The major histocompatibility complex in Old World camelids and low polymorphism of its class II genes
© Plasil et al. 2016
Received: 9 November 2015
Accepted: 18 February 2016
Published: 1 March 2016
The Major Histocompatibility Complex (MHC) is a genomic region containing genes with crucial roles in immune responses. MHC class I and class II genes encode antigen-presenting molecules expressed on the cell surface. To counteract the high variability of pathogens, the MHC evolved into a region of considerable heterogeneity in its organization, number and extent of polymorphism. Studies of MHCs in different model species contribute to our understanding of mechanisms of immunity, diseases and their evolution. Camels are economically important domestic animals and interesting biomodels. Three species of Old World camels have been recognized: the dromedary (Camelus dromedarius), Bactrian camel (Camelus bactrianus) and the wild camel (Camelus ferus). Despite their importance, little is known about the MHC genomic region, its organization and diversity in camels. The objectives of this study were to identify, map and characterize the MHC region of Old World camelids, with special attention to genetic variation at selected class MHC II loci.
Physical mapping located the MHC region to the chromosome 20 in Camelus dromedarius. Cytogenetic and comparative analyses of whole genome sequences showed that the order of the three major sub-regions is “Centromere - Class II – Class III – Class I”. DRA, DRB, DQA and DQB exon 2 sequences encoding the antigen binding site of the corresponding class II antigen presenting molecules showed high degree of sequence similarity and extensive allele sharing across the three species. Unexpectedly low extent of polymorphism with low numbers of alleles and haplotypes was observed in all species, despite different geographic origins of the camels analyzed. The DRA locus was found to be polymorphic, with three alleles shared by all three species. DRA and DQA sequences retrieved from ancient DNA samples of Camelus dromedarius suggested that additional polymorphism might exist.
This study provided evidence that camels possess an MHC comparable to other mammalian species in terms of its genomic localization, organization and sequence similarity. We described ancient variation at the DRA locus, monomorphic in most species. The extent of molecular diversity of MHC class II genes seems to be substantially lower in Old World camels than in other mammalian species.
Pathogens are considered to be one of the driving forces of evolution. The major histocompatibility complex (MHC) is a genomic region containing immune response (IR) genes, which play a crucial role in host and pathogen interactions. MHC class I and class II genes encode antigen-presenting molecules responsible for the dual recognition of antigenic peptides on the cell surface . MHC-encoded antigen presenting molecules are thus directly involved in molecular interactions with specific peptides derived from pathogens to which a population is exposed. Therefore, the MHC genes are under strong selective pressure and contain signatures of both positive and negative selection . To counteract the high variability of pathogens and pathogen-derived molecules, the MHC of Gnathostomata evolved into a region of considerable heterogeneity in its organization, number, and extent of polymorphism both within and between species [3–5]. Spanning approximately 4 megabases (Mb), the MHC region consists of hundreds of different genes with a variety of functions including antigen presentation and processing as well as non-immune processes . Consequently, MHC class I and class II genes are amongst the most polymorphic genes studied in vertebrates with more than 100 alleles reported in different species, including humans [6, 7]. In MHC class II genes, a majority of the functionally important polymorphisms are concentrated in exon 2, which encodes the antigen-binding site of the molecule [8, 9]. This diversity is correlated with pathogen richness .
Infectious diseases of livestock have a significant economical impact on animal husbandry, and they also may affect human health directly or through food chains. Studies of MHCs in different model species contribute to our understanding of mechanisms of infectious diseases. Economically as well as culturally important among domestic animals are camels, with their long history of adaptation to arid environments and with their capability of providing transport and various commodities important for human development [11–13]. Currently, three extant species of Old World camels are recognized [14–16]. The dromedary (Camelus dromedarius) and Bactrian camel (Camelus bactrianus) are key domestic species in semi-arid and desert areas and are used for food production and camel racing throughout many Arabian, Northern African and Asian countries. The only surviving and critically endangered wild camel species (Camelus ferus) is closely related to them and diverged from the domestic Bactrian camel approximately 1,000,000 years ago [14, 15].
In terms of infectious disease, the Old World camels (genus Camelus) are an interesting biomodel. They are resistant to serious infections threatening other livestock inhabiting the same geographical regions [17, 18]. Recently, dromedaries have been identified as potential vectors of the Middle East Respiratory Syndrome (MERS) virus [19, 20]. The immune system of camels displays characteristic features of practical importance, like heavy chain antibody homodimers [21, 22]. Furthermore, all extant Camelus species are renowned for their ability to cope with harsh environmental challenges, including high temperatures, drought, and famine combined with high level of physical activities. However, little is known about the MHC genomic region, its organization and diversity in camels .
Recently, draft genome sequences have been made available for all three species [13, 16, 24, 25]. Although some MHC genes have been annotated in these assemblies, the draft genome sequences still contain gaps and errors . It has been repeatedly recognized for other species, that the complexity of the MHC and other complex regions involved in mechanisms of immunity and disease cannot be resolved at this level . Moreover, in camels the full genome sequences available were derived from single individuals, while the complexity of MHC and of its sub-regions should be based on targeted re-sequencing of multiple individuals originating from genetically different populations .
Therefore, the objectives of this study were to i) identify and map the MHC region in the genomes of Old World camelids, ii) characterize its overall genomic organization, and iii) characterize the genetic variation at selected class MHC II loci in modern and ancient samples.
Sample collection and DNA extraction
Total numbers of Old World camelids analyzed for MHC class II genes
Historical dromedary camel samples used in this study
Gene partially recovered
Mamluk (1260–1456 AD)
Mamluk (1260–1456 AD)
Ottoman (1456–1870 AD)
Physical mapping of the MHC region
Primers used to amplify different MHC sequences in Old World camelids
Sequence (5' → 3')
PCR product length
Preventing allele dropout
Preventing allele dropout
Preventing allele dropout
Bact, drom, ferus
FISH probe MHCII
FISH probe MHCI
Overall genomic organization of the MHC region in Old World camelids
Locations of BLAST hits on the Bactrian genome scaffolds KN276514.1 and KN277189.1 (Accession number JARL00000000.1)
DQB exon 2
MHC class II
butyrophilin-like protein 1-like
MHC class II scaffold
butyrophilin subfamily 1 member A1
MHC class I & III scaffold
MHC class III
MHC class III
BoLA, MHC class I A
MHC class I
Amplification and sequencing of MHC class II genes from modern camels
Due to their functional importance, we specifically focused on the analysis of the exon 2 coding sequences of four genes, namely DRA, DRB, DQA and DQB. Camel-specific primers were designed using the Primer3 software . For this purpose, species- and locus-specific regions were identified by BLAST  search of bovine DRA, DRB, DQA, and DQB, exon 2 sequences against the wild Bactrian camel draft genome assembly . This approach was successful for all loci except DQB, because no DQB-like sequences were found in the draft genomes available. In a second step, based on the camel-specific sequences retrieved during the first round of amplifications, primers located in the neighboring introns and amplifying the full-length exon 2 sequences could be designed. In addition, we developed a set of primers specific for each locus separately to check possible allelic dropouts (Table 3). As for DQB, attempts to use bovine primers DQB-LA40, DQB-LA41 and DQB-LA48  failed. Eventually, the zoo-primers GH28 and GH29 amplifying DQB exon 2 in various mammalian species were used successfully . All primer sequences and resulting PCR product lengths are summarized in Table 3.
The PCR reactions were performed in a reaction volume of 12.5 μl containing 50 μg/ml of DNA, 1x KAPA2G Buffer A (with MgCl2), 1x KAPA Enhancer 1, 0.2 mM of each dNTPs, 0.5 μM of forward and reverse primer and 0.5 U of KAPA2G Robust HotStart DNA Polymerase (Kapa Biosystems, USA). Negative controls were included in each PCR. Amplified PCR products were purified with ExoSAP-IT using standard protocol (Affymetrix, USA) and subjected to Sanger sequencing (Macrogen Europe, the Netherlands). Next generation sequencing (NGS) was used for a subset of samples (n = 20) as a part of our task to have all variants confirmed based on at least two independent PCRs. For the remaining samples, Sanger data available allowed the confirmation. Two platforms, Roche GS Junior or Illumina MiSeq were used according to standard protocols.
Data from Roche GS Junior were converted from sff to fasta format using sff_extract 0.3.0 . Individual libraries within.sff file were isolated using sfffile command included in the Roche Data Analysis V2.9 . Data from GS Junior and MiSeq were checked using FastQC quality control tool . All reads were trimmed with QTrim v1.1  and quality filtered with –q20 using cutadapt_v1.4.1 . Trimmed reads were aligned to the wild camel genome reference sequence  [Genbank: AGVR00000000] using BWA v0.6.2  with default parameters. We identified polymorphisms using Samtools v1.2  and viewed results in IGViewer 2.3 . For further analysis of polymorphisms, the GATK UnifiedGenotyper v2.7-2  was used with the following settings : sample ploidy = 40, site quality prior = 20, standard min confidence threshold for calling = 30, minimum power threshold for calling = 0.95.
The polymorphisms identified from the NGS data were validated by cloning and Sanger sequencing. Amplicons from selected heterozygous individuals were ligated to the pJET1.2/blunt vector and transformed using the CloneJet™ PCR cloning kit (Fermentas) according to the manufacturer’s instructions. Escherichia coli TOP 10 were used as competent cells. Colonies were screened for inserts of the expected length (~200 – 800 bp) by PCR, using the amplicon-specific primers. Purified PCR products were Sanger sequenced (Macrogen Europe). BioEdit 18.104.22.168 with implemented ClustalW algorithm for multiple alignments was used for the quality-check of the generated data using the ABI 3730XL DNA Analyzer .
Amplification and sequencing of MHC class II genes from ancient dromedary samples
Exons 2 of two MHC genes, DRA (246 bp) and DQA (249 bp) from the ancient dromedary specimens were analyzed. Two overlapping regions (fragments of 138 bp and 237 bp) of each gene were amplified and sequenced (Table 2). The PCR amplification was carried out in 20 μl volume containing 1x PCR buffer (Invitrogen), 4 mM MgCl2 (Invitrogen), 1 mg/ml BSA (Invitrogen), 250 μM mix dNTPs (Invitrogen), 1.5 μM for each primer (Invitrogen), 0.5 U of AmpliTaq Gold (Invitrogen) and 5 μl DNA template. The PCR reactions were amplified using an iCycler™ Thermal cycler (Bio-RAD) located in a separate facility. The amplification programme consisted of initial denaturation at 94 °C for 9 min followed by 60 cycles (94 °C for 20 s, 55 °C for 30 s, 72 °C for 30 s) and a final extension of 72 °C for 4 min. The PCR products were purified using the QIAquick PCR purification kit (Qiagen) and sequenced in both directions on ABI 3730 XL-Analyzer (Eurofins MWG GmbH, Ebersberg, Germany). Each sequence position was determined from two independent PCR amplifications in both directions to avoid sequence errors caused by template damage. The MHC sequences obtained from the ancient samples were aligned to the MHC DQA exon 2 [GenBank: AGVR01020882.1|:14962–15210] and DRA exon 2 [GenBank: AGVR01020883.1|:30918–31163] reference sequences using CodonCode Aligner v.22.214.171.124 (Codon Code Corporation, USA) and compared to the NCBI nucleotide database sequences, using the BLAST  with default blastn parameters.
Cross-validation of MHC class II alleles with genome re-sequencing data of dromedaries
To further validate the dromedary alleles for the MHC class II genes DRA, DRB, DQA and DQB, all Sanger sequences retrieved were compared to whole genome sequence (WGS) data obtained from a genome re-sequencing project of nine dromedaries (Fitak et al. in prep). Briefly, all sequencing was performed using an Illumina HiSeq and reads were trimmed and aligned to the dromedary reference [GenBank: GCA_000803125.1] . We realigned reads near insertion-deletion polymorphisms, recalibrated the base quality scores, and identified variants according to the recommended guidelines for the Genome Analysis Toolkit v3.1-1 [46, 48]. We identified the genomic location of the MHC class II genes in the dromedary reference using a nucleotide BLAST  search. We compared these regions with the variants identified above and inferred haplotypes when phase could be unambiguously determined (≤1 heterozygous genotype in the locus). Frequency of heterozygotes was calculated based on Sanger sequences as a proportion of heterozygotes out of all individual camels sequenced.
BioEdit 126.96.36.199 with ClustalW algorithm was used to align the allelic sequences obtained . The Jukes-Cantor  and Kimura-2-parameter  were chosen as best-fit evolutionary models based on the Akaike Information Criterion with correction for small sample size  to build distance matrices and to construct neighbor-joining phylogenetic trees  using MEGA6 . Vicugna pacos DRA exon 2 [GenBank: ABRR02040968.1|:530–775], DRB exon 2 [GenBank: ABRR02040966.1|:2004–2273] and DQA exon 2 [GenBank: ABRR02040956.1|:13508–13756] sequences were used as outgroups. We assessed the nodal support in the phylogenetic tree using 1000 bootstrap replications.
General recommendations by Klein et al.  were followed for the designation of the camel MHC loci, Mhc Cafe (C. ferus), Mhc Caba (C. bactrianus) and Mhc Cadr (C. dromedarius), respectively. Allele numbers followed the region and locus abbreviation (e.g. MhcCafe-DRA*01). For alleles that could not be assigned to a specific locus, two-digit numbers after the asterisk symbol (*) were used. The accession numbers for alleles are GenBank: KT936396-KT936421.
Physical mapping of the MHC region
Overall organization of the MHC region in domestic Bactrian camels
Exon 2 polymorphisms of MHC class II genes in Old World camelids
Distribution of MHC class II exon 2 allelic sequences in the three camel species observed in Sanger sequenced samples
DRB exon 2
Location of MHC Class II genes in the dromedary reference genome (Accession GCA_000803125.1) and the number of SNPs identified from Sanger (SSANGER) and next-generation (SNGS) sequencing
DRA Exon 2
DRB Exon 2
DQA Exon 2
DQB Exon 2b
No significant matches detected
DQA exon 2
DQB exon 2
In this study we combined cytogenetics, Sanger sequencing, and NGS to investigate the MHC in Old World camels. Our results indicated that the MHC region of these three species is structurally similar to that of New World camelids (llamas) and of bovids. These results are in agreement with data previously reported for llamas [32, 57]. A combination of different techniques was necessary to recapitulate the MHC organization. We have shown that even whole genome sequences with coverage 65x could not provide complete information on the MHC region in camelids and confirmed that targeted re-sequencing is needed to resolve the complexity of this region. New techniques, like long-read NGS, are needed to further characterize this important genomic region.
FISH analysis located the MHC region on the short arm of chromosome 20 in dromedaries. Taking into consideration the high similarities between camelid genomes and karyotypes in general, we may assume that chromosomes Cba 20 and Cfe 20 carry the MHC in the other two species as well. The structure of the entire chromosome is evolutionary conserved between camelids and bovids and these chromosomes are homologous to the MHC-carrying llama and bovine chromosomes LPA20 and Bta 23, respectively [32, 55]. The MHC of camels is similar to the MHC of cattle and other bovids not only in terms of their physical location, but also of their genetic structure. The order and orientation of the three major regions, i.e. centromere – class II – class III and class I as inferred from the WGS  were directly visualized by the FISH (Fig. 1).
Overall exon 2 similarities of nucleotide sequences (n) and peptide sequences (p) between camel, cattle, human, pig, horse, sheep and goat. Due to high similarity between all camels only Camelus ferus sequences were used as reference Accession numbers are listed in Table 8
Accession numbers of MHC class II exon 2 sequences used for comparison in Table 7
From the evolutionary perspective, only genes coding for antigen-presenting molecules, i.e. class I and class II, belong to the ancestral MHC . Their genetic variation is functionally important and it was shown to be associated with a variety of diseases. Their complexity and genetic organization require specific methodological approaches, differing between the class I and class II regions. Here, we studied functionally important and usually the most polymorphic class II genes DRA, DRB, DQA and DQB, encoding the α and β chains composing functional DR and DQ antigen-presenting dimers .
MHC class II genes are highly variable between different species due to differences in numbers of genes evolved by duplications as well as in the extent of polymorphism between individual genes [59, 60]. Intraspecific variation may be due not only to high numbers of genes and alleles, but also to variation in gene number among individual haplotypes observed in different species, including cattle . It was therefore surprising to observe low variability in the MHC class II exon 2 genomic sequences in the three camelid species. Low numbers of alleles and high numbers of homozygotes in all loci, and many alleles shared across species substantially differ from most other mammalian species with tens or even hundreds of alleles and a high degree of heterozygosity . Based on our observations, we extended the numbers of animals analyzed making sure that the camels studied originated from all major regions in the world (see Additional file 1). Three approaches (Sanger, NGS, cloning) were used to confirm the sequences retrieved and different primer pairs spanning overlapping regions were used to minimize allelic drop-outs. In addition, zoo-primers amplifying canonical MHC class II loci in other species were used. All these approaches produced similar results. The extent of allelic variation identified in groups of animals comparable to studies of other mammalian models seems to be unusually low in this particular family. We only can speculate whether there is another methodological limitation, which avoided us to assess the entire range of existing variation or whether there are reasons related to the biology of this family. Our data did not provide information about the extent of genetic variation in other MHC genes, especially in the class I loci. Lower MHC variation in different species is usually associated with (i) bottlenecks or reduced sizes of specific populations , (ii) pathogen-poor environment , (iii) particular traits of social interactions such as monogamy combined with small population numbers and low reproduction rate , or (iv) limited chance for lateral pathogen transmission . Out of these, the pathogen poor environment is an attractive hypothesis. We observed a lower overall genomic heterozygosity in dromedaries compared to domestic and wild Bactrian camels, which could hint to a generally lower genetic diversity in dromedaries (Fitak et al. in prep). However, for the MHC region, the low level of genetic diversity was observed in all three species.
The whole genome sequences available combined with the results of this study still did not allow us to determine the complete number of different class II loci. In most species, the DRA molecule is encoded by a single locus and it is usually monomorphic or with very little variation [66, 67]. Our observation of two SNPs with one non-synonymous substitution is in agreement with this general pattern. All three camel species shared identical alleles, although their distribution differed according to species. Interestingly, the allele DRA*03 prevailing in C. ferus (frequency = 0.444) was rarely observed in both domesticated species, C. bactrianus (0.05) and C. dromedarius (0.067).
The DRβ chain is usually encoded by multiple highly polymorphic loci . Hundreds of alleles and variation in the numbers of loci were observed in primates . However, in some species like musk-ox and fallow deer, the DRB genes were found to be monomorphic . In the three camel species, this was the only locus where species-specific SNPs were observed and it seems to be the least conserved out of the loci studied. This corresponds to high inter-species variability observed in other mammals . The lowest numbers of DRB alleles were found in C. ferus, which is probably due to the limited number of individuals sampled of this species, originating from a single population and to the fact that wild camels experienced a population reduction of 80 % over the last 100 years .
In most mammals, the DQA region is typically multi-locus and highly polymorphic . In cattle, variation in the number of DQA genes among individual haplotypes were reported [71–73]. Our in silico search of the camelid genomes revealed two possible DQA loci. However, the lower scoring locus seems to be a non-functional copy, as no other MHC genes could be found within the same scaffold (data not shown). Although several SNPs allowing multiple haplotype combinations were observed in the camel exon 2 DQA nucleotide sequences, only three allelic haplotypes were observed, two of them shared by all three camel species although with different frequencies (Table 5). The DQA sequences were also highly similar to human sequences (0.843 and 0.780 for nucleotide and peptide sequences, respectively), and in contrast to the DR loci, they showed high similarities with their cattle and pig orthologues (Table 7).
The DQB genomic region seems to be very complex in camels like in many other mammalian species, with many repetitive sequences of different types . For this reason probably, the camel whole genome sequences published so far do not contain this region. The fact that we were unable to amplify full-length exon 2 sequences by using several pairs of DQB zoo-primers (human, cattle, equine) and that even high-coverage whole genome sequencing and/or NGS did not allow resolving the organization of the DQB region, is in agreement with this assumption. In this situation, we had to use the zoo-primers GH 28 and 29, shown previously to amplify exon 2 DQB sequences from at least two loci of multiple mammalian species [36, 74]. The partial DQB exon 2 sequences obtained here contained high numbers of SNPs, with many non-synonymous substitutions. However, they showed the same patterns like the DQA locus, with very few individual haplotypes. As the DQB sequences obtained here are truncated, some additional variation may exist in these putative loci. A unique feature of the DQB exon 2 sequences is the 12 bp insertion not observed in other mammalian species. Based on in silico translation, the putative polypeptide may be fully functional.
The study of highly polymorphic immune genes in ancient human (Denisovan) DNA samples revealed that adaptive introgression of archaic alleles has significantly shaped the modern human immune system . Analyses of MHC genes from ancient domestic animal specimens thus can help to elucidate the historical events occurring during the domestication process. Most ancient DNA studies in domestic animals relied on mtDNA due to general difficulties associated with the recovery of nuclear DNA (nuDNA) from archaeozoological materials. Despite their importance, there have been no studies of ancient immune genes and their role in domestication and adaptation in livestock to date. This dataset represents the first MHC sequences retrieved from ancient camel specimens from hot and arid environments, which are notoriously the most unfavorable for the survival of DNA . Although fragmentary at this stage, the data showed that some DRA haplotypes have been maintained over time. The three extra C/T substitutions observed in AQ30 still need to be validated as true polymorphisms in additional (historical) samples, rather than representing ancient DNA damage commonly observed as C to T (complementary G to A) change resulting from post-mortem cytosine deamination .
Previously, Antczak  reported on the existence of polymorphic MHC class I and class II genes and on MHC-linked microsatellite repeats located in the Bactrian camel genome. A whole genome cytogenetic map including data on the MHC region is available for New World camelids . However, no specific sequences were available for a comparison for the purposes of this study.
In summary, this study provided the first evidence that camels possess an MHC comparable to other mammalian species in terms of its genomic localization, organization and sequence similarity. This is the first complex report on the order of the three MHC major sub-regions in Old World camels, based on physical mapping. We described ancient variation at the DRA locus, monomorphic in most species. The extent of molecular diversity of MHC class II genes seems to be substantially lower in Old World camels than in other mammalian species. The major part of the diversity could reside in the complex DQB region, which was difficult to resolve and remained unannotated in the whole genome sequences.
Availability of supporting data
All alignments and resulting phylogenetic trees are available at the TreeBASE (http://treebase.org/treebase-web/home.html) under DOI http://purl.org/phylo/treebase/phylows/study/TB2:S18850.
All sequences were submitted to GenBank (http://www.ncbi.nlm.nih.gov/genbank/) and are available under accession numbers KT936396-KT936421.
Projects: The work was supported by the Central European Institute of Technology (CEITEC) CZ.1.05/1.1.00/02.0068, by the project Aktion (68p7), and by the Austrian Science Foundations (FWF; P24706-B25 to PB); PB is recipient of an APART fellowship (11506) of the Austrian Academy of Sciences.
The authors would like to thank Drs. Joris Peters (Institute of Palaeoanatomy, Domestication Research and the History of Veterinary Medicine, Ludwig-Maximilian University, Munich, Germany), Moneeb Qablan (University of Veterinary and Pharmaceutical Sciences Brno, Czech Republic), Elena Ciani and Ingrid Alloggio (University of Bari, Italy) for providing selected samples.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- Janeway CA, Travers P, Walport M, Shlomchik MJ. Immunobiology: The Immune System in Health and Disease. 5th ed. New York: Garland Science; 2001. http://www.ncbi.nlm.nih.gov/books/NBK27156/.Google Scholar
- Meyer D, Thomson G. How selection shapes variation of the human major histocompatibility complex: a review. Ann Hum Genet. 2001;65:1–26.View ArticlePubMedGoogle Scholar
- Hedrick PW. Evolutionary genetics of the major histocompatibility complex. American Naturalist. 1994;143:945–964.Google Scholar
- Reche PA, Reinherz EL. Sequence variability analysis of human class I and class II MHC molecules: functional and structural correlates of amino acid polymorphisms. J Mol Biol. 2003;331:623–41.View ArticlePubMedGoogle Scholar
- Cho S, Attaya M, Monaco JJ. New class ll-like genes in the murine MHC. Nature. 1991;353:573–6.View ArticlePubMedGoogle Scholar
- Bontrop RE, Otting N, Groot NG, Doxiadis GG. Major histocompatibility complex class II polymorphisms in primates. Immunol Rev. 1999;167:339–50.View ArticlePubMedGoogle Scholar
- Robinson J, Halliwell JA, McWilliam H, Lopez R, Marsh SGE. IPD—the Immuno Polymorphism Database. Nucleic Acids Res. 2013;41:D1234–40.View ArticlePubMedPubMed CentralGoogle Scholar
- He Y, Xi D, Leng J, Qian T, Jin D, Chen T, et al. Genetic variability of MHC class II DQB exon 2 alleles in yak (Bos grunniens). Mol Biol Rep. 2014;41:2199–206.View ArticlePubMedGoogle Scholar
- Alcaide M, Munoz J, Martínez‐de la Puente J, Soriguer R, Figuerola J. Extraordinary MHC class II B diversity in a non‐passerine, wild bird: the Eurasian Coot Fulica atra (Aves: Rallidae). Ecol Evol. 2014;4:688–98.View ArticlePubMedPubMed CentralGoogle Scholar
- Wegner KM, Reusch TBH, Kalbe M. Multiple parasites are driving major histocompatibility complex polymorphism in the wild. J Evol Biol. 2003;16:224–32.View ArticlePubMedGoogle Scholar
- Bulliet RW. The Camel and the Wheel, vol. 56. Cambridge, MA: Harvard University Press; 1975. p. 340.Google Scholar
- Burger PA. Genetic Traces of Domestication in Old World Camelids. In: Knoll EM, Burger PA, editors. Camels in Asia and North Africa: Interdisciplinary Perspectives on Their Past and Present Significance. Vienna: Austrian Academy of Science Press; 2012. p. 17–28.Google Scholar
- Wu H, Guang X, Al-Fageeh MB, Cao J, Pan S, Zhou H, et al. Camelid genomes reveal evolution and adaptation to desert environments. Nat Commun. 2014;5:1–9.Google Scholar
- Ji R, Cui P, Ding F, Geng J, Gao H, Zhang H, et al. Monophyletic origin of domestic bactrian camel (Camelus bactrianus) and its evolutionary relationship with the extant wild camel (Camelus bactrianus ferus). Anim Genet. 2009;40:377–82.View ArticlePubMedPubMed CentralGoogle Scholar
- Silbermayr K, Orozco-terWengel P, Charruau P, Enkhbileg D, Walzer C, Vogl C, et al. High mitochondrial differentiation levels between wild and domestic Bactrian camels: a basis for rapid detection of maternal hybridization. Anim Genet. 2010;41:315–8.View ArticlePubMedGoogle Scholar
- Jirimutu, Wang Z, Ding G, Chen G, Sun Y, Sun Z, Zhang H, Wang L, Hasi S, Zhang Y, Li J, Shi Y, Xu Z, He C, Yu S, Li S, Zhang W, Batmunkh M, Ts B, Narenbatu, Unierhu, Bat-Ireedui S, Gao H, Baysgalan B, Li Q, Jia Z, Turigenbayila, Subudenggerile, Narenmanduhu, Wang Z, et al. Genome sequences of wild and domestic bactrian camels. Nat Commun. 2012; 3:1202.Google Scholar
- Wernery U, Kaaden OR. Foot-and-mouth disease in camelids: a review. Vet J. 2004;168:134–42.View ArticlePubMedGoogle Scholar
- Dirie MF, Abdurahman O. Observations on little known diseases of camels (Camelus dromedarius) in the Horn of Africa. Revue scientifique et technique-Office international des épizooties. 2003;22:1043–50.Google Scholar
- Azhar EI, El-Kafrawy SA, Farraj SA, Hassan AM, Al-Saeed MS, Hashem AM, et al. Evidence for Camel-to-Human Transmission of MERS Coronavirus. N Engl J Med. 2014;370(26):2499–505.View ArticlePubMedGoogle Scholar
- Hemida MG, Elmoslemany A, Al‐Hizab F, Alnaeem A, Almathen F, Faye B, et al. Dromedary Camels and the Transmission of Middle East Respiratory Syndrome Coronavirus (MERS‐CoV). Transbound Emerg Dis. 2015. doi:10.1111/tbed.12401.PubMedGoogle Scholar
- Muyldermans S, Baral TN, Retamozzo VC, De Baetselier P, De Genst E, Kinne J, et al. Camelid immunoglobulins and nanobody technology. Vet Immunol Immunopathol. 2009;128:178–83.View ArticlePubMedGoogle Scholar
- Tillib SV, Vyatchanin AS, Muyldermans S. Molecular analysis of heavy chain-only antibodies of Camelus bactrianus. Biochem Mosc. 2014;79:1382–90.View ArticleGoogle Scholar
- Antczak D. Major Histocompatibility Complex Genes Of The Dromedary Camel. In: Qatar Foundation Annual Research Conference. Doha, Qatar: BIOP 015;2013.Google Scholar
- Burger PA, Palmieri N. Estimating the Population Mutation Rate from a de novo Assembled Bactrian Camel Genome and Cross-Species Comparison with Dromedary ESTs. J Hered. 2013;105(6):839–46.PubMedPubMed CentralGoogle Scholar
- Fitak RR, Mohandesan E, Corander J, Burger PA. The de novo genome assembly and annotation of a female domestic dromedary of North African origin. Mol Ecol Resour. 2015. doi:10.1111/1755-0998.12443.PubMedGoogle Scholar
- Green ED, Guyer MS, Institute NHGR. Charting a course for genomic medicine from base pairs to bedside. Nature. 2011;470:204–13.View ArticlePubMedGoogle Scholar
- Lighten J, van Oosterhout C, Bentzen P. Critical review of NGS analyses for de novo genotyping multigene families. Mol Ecol. 2014;23:3957–72.View ArticlePubMedGoogle Scholar
- Green MR, Sambrook J. Molecular Cloning: A Laboratory Manual, vol. 1. New York: Cold Spring Harbor Laboratory Press; 2012.Google Scholar
- Knapp M, Clarke AC, Horsburgh KA, Matisoo-Smith EA. Setting the stage–building and working in an ancient DNA laboratory. Annals of Anatomy-Anatomischer Anzeiger. 2012;194:3–6.View ArticleGoogle Scholar
- Rohland N, Hofreiter M. Comparison and optimization of ancient DNA extraction. Biotechniques. 2007;42:343.View ArticlePubMedGoogle Scholar
- Rohland N, Siedel H, Hofreiter M. A rapid column‐based ancient DNA extraction method for increased sample throughput. Mol Ecol Resour. 2010;10:677–83.View ArticlePubMedGoogle Scholar
- Avila F, Das PJ, Kutzler M, Owens E, Perelman P, Rubes J, et al. Development and application of camelid molecular cytogenetic tools. J Hered. 2014;201(105):858–69.Google Scholar
- Basic Local Alignment Search Tool. http://blast.ncbi.nlm.nih.gov/Blast.cgi. Accessed 15 Oct 2015.
- Rozen S, Skaletsky H. Primer3 on the WWW for general users and for biologist programmers. In: Bioinformatics methods and protocols. New York, NY. USA: Springer; 1999. 365–386.Google Scholar
- Sigurdardóttir S, Borsch C, Gustafsson K, Andersson L. Gene duplications and sequence polymorphism of bovine class II DQB genes. Immunogenetics. 1992;35:205–13.View ArticlePubMedGoogle Scholar
- Gyllensten UB, Lashkari D, Erlich HA. Allelic diversification at the class II DQB locus of the mammalian major histocompatibility complex. Proc Natl Acad Sci. 1990;87:1835–9.View ArticlePubMedPubMed CentralGoogle Scholar
- Sff_extract. http://bioinf.comav.upv.es/sff_extract/index.html. Accessed 9 July 2014.
- GS de novo Assembler. http://www.454.com/products/analysis-software/. Accessed 9 July 2014
- FastQC. http://www.bioinformatics.babraham.ac.uk/projects/fastqc/. Accessed 10 July 2014.
- Shrestha R, Lubinsky B, Bansode V, Moinz M, McCormack G, Travers S. QTrim: a novel tool for the quality trimming of sequence reads generated using the Roche/454 sequencing platform. BMC Bioinformatics. 2014;15:33.View ArticlePubMedPubMed CentralGoogle Scholar
- Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 2011;17:10–2.View ArticleGoogle Scholar
- Li H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv preprint arXiv:13033997 2013.Google Scholar
- Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. 1000 Genome Project Data Processing Subgroup. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009;25:2078–9.View ArticlePubMedPubMed CentralGoogle Scholar
- Robinson JT, Thorvaldsdóttir H, Winckler W, Guttman M, Lander ES, Getz G, et al. Integrative genomics viewer. Nat Biotechnol. 2011;29:24–6.View ArticlePubMedPubMed CentralGoogle Scholar
- McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010;20:1297–303.View ArticlePubMedPubMed CentralGoogle Scholar
- DePristo MA, Banks E, Poplin R, Garimella KV, Maguire JR, Hartl C, et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat Genet. 2011;43:491–8.View ArticlePubMedPubMed CentralGoogle Scholar
- Hall TA. BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. In: Nucleic acids symposium series, vol. 41. 1999. p. 95–8.Google Scholar
- Auwera GA, Carneiro MO, Hartl C, Poplin R, del Angel G, Levy‐Moonshine A, et al. From FastQ data to high‐confidence variant calls: the genome analysis toolkit best practices pipeline. Curr Protoc Bioinformatics. 2013;11(1110):11.10.1–11.10.33.Google Scholar
- Jukes TH, Cantor CR. Evolution of protein molecules. Mamm Protein Metab. 1969;3:21–132.View ArticleGoogle Scholar
- Kimura M. A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J Mol Evol. 1980;16:111–20.View ArticlePubMedGoogle Scholar
- Akaike H. A new look at the statistical model identification. Automatic Control, IEEE Transactions on. 1974;19:716–23.View ArticleGoogle Scholar
- Saitou N, Nei M. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol. 1987;4:406–25.PubMedGoogle Scholar
- Tamura K, Stecher G, Peterson D, Filipski A, Kumar S. MEGA6: molecular evolutionary genetics analysis version 6.0. Mol Biol Evol. 2013;30:2725–9.View ArticlePubMedPubMed CentralGoogle Scholar
- Klein J, Bontrop RE, Dawkins RL, Erlich HA, Gyllensten UB, Heise ER, Jones PP, Parham P, Wakeland EK, Watkins DI. Nomenclature for the major histocompatibility complexes of different species: a proposal. In: Solheim BG, Ferrone S, Möller E. editors. The HLA System in Clinical Transplantation. Berlin, Heidelberg, Germany: Springer. 1993; 407–411.Google Scholar
- Balmus G, Trifonov VA, Biltueva LS, O’Brien PC, Alkalaeva ES, Fu B, et al. Cross-species chromosome painting among camel, cattle, pig and human: further insights into the putative Cetartiodactyla ancestral karyotype. Chromosom Res. 2007;15:499–514.View ArticleGoogle Scholar
- Kumánovics A, Takada T, Lindahl KF. Genomic organization of the mammalian MHC. Annu Rev Immunol. 2003;21:629–57.View ArticlePubMedGoogle Scholar
- Avila F, Baily MP, Perelman P, Das PJ, Pontius J, Chowdhary R, et al. A Comprehensive Whole-Genome Integrated Cytogenetic Map for the Alpaca (Lama pacos). Cytogenet Genome Res. 2014;144:196–207.View ArticlePubMedGoogle Scholar
- Klein J, Figueroa F. Evolution of the major histocompatibility complex. Crit Rev Immunol. 1985;6:295–386.Google Scholar
- Parham P. Virtual reality in the MHC. Immunol Rev. 1999;167:5–15.View ArticlePubMedGoogle Scholar
- Mikko S, Røed K, Schmutz S, Andersson L. Monomorphism and polymorphism at Mhc DRB loci in domestic and wild ruminants. Immunol Rev. 1999;167:169–78.View ArticlePubMedGoogle Scholar
- Andersson L, Rask L. Characterization of the MHC class II region in cattle. The number of DQ genes varies between haplotypes. Immunogenetics. 1988;27:110–20.View ArticlePubMedGoogle Scholar
- Bollmer JL, Vargas FH, Parker PG. Low MHC variation in the endangered Galapagos penguin (Spheniscus mendiculus). Immunogenetics. 2007;59:593–602.View ArticlePubMedGoogle Scholar
- Weber DS, Van Coeverden De Groot PJ, Peacock E, Schrenzel MD, Perez DA, Thomas S, et al. Low MHC variation in the polar bear: implications in the face of Arctic warming? Anim Conserv. 2013;16:671–83.View ArticleGoogle Scholar
- Sommer S, Tichy H. Major histocompatibility complex (MHC) class II polymorphism and paternity in the monogamous Hypogeomys antimena, the endangered, largest endemic Malagasy rodent. Mol Ecol. 1999;8:1259–72.View ArticlePubMedGoogle Scholar
- Ellegren H, Mikk S, Wallin K, Andersson L. Limited polymorphism at major histocompatibility complex (MHC) loci in the Swedish moose A. alces. Mol Ecol. 1996;5:3–9.View ArticlePubMedGoogle Scholar
- Zhou H, Hickford JGH, Fang Q, Byun SO. Short Communication: Identification of Allelic Variation at the Bovine DRA Locus by Polymerase Chain Reaction-Single Strand Conformational Polymorphism. J Dairy Sci. 2007;90:1943–6.View ArticlePubMedGoogle Scholar
- Takada T, Kikkawa Y, Yonekawa H, Amano T. Analysis of goat MHC class II DRA and DRB genes: identification of the expressed gene and new DRB alleles. Immunogenetics. 1998;48:408–12.View ArticlePubMedGoogle Scholar
- Takeshima S, Saitou N, Morita M, Inoko H, Aida Y. The diversity of bovine MHC class II DRB3 genes in Japanese Black, Japanese Shorthorn, Jersey and Holstein cattle in Japan. Gene. 2003;316:111–8.View ArticlePubMedGoogle Scholar
- Yadamsuren, A, Dulamtseren E, Reading RP. The conservation status and management of wild camels in Mongolia. In: Knoll EM, Burgr PA, editors. Camels in Asia and North Africa. Interdisciplinary perspectives on their significance in past and present.Vienna. Austrian Academy of Sciences Press. 2012; p 45–54.Google Scholar
- Ballingall KT, Steele P, Lantier I, Cotelli M, Todd H, Lopez G, et al. An ancient interlocus recombination increases class II MHC DQA diversity in sheep and other Bovidae. Anim Genet. 2015;46:333–6.View ArticlePubMedGoogle Scholar
- Ballingall KT, Luyai A, McKeever DJ. Analysis of genetic diversity at the DQA loci in African cattle: evidence for a BoLA-DQA3 locus. Immunogenetics. 1997;46:237–44.View ArticlePubMedGoogle Scholar
- Moutou K, Koutsogiannouli E, Stamatis C, Billinis C, Kalbe C, Scandura M, et al. Domestication does not narrow MHC diversity in Sus scrofa. Immunogenetics. 2013;65:195–209.View ArticlePubMedGoogle Scholar
- Behl JD, Verma NK, Tyagi N, Mishra P, Behl R, Joshi BK. The Major Histocompatibility Complex in Bovines: A Review. ISRN Vet Sci. 2012;2012:1–12.View ArticleGoogle Scholar
- Hořín P, Matiašovic J. A second locus and new alleles in the major histocompatibility complex class II (ELA-DQB) region in the horse. Anim Genet. 2002;33:196–200.View ArticlePubMedGoogle Scholar
- Abi-Rached L, Jobin MJ, Kulkarni S, McWhinnie A, Dalva K, Gragert L, et al. The shaping of modern human immune systems by multiregional admixture with archaic humans. Science. 2011;334:89–94.View ArticlePubMedPubMed CentralGoogle Scholar
- Hofreiter M, Paijmans JL, Goodchild H, Speller CF, Barlow A, Fortes GG, et al. The future of ancient DNA: Technical advances and conceptual shifts. BioEssays. 2015;37:284–93.View ArticlePubMedGoogle Scholar
- Briggs AW, Stenzel U, Meyer M, Krause J, Kircher M, Pääbo S. Removal of deaminated cytosines and detection of in vivo methylation in ancient DNA. Nucleic Acids Res. 2010;38:87.View ArticleGoogle Scholar