G C A T
T A C GG C A T

genes

ArticleA Study of the Genetic Structure of Hybrid Camels
in Kazakhstan
Makpal Amandykova 1,2 , Kairat Dossybayev 1,2 , Aizhan Mussayeva 2 , Naruya Saitou 3, *,Zhazira Zhunusbayeva 1 and Bakytzhan Bekmanov 1,2
1

2

3

*

Citation: Amandykova, M.;
Dossybayev, K.; Mussayeva, A.;
Saitou, N.; Zhunusbayeva, Z.;
Bekmanov, B. A Study of the Genetic
Structure of Hybrid Camels in

Faculty of Biology and Biotechnology, Al-Farabi Kazakh National University, Al-Farabi Ave. 71,
Almaty 050040, Kazakhstan; makpal_30.01@mail.ru (M.A.); kairat1987_11@mail.ru (K.D.);
zhazira.zhunusbayeva@kaznu.edu.kz (Z.Z.); bobekman@rambler.ru (B.B.)
Laboratory of Genetics and Cytogenetics, Institute of Genetics and Physiology SC MSHE RK, Al-Farabi
Ave. 93, Almaty 050060, Kazakhstan; aimus_@mail.ru
Saitou Naruya Laboratory, National Institute of Genetics, 1111 Yata, Mishima 411-8540, Shizuoka, Japan
Correspondence: saitounr@nig.ac.jp

Abstract: Camel farming is gaining scientific interest due to its unique agricultural characteristics.
Camels are versatile for milk and meat production, wool, racing, transport, and tourism. To use theirfull potential, it is essential to improve our understanding of the genetic structure of these animals.
One-humped and two-humped camels have received detailed genetic descriptions, while there isno such information for their hybrids, which outperform their parent species in several agriculturalcharacteristics. Thus, in this study, for the first time, the whole genome sequencing data (WGS) of
five hybrid camels bred in the Almaty region of Kazakhstan are presented in comparison with the
WGS data of one-humped, two-humped, and wild camels. A total of 43,552,164 single-nucleotide
polymorphisms were found across the studied groups. Further comparison of these SNPs showed
the following number of private SNPs among the populations: hybrid camels (3,271,083), wild camels(2,515,591), Bactrians (1,244,694), and dromedaries (531,224). The genetic structure of the studied
animals was described, and a phylogenetic tree was built to assess their genetic distance. It was
found that the studied hybrids are genetically closer to dromedaries since they were on the closebranch of the phylogenetic tree.
Keywords: Kazakhstan hybrid camels; whole genome sequencing; single nucleotide polymorphism;
genetic structure analysis; phylogenetics

Kazakhstan. Genes 2023, 14, 1373.
https://doi.org/10.3390/
genes14071373

1. Introduction
Academic Editors: Bill Ballard andJeffrey Kidd
Received: 12 May 2023
Revised: 23 June 2023
Accepted: 26 June 2023
Published: 28 June 2023

Copyright: © 2023 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms andconditions of the Creative Commons
Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Camels have been used since about the 15th century BC as a mode of transportation [1],while their domestication took place somewhere between 3000 and 6000 years ago. The
family Camelidae appeared around 40 million years ago in the middle Eocene, and thefamily’s first ancestors appeared in North America [2]. Afterward, they differentiated into
Old and New World camelids. Molecular studies estimated that this split happened
11–16 million years ago [3] or 25 million years ago [4,5]. The old-world camelids migrated tothe eastern hemisphere and split into two species: Camelus bactrianus (two-humped camels)
and Camelus dromedarius (one-humped camels). The divergence of Camelus dromedarius andCamelus bactrianus species is estimated to have occurred between 4.4 and 8 million years
ago [5]. Wild two-humped camels (Camelus ferus) separated from domestic two-humped
camels between 0.6 and 1.8 million years ago [6].
One-humped camels inhabit the deserts of Arabia, while the primary habitat of twohumped camels is in Asia. These species can be crossed and produce fertile offspring
partly because they have the same sets of chromosomes (2n = 74) [7]. The crossbreeding of
one-humped and two-humped camels has been practiced in the Middle East and Central
Asia since ancient times to produce camels with a muscular body constitution, which

Genes 2023, 14, 1373. https://doi.org/10.3390/genes14071373

https://www.mdpi.com/journal/genes

Genes 2023, 14, 1373

2 of 13are more enduring for transporting goods in trade caravans and for military use. Camelhybridization is now widely used in two countries: Turkey and Kazakhstan. In Turkey,
hybridization is widespread in order to obtain large animals for participation in annual
camel fights, whereas in Kazakhstan, hybridization is utilized to obtain more productive
camels that can better withstand the harsh climate of Central Asia [8]. According to someauthors, hybrid wool productivity increased by 192% compared with the pure dromedary
breed, and hybrid milk production was 69% higher than the Bactrian and even slightly
higher (2%) than the dromedary. The milk composition differed between the two species,
with the hybrids being intermediate: Bactrian milk had a higher concentration of vitamin C
and minerals and a higher fat content but lower long-chain fatty acids [9,10]. Furthermore,
due to the heterosis, hybrids have advantages over their parents in terms of precocity andhigh productivity [11].
Even though the genetic status of the two domestic species has long been established,wild Bactrian camels were only recently recognized as separate species based on molecular
genetic data, particularly mitochondrial DNA and nuclear markers [6,12]. In 2002, they wereclassified as critically endangered animals; there were approximately 950 wild Bactrians
worldwide. In May 2006, wild Bactrians were listed in the IUCN Red List of Threatened
Species. Currently, there are only three separate habitats for wild camels; 600 individuals
are based in northwestern China (Lake Lop, the Taklamakan desert, and the Arjin Shan
ranges) and 450 individuals are based in southwestern Mongolia (Trans-Altai Gobi desert).
It is worth noting that wild camels are unique objects for studying the adaptive mechanismsof the immune system, as they have adapted to live in the harsh conditions of a desert
climate [13]. Research on discovering the essential genes involved in their adaptation to
the desert environment may lead to understanding the disease resistance in various animal
species, which can be used in breeding programs.
In Kazakhstan, both Bactrians and dromedaries and their hybrids are widespread; insome cases, all three representatives can be found on the same farm. Camel breeding is oneof the most profitable sectors of the Kazakhstan economy, as it makes it possible to fully meetthe population’s needs with regards to wool, milk, and meat in the country’s desert climate.
In 2022, the camel population in Kazakhstan reached 2.6 million [14]. The zones with themost significant distribution of camels in Kazakhstan include the Aktobe, Mangystau, South
Kazakhstan, Kyzylorda, Atyrau, and Almaty regions. Hybridization between one-humped
and two-humped camels has various options for crossing. Depending on the initial parental
forms, in Kazakhstan, two methods of hybridization have been identified: Kazakh—whena female Bactrian is crossed with a male dromedary—and Turkmen—when a female
dromedary is crossed with a male Bactrian. While studying the genetics of the productive
profile of Kazakh camel populations, Baimukanov et al. established the genetic profile
of camels (live weight, milk production, wool shearing, and body measurements). The
study’s results showed the effectiveness of breeding hybrid camel dams of the dromedarygroup for the production of camel milk due to the optimal ratio of milk fat and protein [11].
The rapid development of molecular genetics methods over the past decades has
positively affected the prospect of obtaining extensive data on the genetic structure ofcamels (genetic variation, molecular markers, parentage control, the gene of interest, wholegenome, dating, and others). To date, the genetic study of camels is sorted into several
categories, such as the following: the assessment of genetic diversity and population structure for studying local or regional groups; large-scale phylogenetic studies investigating
the demographic history of populations; studies investigating the association between
phenotypic traits and underlying genotypes for using marker-assisted breeding programs
or adaptation to a particular environment [12]. Also, the genetic data provide important
clues about the breeding strategies and selection processes of camels that people used in
antiquity. Other important methods for studying the genetics of camels are described indetail by Piro et al. [15].
The use of microsatellites is considered to be a powerful tool for tracking alleles
in a population and assessing genetic variation within and between breeds [16]. The

Genes 2023, 14, 1373

3 of 13international panel on Animal Genetic Diversity (ISAG-FAO, 2004) recommended a list of
25 microsatellites markers for the evaluation of genetic diversity in camelids; 16 of them areconsidered to be the most polymorphic and are thus highly recommended for dromedarycamel genetic characterization [15]. The genetic diversity of four groups of Moroccan camels
was studied based on these 16 microsatellite markers, which showed high informativeness,revealing a high level of diversification of the studied genetic resources of camels [17].
Furthermore, the different studies on dromedary genetic diversity were not limited tothese 16 microsatellites but instead used a range of varying microsatellite markers whose
number and name differ from one study to another [15]. Similar results were obtained in astudy of two groups of Saudi Arabian dromedary camels, where 21 microsatellite loci were
examined, and it was found that very little gene flow occurred between these groups [18].
The mitochondrial DNA (mtDNA) reflects maternal inheritance and helps establish
genetic variation between species [15]. The three existing species of camels inhabit hot andlow-mountainous deserts, as well as cold and high-altitude deserts. mtDNA sequencing
contributes to studying the role of natural selection under different environmental pressuresand can improve our understanding of the evolutionary history of this genus. As a resultof these studies, the evolutionary time of divergence between domestic and wild Bactriancamels is estimated to be around 1.1 (0.58–1.8) million years ago [6]. On the other hand,
mtDNA sequence analysis revealed dromedary domestication processes and the dynamics
of domestication and cross-continental movement of the dromedary camel. Almathen et al.
combined ancient DNA sequences of wild and early domesticated dromedary samples
from arid regions with nuclear microsatellite and mitochondrial genotype information,
demonstrating the potential of using mitochondrial DNA for ancient camel studies [19].
SNP chip technology is also considered a highly informative method for studying
animals’ genetic structure and genetic diversity. These markers can be beneficial because
they are easy to use and reproducible. The development of SNP markers that cover thecoding part of the genome is also needed to understand the relationship between genetic
and phenotypic variations in camels or other species [15,16].
Whole genome sequencing (WGS) is the most effective technology conducted in animal husbandry, which makes it possible to extensively understand the genomic structureof the studied farm animals. Unlike SNP chip technology, WGS can produce complete
structural genetic information [20]. Nuclear SNPs are also applied in some studies ofthe dromedary camel [21]. These markers can be used as an alternative to microsatellites,
especially in genetic diversity studies, detecting relevant phenotypic traits in livestock [15].
For example, when comparing the genetic sequences of one-humped and two-humped
camels, 116,000 SNPs were identified, which determined that 85% of the genomic sequences expressed in the one-humped camel can be found in the two-humped camel [22].
These results may provide some insight into the evolution of Bactrian camels, and thediscovery of genome-wide genetic variation paves the way for developing techniquessuch as genome-wide association studies and genomic selection [23]. In another context,
Ruiz et al. [24] developed a diagnostic panel of SNPs to identify the hybridization patterns
in camels with uncertain origins to support hybrid breeding management and detect potential rare dromedary introgression in the remaining wild Bactrian camels in Mongolia andChina. Recently, in a genome-wide association study, by using genotyping via sequencing,
Sani et al. [25] were able to identify 99 SNP markers that could be associated with important
traits to improve camel breeding, namely, birth, weight, daily gain, and body weight [26].
Other studies also describe the distribution, breeds, evolutionary history, domestication, and genetic diversity of various camel populations based on mtDNA, nuclear DNA,and whole genome sequencing [27,28], such as the identification of the association ofpolymorphisms in growth hormone, insulin-like growth factor-I, and other genes withsome physical characteristics of camels [27]. While most of these studies covered major
geographic regions/countries and identified millions of SNPs amenable to implementation within array-based genotyping platforms, future studies will likely focus on in-depth
analyses of within-population/within-country genetic diversity to capture fine-scale ge-

Genes 2023, 14, 1373

4 of 13

nomic variation and population structures. The latest technologies for studying the genetic
structure, including the genotypes and phenotypes of pure breed Bactrian and dromedarycamels and their hybrids, will allow us to build each “breed standard” and detect genotypes
with highly productive features [29].
It should be noted that the genetic characteristics of Kazakhstani camel populations are
yet to be studied, apart from the studies based on microsatellites [30] and camel casein gene
polymorphism [31]. As for hybrids, data on studies of their genetic characteristics still need
to be included. Thus, in this study, we aim to identify the genome-wide variations (SNPs)
in Kazakhstani hybrids of one-humped and two-humped camels using the whole genome
sequencing data of five hybrid camels compared with the whole genome sequencing dataof six Bactrian, four dromedary, and five wild camels. Our main goal is to describe thegenetic structure of hybrid camels in comparison with their parental species (one-humped
and domestic two-humped camels) and wild camels.
2. Materials and Methods
2.1. Sample Collection
Whole genome sequencing data of 20 camels was used for the study: six samplesof Camelus bactrianus (Kazakhstan camel population, n = 6♀), four samples of Camelus
dromedarius (Iranian camel population, n = 3♀; n = 1♂), five samples of Camelus ferus (GobiDesert, Mongolia, the sex of the animals is missing), and five samples of hybrids (n = 5♀) of
one-humped and two-humped camels (Kazakhstan). Information on the parental speciesof hybrid camels is presented in Table 1.
Table 1. Hybrid camels origin information.
№

Description

Hybrid-1
Hybrid-2
Hybrid-3
Hybrid-4
Hybrid-5♀Bactrian × ♂Dromedary♀Bactrian × ♂Dromedary♀Dromedary × ♂Bactrian♀Bactrian × ♂Dromedary♀Bactrian × ♂Dromedary

Information about the parental individuals of hybrids often plays an essential role
in research on the mitochondrial genome of hybrids. However, it may also be the key
to understanding some study results when studying their genetic structure using wholegenome sequencing data.
The first 15 samples (the age and developmental stage of the animals are missing)were taken from the NCBI database from a study by Chinese researchers on the wholegenome sequencing data of 128 camels (GenBank accession number SRP107089). For theremaining five hybrids, whole genome sequencing was performed. The number of studied
animals from each population was determined following the number of sequenced samplesof hybrid camels to balance the obtained results. The blood samples of the hybrids aged
2–3 years were collected by a veterinarian in EDTA vacuum tubes on the camel farm in the
Akshi village of the Ili district of the Almaty region (Kazakhstan), which is one of the largest
camel breeding centers in this area. Camels of both species (Bactrian and dromedary andtheir hybrids) are bred here. All animal care and experiments were approved by the Local
Ethics Committee of the Institute of Genetics and Physiology SC MSHE RK (14 April 2022,
Almaty, Kazakhstan). All the samples and data processed in our study were obtained withthe consent of the breeding farm. To reduce the stress on animals, positive rewards such as
petting were implemented before restraint for blood collection. Further, the blood samples
were delivered to the Laboratory of Animal Genetics and Cytogenetics of the Institute of
Genetics and Physiology (Almaty, Kazakhstan) in containers with refrigerant and stored ina freezer (at −25 ◦ C) until used for DNA extraction.

Genes 2023, 14, 1373

5 of 132.2. DNA Extraction and Quality Assessment
DNA extraction was performed using the GeneJET Genomic DNA Purification Kit(ThermoScientific, Waltham, MA, USA) according to the manufacturer’s protocol. For
preparing the extraction solution, 1:1 volume of Binding Buffer was added to the completed
PCR mixture and mixed, yielding a yellow-colored solution, which indicated an optimal
pH for DNA binding. A total of 800 µL of the yellow-colored solution was transferred up
to the GeneJET. The flow-through purification column was discarded after centrifuging
for 30–60 s. Then, 700 µL of Wash Buffer was added to the GeneJET purification column
and centrifuged for 30–60 s. After discarding the flow-through, the purification column
was placed back into the collection tube. A total of 50 µL of Elution Buffer was added tothe center of the GeneJET purification column membrane and centrifuged for 1 min. The
purified DNA was stored at −20 ◦ C prior to use.
The determination of the quantitative and qualitative indicators of DNA was carriedout on a NanoDrop One and a Qubit Fluorometer (ThermoScientific, USA). The obtained
data are presented in Table 2.
Table 2. DNA concentration of hybrid camels.
DNA Concentration (ng/µL)№

DNA Samples

1

NanoDrop One Data

Qubit Fluorometer Data

Hybrid-1

57.6

53.4

2

Hybrid-2

67.8

60.4

3

Hybrid-3

51.2

48.6

4

Hybrid-4

69.1

62.1

5

Hybrid-5

55.3

53.6

Whole genome sequencing requires DNA at a concentration of at least 50 ng/µL.
Thus, the quantitative indicators of our DNA samples were more than suitable for further
analysis. DNA quality was also checked via agarose gel electrophoresis.
2.3. Whole Genome Sequencing
Sequencing was carried out on the Illumina New Generation Sequencing platform(NovaSeq 6000) from Macrogen company (Seoul, Republic of Korea) and consisted offour stages: quality control of DNA samples and preparation for the library construction;library construction; sequencing; acquiring raw data in *.fastq file format. The sequencing
library was prepared via the random fragmentation of the DNA samples, followed by
50 and 30 adapter ligation. Alternatively, “tagmentation” combines the fragmentationand ligation reactions into a single step, which significantly increases the efficiency ofthe library preparation process. Adapter-ligated fragments were then PCR-amplified
and gel-purified. The library was loaded into a flow cell for cluster generation, where
fragments were captured on a lawn of surface-bound oligos complementary to the library
adapters. Each fragment was then amplified into distinct, clonal clusters through bridge
amplification. Illumina SBS technology utilizes a proprietary reversible terminator-based
method that detects single bases as they are incorporated into DNA template strands. As
all four reversible, terminator-bound dNTPs were present during each sequencing cycle,
natural competition minimized incorporation bias and significantly reduced raw error
rates compared to other technologies, resulting in highly accurate base-by-base sequencing,which virtually eliminates sequence-context-specific errors, even within repetitive sequence
regions and homopolymers. Sequencing data were converted into raw data for analysis.
The Illumina sequencer generates raw images utilizing sequencing control software forsystem control and base calling through an integrated primary analysis software called
RTA (Real Time Analysis). The BCL (base calls) binary was converted into FASTQ utilizing
the Illumina package bcl2fastq. The following indicators were calculated for the raw data:

Genes 2023, 14, 1373

6 of 13the total number of bases; the total number of reads; GC content (%); quality score of 20(Q20, %), which represents an error rate of 1 in 100 (meaning every 100 bp sequencing readmay contain an error), with a corresponding call accuracy of 99%; and quality score of 30(Q30, %) with a call accuracy of 99.9%.
2.4. Sequencing Data Analysis
The processing and analysis of raw sequencing data were performed in several stages
using bioinformatics analysis methods. Quality control of the raw sequencing reads
was performed using FastQC v.0.12.0 (http://opengene.org/fastp/fastp/, accessed on
11 June 2023), which provides an overview of basic quality control metrics for raw sequencing data [32]. Clean reads were mapped to the Camelus ferus reference assembly (NCBI
Accession: NW_006210177.1) using Burrows–Wheeler aligner v.0.7.15 (BWA-MEM algorithm) (https://github.com/bwa-mem2/bwa-mem2/, accessed on 11 June 2023), which
has the best performance based on alignment rate and gene coverage [33]. The SAMTools
v.1.17 (https://github.com/samtools/, accessed on 11 June 2023) [34] was used to sort andindex the files. Further, the identification of repeated reads was carried out on the Picard
tool v.3.0.0 (https://github.com/broadinstitute/picard/, accessed on 11 June 2023) [35],and the identification of differences between aligned reads and the reference genome
was carried out on bcftools v.0.1.13 (https://github.com/samtools/bcftools/, accessed on
11 June 2023) [36]. The quality control of the obtained SNPs was carried out based on Plink
v.1.9 (https://www.cog-genomics.org/plink/, accessed on 11 June 2023) [37] to remove
SNPs with insufficient genotyping quality using several parameters, such as the following:
absence of SNPs in a significant part of the individuals, individuals with a high level ofgenotype absence (--geno 0.01, --mind 0.02), a low minor allele frequency threshold set toeliminate genotyping errors (--maf 0.01) and Hardy–Weinberg equilibrium (--hwe 0.001),
individuals with a high or low heterozygosity index (--indep 50 5 2).
2.5. Genetic Structure Analysis
Admixture v.1.3 (https://dalexander.github.io/admixture/, accessed on 11 June 2023),
which provides maximum likelihood estimations of individual ancestries from multilocus
SNP genotype datasets [38], and PCA (https://principal-component-analysis-pca.apponic.
com/, accessed on 11 June 2023), which estimates population structure and sample ancestry
in genetic datasets [39], were used for a comparative description of the genetic structure of
the studied animals. The R Package v.4.2.3 (Shortstop Beagle) (https://www.r-project.org/,
accessed on 11 June 2023) [40] was used to search for breed-specific and breed-wide SNPs.
The neighbor-joining (NJ) method, which is based on the distance between species [41], wasused to construct the phylogenetic tree, and the results were visualized using the FigTree
program v.1.4.4 (http://tree.bio.ed.ac.uk/software/figtree/, accessed on 11 June 2023) [42].
3. Results and Discussion
3.1. Whole Genome Sequencing and Data Filtering
As a result of sequencing, raw data in *.fastq format was obtained, and the total
number of reads varied from 717,006,544 to 1,377,460,994 among five camels. This result
was consistent with the whole genome sequencing results of Iranian camels, as the average
number of reads is fairly similar [23,43]. The average GC content, which typically includes
many protein-coding genes, was 41.92%, and Q30 was 92.99%. Our sequencing data showeda high Phred quality (Q20 > 97%, Q30 > 82%), which is a measure of the quality of theidentification of the nucleobases generated by automated DNA sequencing, and the GC
content was stable at between 41.84 and 42.01% (Table 3 and Figure 1).

Genes 2023, 14, 1373

average number of reads is fairly similar [23,43]. The average GC content, which typically
includes many protein‐coding genes, was 41.92%, and Q30 was 92.99%. Our sequencing
data showed a high Phred quality (Q20 > 97%, Q30 > 82%), which is a measure of the quality
7 of 13of the identification of the nucleobases generated by automated DNA sequencing, and the GC
content was stable at between 41.84 and 42.01% (Table 3 and Figure 1).
Table
3. Rawdata
statistics.
Table
3. Rawdata
statistics.

14 (%) 4 AT AT
5 5
1
2
3
Sample
IDTotal
Total Read
Total3 Reads GC
Sample ID
Read Bases(bp) 2Bases (bp)
Total
Reads
(%)GC
(%)(%)

Q20 (%)(%) 66Q20

Q30
Q30(%)(%)7 7Hybrid camel‐1
129,838,121,006
859,855,106
58.06
97.17
92.70
Hybrid camel-1
129,838,121,006
859,855,106
41.94 41.94
58.06
97.17
92.70
Hybrid camel‐2
137,538,079,710
910,848,210
41.92
58.08
97.32
93.02
Hybrid camel-2
58.08
97.32
93.02
Hybrid camel‐3 137,538,079,710
207,996,610,094 910,848,210
1,377,460,994 41.92 41.91
58.09
97.23
82.89
Hybrid camel‐4 207,996,610,094
108,267,988,144 1,377,460,994
717,006,544 41.91 42.01
57.99
97.38
93.22
Hybrid camel-3
58.09
97.23
82.89
Hybridcamel‐5
134,823,736,024
892,872,424
41.84
58.16
97.36
93.13
Hybrid camel-4
108,267,988,144
717,006,544
42.01
57.99
97.38
93.22
1 Sample name. 2 Total number of bases sequenced. 3 Total number of reads. For Illumina paired‐end
Hybrid camel-5
134,823,736,024
892,872,424
41.84
58.16
97.36
Ratio ofsequencing, this value refers to the sum of read 1 and read 2. 4 GC content. 5 AT content. 6 93.13
1 Sample
2 Total7 Ratiobasesname.
that havea Phredscoreof over320.
of bases
thatForhavea Phredquality sequencing,score ofnumberqualityof basessequenced.
Total
numberof reads.
Illumina
paired-end
thisovervalue30.
refers to the sum of read 1 and read 2. 4 GC content. 5 AT content. 6 Ratio of bases that have a Phredquality score of over 20. 7 Ratio of bases that have a Phred quality score of over 30.

Figure1. (A)ADMIXTURE
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for all studied
animals
were generated. After the first step of quality control, 470,961 SNPs passed the filters. Afterthe exclusion of SNPs absent in a significant part of the individuals and the exclusionof individuals with a high level of genotype absence (--geno 0.01, --mind 0.02), a low
minor allele frequency threshold was set to eliminate genotyping errors (--maf 0.01) andHardy–Weinberg equilibrium (--hwe 0.001), resulting in a total of 253,213 SNPs being
selected. Another important step to note is the exclusion of individuals with a high or low
heterozygosity index (--indep 50 5 2), which resulted in 31,015 SNPs being selected forfurther study.

being selected. Another important step to note is the exclusion of individuals with a highor low heterozygosity index (‐‐indep 50 5 2), which resulted in 31,015 SNPs being selected
for further study.
Genes 2023, 14, 1373

3.3. Population Structure Analysis

8 of 13

A genetic analysis of the population structure was performed to estimate thedifferent ancestral proportions among the studied camel groups. Diversity in SNPs across3.3.groups
Population
Analysis
thewasStructure
determined
for the various most probable number of populations (K),
best
K
value
indicates
a low cross‐validation
error (CV)comparedother K
whereAthe
genetic analysis of the population
structure was performed
to estimate
the todifferent
values.
Theproportions
CV score foundthethelowesterror
levelgroups.
at K numbers
2, 3,in4, SNPs
and 5 across(Figurethe
1B).
ancestral
among
studiedcamel
Diversitygroupswas determined
for the supported
various mostprobablenumberof populations(K), division
where
The
cross‐validation
procedurethat
K = 2 was
optimal,showing a clear
the best theK valueindicates(Figure
a low cross-validation
error (CV) compared to other K values.
betweenpopulations
1А).
The AtCVa scorefound
thelowest
error
level
at
K
numbers
3, 4, and(Figure1B). The
value of K = 2, we noticed that Bactrians and wild2,camels
are 5almost
similarsincecross-validation
procedure
supported
that
K
=
2
was
optimal,showingaclear
division isthey descend from the same species and are both two‐humped. The exact similarity
between the
populations (Figure1A). However, by increasing the value to K = 3 or more,
observed
in dromedaries
with hybrids.
At a valueof
ofBactrians
K = 2, we andnoticedthat
Bactrians
wildgroups
camelscan
are alreadyalmost similarsince
the separation
wild
camelsfromandother
be observed.
they
descend
from
the
same
species
and
are
both
two-humped.
The
exact
similarity
is
The PCA supported this statement, showing Bactrians and wild camels grouped distantly
observed in dromedaries with hybrids. However, by increasing the value to K = 3 or more,from other groups (Figure 3). Despite the increase in the K value, the similarity ofthe separation of Bactrians and wild camels from other groups can already be observed. The
dromedaries and hybrids persisted and was confirmed by PCA Plot (Figure 2) and our
PCA supported this statement, showing Bactrians and wild camels grouped distantly fromphylogenetic tree (Figure 3), indicating the introgression of dromedaries into the hybrid
other groups (Figure 3). Despite the increase in the K value, the similarity of dromedaries
camels.
and hybrids persisted and was confirmed by PCA Plot (Figure 2) and our phylogenetic tree
(Figure 3), indicating the introgression of dromedaries into the hybrid camels.

Figure2.
2. Principal
Principal component
component analysis
CamelusFigureanalysis (PCA)(PCA)ofofCamelus
Camelusbactrianus,
bactrianus,Camelus
Camelusdromedarius,
dromedarius,
Camelusferus,
on SNP
SNP data.
data. All
Allsamples
samplesare
arerepresented
representedbybya dot
a dot
and
ferus,andandHybridHybrid camel
camel samples based on
andarearecoloredtype ofof camel.
camel.
coloredaccording
according toto thethe type

3.4. Phylogenetic Tree Construction
The phylogenetic tree (Figure 3), constructed by employing the Neighbor Joining
method, showed that the wild camels (Camelus ferus) and domestic Bactrian camels (Camelus
bactrianus) had distinct branches that were distant from the other two groups of camels.
In contrast, branches of hybrids were close to dromedary camels (Camelus dromedarius).
Thus, it can be assumed with great certainty that the first generation of hybrids under study
was then repeatedly crossed with dromedaries, which is unsurprising. Crossbreeding
hybrid camels with each other usually has the opposite effect and leads to a decrease in
the productive qualities of animals; therefore, usually, the first generation of camels is
crossbred by one of the parental representatives [11]. However, two hybrid camels are stillgrouped into branches separate from dromedaries. The exception is one dromedary, which
was located among hybrids in the phylogenetic tree. This can be explained by the mosaic

Genes 2023, 14, 1373

9 of 13structure of the genome of this camel, i.e., due to being phenotypical of dromedaries,
the genome of this camel includes the genome composition of both one-humped andtwo-humped camels and indicates the presence of hybridization.
To determine the common and private SNPs found in the studied populations, thefrequency of occurrence of alleles was determined, and the Plink program was used toGenes 2023, 14, x FOR PEER REVIEW
9 of 13select SNPs with a frequency equal to zero. The result is visually represented in the Venn
diagram below (Figure 4).

Genes 2023, 14, x FOR PEER REVIEW

Figure tree
3. Phylogenetic
with the neighbor‐joining(NJ)Camelus
methodfor Camelus
Figure 3. Phylogenetic
constructed tree
withconstructed
the neighbor-joining(NJ) method forbactrianus,
10 of 13
bactrianus,
CamelusCamelusand Hybrid
camel. not(Imagesof camels
to scaleandCamelus dromedarius,
Camelusferus,dromedarius,and Hybrid
camel.ferus,(Imagesof camels
to scaleand not
were
taken
were taken from open sources http://www.pinterest.com/, accessed on 12 May 2023).
from open sources http://www.pinterest.com/, accessed on 12 May 2023).

3.4. Phylogenetic Tree Construction
The phylogenetic tree (Figure 3), constructed by employing the Neighbor Joining
method, showed that the wild camels (Camelus ferus) and domestic Bactrian camels(Camelus bactrianus) had distinct branches that were distant from the other two groups ofcamels. In contrast, branches of hybrids were close to dromedary camels (Camelus
dromedarius). Thus, it can be assumed with great certainty that the first generation of
hybrids under study was then repeatedly crossed with dromedaries, which isunsurprising. Crossbreeding hybrid camels with each other usually has the opposite effectand leads to a decrease in the productive qualities of animals; therefore, usually, the first
generation of camels is crossbred by one of the parental representatives [11]. However,two hybrid camels are still grouped into branches separate from dromedaries. The
exception is one dromedary, which was located among hybrids in the phylogenetic tree.
This can be explained by the mosaic structure of the genome of this camel, i.e., due tobeing phenotypical of dromedaries, the genome of this camel includes the genome
composition of both one‐humped and two‐humped camels and indicates the presence ofhybridization.
To determine the common and private SNPs found in the studied populations, thefrequency of occurrence of alleles was determined, and the Plink program was used to
select SNPs with a frequency equal to zero. The result is visually represented in the Venn
diagram below (Figure 4).

Figure4. Venndiagramshowing
the overlapof SNPs
for Camelus
bactrianus,
dromedarius,
Figure4. Venndiagramshowing
the overlapof SNPs
for Camelus
bactrianus,
CamelusCamelus
dromedarius,
Camelusferus,
Hybridcamel.
Camelusferus,
andandHybridcamel.

A comparison of identified SNPs of the studied groups revealed 2,631,403 SNPs
(13%) shared across all populations. Interestingly, hybrid camels had the largest numberof unique SNPs (3,271,083), pointing to their genetic distance from other studied groupsof camels. Additionally, 2,515,591 of the identified SNPs are unique to wild camels, whilein Bactrians, this number is 1,244,694, and the fewest private SNPs were found in

Genes 2023, 14, 1373

10 of 13

A comparison of identified SNPs of the studied groups revealed 2,631,403 SNPs (13%)
shared across all populations. Interestingly, hybrid camels had the largest number of unique
SNPs (3,271,083), pointing to their genetic distance from other studied groups of camels.
Additionally, 2,515,591 of the identified SNPs are unique to wild camels, while in Bactrians,
this number is 1,244,694, and the fewest private SNPs were found in dromedaries (531,224).
Hybrids and dromedaries had the most significant number of common SNPs (22%), which
was significantly less than those in hybrids with Bactrians and hybrids with wild camels(4% and 1%, respectively). This also confirms the proximity of hybrids to dromedaries.
Additionally, it should be noted that 13% of the identified SNPs were common for hybrids,
dromedaries, and Bactrians, which is quite logical, given that dromedaries and Bactrians are
the genetic parents of hybrid camels [11]. Wild camels also share more SNPs with Bactrians
than with dromedaries, consistent with the results of the 128 camel sequencing data [44].
Since the Bactrians and dromedaries used in this study have different geographical origins,
hailing from either Kazakhstan or Iran, future studies should aim to comparatively analyze
Bactrians and dromedaries of Kazakhstan origin to check the presence of common SNPs,
taking inspiration from earlier research works [23,46].
The results indicated that wild camels had the highest nucleotide diversity and genetic
diversity; these features may be attributable to the preservation of the genetic diversity ofthis group’s ancestors. Population structural analysis results suggested that wild camels
were phylogenetically distant from camels of other groups; this may be due to the geographical distribution of the wild camels. Wild camels are common in parts of northwestern
China and southwestern Mongolia, which is far from the location of the domestic camels,
resulting in less genetic communication between wild and domestic camels. Also, it can beassumed that this separation of wild camels from domestic ones results from the lack of
directed artificial selection among their populations, which leads to a low rate of inbreeding.
The process of natural selection emphasizes high adaptability to one’s habitat. This result
was consistent with a study by Ming et al., wherein the separation of wild camels from othergroups of studied camels, including dromedaries; Iranian, Kazakh, and Russian Bactrians;
and others, could be seen [44]. Furthermore, another study [43] showed low heterozygosity
in wild Bactrian camels, which was explained by their small population size.
Even though hybrid camels were close to dromedaries in terms of genetic structure,
the separation between two hybrids and the dromedaries on the phylogenetic tree may
provide a reason to assume that hybrid camels form their unique genome differently totheir parental species.
4. Conclusions
We used the whole genome sequencing data of five hybrid camels and publicly
available genomic data of other camels to analyze the SNPs present in the genomes of
Bactrian, dromedary, wild, and hybrid camels and systematically studied their genetic
diversity and genetic structure. This study revealed differences in the genome of hybrids
derived from one-humped, two-humped, and wild camels. Moreover, hybrid camels had
the most significant number of unique SNPs compared to parental species. The results ofthe present study could facilitate further studies into the genetic resources of this mammal,
as well as the conservation of these resources. These investigations require subsequentvalidation so we can better understand the concepts behind these results, which can beachieved by increasing the number of studied animals and performing more studies in thisfield. At the same time, the results of this study can serve as comparative data for new
research on this topic.
Author Contributions: Conceptualization, M.A., K.D., B.B. and N.S.; methodology, M.A., K.D., A.M.,
B.B. and Z.Z.; software, M.A.; validation, B.B., A.M. and N.S.; formal analysis, M.A.; investigation,
M.A.; resources, N.S. and Z.Z.; data curation, M.A., K.D. and B.B.; writing—original draft preparation,
M.A. and K.D.; writing—review and editing, B.B., A.M., N.S. and Z.Z.; visualization, B.B.; supervision,
B.B. and N.S.; project administration, K.D.; funding acquisition, K.D., B.B. and N.S. All authors haveread and agreed to the published version of the manuscript.

Genes 2023, 14, 1373

11 of 13

Funding: This research was funded by the Scientific Committee of Ministry of Science and Higher
Education of the Republic of Kazakhstan, grant number AP14870678 «Study of genetic diversity andpopulation genetic structure of Camelus dromedarius and Camelus bactrianus in Kazakhstan».
Institutional Review Board Statement: The animal study protocol was approved by the Local Ethics
Committee of the Institute of Genetics and Physiology SC MSHE RK (14 April 2022, Almaty, Kazakhstan).
Informed Consent Statement: Not applicable.
Data Availability Statement: The whole genome sequencing raw data of the hybrid camels used inthis study are available from the GenBank BioProject number PRJNA985411.
Acknowledgments: We express our sincere thanks to the head of the camel farm of the Ili district of
the Almaty region Utemis Makhanov for providing detailed information about the hybrid camels
chosen for this study and Nurbergen Tanirbergenuly and other farm staff for their assistance incollecting blood samples. The authors would also like to thank Kulboldin Temirlan for helping inconstructing the Venn diagram. Additionally, we express our gratitude to the Bolashak International
Scholarship program for supporting BB (N.7154).
Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in the designof the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; orin the decision to publish the results.

References
1.
2.

3.
4.

5.
6.

7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.

Wapnish, P. Camel caravans and camel pastoralists at Tell Jemmeh. J. Anc. Near East. Soc. 1983, 13, 101–121.
Balmus, G.; Trifonov, V.A.; Biltueva, L.S.; O’Brien, P.C.M.; Alkalaeva, E.S.; Fu, B.; Skidmore, J.A.; Allen, T.; Graphodatsky, A.S.;
Yang, F. Cross-species chromosome painting among camel, cattle, pig and human: Further insights into the putative Cetartiodactyla ancestral karyotype. Chromosom. Res. 2007, 15, 499–514. [CrossRef]
Kadwell, M.; Fernandez, M.; Stanley, H.F.; Baldi, R.; Wheeler, J.C.; Rosadio, R.; Bruford, M.W. Genetic analysis reveals the wild
ancestors of the llama and the alpaca. Proc. R. Soc. Lond. 2001, 268, 2575–2584. [CrossRef]
Ji, R.; Cui, P.; Ding, F.; Geng, J.; Gao, H.; Zhang, H.; Yu, J.; Hu, S.; Meng, H. Monophyletic origin of domestic bactrian camel(Camelus bactrianus) and its evolutionary relationship with the extant wild camel (Camelus bactrianus ferus). Anim. Genet. 2009, 40,
377–382. [CrossRef] [PubMed]
Wu, H.; Guang, X.; Al-Fageeh, M.B.; Cao, J.; Pan, S.; Zhou, H.; Zhang, L.; AbuTarboush, M.H.; Xing, Y.; Xie, Z.; et al. Camelid
genomes reveal evolution and adaptation to desert environments. Nat. Commun. 2014, 5, 5188. [CrossRef]
Mohandesan, E.; Fitak, R.R.; Corander, J.; Yadamsuren, A.; Chuluunbat, B.; Abdelhadi, O.; Raziq, A.; Nagy, P.; Stalder, G.;
Walzer, C.; et al. Mitogenome Sequencing in the Genus Camelus Reveals Evidence for Purifying Selection and Long-term
Divergence between Wild and Domestic Bactrian Camels. Sci. Rep. 2017, 7, 9970. [CrossRef] [PubMed]
Murray, E. Fowler Medicine and Surgery of South American Camelids: Llama Alpaca Vicuna Guanaco; Iowa State University Press:
Ames, LA, USA, 1995.
Dioli, M. Dromedary (Camelus dromedarius) and Bactrian camel (Camelus bactrianus) crossbreeding husbandry practices in Turkey
and Kazakhstan: An in-depth review. Pastor. Res. Policy Pract. 2020, 10, 6. [CrossRef]
Faye, B.; Konuspayeva, G.; Messad, S.; Loiseau, G. Discriminant milk components of Bactrian camel (Camelus bactrianus),
dromedary (Camelus dromedarius) and hybrids. Dairy Sci. Technol. 2008, 88, 607–617. [CrossRef]
Konuspayeva, G.; Faye, B.; Loiseau, G.; Levieux, D. Lactoferrin and immunoglobin content in camel milk from Kazakhstan.
J. Dairy Sci. 2006, 90, 38–46. [CrossRef]
Baimukanov, D.A. Cytogenetics and Selection of Two-Humped, One-Humped Camels and Their Hybrids; Bastau: Almaty, Kazakhstan,
2002; p. 160.
Burger, P. The history of Old World camelids in the light of molecular genetics. Trop. Anim. Health Prod. 2016, 48, 905–913.
[CrossRef]
Wild Camels. Available online: https://www.wildcamels.com/bactrian-camels/ (accessed on 5 February 2023).
Eldala. Available online: https://eldala.kz/novosti/zhivotnovodstvo/12959-pogolove-loshadey-v-kazahstane-vyroslo-na-12-za-god (accessed on 5 February 2023).
Piro, M. Aspects of Molecular Genetics in Dromedary Camel. Front. Genet. 2021, 12, 723181. [CrossRef] [PubMed]
Cheng, H.H.; Levin, I.; Vallejo, R.L.; Khatib, H.; Dodgson, J.B.; Crittenden, L.B.; Hillel, J. Development of a genetic map of thechicken with markers of high utility. Poult. Sci. 1995, 74, 1855–1874. [CrossRef]
Piro, M.; Mabsoute, F.E.; Khattaby, N.E.; Laghouaouta, H.; Boujenane, I. Genetic variability of dromedary camel populations
based on microsatellite markers. Animal 2020, 14, 2452–2462. [CrossRef] [PubMed]
Mahmoud, A.H.; Abu-Tarbush, F.M.; Alshaik, M.; Aljumaah, R.; Saleh, A. Genetic diversity and population genetic structure of
six dromedary camel (Camelus dromedarius) populations in Saudi Arabia. Saudi J. Biol. Sci. 2020, 27, 384–1389.

Genes 2023, 14, 1373

19.

20.
21.

22.
23.
24.
25.

26.

27.
28.
29.
30.
31.
32.
33.
34.
35.
36.

37.

38.
39.
40.
41.
42.
43.
44.

12 of 13

Almathen, F.; Charruau, P.; Mohandesan, E.; Mwacharo, J.M.; Orozco-Terwengel, P.; Pitt, D.; Abdussamad, A.M.; Uerpmann, M.;
Uerpmann, H.P.; De Cupere, B.; et al. Ancient and modern DNA reveal dynamics of domestication and cross-continental dispersalof the dromedary. Proc. Natl. Acad. Sci. USA 2016, 113, 6707–6712. [CrossRef]
Eynard, S.E.; Windig, J.J.; Hiemstra, S.J.; Calus, M.P.L. Whole-genome sequence data uncover loss of genetic diversity due toselection. Genet. Sel. Evol. 2016, 48, 33. [CrossRef]
Lado, S.; Elbers, J.P.; Rogers, M.F.; Melo-Ferreira, J.; Yadamsuren, A.; Corander, J.; Horin, P.; Burger, P.A. Nucleotide Diversity ofFunctionally Different Groups of Immune Response Genes in Old World Camels Based on Newly Annotated and ReferenceGuided Assemblies. BMC Genom. 2020, 21, 606. [CrossRef]
Burger, P.A.; Palmieri, N. Estimating the Population Mutation Rate from a de novo Assembled Bactrian Camel Genome andCross-Species Comparison with Dromedary ESTs. J. Hered. 2014, 105, 839–846. [CrossRef]
Khalkhali-Evrigh, R.; Hafezian, S.H.; Hedayat-Evrigh, N.; Farhadi, A.; Bakhtiarizadeh, M.R. Genetic variants analysis of threedromedary camels using whole genome sequencing data. PLoS ONE 2018, 13, e0204028. [CrossRef]
Ruiz, E.; Mohandesan, E.; Fitak, R.R.; Burger, P.A. Diagnostic Single Nucleotide Polymorphism Markers to Identify Hybridization
Between Dromedary and Bactrian Camels. Conserv. Genet. Resour. 2015, 7, 329–332. [CrossRef]
Bitaraf Sani, M.; Zare Harofte, J.; Banabazi, M.H.; Esmaeilkhanian, S.; Shafei Naderi, A.; Salim, N.; Teimoori, A.; Bitaraf, A.;
Zadehrahmani, M.; Burger, P.A.; et al. Genomic Prediction for Growth Using a Low-Density SNP Panel in Dromedary Camels.
Sci. Rep. 2021, 11, 7675. [CrossRef]
Al-Sharif, M.M.; Radwan, H.A.; Hendam, B.M.; Ateya, A.I. Exploring single nucleotide polymorphisms in GH, IGF-I, MC4R and
DGAT1 genes as predictors for growth performance in dromedary camel using multiple linear regression analysis. Small Rumin.
Res. 2022, 207, 106619. [CrossRef]
Ming, L.; Siren, D.; Hasi, S.; Jambl, T.; Ji, R. Review of genetic diversity in Bactrian camel (Camelus bactrianus). Anim. Front. 2022,
12, 20–29. [CrossRef] [PubMed]
Burger, P.A.; Ciani, E. Structural and functional genomics in Old World camels—Where do we stand and where to go. Anim.
Front. 2022, 12, 30–34. [CrossRef] [PubMed]
Akhmetsadykova, S.H.; Konuspayeva, G.; Akhmetsadykov, N. Camel breeding in Kazakhstan and future perspectives. Anim.
Front. 2022, 12, 71–77. [CrossRef] [PubMed]
Adilbekova, E.; Alybayev, N.; Arunas, S.; Abuov, G. Genetic typing of South Kazakhstan populations’ dairy camels using DNA
technology. Anim. Biotechnol. 2020, 31, 547–554.
Amandykova, M.; Dossybayev, K.; Mussayeva, A.; Bekmanov, B.; Saitou, N. Comparative Analysis of the Polymorphism of theCasein Genes in Camels Bred in Kazakhstan. Diversity 2022, 14, 285. [CrossRef]
Babraham Bioinformatics. Available online: https://www.bioinformatics.babraham.ac.uk/projects/fastqc/ (accessed on
5 February 2023).
Sourceforge.Net. Available online: https://bio-bwa.sourceforge.net/bwa.shtml (accessed on 5 February 2023).
Htslib.Org. Available online: http://www.htslib.org/download/ (accessed on 5 February 2023).
Github. Available online: https://broadinstitute.github.io/picard/ (accessed on 5 February 2023).
Danecek, P.; Auton, A.; Abecasis, G.; Albers, C.A.; Banks, E.; DePristo, M.A.; Handsaker, R.E.; Lunter, G.; Marth, G.T.;
Sherry, S.T.; et al. 1000 Genomes Project Analysis Group, The variant call format and VCFtools. Bioinformatics 2011, 7, 2156–2158.
[CrossRef]
Purcell, S.; Neale, B.; Todd-Brown, K.; Thomas, L.; Ferreira, M.A.; Bender, D.; Maller, J.; Sklar, P.; De Bakker, P.I.; Daly, M.J.; et al.
Plink: A tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 2007, 81, 559–575.
[CrossRef]
Alexander, D.H.; Novembre, J.; Lange, K. Fast model-based estimation of ancestry in unrelated individuals. Genome Res. 2009,19, 1655–1664. [CrossRef]
R-Project.Org. Available online: https://cran.r-project.org/web/packages/ggfortify/vignettes/plot_pca.html (accessed on
5 February 2023).
Gao, C.-H.; Yu, G.; Cai, P. ggVennDiagram: An Intuitive, Easy-to-Use, and Highly Customizable R Package to Generate Venn
Diagram. Front. Genet. 2021, 12, 706907. [CrossRef] [PubMed]
Saitou, N.; Nei, M. The neighbor-joining method: A new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 1987,
4, 406–425. [PubMed]
Rambaut, A. FigTree v1.4.2 Molecular Evolution, Phylogenetics and Epidemiology, Institute of Evolutionary Biology, Universityof Edinburgh. 2014. Available online: http://tree.bio.ed.ac.uk/software/figtree/ (accessed on 5 February 2023).
Hedayat-Evrigh, N.; Khalkhali-Evrigh, R.; Bakhtiarizadeh, M.R. Genome-Wide Identification and Analysis of Variants in Domestic
and Wild Bactrian Camels Using Whole-Genome Sequencing Data. Int. J. Genom. 2020, 2020, 2430846. [CrossRef] [PubMed]
Ming, L.; Yuan, L.; Yi, L.; Ding, G.; Hasi, S.; Chen, G.; Jambl, T.; Hedayat-Evright, N.; Batmunkh, M.; Badmaevna, G.K.; et al.
Whole-genome sequencing of 128 camels across Asia reveals origin and migration of domestic Bactrian camels. Commun. Biol.
2020, 3, 1–9. [CrossRef]

Genes 2023, 14, 1373

45.
46.

13 of 13

Cog-Genomics.org. Available online: https://www.cog-genomics.org/plink/ (accessed on 5 February 2023).
Sabahat, S.; Brauning, R.; Clarke, S.M.; Nadeem, A.; Thomson, P.C.; Khatkar, M.S. SNP discovery and population structure
analysis in Lassi and Marecha camel breeds using a genotyping by sequencing method. Anim. Genet. 2020, 51, 620–623. [CrossRef]

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