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Citation: Buggiotti, L.; Yudin, N.S.;
Larkin, D.M. Copy Number Variants
in Two Northernmost Cattle Breeds
Are Related to Their Adaptive
Phenotypes. Genes 2022,13, 1595.
https://doi.org/10.3390/
genes13091595
Academic Editor: Nico M. Van
Straalen
Received: 29 July 2022
Accepted: 2 September 2022
Published: 6 September 2022
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genes
G C A T
T A C G
G C A T
Communication
Copy Number Variants in Two Northernmost Cattle Breeds Are
Related to Their Adaptive Phenotypes
Laura Buggiotti 1, Nikolay S. Yudin 2,3 and Denis M. Larkin 1,*
1Royal Veterinary College, University of London, London NW1 0TU, UK
2
The Federal State Budgetary Institution of Science Federal Research Center Institute of Cytology and Genetics,
Siberian Branch of the Russian Academy of Sciences (ICG SB RAS), Novosibirsk 630090, Russia
3
Kurchatov Genomics Center, the Federal Research Center Institute of Cytology and Genetics, Siberian Branch
of the Russian Academy of Science (ICG SB RAS), Novosibirsk 630090, Russia
*Correspondence: dlarkin@rvc.ac.uk
Abstract:
Copy number variations (CNVs) are genomic structural variants with potential functional
and evolutionary effects on phenotypes. In this study, we report the identification and characterization
of CNVs from the whole-genome resequencing data of two northernmost cattle breeds from Russia:
the Yakut and Kholmogory cattle and their phylogenetically most related breeds, Hanwoo and
Holstein, respectively. Comparisons of the CNV regions (CNVRs) among the breeds led to the
identification of breed-specific CNVRs shared by cold-adapted Kholmogory and Yakut cattle. An
investigation of their overlap with genes, regulatory domains, conserved non-coding elements
(CNEs), enhancers, and quantitative trait loci (QTLs) was performed to further explore breed-specific
biology and adaptations. We found CNVRs enriched for gene ontology terms related to adaptation to
environments in both the Kholmogory and Yakut breeds and related to thermoregulation specifically
in Yakut cattle. Interestingly, the latter has also been supported when exploring the enrichment
of breed-specific CNVRs in the regulatory domains and enhancers, CNEs, and QTLs implying
the potential contribution of CNVR to the Yakut and Kholmogory cattle breeds’ adaptation to a
harsh environment.
Keywords: CNV; cattle; cold adaptation
1. Introduction
Copy number variations (CNV) refer to a structural variation type where DNA seg-
ments of >1 kb are present in individual genomes in varying copy numbers, compared
to a reference genome [
1
]. CNVs are less frequent than single nucleotide polymorphisms
(SNPs) and other variations. However, they can potentially have a larger functional and
evolutionary impact, such as changing gene structure and dosage, altering gene regula-
tion, and exposing recessive alleles [
2
,
3
]. CNVs and their impacts have been extensively
studied, especially in humans [
4
], where CNVs are considered to affect gene expression
and, therefore, some phenotypes of interest. For example, CNV loss in the NPY4R gene
was associated with obesity [
5
]. Other studies have revealed that genomic diversity could
be increased due to the differential selection of CNVs for adaptations to different environ-
ments [
6
–
8
]. For instance, 30% of young fast evolving duplicated genes in sticklebacks are
in CNVs and these genes are enriched in functional categories related to environmental
adaptations [
8
]. Studies in livestock also highlight the role of CNVs in shaping various
phenotypes. A partial or complete duplication of the KIT gene causes different patterns
of white coat coloration in pigs and in some of the cattle breeds [
9
,
10
], while a white coat
color in sheep has been associated with a duplication of the ASIP gene [11].
The present study focuses on CNV detection from the whole-genome resequencing
data of two cold-adapted cattle breeds from Russia: the Kholmogory and Yakut cattle.
Both breeds live in harsh environments but have very different population histories. The
Genes 2022,13, 1595. https://doi.org/10.3390/genes13091595 https://www.mdpi.com/journal/genes
Genes 2022,13, 1595 2 of 7
Kholmogory was formed in the European part of Russia around 300 years ago [
12
], while
the Yakut cattle was formed at the Baikal area of Siberia and likely migrated together with
the Yakut people to contemporary Yakutia about 500–800 years ago [
13
]. To identify CNVs
and CNV regions (CNVRs) which could co-evolve with the adaptation of the Russian
cattle breeds to harsh climate conditions, we utilized sequences of four breeds (Yakut,
Kholmogory, Holstein, and Hanwoo). Previously, the Yakut cattle has been found to be
related to Korean Hanwoo, and Kholmogory to Holstein [
14
]. Therefore, we compared
Kholmogory and Yakut cattle to phylogenetically close breeds to search for CNVs that
could have an influence on breed-specific biology and adaptations.
2. Materials and Methods
The Yakut and Kholmogory cattle breeds were previously whole-genome resequenced [
15
]
and mapped to the reference Hereford cattle assembly (UMD3.1, BosTau6) using BWA-
MEM [
16
] with default parameters; Hanwoo and Holstein resequencing data were down-
loaded from the Sequence Repository Archive [
17
]. A total of 98 high-quality samples of
the four cattle breeds (Yakut (29), Kholmogory (32), Hanwoo (19), and Holstein (18)) were
used. The cn.MOPS R package (copy number estimation by a Mixture of Poissons [
18
])
was used for CNV detection. Based on the average sequence coverage of our data (~11X),
window length was set to 700 (windowLength = readLength
×
50/coverage) and posterior
probabilities were estimated (posteriorProbs). The cn.MOPS tool represents a CNV detec-
tion pipeline that models the depths of coverage across multiple samples at each genomic
position. Using a Bayesian approach, it decomposes read variants across samples into
integer CNVs and noise using mixture components and Poisson distributions, respectively.
The multiple samples approach increases statistical power and decreases computational
burden and the FDR in CNV detection. CNVs were then used to construct a set of copy
number variable regions (CNVRs) for Kholmogory, Yakut, Hanwoo, and Holstein breeds.
The CNVRs were constructed by merging CNVs across samples of the same breed that
exhibited at least 50% pairwise reciprocal overlap in their genomic coordinates; unique
CNVRs per breed were those with less than 10% overlap with CNVRs in other breeds.
BEDTools [
19
] and BEDOPS [
20
] tools were used to calculate CNVR overlaps. Genomic
Regions Enrichment of Annotations Tool (GREAT), [
21
] was used to assign each gene of the
reference Hereford cattle assembly (UMD3.1, BosTau6) to a regulatory domain consisting
of a basal domain that extends 5 kb upstream and 1 kb downstream from its transcription
start site (total length of the regions per gene is 6000 bp). The karyoploteR [
22
] package
was used to plot the cattle chromosome map and to visualize the CNVRs locations for the
four breeds.
3. Results and Discussion
A total of 860,380 autosomal CNVs were detected in the four-breed set, which were
then merged into 71,549 CNVRs. Interestingly, the Yakut and Kholmogory breeds shared the
largest fraction of CNVRs (138.41 Mb). The second largest shared fraction of Kholmogory
CNVRs was with Holstein (61.05 Mbp) and Yakut CNVRs with Hanwoo (27.92 Mbp),
confirming known breed relations. A total of 19,502 CNVRs (total length: 106.09 Mbp) were
breed-specific for the Yakut, 2238 (18.61 Mbp) for the Kholmogory, 2535 (8.27 Mbp) for the
Hanwoo and 1625 (4.95 Mbp) for the Holstein cattle (Figure 1).
Genes 2022,13, 1595 3 of 7
Genes 2022, 13, x FOR PEER REVIEW 3 of 7
Figure 1. Whole genome distribution of breed-specific CNVRs for the four breeds.
To reveal a possible contribution of CNVRs to breed-specific biology and adapta-
tions, we investigated 5522 genes found in the four breed-specific CNVRs, of which 2962,
1034, 862, and 664 genes were found in the Yakut, Hanwoo, Kholmogory, and Holstein
CNVRs, respectively (Table S1). A gene ontology (GO) enrichment analysis highlighted
distinct pathways being enriched in these gene sets, with the second largest number (35)
found in the Yakut cattle, among which we observed cognition, the regulation of small
GTPase-mediated signal transduction, the detection of mechanical stimulus, etc. (Table
S2a). The Kholmogory cattle had the third largest number of GO categories (22) of which
intracellular signal transduction, GTPase regulator activity, adenyl nucleotide binding,
etc. were uniquely present. The Hanwoo had the largest number of GO categories (38),
while Holstein had the same number of GO categories as Kholmogory (22). Interestingly,
all the breeds showed enrichment for the GO category response to stimulus, although the
genes were different. Moreover, a DAVID functional annotation cluster analysis [23] high-
lighted the enrichment of ubiquitin protein in the Yakut cattle, which is involved in pro-
tein degradation and found to be enriched in Antarctic fish [24]. The authors hypothesized
that the cost of living for cold-adapted ectotherms commits more effort to maintaining
protein homeostasis. Moreover, ATPase activity, microtubule motor activity, and blood
coagulation inhibitor were also found to be enriched in the Yakut cattle CNVRs, which
could potentially influence thermoregulation (Table S2b). There were 7414 CNVRs shared
between the Yakut and Kholmogory breeds, overlapping 2925 genes, which were en-
riched in various pathways such as keratin filament, kinase, oxytocin signaling pathway,
etc. (Table S3a,b).
Figure 1. Whole genome distribution of breed-specific CNVRs for the four breeds.
To reveal a possible contribution of CNVRs to breed-specific biology and adapta-
tions, we investigated 5522 genes found in the four breed-specific CNVRs, of which 2962,
1034, 862, and 664 genes were found in the Yakut, Hanwoo, Kholmogory, and Holstein
CNVRs, respectively (Table S1). A gene ontology (GO) enrichment analysis highlighted
distinct pathways being enriched in these gene sets, with the second largest number (35)
found in the Yakut cattle, among which we observed cognition, the regulation of small
GTPase-mediated signal transduction, the detection of mechanical stimulus, etc. (Table
S2a). The Kholmogory cattle had the third largest number of GO categories (22) of which
intracellular signal transduction, GTPase regulator activity, adenyl nucleotide binding, etc.
were uniquely present. The Hanwoo had the largest number of GO categories (38), while
Holstein had the same number of GO categories as Kholmogory (22). Interestingly, all
the breeds showed enrichment for the GO category response to stimulus, although the
genes were different. Moreover, a DAVID functional annotation cluster analysis [
23
] high-
lighted the enrichment of ubiquitin protein in the Yakut cattle, which is involved in protein
degradation and found to be enriched in Antarctic fish [
24
]. The authors hypothesized
that the cost of living for cold-adapted ectotherms commits more effort to maintaining
protein homeostasis. Moreover, ATPase activity, microtubule motor activity, and blood
coagulation inhibitor were also found to be enriched in the Yakut cattle CNVRs, which
could potentially influence thermoregulation (Table S2b). There were 7414 CNVRs shared
between the Yakut and Kholmogory breeds, overlapping 2925 genes, which were enriched
in various pathways such as keratin filament, kinase, oxytocin signaling pathway, etc.
(Table S3a,b).
Yakut cattle-specific CNVRs involved multiple fatty-acid related genes such as the
CYP4A11 (cytochrome P-450 4A11), which is implicated in lipogenesis and growth traits.
Genes 2022,13, 1595 4 of 7
This CNVR has previously been reported in various Chinese native taurine cattle breeds
(Jaxian, Quinchuan, Nanyang, Jinnan, Luxi, and Chinese Red Steppe [
25
]). The Kholmogory
cattle unique CNVRs covered over one-thousand annotated genes, among which a few were
interleukin genes (IL17RE,IL20RA,IL10RA,IL10) associated with immune response, as well
as PLA2G4A, which is involved in inflammatory responses [
26
]. To further investigate the
potential association of CNVRs with gene regulation we investigated the landscape of breed-
specific CNVRs overlapping regulatory domains by using the GREAT approach [
21
]. We
found 1109, 663, 659, and 516 genes with breed-specific CNVRs in their GREAT domains in
Yakut, Holstein, Hanwoo, and Kholmogory cattle breeds, respectively. The GO enrichment
analysis of the latter sets of genes found the response to stimulus to be enriched in the Yakut
but not in the Kholmogory cattle (Table S4a), while a DAVID functional annotation cluster
analysis revealed the term lipid transport and lipoprotein metabolic process to be unique to
Yakut cattle when considering only breed-specific CNVRs in GREAT domains (
Table S4b
),
suggesting a potential fundamental role of CNVRs in regulating thermogenesis [
27
], a
major adaptive mechanism to extreme climates. Moreover, the top DAVID functional
cluster (Table S4b) contained genes that are involved in cytoskeletal reorganization (such as
PADI- genes), which also plays a role in shaping the adaptation to a cold environment [
28
].
Kholmogory, on the other hand, had the unique GO terms: metal ion transport, cellular
response to organic substance and transporter activity, among others, suggesting again their
potential role in the adaptation to new ecological niches [
29
,
30
]. Finally, we investigated
the enrichment of breed-specific CNVRs in three functional classes: (i) conserved non-
coding elements (CNEs); (ii) enhancers; (iii) QTLs regions, by using GAT [
31
]. Interestingly,
breed-specific CNVRs were enriched with CNEs [
32
] in all four breeds, highlighting again
their potential involvement in gene regulation, and Yakut cattle-specific CNVRs were
significantly negatively enriched of both cetartiodactyla and ruminant CNEs (Figure 2).
The QTLs enrichment analysis suggests that Yakut cattle-specific CNVRs are significantly
negatively enriched in all major QTLs categories but meat and carcass, while CNVs in the
other three breeds show positive or negative associations with a limited number of QTL
categories (Figure 2). One explanation for the QTLs enrichment results is that in a natural
population subjected to a harsh climate such as Yakut cattle, selection acts on CNVRs
contributing to phenotypes that are quite different from those which are normally under
selection by humans.
Genes 2022,13, 1595 5 of 7
Genes 2022, 13, x FOR PEER REVIEW 5 of 7
Figure 2. Breed-specific CNVR overlapping CNEs, enhancers, and QTLs. Abbreviations are as fol-
lows: YKT—Yakut, KHO—Kholmogory, HOL—Holstein, HNW—Hanwoo, CNE—conserved non-
coding elements.
4. Conclusions
Overall, our results point to novel copy number variants and their potential contri-
butions to local adaptations in the northernmost cattle breeds from Russia and shared
CNV events involving GO terms such as a response to stimulus related to thermoregula-
tion. The enrichment of ubiquitin proteins in Yakut cattle unique CNVRs might indicate
their contribution to maintaining protein homeostasis; moreover, the enrichment of mul-
tiple fatty-acid related genes implicated in lipogenesis and growth traits suggests their
potential involvement in thermoregulation, as well as the petite size of the Yakut cattle
breed.
Finally, both the Yakut and Kholmogory cattle breeds had breed-specific CNVRs en-
riched in regulatory domains and enhancers, CNEs, and QTLs highlighting their potential
contribution to harsh environment adaptations.
Supplementary Materials: The following supporting information can be downloaded at:
www.mdpi.com/xxx/s1, Table S1: Breed-specific CNVRs overlapping cattle genes (Btau6); Table
S2a: GO analysis of genes in breed-specific CNVRs for the four breeds; Table S2b: DAVID functional
cluster analysis of breed-specific CNVRs; Table S3a: GO analysis of genes in CNVRs shared between
the Yakut and Kholmogory cattle breeds; Table S3b: DAVID functional cluster analysis of YKT-KHO
shared CNVRs; Table S4a: GO analysis of breed-specific CNVRs in regulatory domain (GREAT);
Table S4b: DAVID functional cluster analysis of breed-specific CNVRs in regulatory domain
(GREAT).
Author Contributions: Conceptualization, L.B. and D.M.L.; methodology, L.B.; formal analysis,
L.B.; investigation, L.B. and D.M.L.; resources, D.M.L. and N.S.Y.; writing—original draft
Figure 2.
Breed-specific CNVR overlapping CNEs, enhancers, and QTLs. Abbreviations are as
follows: YKT—Yakut, KHO—Kholmogory, HOL—Holstein, HNW—Hanwoo, CNE—conserved
non-coding elements.
4. Conclusions
Overall, our results point to novel copy number variants and their potential contribu-
tions to local adaptations in the northernmost cattle breeds from Russia and shared CNV
events involving GO terms such as a response to stimulus related to thermoregulation.
The enrichment of ubiquitin proteins in Yakut cattle unique CNVRs might indicate their
contribution to maintaining protein homeostasis; moreover, the enrichment of multiple
fatty-acid related genes implicated in lipogenesis and growth traits suggests their potential
involvement in thermoregulation, as well as the petite size of the Yakut cattle breed.
Finally, both the Yakut and Kholmogory cattle breeds had breed-specific CNVRs
enriched in regulatory domains and enhancers, CNEs, and QTLs highlighting their potential
contribution to harsh environment adaptations.
Supplementary Materials:
The following supporting information can be downloaded at: https:
//www.mdpi.com/article/10.3390/genes13091595/s1, Table S1: Breed-specific CNVRs overlapping
cattle genes (Btau6); Table S2a: GO analysis of genes in breed-specific CNVRs for the four breeds;
Table S2b: DAVID functional cluster analysis of breed-specific CNVRs; Table S3a: GO analysis
of genes in CNVRs shared between the Yakut and Kholmogory cattle breeds; Table S3b: DAVID
functional cluster analysis of YKT-KHO shared CNVRs; Table S4a: GO analysis of breed-specific
CNVRs in regulatory domain (GREAT); Table S4b: DAVID functional cluster analysis of breed-specific
CNVRs in regulatory domain (GREAT).
Genes 2022,13, 1595 6 of 7
Author Contributions:
Conceptualization, L.B. and D.M.L.; methodology, L.B.; formal analysis, L.B.;
investigation, L.B. and D.M.L.; resources, D.M.L. and N.S.Y.; writing—original draft preparation, L.B.;
writing—review and editing, D.M.L. and N.S.Y.; project administration, D.M.L.; funding acquisition,
D.M.L. and L.B. All authors have read and agreed to the published version of the manuscript.
Funding:
This work was funded by the Russian Scientific Foundation (RSF) grant no. 19-76-20026.
LB was funded by Marie Skłodowska-Curie grant agreement No. 703376.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement:
Whole genome sequences data that support the findings of this study
have been deposited in GenBank (PRJNA642008).
Conflicts of Interest: The authors declare no conflict of interest.
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