-level diagnostic sensitivity (Se_I) of 91.7 % (CI 95 %: 85.0 %, 95.6 %) and specificity (Sp_I) of 98.9 % (CI 95 %: 96.2 %, 99.7 %). If the OD was >4.0 (the upper limit of detection of the Spectrophotometer) the S/P% was arbitrarily set at >500 %.

The target population comprised Lithuanian goat herds made of more than 5 goats. It was assumed to count approximately 550 herds as according to the Lithuanian Register of Farm Animals in approximately 3500 of 4000 goat herds (87.5 %) registered in Lithuania from 1 to 5 goats are kept. The required number of herds to be selected randomly from the Lithuanian goat population (the herd-level sample size) was calculated assuming an expected TP_H of 50 %, precision of estimation of TP_H of ±20 %, the herd-level diagnostic sensitivity (Se_H) of 96 %, and the herd-level diagnostic specificity (Sp_H) of 94 % (detail of calculations provided in the next paragraph). The level of confidence was set at 95 % in all estimations and analyses. The required herd-level sample size was 28 herds. The study was designed so that a SRLV-infected herd could be detected if the within-herd true prevalence was at least 20 %. Simple random sampling of herds was applied. The required number of goats to be selected randomly from each herd (the within-herd sample size) was calculated assuming the aforementioned Se_I of the ELISA (rounded to 92 %) and Sp_I of 100 % i.e. 1 seropositive animal was considered as sufficient to classify the herd as SRLV-infected. In each herd, all adult males (aged ≥1 year) and the representative number of adult females (aged ≥1 year) were included in the study. The required within-herd sample size was 8–17 animals. In each herd, the owners were asked about the contact between goats and sheep on a farm, at the moment of the visit or in the recent past (during preceding 5 years).

Se_H and Sp_H were calculated using the FreeCalc method in the HerdPlus module of the EpiTools assuming Se_I of 92 % and Sp_I of 99 % as stated before, the median size of a Lithuanian goat herd in the target population equal to 20 goats and the within-herd sample size of 12 randomly selected goats. On these assumptions, Se_H and Sp_H were 96 % and 94 %, respectively.

In each randomly selected herd, blood samples were collected from the jugular vein to 10-ml clot activator tubes (BD Vacutainer, BP-Plymouth, UK), left overnight at +4°C for clotting, and centrifuged at 3000 rpm (1390×g) for 10 min. The serum was harvested to 2-ml Eppendorf tubes and frozen at −20°C until ELISA testing. Blood sampling was approved by the Lithuanian State Food and Veterinary Service (Approval No. B1–866, 27/04/2021) and the owners of selected herds granted informed consent for participation in the study.

2.2. Molecular testing and SRLV gene sequencing

The owners of seropositive herds were contacted and asked for permission to resample some of the seropositive goats for molecular tests. Blood samples were collected from the jugular vein to 10-ml tubes with ethylenediaminetetraacetic acid (EDTA) as an anticoagulant (BD Vacutainer, BP-Plymouth, UK) and centrifuged at 3000 rpm (1390×g) for 10 min. 500 μl of buffy coat were harvested and erythrocytes were lysed using 1 ml of RBC Lysis Buffer (G-Biosciences, St. Louis, Missouri, USA) to obtain leukocyte pellets which were then stored at −20°C until testing. DNA from leukocyte pellets was extracted using the Qiagen DNeasy® Blood & Tissue kit (Qiagen, Hilden, Germany) and eluted in 100 μl of elution buffer according to the manufacturer’s protocol. Extracts were tested using a two-stage nested real-time PCR (nRT-PCR) for the presence of proviral DNA of SRLV genotype A and B. Briefly, the nRT-PCR was carried out in two successive amplification steps. The first step was a conventional qualitative PCR and contained 12.5 μl of Hotstar Taq Master Mix (HotStarTaq DNA Polymerase kit, Qiagen GmbH, Hilden, Germany), 0.15 μl of mixture of primers and 5 μl of the extracted DNA. Amplification started with the activation of the polymerase at 95°C for 15 min, followed by 40 cycles: 20 s at 94°C for denaturation of double-stranded DNA 30 s at 60°C for annealing of primers to each of the single-stranded original proviral DNA templates, and 45 s at 72°C for extension (elongation) of the new proviral DNA strands from the primers. In the second step, all products of the first PCR were tested in parallel using two genotype-specific RT-PCRs for a sensitive detection and discrimination between SRLV genotypes A and B. RT-PCR reactions contained 12.5 μl of TaqMan™ Universal PCR Master Mix (Applied Biosystems, Life Technologies, Waltham, MA, USA), 0.25 μl of each primer, 0.5 μl of probes, and 5 μl of the PCR product from the first step. Amplification profiles consisted of a hold stage of 20 s at 95°C and a PCR stage of 45 cycles: 15 s at 95°C for denaturation and 60 s at 60°C for annealing. Thermal cycling was performed using the 7300 Real-Time PCR System (Applied Biosystems, Life Technologies, Waltham, MA, USA) and the LightCycler 480 II (Roche Diagnostics, Rotkreuz, Switzerland). Results of nRT-PCR were considered positive if the cycle threshold (Ct) value was <35. For positive samples exact Ct values were recorded as a relative information of viral load in the sample.

From each nRT-PCR-positive herd, one PCR product of each SRLV genotype (A and B) was gel-extracted using primers from the 2nd stage of PCR but without the probes. Then, PCR products were sequenced in both directions using the Sanger dideoxy sequencing method in a commercial laboratory (Genomed SA, Warsaw, Poland). The obtained SRLV sequences were manually checked and edited using Geneious Prime software version 2024.0.7 (GraphPad Software, LLC, Boston, MA, USA), and then deposited in GenBank (accession numbers: PP855635 through PP855644). The genetic relatedness among the SRLV strains was analyzed based on approximately 200–250 bp-long fragment covering the distal fragment of the Long Terminal Repeat (LTR) region and the short proximal fragment of gag gene sequence (LTR-gag) of proviral DNA located within the nRT-PCR target sequence. LTR-gag sequences were denoted by the first letter indicating SRLV genotype according to nRT-PCR (A or B), two-letter country code of Lithuania (LT), and one-letter herd symbol (e.g. C) followed by the ordinal number of a goat from which the sequence was obtained. A total of 10 sequences supplemented with 27 closely related reference RNA or proviral DNA sequences of the whole SRLV genome of subtypes A1 (EV1, Kv1514, Kv1772, SA-OMVV), A2 (OvLV 85/34, USMARC-200303013–1, 1150), A2/A3 (697), A4 (AY445885), A18 (SRLV025), A19 (SRLV009), B1 (CAEV-Cork, SRLV020, SRLV/B1/Goat/MX/INIFAP-1/2013, FESC-752, SRLV_To1.89, SRLV010, Gansu), B2 (Ov496, SRLV001, SRLV042), B3 (Fonni, Volterra), C1 (1GA), E1 (Roccaverano), and E2 (Seui) retrieved from GenBank were analyzed phylogenetically.

Phylogenetic and molecular evolutionary analyses were conducted using the Molecular Evolutionary Genetics Analysis (MEGA) software version 11. First, proviral DNA sequences obtained were aligned using the Muscle algorithm. Phylogeny construction was carried out using the neighbor-joining (NJ) method. The evolutionary distances were computed using the Tamura-Nei method and expressed as the numbers of nucleobase substitutions (transitions and transversions) per site along the horizontal phylogenic tree branches. Graphically, it was indicated by the sum of lengths of all horizontal branches between two SRLV strains. Percentage of identity of two strains was calculated as 100 % minus the sum of all nucleobase substitutions per site between the two strains. The confidence level of the topologies was assessed with 1000 bootstrap replicates and presented on the phylogenic tree as the proportion of bootstrap trees showing that same topology. All positions containing gaps and missing data were ignored. A strain was classified to a certain subtype if it differed from the prototypic strain(s) by less than 0.15 nucleobase substitutions per site (≥85 % identity.

2.3. Epidemiological and statistical analysis

The apparent herd-level prevalence (AP_H) was the proportion of herds in which at least one adult goat tested positive in the ELISA. The TP_H was estimated using a Bayesian approach in the EpiTools online epidemiological calculator. After collecting all the samples, Se_H and Sp_H of the ELISA were calculated separately for each herd based on the size of this herd and the size of the sample selected from this herd so that the distributions of Se_H and Sp_H in the study population were known. These results were used to choose optimal shape parameters of the beta distribution (a, b) for modelling prior distributions of Se_H and Sp_H of the ELISA: Se_H ∼ Beta(21.5, 0.9), and Sp_H ∼ Beta(50.0, 3.5). For the TP_H, the uniform prior beta distribution with parameters (1, 1) was assumed as nothing was known about the epidemiological situation of SRLV infection in the Lithuanian goat population. The TP_H was estimated as a posterior median with the 95 % probability (credible) interval (95 % CrI).

Numerical variables (numbers of goats, S/P%, Ct values) were assessed for normality of distribution using the normal probability Q-Q plots and the Shapiro-Wilk test. As normality assumption was violated, they were summarized as the median, interquartile range (IQR), and range, and compared between groups using the Mann-Whitney U test. Categorical variables (sex of goats, herd size category, serological status) were summarized as counts (n) and proportions (%), and compared between groups using the maximum-likelihood G test or Fisher exact test if the expected count in any cell of the contingency table was <5. The 95 % confidence intervals (CI 95 %) for proportions were calculated using the Wilson score method. Statistical tests were two-tailed and a significance level (α) was set at 0.05. Statistical analysis was performed in TIBCO Statistica 13.3 (TIBCO Software Inc., Palo Alto, CA). The map of Lithuania was downloaded from the simplemaps Interactive Maps & Data and further modified.

3. Results

The study comprised 30 goat herds counting from 10 to 500 adult goats with the median (IQR) of 22 (12 – 38) adult goats. In 23 / 30 herds (77 %), from 1 to 4 males were kept (median of 1). Fifteen herds (50 %) were very small (≤20 adult goats), 12 herds (40 %) were small (21–50 adult goats), and in only 3 herds (10 %) more than 50 adult goats were kept. Herds were located in all 10 counties of Lithuania, however as many as 8 herds (27 %) were situated in the Vilnius (capital) county, while four counties were represented by only one or two herds. The process of sample selection and the results obtained are graphically presented in the flowchart and detailed data for each herd (denoted by #ID number) are included in the Microsoft Excel spreadsheet. In 14 / 30 herds (47 %), goats were kept together with sheep during the sampling or over preceding 5 years.

Proportion of herds seropositive for small ruminant lentivirus (SRLV) infection in four herd size categories.

In each herd, 4–32 goats (median: 12, IQR: 10 – 15) were tested. This corresponded to the median sampling fraction of 58 % of goats in the herd (IQR: 40–88 %; range: 2–100 %). In 19 / 30 herds (63 %), the number of blood-sampled goats satisfied the prior requirements for the within-herd sample size, whereas in the remaining 11 herds the number of blood-sampled goats was lower than required by 1–7 animals (median of 3). In total, 380 adult goats were serologically tested – 39 males (10.3 %) and 341 females.

At least one seropositive goat was found in 17 / 30 tested herds which corresponded to the AP_H of 57 % (CI 95 %: 39 %, 73 %). Seropositive herds were evenly distributed throughout the country with only 2 counties in which tested herds (1 herd in each) were seronegative. The AP_H was neither significantly associated with the herd size (p=0.902) nor with the contact with sheep on a farm (p=0.961). The AP_H did not differ significantly between herds in which the prior requirements for the within-herd sample size were (11 / 19 herds; 58 %) or were not satisfied (6 / 11 herds; 55 %; p=0.728). The TP_H was 56 % (95 % CrI: 36 %, 76 %).

In total, 75 / 380 goats tested positive in ELISA (19.7 %) – 6 / 39 males (15.4 %) and 69 / 341 females (20.2 %) (p=0.459). In 12 / 17 herds only females tested positive, in 4 / 17 herds – males and females, and in 1 herd (#23) only a single male tested positive. In seropositive herds, from 1 to 11 goats tested positive with the median (IQR) of 3 (2 – 7) goats. These numbers corresponded to 7 % through 100 % (median: 26 %, IQR: 17 % – 34 %) of goats tested within a herd. In 3 herds (herd #5, #22, #23), only one of the tested goats was seropositive. In 4 herds (herd #3, #6, #18, and #22), all adult goats were tested, and in 3 of these herds some seropositive animals were identified: 1 seropositive goat / 12 goats in herd #22 (8 %), 5 / 16 (31 %) in herd #18, and 11 / 32 (34 %) in herd #3. The fourth herd (#6) counting 11 goats was all negative. S/P% of ELISA-positive samples ranged from 56.8 % to >500 % with the median (IQR) of 316 % (203 % – >500 %), and they did not differ significantly between males and females (p=0.207).

In 10 seropositive herds whose owners consented for resampling of seropositive goats (herds #3, #4, #7, #9, #14, #18, #20, #23, #24, and #27 in 1–5 randomly selected seropositive goats were tested using the nRT-PCR (27 goats in total). In 22 / 27 seropositive goats (81 %) from 9 / 10 seropositive herds, the result was positive: in 4 herds goats tested positive for genotype A (7 goats in total from herds #14, #23, #24, #27), in 4 herds goats tested positive for genotype B (12 goats in total from herds #3, #7, #9, #20), and in 1 herd (#18) – 2 goats were positive for genotype B and 1 goat was positive for genotype A which implied the coinfection of a herd with the two genotypes. In one herd (#4), a single goat tested using the nRT-PCR was negative. In total, 8 goats were positive for genotype A and 14 goats for genotype B. Ct values ranged from 6th to 21st cycle and they were significantly lower in the case of genotype B (median: 15th cycle, IQR: 12th – 18th cycle) than genotype A (median: 19th cycle, IQR: 17th – 20th cycle; p=0.029) which implied relatively higher viral load of SRLV genotype B than A. Goats had contact with sheep in 4 of 9 herds positive in nRT-PCR. Genotype A was detected in 1 of these 4 herds (#24), genotype B in 2 herds (#3 and #9), and mixed infection with genotypes A and B also in 1 herd (#18).

From each of 9 seropositive herds confirmed to be SRLV-infected by the nRT-PCR, 1 PCR product of each genotype was sent for Sanger sequencing (10 samples in total) and the LTR-gag sequences were used to construct the phylogenic tree (Fig. 4). The sequences were 203–299 bp-long (median of 248 bp) and consisted of the LTR fragment whose length was between 169 and 207 bp (median of 204 bp) and the gag gene fragment whose length was between 34 and 95 bp (median of 44 bp). Four herds turned out to be infected with strains most closely related to the subtype B1 (strains B-LT-C30, B-LT-E69, B-LT-I244, and B-LT-J87; 90.5 % – 90.7 % identity), 3 herds with strains most closely related to the subtype A2 (strains A-LT-D317, A-LT-F347, and A-LT-H152; 89.8 % – 91.9 % identity), and a herd with mixed infection was infected with strains most closely related to the B1 (B-LT-B210; 90.7 % identity) and A2 subtype (A-LT-B208; 89.9 % identity). In a herd, in which only one male goat was seropositive (#23), this male goat was found to be infected with the strain (A-LT-G300) most closely related to the subtype A1 although the number of nucleobase substitutions per site between this SRLV strain and the prototypic strain from the subtype A1 was almost twice as high (20.3 %, i.e. only 79.7 % identity) as the number of nucleobase substitutions per site between other strains and corresponding prototypic SRLV subtypes. The SRLV strain from this herd was distant from all the other Lithuanian strains.

4. Discussion

Our study is the first to show that SRLV infection is present in the population of Lithuanian goats and approximately a half of herds are infected. Both genotypes A and B are responsible for the infection and SRLV strains appear to belong to classical subtypes A2 and B1. TP_H was estimated with rather limited precision so in fact the true figure lies somewhere within a quite wide range – between one third and three fourths of Lithuanian herds.

TP_H of SRLV infection in Lithuania appears to be similar to the situation in Poland. The overall TP_H in Poland was 61 % (CI 95 %: 53 %, 68 %), however it was shown to be positively associated with the herd size. An average goat herd in Lithuania is smaller than in Poland so when TP_H in Lithuania is compared to TP_H in very small or small Polish herds (≤50 goats), they turn out to be almost the same. In this context, it is not surprising that TP_H did not prove to be significantly associated with the herd size in Lithuania. Most herds in Lithuania were very small or small (≤50 goats) according to our classification and TP_H in these two categories had not differed significantly in Poland either. Only three Lithuanian herds included in this study counted more than 50 goats and this number was certainly too low to allow for any reliable attempt to detect statistically significant difference.

The TP_H estimation may be negatively affected by several evident shortcomings of our study. First, the minimum within-herd true prevalence that our study was able to detect reliably (i.e. a kind of limit of detection of CAE inherent for this study) was as high as 20 %. This means that if fewer animals were infected they were likely missed. Such a situation was possible as in 1 of 3 herds in which all goats were tested only 1/11 goats turned out to be positive. Additionally, in 11 of 30 tested herds even fewer animals than theoretically required were indeed tested which resulted mostly from organizational issues. On the other hand, we set the cut-point for classifying a herd as SRLV-infected at 1 seropositive goat which corresponds to the assumption that ELISA has 100 % Sp_I. However, the ELISA is known not to be perfectly specific even though its Sp_I has been shown to be very high, reaching values of 99. Therefore, the status of 2 herds in which only one goat tested positive in ELISA and which were not verified in the nRT-PCR (#5 and #22), should be treated with caution. However, even if these two herds are actually uninfected, AP_H and TP_H of SRLV infection in Lithuania is 50 % (CI 95 %: 33 %, 67 %) and 48 % (95 % CrI: 29 %, 69 %), respectively. Both these figures remain well within the estimated 95 % CrI of the initial TP_H.

The case of the herd (#23) in which only one goat tested positive, but this animal’s status was confirmed by the nRT-PCR and Sanger sequencing (strain A-LT-G300) is particularly interesting. In this herd counting 27 goats, 15 goats (1 male and 14 females) were serologically tested and only a male (buck) tested positive. Obviously, it might have been a false positive result, but the owner fortunately consented for resampling for the nRT-PCR and the buck eventually turned out to be infected with SRLV of genotype A quite closely related to subtype A1 (80 % identity). It was the only goat that could be infected with a strain of subtype A1 which sets this buck apart from the rest of infected goats in this study. The subtype A1 has been shown to circulate in this part of Europe so it is not impossible that this buck was indeed infected with this SRLV subtype. Furthermore, bucks have been shown to constitute an important source of SRLV infection and efficient mode of transmission as they are frequently exchanged between herds in order to maintain genetic diversity in natural reproduction. So it is not impossible that this infected buck had been recently introduced into this herd and we just managed to capture a moment of CAE spilling over into a naïve herd along with a newly-introduced animal. Unfortunately, no data on the history of this buck was available so it remains nothing more but an unverified suspicion.

On the other hand, classification of SRLV strains to a specific subtype is a difficult process whose reliability vastly depends on the part of viral genome sequenced and aligned. In our study, we used proviral DNA sequences of the LTR region which were quite short (approximately 200–250 bp) compared to two long fragments of gag and pol genes (1.2 kb and 1.8 kb) on which the current classification of SRLV is based. Even though, short LTR sequences have been shown to allow for assignment of strains to genotypes and subtypes we decided to include in the phylogenic analysis only these reference strains whose whole-genome sequences were available in GenBank. And the strain A-LT-G300 in fact did not satisfy a strict criterion of >85 % identity with a prototypic strain of any subtype. Therefore, classification of this strain into subtype A1 should be treated with caution, because it is possible that it in fact belongs to other subtype of genotype A, whose whole-genome sequence has not been so far deposited in GenBank. Other explanation of lower relatedness of this strain can be some faults in the Sanger sequencing process as this proviral DNA sequence was the shortest (203 bp) of all sequences obtained in our study.

One of 10 seropositive herds whose owners consented for retesting, turned out to be negative in the nRT-PCR. It is a very weak evidence of a SRLV-free status of this herd due to relatively low Se_I of the nRT-PCR (76 % according to. Of 27 goats tested with the nRT-PCR, 22 (81 %) turned out to be positive which corresponds closely to the reported Se_I of this nRT-PCR and other real time PCRs for SRLV. False negative results could have been caused by the low level of proviral DNA in tested samples as SRLV-infected monocytes are sparse in goat’s blood or unsuccessful proviral DNA isolation, which both can be considered as a kind of technical shortcomings of molecular diagnostic approach. Less likely is the influence of genetic variability of SRLV strains circulating in Lithuania as our study shows that they belong to rather classical genetic subtypes.

The coinfection of a herd with two different SRLV genotypes, observed in one of Lithuanian herds (#18), is nothing surprising. In countries in which goat farming does not constitute an important farming sector, goat herds are usually developed by gradual buying of goats from various sources and newly-purchased goats are extremely rarely tested for CAE prior to comingling with other animals on the account of very low awareness of farmers, high costs of laboratory tests (including veterinary service), and a low individual financial value of a goat. Lithuania numbers among such countries, together with most of other central and eastern European countries. Given that approximately 50 % of goats appear to be SRLV-infected, half-by-half with genotype A and B, a probability of purchasing infected goats from two different sources and hence carrying two different SRLV subtypes should not be considered as low. The lack of significant association between the contact with sheep and the presence of genotype A or B in a herd is not surprising. Many studies have shown that the interspecies transmission of various genetic types and subtypes of SRLV is a common phenomenon and nowadays both genotypes A and B are prevalent in goat populations of various countries regardless of the presence of contact between goats and sheep. Therefore, it is very difficult to hypothesize on the potential source of SRLV infection for the Lithuanian goat population based on results of our molecular studies. Most likely, SRLV has been imported along with sheep and/or goats from western countries like it happened in Poland. The fact that the phylogenic analysis revealed the presence of classical subtypes A2 and B1 indicates that the circulation of SRLV has not been very intensive so far, probably due to extensive character of goat farming in Lithuania.

Concluding, it is the first study to clearly show that SRLV infection with both classical SRLV genotypes A and B is present and widespread in the population of Lithuanian goats. This implies that CAE is likely to become a considerable health and welfare problem of goats, especially in these herds which will attempt to intensify their development and production. Therefore, active surveillance and control programs are highly warranted to alleviate potential negative consequences of further spread of SRLV infection both between herds and within already infected herds.

Summary

🐐 Caprine Arthritis-Encephalitis (CAE)

CAE is a chronic viral disease affecting goats, caused by the Caprine Arthritis-Encephalitis Virus (CAEV), a lentivirus in the Retroviridae family.

➤ Key Features:

• Transmission:
  • Mainly through colostrum or milk from infected does to kids.
  • Also via close contact, contaminated equipment, and possibly sexual transmission.
• Clinical Forms:
  1. Arthritis – Common in adult goats; swollen joints, lameness.
  2. Encephalitis – Primarily in kids (2-6 months); nervous signs, ataxia, paralysis.
  3. Interstitial pneumonia – Especially in young animals.
  4. Mastitis – “Hard udder” syndrome with little milk production.
• Diagnosis:
  • Serological tests (ELISA, AGID)
  • PCR for virus detection
• Control:
  • No vaccine or cure.
  • Focus on prevention: testing, culling, raising kids on CAEV-free milk.

🧬 Genetic Characteristics of Small Ruminants

Small ruminants include goats (Capra hircus) and sheep (Ovis aries), valued for meat, milk, wool, and fiber. Their genetics play a key role in disease resistance, productivity, and adaptation.

➤ Genetic Traits of Interest:

• Disease Resistance: Some breeds show natural resistance to diseases like CAE, scrapie, and internal parasites.
• Production Traits:
  • Milk yield (e.g., Saanen goats, East Friesian sheep)
  • Growth rate and carcass quality (e.g., Boer goats, Dorper sheep)
  • Wool/fiber characteristics (e.g., Merino sheep for fine wool, Angora goats for mohair)
• Reproductive Traits:
  • Twinning rate, fertility, kidding/lambing interval
• Adaptability:
  • Desert and tropical breeds (e.g., Red Maasai sheep, West African Dwarf goats) show heat tolerance and resistance to harsh environments.

➤ Use of Genetics:

• Marker-assisted selection (MAS) and genomic selection are being developed to improve traits efficiently.
• Genetic diversity conservation is crucial, especially for indigenous breeds adapted to local environments.

Summary

CAE is a significant viral disease in goats with no cure, managed through preventive breeding and hygiene. Genetic improvement in small ruminants focuses on enhancing productivity and resilience through selective breeding and modern genomic tools.