Cahi-DRB and DQB1 Alleles in Sirohi Goat

Cahi-DRB and DQB1 Alleles in Sirohi Goat Genetic diversity of DRB and DQB genes of caprine MHC class II in Sirohi goat G. R. Gowane, Najif Akram, S.S. Misra, Ved Prakash and Arun Kumar Running Head: CahiDRB and DQB1 alleles in Sirohi goat ABSTRACT Objective of the study was to assess the genetic diversity of the Sirohi goat for DRB and DQB1 loci and to study their association with antibody response induced by the Peste des petits ruminants (PPR) vaccine. A total of 360 Sirohi kids were studied using Single Stranded Confirmation Polymorphism (SSCP) followed by Sequence Based Typing (SBT)-PCR for DRB and DQB1 diversity. C-ELISA was used to assess immune response post PPR vaccination. Study revealed rich diversity of MHC region. A total of 18 DRB and 15 DQB1 alleles were obtained. Allele DRB*0104 and allele DQB1*0101 were most common. All the alleles reported are new. Study revealed variability in DRB and DQB1 region not only at nucleotide but also at amino acid level with high Wu-Kabat index. A total of 16 out of 89 amino acid residue sites had more than 3 amino acid substitutions in DRB. Similarly, 19 out of 86 residue sites in DQB1 had more than 3 amino acid substitutions. Positive evolutionary selection was evident in Sirohi for MHC region. Non-significant association of DRB and DQB1 genotypes with PPRV vaccine response revealed complexity of the phenotype and importance of other factors for vaccine response. Rich diversity of DRB and DQB1 gene reflects the fitness of the population and importance of this locus for future selection programs. Keywords: Cahi-DRB, Cahi-DQB1, Major histocompatibility complex, Vaccine response 1. Introduction Major Histocompatibility Complex (MHC) of goats is polymorphic. A few of the genes such as Caprine Leukocyte Antigen (Cahi)-DRB and Cahi-DQB1 from this complex are recently being investigated for their polymorphism and further potential association with important diseases of goat. The class II antigens encoded by MHC class II genes bind to processed peptides from extracellular antigens and present them to epitope specific CD4+ T lymphocytes. Cahi-DRB exon 2 is polymorphic so is Cahi-DQB1, due to their importance in antigen binding groove formation and evolutionary importance in antigen capture and presentation. Peptide binding site (PBS) in goat is partly coded by DRB and DQB gene. This PBS has several pockets which are highly variable and accommodate the side chains of the bound peptide. A non-synonymous change in the nucleotide sequence of the MHC DRB or DQB1 gene can substantially substitute the coding amino acid and ultimately bring conformational change in the binding groove so as to affect the efficiency of the protein to present the antigen efficiently for further processing. Several reports exists which link the variability in DRB alleles in cattle, sheep and other mammals to resistance or susceptibility to diseases. Herrmann-Hoesing et al. [1] reported that Ovar-DRB1 alleles contribute as a host genetic factor that control provirus level in sheep. Significant association of DRB1 alleles with susceptibility and resistance to Ovine pulmonary adenocarcinoma (OPA) was reported by Larruskain et al. [2] in sheep. However as far as studies on goat are concerned, there are very few caprine DRB and DQB1 sequences in Gene Bank. Similarly, there is a scarcity of research database for allelic association of DRB and DQB alleles with disease resistance or susceptibility in goat. It is for no surprise that even the IPD-MHC database has no space dedicated for goat MHC. Amills et al. [3] assessed the genetic variability in DRB of goat. This was followed by a few report s [4-8] to characterize DRB locus (exon 2 of DRB) in goat. Amills et al. (2004) also characterized DQB1 locus in goat, however not much work [9] has been carried out since then for its genetic polymorphism. Genetic variability in response to vaccination is likely to become an even more significant factor in designing ideal vaccines [10]. The genes identified might also be important for disease resistance traits, and could potentially provide the tools to select good responders opening the doors for potential implications in future selection programme [11,12]. The Peste des petits ruminant (PPR) being the plague of small ruminants pose heavy threat to the rural economy of India. It is caused by a PPR virus (PPRV) of the genus Morbillivirus within the family Paramyxoviridae. India constitutes a great diversity of small ruminants with 135.17 million goat and 65.07 million sheep (19th Livestock census) [13]. In PPRV endemic regions including India, control measures involve regular vaccination with live attenuated PPR virus vaccine of lineage IV, which has high antigenic stability and induce long term immune response [14]. Currently, three live attenuated PPR vaccines (Sungri/96, Arasur/87 and CBE/97 stains) are available in India for prevention of this disease, of which, Sungri/96, developed by ICAR-Indian Veterinary Research Institute (IVRI), Mukteswar has undergone extensive field trial [15-17]. It is possible that the vaccine induced protection across individuals is not homogenous, wherein, vaccine gives a complete protection for a proportion of individuals while rest acquire only incomplete (leaky) protection of varying magnitude [18]. Variable vaccine response in the population has been reported for several diseases in humans as well as animals [19-27]. Role of host genetics and other non-genetic factors in variation to vaccine response especially for PPR vaccine has not been studied till today in details. The importance of host genetics in vaccine response studies is important as genetic variability may influence vaccine response and hence confound vaccine efficacy studies. Objective of the present study is to decipher the Cahi-DRB and Cahi-DQB1 polymorphisms in detail using sequence based typing polymerase chain reaction (SBT-PCR) and to associate the variation obtained with PPR vaccine elicited immune response in Sirohi goat kids maintained at the farm condition in semi-arid region of India. 2. Materials and Methods 2.1 Animals The study population was a flock of purebred Sirohi goats. The flock was located at ICAR-Central Sheep Wool Research Institute, Avikanagar in the semi-arid region of Rajasthan, India at 75025â‚ ¬Ã‚ ²E, 26018â‚ ¬Ã‚ ²N, at an altitude of 320 m above mean sea level. The data for the experiment involved 360 Sirohi goat kids. All the animals under the study belonged to same age group, i.e. weaner with mean age at vaccination 142.43 days (SD = 14.67). All the animals in this flock were kept under semi-intensive management system.   Concentrate mixture was offered ad libitum to suckling kids from 15 days of age till weaning (90 days). After 3 weeks of age till weaning, kids were sent for grazing for 3 h each in morning and evening, but not along with their dams. During the post-weaning period in addition to 8-10 h grazing and dry fodder supplementation, 300 g of concentrate mixture was provided in the evening hours after browsing. The grazing area consisted of forestland with natur al fodder trees like Khejri (Prosopis cineraria), Ardu (Ailanthus spp.), and Neem (Azadirecta indica). Bushes and surface vegetation including the improved pastures of Cenchrus ciliarisis are also available. Due to scarce grazing resources from March to June, the goats were supplemented with hay of Cenchrus, Cowpea, and Dolichos; pala leaves (Zizyphus) and fodder tree lopping. 2.2 Amplification and typing of DRB alleles Whole blood (1 ml) was collected aseptically from the jugular vein of lambs for DNA isolation (GenElute Blood Genomic DNA Kit, SIGMA) according to the manufacturers instructions. Exon 2 of the DRB gene was amplified from genomic DNA using the primers as suggested by Amills et al. [3], where DRB.1: 5-TATCCCGTCTCTGCAGCACATTTC-3 and DRB.2: 5-TCGCCGCTGCACACTGAAACTCTC-3 primers were used for amplifying 285 bp product. The reaction mixture of 50ÃŽÂ ¼l comprised of: 10X Taq Buffer (05ÃŽÂ ¼l), 25mM MgCl2 (03ÃŽÂ ¼l), 10mM dNTP (1ÃŽÂ ¼l), 20 pmol (1ÃŽÂ ¼l) of each primer, Taq DNA Polymerase (1IU), Template (1ÃŽÂ ¼l) and Nuclease Free Water (NFW) to make 50ÃŽÂ ¼l. The thermal profile was optimized for amplification of the DRB exon2 as follows: Initial denaturation (94 °C for 4 min), followed by 35 cycles (denaturation for 94 °C for 60 s, annealing at 66 °C for 60s and extension at 72 °C for 60s) and a final extension at 72 °C for 5 min. A single clear band of 285 bp on agarose gel (2%) was obtained. The amplified products were subjected to Single Stranded Confirmation Polymorphism (SSCP) for determination of the genotypic variation [28]. The samples were then grouped according to various genotypes as obtained on the SSCP gel. The representative samples were then again amplified using the PCR protocol as above and purified PCR products (GenElute„ ¢ Gel Extraction Kit, SIGMA) were sequenced by BigDye (Applied Biosystems, USA) sequencing reaction that exploits di-deoxy chain termination principle. The PCR-Sequence Based Typing (PCR-SBT) was used for further analysis. The homozygous sequences obtained were assigned an allelic name using nomenclature system as suggested by Ballingall and Tassi [29] to suit IPD MHC nomenclature system. The heterozygote samples were re-sequenced after cloning (InsTAclone PCR Cloning Kit, Thermo Fisher) to obtain one allele that was subsequently used to deduce another allele in heterozygous sample. Novel alleles were cloned, sequenced and confir med at least thrice. The amino acids at pocket positions were determined from the nucleotide sequences of the alleles using EditSeq software package V5.0 [30]. Alleles which were derived and not confirmed in SBT-PCR were not named. 2.3 Amplification and typing of DQB1 alleles Exon 2 of the DQB1 gene was amplified from genomic DNA using the primers as described by Amills et al. [31], where DQB-F: 5- CCC CGC AGA GGA TTT CGT G -3 and DQB-R: 5- ACC TCG CCG CTG CCA GGT -3 primers were used for amplifying 280 bp product having 8bp intron1, 270bp exon2 and 2bp intron2. The reaction mixture of 50ÃŽÂ ¼l comprised of: 10X Taq Buffer (05ÃŽÂ ¼l), 25mM MgCl2 (03ÃŽÂ ¼l), 10mM dNTP (1ÃŽÂ ¼l), 20 pmol (1ÃŽÂ ¼l) of each primer, Taq DNA Polymerase (1IU), Template (1ÃŽÂ ¼l) and Nuclease Free Water (NFW) to make 50ÃŽÂ ¼l. The thermal profile was optimized for amplification of the DQB exon2 as follows: Initial denaturation (94 °C for 4 min), followed by 35 cycles (denaturation for 94 °C for 45 s, annealing at 67 °C for 45s and extension at 72 °C for 45s) and a final extension at 72 °C for 5 min. A single clear band of 280 bp on agarose gel (2%) was obtained. The amplified products were subjected to Single Stranded Confirmation Polymorphism (SSCP ) for determination of the genotypic variation [28]. The samples were then grouped according to various genotypes as obtained on the SSCP gel. The PCR-SBT approach was used for analysis. Alleles were named as per requirements of the IPD-MHC database [29], derived alleles were not named. 2.4 PPR Vaccination, Sampling and ELISA for detection of antibody against PPRV vaccine As part of the scheduled vaccination program, the animals were vaccinated (1 ml subcutaneous) with freeze dried live attenuated PPR virus (Sungri 96 strain) vaccine with PPR virus titre †°Ã‚ ¥ 102.5 TCID50 (Raksha-PPR, Indian Immunologicals, India).   Whole blood was collected aseptically by jugular vein puncture from the kids at 28 days post vaccination (28DPV) for serum separation. Serum was collected and stored at ˆ’20- ¦C until testing. The ELISA for further analysis was done as described earlier [27]. 2.6 Statistical Analysis The allelic frequencies, genotypic frequencies, phylogenetic analysis and residue substitution was studied using Microsoft excel package of the MS office (2010) and EditSeq (DNA STAR) software. Phylogenetic analysis was performed using MEGA 4.0, neighbor joining method. To assess the effect of genotype on vaccine response (observed PI values), a General Linear Model (GLM) was used that included Cohort (2 levels), Sex (2 levels), age at vaccination (continuous) as fixed effects along with either DRB or DQB1 genotype. All the above analyses were performed using a statistical package SPSS [32]. 2.7 The dn/ds ratio and Wu Kabat variability index The frequencies of non-synonymous (dn) versus synonymous (ds) substitutions were calculated by the method of Yang and Nielsen [33] with the help of software PAML 4 [34]. The Wu Kabat variability index with respect to amino acids at peptide binding pockets was calculated using the formula given by Wu and Kabat [35]. Index =  Ã‚  Ã‚   The number of different amino acids occurring at a given position  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚   Frequency of the most common amino acid at the position Where, frequency of the common amino acid is obtained as number of times the most common amino acid occurs divided by the total number of protein examined. 3. Results and Discussion 3.1 Genetic variability for DRB Sirohi goat kids (N=360) were typed for DRB exon 2. A total of 18 new alleles were obtained after analysis in the population using SBT-PCR approach (Table 1). Out of the 18 alleles, 12 alleles were confirmed by cloning and sequencing, however 6 were derived using SBT-PCR. All 12 alleles were new and named as per the requirements of the Immuno-Polymorphism Database (IPD) following guidelines [29]. Alleles were Cahi-DRB*0701  Ã‚   (accession no. KX431913), Cahi-DRB*0104  Ã‚   (accession no. KX431914), Cahi-DRB*0402 (accession no. KX431915), Cahi-DRB*0102  Ã‚   (accession no. KX431916), Cahi-DRB*0202  Ã‚   (accession no. KX431917), Cahi-DRB*0501 (accession no. KX431918), Cahi-DRB*0401 (accession no. KX431919), Cahi-DRB*0103 (accession no. KX431920), Cahi-DRB*0203 (accession no. KX431921), Cahi-DRB*0101 (accession no. KX431922), Cahi-DRB*0201 (accession no. KX431923) and Cahi-DRB*0601 (accession no. KX431924). A total of 6 new alleles were derived using PCR-SBT approach, however not given names as per IPD-MHC nomenclature (N7, N11, N13, N16, N17, N18). Allele CahiDRB*0104 had highest frequency 29.72% followed by *0701 allele (22.64%), *0202 (13.89%) and *0102 (11.25%). In congruence with our finding, rich diversity of this region has been reported earlier in different goat breeds worldwide [3-8]. However, most of the studies were carried out using Restriction Fragment Length Polymorphism (RFLP) PCR, whereas, the current method of SSCP followed by SBT-PCR has more power to detect the genetic variability at DRB in goat. The ratio of non-synonymous (dN) to synonymous (dS) substitution for DRB gene in the Sirohi goat population was 3.24. This ratio was significantly greater than 1 indicating positive evolutionary selection for DRB gene in the present populations. However, the results are read with caution as the evidence is presumed and not absolute, due to lack of evidence for Capra species. It may be impossible to infer the selection pressure from the dN/dS measurement [36]. In another study, 11.1 ratio for dN/dS was recorded in Peptide Binding Region of 12 Chinese indigenous goats for DRB*02 sequences [6]. PBR being polymorphic, its importance is seen here. According to Simmons et al. [37], the long-term evolution, ancient and silent mutations also carried with translated mutations and became maintained in these regions. Pathogen-host interaction is complex, according to the Red Queen hypothesis [38], to be a part of this competition, diversity of MHC is important from hosts perspective. Plotting the phylogenetic tree for allelic relationship at nucleotide level revealed that the diversity was large (Fig 1). Clustering of the alleles revealed that some alleles tended to form closer clusters than others. Fig 2 reveals the amino acid variation between the alleles and it is seen that the population is polymorphic at coding region too, thus providing enough raw material for Sirohi goat population to tackle the pathogen variability. Study found that alleles DRB*0101, *0102, *0103 and *0104 had less than or equal to 4 codon change and hence clubbed together in one family. Derived allele *N18 also formed member of this group due to similarity of amino acid sequence. Similarly, alleles *0201, *0202, and *0203 had less than 4 amino acid differences. Alleles *0401 and *0402 had less than 4 amino acid differences, whereas, alleles *0501, *0601 and *0701 differed by more than 4 amino acid differences from each group. Predicted allele *N7 was related to *0701 due to similarity at amino acid level. Derived alleles *N11, *N13 and *N17 formed a group separate from others, similarly derived allele *N16 formed a different group. Phylogenetic analysis revealed that clustering based on nucleotide similarity and differences remained almost similar to clustering based on amino acid differences. 3.2 Genetic variability for DQB1 Sirohi goat kids (N=339) were typed for DQB1 exon 2. A total of 15 new alleles were obtained after analysis in the population using SBT-PCR approach (Table 1). Out of the 15 alleles, 13 alleles were confirmed by cloning and sequencing, however 2 were derived using SBT-PCR. All 13 alleles were new and named as per the requirements of the IPD [30]. Alleles were CahiDQB1*0101 (Accession number KX431925), CahiDQB1*0201 (Accession number KX431926), CahiDQB1*0301 (Accession number KX431927), CahiDQB1*0302 (Accession number KX431928), CahiDQB1*0103 (Accession number KX431929), CahiDQB1*0501 (Accession number KX431930), CahiDQB1*0104 (Accession number KX431931), CahiDQB1*0701 (Accession number KX431932), CahiDQB1*0801 (Accession number KX431933), CahiDQB1*0102 (Accession number KX431934), CahiDQB1*070101 (Accession number KX431935), CahiDQB1*0502 (Accession number KX431936) andCahiDQB1*0202 (Accession number KX431937). A total of 2 new alleles were derived using PCR-SBT approach, however not given names as per IPD-MHC nomenclature (*N2, *N3). Allele CahiDQB1*0101 had highest frequency 27.22% followed by *070101 allele (13.02%), *N2 (11.69%) and *0201 (11.54%). Very high genetic diversity for this region has also been reported earlier [3, 31]. Similar diversity is also observed in sheep and cattle DQB1 region, however for goat there are very few studies. This study is the first report for DQB1 diversity in any Indian goat breed. To study the evolutionary stability or instability of the DQB1 region in Sirohi goat, the ratio of non-synonymous (dN) to synonymous (dS) substitution for Sirohi goat has been studied. We found that the ratio was 1.08. Yakubu et al. [9] reported a ratio of 2.14 in Nigerian goat breeds.   Results reveal balancing selection in favour of variability at DQB1 in Sirohi goat. Phylogenetic analysis for alleles reported that the diversity at nucleotide level was large (Fig 1). There was a clustering of alleles for their nucleotide substitutions and thus clubbing in one or the other family. Fig 3 reveals the amino acid variation between the alleles and it is seen that the population is polymorphic at coding region. Alleles DQB1*0101, *0102, *0103 and *0104 were in one group as they had less than 4 amino acid changes. Similarly, alleles *0201, *0202, and *0203 had less than 4 amino acid differences. Alleles *0201 and *0202 formed another family, alleles *0301 and *0302 formed separate family, and alleles 0501 and 0502 were clubbed together. It was seen that derived alleles N3 had similarity at amino acid level with allele *0201, indicative of synonymous substitution at nucleotide level.   Alleles *0701 and 070101 were in one family and they did not have a single amino acid substitution. However, they had synonymous differences at nucleotide level that resul ted in the no change at peptide level. Derived allele *N2 was related with *N3, however placed in separate group due to differences at amino acid level. 3.3 Association of DRB and DQB1 genes with PPRV vaccine elicited immune response Results of C-ELISA on sera samples at 28DPV revealed mean PI value of 69.99 ±0.42 (Min 13.32, max 91.60) with minimum PI 35.12 and maximum PI 98.82.  Ã‚   Average   age   at vaccination   was   142.43    ±Ã‚   14.67   days   with   minimum   age   93 days   and maximum   age   164   days.   Variability in the vaccine response was evident in the lambs.   Frequency distribution of Ovar-DRB and DQB1 alleles revealed rich diversity amongst Sirohi goat. A total of 16 DRB genotypes and 16 DQB1 genotypes were observed to be present in the population of Sirohi goat flock. For association analysis, genotypes with >5 occurrences in the population (11 genotypes in DRB and 12 genotypes in DQB1) were only used to avoid biased estimates. Genotypic association analysis was carried out to assess the effect of genotype (Table 2) along with other environmental factors on vaccine response in Sirohi goat sheep. In the DRB group (N=299), Genotype I(DRB*0104-*0104) had highest frequency (30.10%) followed by genotype A(DRB*0701-*0701) 22.07% and genotype M(DRB*0202-*0202) 13.38%. In the DQB1 group (N=298), highest frequency was obtained for genotype E(DQB1*0801-*0801) 20.13%, followed by genotype J(DQB1*0301-*0101) 14.43% and genotype G(DQB1*0502-*0502) 11.41%. In the model that studied the effect of DRB genotype along with other environmental factors such as cohort, sex of the animal and age group, on vaccine response, explained 63.6% variation (R2=0.636). The genotypic association study revealed non-significant (P = 0.606) effect of genotype on 28DPV PI value, whereas significant effect of cohort and age at vaccination. However, ranking of genotypes revealed that the genotype L(DRB*0102-*0102) gave highest response for PPRV vaccination at 28th day (Table 2) followed by genotype J(DRB*0402-*0402) and A(DRB*0701-*0701).   Lowest response was obtained for the genotype E(DRB*0201-*0201) preceded by D(DRB*0101-*N13) and I(DRB*0104-*0104). It was noteworthy that alleles in high ranking genotypes were exclusive to low ranking genotypes. Effect of genotype was non-significant on the vaccine response, however, the trend was visible with increasing rank and declining mean PI for 28DPV (Table 2). The variability within DRB region of Sirohi goat population was calculated using the Wu-Kabat Variability Index (Table 3). The ability of a pocket to anchor a peptide is due to the electrostatic charges of the pocket region and electrostatic charges of the peptide [39]. Out of several amino acid positions in DRB, a total of 16 different amino acid positions were polymorphic with three or more than 3 amino acid differences (residue 6, 21, 32, 35, 37, 52, 61, 62, 65, 66, 68, 69, 72, 73, 76 and 81). The region revealed Wu-Kabat index varying from 2.20 to 6.95. Highest index was observed at residue 6 (6.95%), followed by ÃŽÂ ²65 (6.41%) and ÃŽÂ ²73 (5.94%).   Present results corroborates with the earlier observations in sheep breeds [41, 42], where positive selection at important residues in DRB1 amino acid sequence was observed. In DQB1 group, again the inclusive model could explain 62% of the total variation in the 28DPV vaccine response trait (R2=0.62). The model included sex, age and cohort of the animal along with the DQB1 genotype. The effect of genotype was non-significant (P = 0.868), however, the effect of cohort and age at vaccination were highly significant (PDQB1*0104-*0701) gave highest response for PPRV vaccination at 28th day (Table 2) followed by Genotype E(DQB1*0801-*0801) and I(DQB1*0201-*0201). Lowest response was obtained for the genotype D(DQB1*0101-*N3) preceded by A(DQB1*0101-*0101) and then by F(DQB1*070101-*070101). Alleles in low ranking genotypes and high ranking genotypes were exclusive to each other and hence represent the allelic substitution as an effect for change in the vaccine response. The variability within DQB1 region of Sirohi goat population was calculated using the Wu-Kabat Variability Index (Table 4).Our result suggest a lot of interesting sites in the amino acid structure of the DQB1, where substitution has taken place. The Wu-Kabat index reveal variability starting from 2.67 at ÃŽÂ ²29, ÃŽÂ ²60 to 7.19 at ÃŽÂ ²81. A total of 19 residues in the translated sequence of DQB1 were found to be polymorphic with at least three amino acid substitutions. Similar results were reported by Amills et al. (2004), where many amino acid residues within and outside the pockets were found to be polymorphic in nature. In present study, although a significant association of these substitutions with vaccine response is not observed, but variability of the region is well explored. Many factors influence the vaccine response as a trait in mammals. Role of environmental factors as well as other MHC and non-MHC genes is important, however apart from that the nature of the responding variable is also one of the most important criteria to look for in such analysis. PPR vaccine is a strong antigen and its invasion produces a cascade of reactions responsible for antibody production. In our earlier study [27], 94.92% Sirohi kids were observed to be protected with a single dose of PPRV vaccine. Therefore in spite of having variability within the protected category, the differences between the animals is not much and hence association of minor change in the phenotype vis a vis genotype is not visible.   There are several studies which revealed the effect of QTLs and non-genetic factors in detail showing the role of non-MHC genes and environmental influences on vaccine response [12,26,27,42,]. In goat, only one study [8] could show significant association of DRB gene p olymorphism obtained by PCR-RFLP with Johnes disease. Apart from this there are no studies which reveal association of MHC genotypes with disease resistance or susceptibility in goat. 4. Conclusion The genetic variability of DRB and DQB1 gene in Sirohi goat revealed a very rich diversity of this locus with positive evolutionary trend. Our study provide first description of the evidence of such a strong diversity of MHC in Indian goat breed for DRB and DQB region. Due to complex nature of the phenotype, i.e. vaccine response, and good response to the antigen used, association with studied loci was not observed. Apart from this several factors apart from MHC also affected the outcome of the response. Observed variability within the DRB and DQB1 loci reveals potential of the breed for combating several antigenic attacks and hence importance of the studied region in antigen capture and presentation to T cells. Acknowledgements Authors duly acknowledge Department of Biotechnology (GOI) for project grant to carry out the desired work. Authors are thankful to the Director ICAR-CSWRI for providing facilities for carrying out the work. Authors are also thankful to AICRP on Goat for funding the project on Sirohi goat at ICAR-CSWRI Avikanagar. Conflict of Interest Statement: The authors declare that they have no conflict of interest. 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