Assessment of Genetic Relationship and Application of Computational Algorithm to Assess Functionality of Non-Synonymous Substitutions in DQA2 Gene of Cattle, Sheep and Goats
Author(s)
Steven B. Ugbo1*,
Abdulmojeed Yakubu2*,
Jude N. Omeje3,
Bwaseh S. Bibinu1,
Ibrahim S. Musa2,
Joseph O. Egahi1,
N. I. Dim1
Affiliation(s)
1 Department of Animal Breeding and Physiology, University of Agriculture, Makurdi, Nigeria. 2 Department of Animal Science, Faculty of Agriculture, Nasarawa State University, Keffi, Shabu-Lafia Campus, Lafia, Nigeria. 3 Department of Veterinary Medicine and Surgery, University of Abuja, Abuja, Nigeria.
1 Department of Animal Breeding and Physiology, University of Agriculture, Makurdi, Nigeria. 2 Department of Animal Science, Faculty of Agriculture, Nasarawa State University, Keffi, Shabu-Lafia Campus, Lafia, Nigeria. 3 Department of Veterinary Medicine and Surgery, University of Abuja, Abuja, Nigeria.
ABSTRACT
The major histocompatibility complex (MHC) is a fundamental part of the immune system in nearly all vertebrates. DQA2 is a member of the MHC complex and an important candidate gene involved in susceptibility/resistance to various diseases. Therefore, the present study aimed at investigating computationally molecular genetic variation of DQA2 gene of cattle, sheep and goats especially on its evolution and differentiation within and among species as well as the attendant effects of the polymorphism on the function of DQA2 gene. A total of thirty three DQA2 nucleotide sequences comprising cattle (10), sheep (12) and goats (11) were retrieved from the GenBank. Forty seven amino acid substitutions of the wild type alleles located in the putative peptide coding region of caprine DQA2 alleles were obtained from the alignment of deduced amino acid sequences of goats. Out of these, eleven amino acid substitutions (H14L, H14R, L34M, E35L, G56S, G56R, 161V, A62E, D69Q, T72N and T72G) were returned neutral; an indication that they did not impair protein function. The Expected Accuracy (EA) ranged from 53% - 87%. For sheep, sixteen amino acid substitutions (A11P, A11T, A11G, A11M, L14S, L14T, V27L, V27S, G35S, S46T, D55E, L57T, L57A, L57G, K65Q and V68I) appeared beneficial while the rest forty seven appeared harmful (EA ranged from 53% - 93%). Twenty four amino acid substitutions did not impair the function of protein while seventy seven substitutions appeared to have a negative effect on the function of protein of cattle (EA ranged from 53% - 94%). The phylogeny based on nucleotide and amino acid sequences of DQA2 gene revealed the close relatedness of the caprine, ovine and bovine species. The present knowledge would be relevant for performing further genotype-phenotype research as well as pharmacogenetics studies in order to show association between caprine, ovine and bovine DQA2 allelic variation and the clinical progression of infectious diseases especially in a developing country such as Nigeria.
The major histocompatibility complex (MHC) is a fundamental part of the immune system in nearly all vertebrates. DQA2 is a member of the MHC complex and an important candidate gene involved in susceptibility/resistance to various diseases. Therefore, the present study aimed at investigating computationally molecular genetic variation of DQA2 gene of cattle, sheep and goats especially on its evolution and differentiation within and among species as well as the attendant effects of the polymorphism on the function of DQA2 gene. A total of thirty three DQA2 nucleotide sequences comprising cattle (10), sheep (12) and goats (11) were retrieved from the GenBank. Forty seven amino acid substitutions of the wild type alleles located in the putative peptide coding region of caprine DQA2 alleles were obtained from the alignment of deduced amino acid sequences of goats. Out of these, eleven amino acid substitutions (H14L, H14R, L34M, E35L, G56S, G56R, 161V, A62E, D69Q, T72N and T72G) were returned neutral; an indication that they did not impair protein function. The Expected Accuracy (EA) ranged from 53% - 87%. For sheep, sixteen amino acid substitutions (A11P, A11T, A11G, A11M, L14S, L14T, V27L, V27S, G35S, S46T, D55E, L57T, L57A, L57G, K65Q and V68I) appeared beneficial while the rest forty seven appeared harmful (EA ranged from 53% - 93%). Twenty four amino acid substitutions did not impair the function of protein while seventy seven substitutions appeared to have a negative effect on the function of protein of cattle (EA ranged from 53% - 94%). The phylogeny based on nucleotide and amino acid sequences of DQA2 gene revealed the close relatedness of the caprine, ovine and bovine species. The present knowledge would be relevant for performing further genotype-phenotype research as well as pharmacogenetics studies in order to show association between caprine, ovine and bovine DQA2 allelic variation and the clinical progression of infectious diseases especially in a developing country such as Nigeria.
Cite this paper
B. Ugbo, S. , Yakubu, A. , Omeje, J. , S. Bibinu, B. , S. Musa, I. , O. Egahi, J. and Dim, N. (2015) Assessment of Genetic Relationship and Application of Computational Algorithm to Assess Functionality of Non-Synonymous Substitutions in DQA2 Gene of Cattle, Sheep and Goats. Open Journal of Genetics, 5, 145-158. doi: 10.4236/ojgen.2015.54011.
B. Ugbo, S. , Yakubu, A. , Omeje, J. , S. Bibinu, B. , S. Musa, I. , O. Egahi, J. and Dim, N. (2015) Assessment of Genetic Relationship and Application of Computational Algorithm to Assess Functionality of Non-Synonymous Substitutions in DQA2 Gene of Cattle, Sheep and Goats. Open Journal of Genetics, 5, 145-158. doi: 10.4236/ojgen.2015.54011.
References
[1] Biek, R. and Real, L.A. (2010) The Landscape Genetics of Infectious Disease Emergence and Spread. Molecular Ecology, 19, 3515-3531.
http://dx.doi.org/10.1111/j.1365-294X.2010.04679.x [2] Zhou, H., Hickford, J.G.H. and Fang, Q. (2005) Polymorphism of the DQA2 Gene in Goats. Journal of Animal Science, 83, 963-968. [3] Yakubu, A., Salako, A.E., De Donato, M., Takeet, M.I., Peters, S.O., Adefenwa, M.A., Okpeku, M., Wheto, M., Agaviezor, B.O., Sanni, T.M., Ajayi, O.O., Onasanya, G.O., Ekundayo, O.J., Ilori, B.M., Amusan, S.A. and Imumorin, I.G. (2013) Genetic Diversity in Exon 2 at the Major Histocompatibility Complex DQB1 Locus in Nigerian Indigenous Goats. Biochemical Genetics, 51, 954-966.
http://dx.doi.org/10.1007/s10528-013-9620-y [4] Niranjan, S.K., Deb, S.M., Kumar, S., Mitra, A., Sharma, A., Sakaram, D., Naskar, S., Sharma, D. and Sharma, S.R. (2010) Allelic Diversity at MHC Class 11 DQ Loci in Buffalo (Bubalusbubalis): Evidence for Duplication. Veterinary Immunology and Immunopathology, 138, 206-212.
http://dx.doi.org/10.1016/j.vetimm.2010.07.014 [5] Amills, M., Ramirez, O., Tomas, A., Obexer-Ruff, G. and Vidal, O. (2008) Positive Selection on Mammalian MHC-DQ Genes Revisited from a Multispecies Perspective. Genes and Immunity, 9, 651-658.
http://dx.doi.org/10.1038/gene.2008.62 [6] Ballingall, K.T., Luyai, A. and McKeever, D.J. (1997) Analysis of Genetic Diversity at the DQA Loci in African Cattle: Evidence for a BoLA-DQA3 Locus. Immunogenetics, 46, 237-244.
http://dx.doi.org/10.1007/s002510050268 [7] McKenzie, G.W., Abbott, A., Zhou, H., Fang, Q., Merrick, N., Forrest, R.H., Sedcole, J.R. and Hickford, J.G. (2012) Genetic Diversity of Selected Genes That Are Potentially Economically Important in Feral Sheep of New Zealand. Genetics Selection Evolution, 42, 43. [8] Vandre, R.K., Gowane, G.R., Sharma, A.K. and Tomar, S.S. (2014) Immune Responsive Role of MHC Class II DQA1 Gene in Livestock. Livestock Research International, 2, 1-7. [9] Vandre, R.K., Sharma, A.K., Gowane, G.R., Rajoriya, R., Rajoriya, S., Sinha, R.K., Kumar, A., Shivhare, M., Caser, D.D. and Meshram, S.K. (2014) Polymorphism and Disease Resistance Possessions of MHC Class II BoLA Genes. DHR International Journal of Biomedical and Life Sciences, 5.
http://www.doublehelixresearch.com/DHRIJBLS [10] George, P.D.C., Rajasekaran, R., Sudandiradoss, C., Ramanathan, K., Purohit, R. and Sethumadhavan, R. (2008) A Novel Computational and Structural Analysis of nsSNPs in CFTR Gene. Genomic Medicine, 2, 23-32.
http://dx.doi.org/10.1007/s11568-008-9019-8 [11] Liu, L. and Kumar, S. (2013) Evolutionary Balancing Is Critical for Correctly Forecasting Disease Associated Amino Acid Variants. Molecular Biology and Evolution, 30, 1252-1257.
http://dx.doi.org/10.1093/molbev/mst037 [12] Zemla, D., Kostova, T., Gorchakov, R., Volkova, E., Beasley, D.W.C., Cardosa, J., Weaver, S.C., Vasilakis, N. and Naraghi-Arani, P. (2014) Genesv—An Approach to Help Characterize Possible Variations in Genomic and Protein Sequences. Bioinformatics and Biology Insights, 8, 1-16.
http://dx.doi.org/10.4137/BBI.S13076 [13] Choi, Y., Sims, G.E., Murphy, S., Miller, J.R. and Chan, A.P. (2012) Predicting the Functional Effect of Amino Acid Substitutions and Indels. PLoS ONE, 7, e46688.
http://dx.doi.org/10.1371/journal.pone.0046688 [14] Larkin, M.A., Blackshields G., Brown, N.P., Chenna, R., McGettigan, P.A., McWilliam, H., Valentin, F., Wallace, I.M., Wilm, A., Lopez, R., Thompson, J.D., Gibson, T.J. and Higgins, D.G. (2007) Clustal W and Clustal X Version 2.0. Bioinformatics, 23, 2947-2948.
http://dx.doi.org/10.1093/bioinformatics/btm404 [15] Bromberg, Y. and Rost, B. (2007) SNAP: Predicts Effect of Non-Synonymous Polymorphisms on Function. Nucleic Acids Research, 35, 3823-3835.
http://dx.doi.org/10.1093/nar/gkm238 [16] Ng, P.C. and Henikoff, S. (2003) SIFT: Predicting Amino Acid Changes That Affect Protein Function. Nucleic Acids Research, 31, 3812-3814.
http://dx.doi.org/10.1093/nar/gkg509 [17] Bairoch, A. and Apweiler, R. (2000) The SWISS-PROT Protein Sequence Database and Its Supplement TrEMBL in 2000. Nucleic Acids Research, 28, 45-48.
http://dx.doi.org/10.1093/nar/28.1.45 [18] Bromberg, Y., Yachdav, G. and Rost, B. (2008) SNAP Predicts Effect on Protein Function. Bioinformatics Applications Note, 24, 2397-2398.
http://dx.doi.org/10.1093/bioinformatics/btn435 [19] Felsenstein, J. (1985) Confidence Limits on Phylogenies: An Approach Using the Bootstrap. Evolution, 39, 783-791.
http://dx.doi.org/10.2307/2408678 [20] Tamura, K., Peterson, D., Peterson, N., Stecher, G., Nei, M. and Kumar, S. (2011) MEGA 5: Molecular Evolutionary Genetics Analysis Using Maximum Likelihood, Evolutionary Distance, and Maximum Parsimony Methods. Molecular Biology and Evolution, 28, 2731-2739.
http://dx.doi.org/10.1093/molbev/msr121 [21] Zhao, Y., Xu, H., Shi, L. and Zhang, J. (2011) Polymorphisms in Exon 2 of MHC Class II DRB3 Gene of 10 Domestic Goats in Southwest China. Asian-Australasian Journal of Animal Science, 24, 752-756.
http://dx.doi.org/10.5713/ajas.2011.10398 [22] Amills, M. (2014) The Application of Genomic Technologies to Investigate the Inheritance of Economically Important Traits in Goats. Advances in Biology, 2014, Article ID: 904281.
http://dx.doi.org/10.1155/2014/904281 [23] McManus, C., Paim, T.D.P., de Melo, C.B., Brasil, B.S.A.F. and Paiva, S.R. (2014) Selection Methods for Resistance to and Tolerance of Helminths in Livestock. Parasite, 21, Article No.: 56.
http://dx.doi.org/10.1051/parasite/2014055 [24] Hickford, J.G.H., Forrest, R.H.J., Zhou, H., Fang, Q. and Frampton, C.M. (2011) Association between Variation in Faecal Egg Count for a Mixed Field-Challenge of Nematode Parasites and Ovine MHC-DQA2 Polymorphism. Veterinary Immunology and Immunopathology, 144, 312-320.
http://dx.doi.org/10.1016/j.vetimm.2011.08.014 [25] Kemper, K.E., Emery, D.L., Bishop, S.C., et al. (2011) The Distribution of SNP Marker Effects for Faecal Worm Egg Count in Sheep, and the Feasibility of Using These Markers to Predict Genetic Merit for Resistance to Worm Infections. Genetics Research, 93, 203-219.
http://dx.doi.org/10.1017/S0016672311000097 [26] Preston, S.J.M., Sandeman, M., Gonzalez, J. and Piedrafita, D. (2014) Current Status for Gastrointestinal Nematode Diagnosis in Small Ruminants: Where Are We and Where Are We Going? Journal of Immunology Research, 2014, Article ID: 210350.
http://dx.doi.org/10.1155/2014/210350 [27] Ellis, S.A. and Hammond, J.A. (2014) The Functional Significance of Cattle Major Histocompatibility Complex Class I Genetic Diversity. Annual Review of Animal Biosciences, 2, 285-306.
http://dx.doi.org/10.1146/annurev-animal-022513-114234 [28] Wuliji, T., Hickford, J.G.H., Lamberson, W.R., Shanks, B.C. and Azarpajouh, S. (2014) Ovine Footrot Gene Marker Screening in a Katahdin Sheep Flock. Proceedings of Joint Annual Meeting of ASAS, Kansas City, 20-24 July 2014. [29] Takeshima, S., Chen, S., Miki, M., Kado, M. and Aida, Y. (2008) Distribution and Origin of Bovine Major Histocompatibility Complex Class II DQA1 Genes in Japan. Tissue Antigens, 72, 195-205.
http://dx.doi.org/10.1111/j.1399-0039.2008.01092.x [30] Sun, Y., Zhang, X., Xi, D., Li, G., Wang, L., Zheng, H., Du, M., Gu, Z., Yang, Y. and Yang, Y. (2015) Isolation and cDNA Characteristics of MHC-DRA Genes from Gayal (Bos frontalis) and Gaytle (Bos frontalis × Bostaurus). Biotechnology & Biotechnological Equipment, 29, 33-39.
http://dx.doi.org/10.1080/13102818.2014.986128 [31] Reche, P.A. and Reinherz, E.L. (2003) Sequence Variability Analysis of Human Class I and Class II MHC Molecules: Functional and Structural Correlates of Amino Acid Polymorphisms. Journal of Molecular Biology, 331, 623-641.
http://dx.doi.org/10.1016/S0022-2836(03)00750-2
[1] Biek, R. and Real, L.A. (2010) The Landscape Genetics of Infectious Disease Emergence and Spread. Molecular Ecology, 19, 3515-3531.
http://dx.doi.org/10.1111/j.1365-294X.2010.04679.x [2] Zhou, H., Hickford, J.G.H. and Fang, Q. (2005) Polymorphism of the DQA2 Gene in Goats. Journal of Animal Science, 83, 963-968. [3] Yakubu, A., Salako, A.E., De Donato, M., Takeet, M.I., Peters, S.O., Adefenwa, M.A., Okpeku, M., Wheto, M., Agaviezor, B.O., Sanni, T.M., Ajayi, O.O., Onasanya, G.O., Ekundayo, O.J., Ilori, B.M., Amusan, S.A. and Imumorin, I.G. (2013) Genetic Diversity in Exon 2 at the Major Histocompatibility Complex DQB1 Locus in Nigerian Indigenous Goats. Biochemical Genetics, 51, 954-966.
http://dx.doi.org/10.1007/s10528-013-9620-y [4] Niranjan, S.K., Deb, S.M., Kumar, S., Mitra, A., Sharma, A., Sakaram, D., Naskar, S., Sharma, D. and Sharma, S.R. (2010) Allelic Diversity at MHC Class 11 DQ Loci in Buffalo (Bubalusbubalis): Evidence for Duplication. Veterinary Immunology and Immunopathology, 138, 206-212.
http://dx.doi.org/10.1016/j.vetimm.2010.07.014 [5] Amills, M., Ramirez, O., Tomas, A., Obexer-Ruff, G. and Vidal, O. (2008) Positive Selection on Mammalian MHC-DQ Genes Revisited from a Multispecies Perspective. Genes and Immunity, 9, 651-658.
http://dx.doi.org/10.1038/gene.2008.62 [6] Ballingall, K.T., Luyai, A. and McKeever, D.J. (1997) Analysis of Genetic Diversity at the DQA Loci in African Cattle: Evidence for a BoLA-DQA3 Locus. Immunogenetics, 46, 237-244.
http://dx.doi.org/10.1007/s002510050268 [7] McKenzie, G.W., Abbott, A., Zhou, H., Fang, Q., Merrick, N., Forrest, R.H., Sedcole, J.R. and Hickford, J.G. (2012) Genetic Diversity of Selected Genes That Are Potentially Economically Important in Feral Sheep of New Zealand. Genetics Selection Evolution, 42, 43. [8] Vandre, R.K., Gowane, G.R., Sharma, A.K. and Tomar, S.S. (2014) Immune Responsive Role of MHC Class II DQA1 Gene in Livestock. Livestock Research International, 2, 1-7. [9] Vandre, R.K., Sharma, A.K., Gowane, G.R., Rajoriya, R., Rajoriya, S., Sinha, R.K., Kumar, A., Shivhare, M., Caser, D.D. and Meshram, S.K. (2014) Polymorphism and Disease Resistance Possessions of MHC Class II BoLA Genes. DHR International Journal of Biomedical and Life Sciences, 5.
http://www.doublehelixresearch.com/DHRIJBLS [10] George, P.D.C., Rajasekaran, R., Sudandiradoss, C., Ramanathan, K., Purohit, R. and Sethumadhavan, R. (2008) A Novel Computational and Structural Analysis of nsSNPs in CFTR Gene. Genomic Medicine, 2, 23-32.
http://dx.doi.org/10.1007/s11568-008-9019-8 [11] Liu, L. and Kumar, S. (2013) Evolutionary Balancing Is Critical for Correctly Forecasting Disease Associated Amino Acid Variants. Molecular Biology and Evolution, 30, 1252-1257.
http://dx.doi.org/10.1093/molbev/mst037 [12] Zemla, D., Kostova, T., Gorchakov, R., Volkova, E., Beasley, D.W.C., Cardosa, J., Weaver, S.C., Vasilakis, N. and Naraghi-Arani, P. (2014) Genesv—An Approach to Help Characterize Possible Variations in Genomic and Protein Sequences. Bioinformatics and Biology Insights, 8, 1-16.
http://dx.doi.org/10.4137/BBI.S13076 [13] Choi, Y., Sims, G.E., Murphy, S., Miller, J.R. and Chan, A.P. (2012) Predicting the Functional Effect of Amino Acid Substitutions and Indels. PLoS ONE, 7, e46688.
http://dx.doi.org/10.1371/journal.pone.0046688 [14] Larkin, M.A., Blackshields G., Brown, N.P., Chenna, R., McGettigan, P.A., McWilliam, H., Valentin, F., Wallace, I.M., Wilm, A., Lopez, R., Thompson, J.D., Gibson, T.J. and Higgins, D.G. (2007) Clustal W and Clustal X Version 2.0. Bioinformatics, 23, 2947-2948.
http://dx.doi.org/10.1093/bioinformatics/btm404 [15] Bromberg, Y. and Rost, B. (2007) SNAP: Predicts Effect of Non-Synonymous Polymorphisms on Function. Nucleic Acids Research, 35, 3823-3835.
http://dx.doi.org/10.1093/nar/gkm238 [16] Ng, P.C. and Henikoff, S. (2003) SIFT: Predicting Amino Acid Changes That Affect Protein Function. Nucleic Acids Research, 31, 3812-3814.
http://dx.doi.org/10.1093/nar/gkg509 [17] Bairoch, A. and Apweiler, R. (2000) The SWISS-PROT Protein Sequence Database and Its Supplement TrEMBL in 2000. Nucleic Acids Research, 28, 45-48.
http://dx.doi.org/10.1093/nar/28.1.45 [18] Bromberg, Y., Yachdav, G. and Rost, B. (2008) SNAP Predicts Effect on Protein Function. Bioinformatics Applications Note, 24, 2397-2398.
http://dx.doi.org/10.1093/bioinformatics/btn435 [19] Felsenstein, J. (1985) Confidence Limits on Phylogenies: An Approach Using the Bootstrap. Evolution, 39, 783-791.
http://dx.doi.org/10.2307/2408678 [20] Tamura, K., Peterson, D., Peterson, N., Stecher, G., Nei, M. and Kumar, S. (2011) MEGA 5: Molecular Evolutionary Genetics Analysis Using Maximum Likelihood, Evolutionary Distance, and Maximum Parsimony Methods. Molecular Biology and Evolution, 28, 2731-2739.
http://dx.doi.org/10.1093/molbev/msr121 [21] Zhao, Y., Xu, H., Shi, L. and Zhang, J. (2011) Polymorphisms in Exon 2 of MHC Class II DRB3 Gene of 10 Domestic Goats in Southwest China. Asian-Australasian Journal of Animal Science, 24, 752-756.
http://dx.doi.org/10.5713/ajas.2011.10398 [22] Amills, M. (2014) The Application of Genomic Technologies to Investigate the Inheritance of Economically Important Traits in Goats. Advances in Biology, 2014, Article ID: 904281.
http://dx.doi.org/10.1155/2014/904281 [23] McManus, C., Paim, T.D.P., de Melo, C.B., Brasil, B.S.A.F. and Paiva, S.R. (2014) Selection Methods for Resistance to and Tolerance of Helminths in Livestock. Parasite, 21, Article No.: 56.
http://dx.doi.org/10.1051/parasite/2014055 [24] Hickford, J.G.H., Forrest, R.H.J., Zhou, H., Fang, Q. and Frampton, C.M. (2011) Association between Variation in Faecal Egg Count for a Mixed Field-Challenge of Nematode Parasites and Ovine MHC-DQA2 Polymorphism. Veterinary Immunology and Immunopathology, 144, 312-320.
http://dx.doi.org/10.1016/j.vetimm.2011.08.014 [25] Kemper, K.E., Emery, D.L., Bishop, S.C., et al. (2011) The Distribution of SNP Marker Effects for Faecal Worm Egg Count in Sheep, and the Feasibility of Using These Markers to Predict Genetic Merit for Resistance to Worm Infections. Genetics Research, 93, 203-219.
http://dx.doi.org/10.1017/S0016672311000097 [26] Preston, S.J.M., Sandeman, M., Gonzalez, J. and Piedrafita, D. (2014) Current Status for Gastrointestinal Nematode Diagnosis in Small Ruminants: Where Are We and Where Are We Going? Journal of Immunology Research, 2014, Article ID: 210350.
http://dx.doi.org/10.1155/2014/210350 [27] Ellis, S.A. and Hammond, J.A. (2014) The Functional Significance of Cattle Major Histocompatibility Complex Class I Genetic Diversity. Annual Review of Animal Biosciences, 2, 285-306.
http://dx.doi.org/10.1146/annurev-animal-022513-114234 [28] Wuliji, T., Hickford, J.G.H., Lamberson, W.R., Shanks, B.C. and Azarpajouh, S. (2014) Ovine Footrot Gene Marker Screening in a Katahdin Sheep Flock. Proceedings of Joint Annual Meeting of ASAS, Kansas City, 20-24 July 2014. [29] Takeshima, S., Chen, S., Miki, M., Kado, M. and Aida, Y. (2008) Distribution and Origin of Bovine Major Histocompatibility Complex Class II DQA1 Genes in Japan. Tissue Antigens, 72, 195-205.
http://dx.doi.org/10.1111/j.1399-0039.2008.01092.x [30] Sun, Y., Zhang, X., Xi, D., Li, G., Wang, L., Zheng, H., Du, M., Gu, Z., Yang, Y. and Yang, Y. (2015) Isolation and cDNA Characteristics of MHC-DRA Genes from Gayal (Bos frontalis) and Gaytle (Bos frontalis × Bostaurus). Biotechnology & Biotechnological Equipment, 29, 33-39.
http://dx.doi.org/10.1080/13102818.2014.986128 [31] Reche, P.A. and Reinherz, E.L. (2003) Sequence Variability Analysis of Human Class I and Class II MHC Molecules: Functional and Structural Correlates of Amino Acid Polymorphisms. Journal of Molecular Biology, 331, 623-641.
http://dx.doi.org/10.1016/S0022-2836(03)00750-2