Abstract
Simple Summary
There are few reports on local pig breeds in Guizhou province. In this
work, the population structure, genetic diversity, and selection
characteristics of three foreign pig breeds and seven Guizhou local pig
breeds were studied. Principal component analysis, adjacent tree
analysis, and ADMIXTURE analysis showed that Chinese and Western pig
breeds had different ancestral sources. Jianhe White Xiang pig (JHBX)
had a distant genetic relationship with the other six local pig breeds
in Guizhou province and had unique genetic characteristics. The genetic
diversity of the JHBX population was low, and the genetic diversity of
the remaining six Chinese native pig populations was generally at a
moderate level. In addition, we also screened the candidate genes that
affect the coat color phenotype of pigs in Guizhou province through
selection signals. Our findings will advance our understanding of the
genetic mechanisms underlying these germplasm characteristics.
Abstract
The local pig breeds in Guizhou possess exceptional meat quality,
robust adaptability, and resilience to harsh feeding conditions, making
them ideal for producing high-quality pork. With over 10 local pig
breeds in the region, we focused on 7 specific breeds: Baixi pigs (BX),
Congjiang Xiang pigs (CJX), Guanling pigs (GL), Jianhe White Xiang pigs
(JHBX), Jiangkou Luobo pigs (JKLB), Kele pigs (KL), and Qiandong Hua
pigs (QDH). Unfortunately, these breeds face threats such as introduced
species and inbreeding, resulting in a decline in population size and
numbers. To better protect and utilize these breeds, we employed
genome-wide single-nucleotide polymorphism (SNP) markers to investigate
the population structure, genetic diversity, and selection
characteristics of 283 pigs across these seven breeds. Our findings
revealed distinct ancestral sources between Chinese and Western pig
breeds, as demonstrated by principal component analysis, adjacent tree
analysis, and ADMIXTURE analysis. Notably, JHBX exhibited a distant
genetic relationship from the other six local pig breeds in Guizhou
province, showcasing unique genetic characteristics. While the genetic
diversity of the six Chinese native pig populations, excluding JHBX,
was generally moderate in Guizhou province, the JHBX population
displayed low genetic diversity. Therefore, it is imperative to
intensify selection efforts to prevent inbreeding decline in JHBX while
further enhancing the protection measures for the other six pig
populations. Additionally, we identified candidate genes influencing
the size disparity among pigs in Guizhou province through signal
selection. Our study outcomes serve as a reference for developing
effective conservation and utilization plans for pig breeds in Guizhou
province and deepen our understanding of the genetic mechanisms
underlying pig body size.
Keywords: population structure, conservation, genetic variability,
population relationship, coat color
1. Introduction
China has one of the richest genetic resources for local pig breeds
worldwide, accounting for approximately one-third of the global breeds
[[40]1]. It has a vast territory and a wide distribution of local pig
breeds, forming many excellent pig breeds. For example, Meishan pigs
[[41]2] and Erhualian pigs [[42]3] in East China have large litter
sizes, and Erhualian pig breed is one of the famous high-yielding pig
breeds in China; Luchuan pigs and Bama pigs in South China have thin
skin and excellent heat resistance [[43]4,[44]5]; Min pigs [[45]6] and
Tibetan pigs [[46]7] have strong cold tolerance; and there are
varieties resistant to rough feeding, with strong adaptability and
excellent meat quality. These pig breeds play a key role in the Chinese
pig industry and contribute to the development of international
commercial breeds.
Western commercial pigs have gradually dominated the Chinese pig
industry in the past few decades owing to their fast growth rate, high
meat yield, and low feed/meat ratio [[47]8,[48]9]. Moreover, the litter
size of Western pig breeds (e.g., Landrace from Denmark and Large White
from France) exceeds that of most local pigs in China now. This is one
of the important reasons why Western pig breeds completely dominate the
market in China. The large number of Wester pig breeds introduced and
unplanned crossbreeding methods have posed a great threat to China’s
indigenous pig breeds, especially after the outbreak of African swine
fever. The population of native Chinese pig breeds (including those in
the Guizhou region) has sharply declined, threatening the germplasm of
Chinese pigs. Therefore, it is important to study the population
structure and genetic diversity of native Chinese pig breeds using
genomic methods to maintain genetic diversity, avoid inbreeding, and
formulate effective conservation strategies.
Guizhou province is in southwest China on the Yunnan–Guizhou Plateau, a
subtropical humid monsoon climate area rich in pig varieties. A number
of pig breeds were bred owing to their unique geographical conditions,
including Baixi pigs (BX), Guanling pigs (GL), Kele pigs (KL), and
Jianhe White Xiang pigs (JHBX). These breeds provide valuable genetic
resources for scientific research and further genetic improvements in
the pig industry. However, the genetic diversity of these varieties
remains unclear, and it has not been reported previously. Therefore,
283 individuals from seven Guizhou provincial pig breeds and three
European breeds were selected to reveal their genetic diversity,
population structure, and historical mixing characteristics. This will
be conducive to the effective conservation and utilization of these
seven varieties in Guizhou and will promote our understanding of the
genetic mechanisms underlying their germplasm characteristics.
2. Materials and Methods
2.1. Animals and SNP Genotyping
A total of 283 pigs from 10 breeds were investigated, comprising 7
breeds from China and 3 breeds from Europe. Of those, 193 were from
seven breeds in Guizhou province, China (BX, Congjiang pigs, GL, Jianhe
white pigs, Jiangkou Radish pigs, KL, and Qiandong Hua pigs), while the
remaining 90 pigs were Duroc, Landrace, and Great White European
breeds.
Genomic DNA was extracted from ear samples using conventional
phenol–chloroform methods and diluted to a final concentration of 50
ng/μL. Genome-wide SNPs were detected using the Porcine SNP50 BeadChip
(Illumina, San Diego, CA, USA). In total, 50,697 SNPs were identified
for subsequent analyses. The genotype files were converted to plink
input files. Plink (v1.90) was used for the quality control of SNP
data, and the criteria were as follows: Individuals with an individual
deletion rate > 10%, individuals with an SNP deletion rate > 10%,
individuals with a minor allele frequency < 5%, and individuals with
sex chromosome deletion were excluded. At the same time, the extracted
data were combined with previously existing Duroc, Landrace, and Large
White pig 50 K SNP chip data, and a follow-up analysis was performed.
2.2. Estimation of Population Genetic Differentiation
Genome-wide Complex Trait Analysis (GCTA) (v1.93) software was used to
calculate the average proportion of shared alleles (Dst), and the
genetic distance between all pairs of individuals was calculated as
(1-Dst). Using the Bionj function in the R package, an adjacency tree
was constructed based on the (1-Dst) matrix, and the iTOL website
([49]https://itol.embl.de/ (accessed on 29 June 2023)) was used to
identify the constructed adjacency tree.
2.3. Genetic Differentiation Index between Breeds
The genetic differentiation index (Fst) between the two breeds was
calculated using vcftools. The Fst value is determined as follows: the
low is 0–0.05, the medium is 0.05–0.15, the high is 0.15–0.25, and the
high genetic differentiation is above 0.25 [[50]10].
[MATH:
Fst=(<
/mo>Ht−Hs)
Ht :MATH]
where Fst is the genetic differentiation index; Ht is the mean
heterozygosity in subpopulations; and Hs is the mean degree of
heterozygosity in a composite population.
2.4. Principal Component Analysis
Principal component analysis (PCA) was performed using GCTA to
determine the relationships among these varieties. First, we calculated
the ten principal components of these varieties. The first two
principal components were selected and visualized using R.
2.5. Inferring Population Structure and ADMIXTURE
Population isolation usually prevents free migration and mating between
subgroups. We used the default parameters of the ADMIXTURE (v1.3.0)
software to estimate the consanguinity structure of the filtered data,
with the number of ancestor populations K ranging from 2 to 20, and an
R script was used to visualize consanguinity structure mixing.
TREEMIX (v1.13) was used to further investigate the history of
interspecific gene flow in pigs [[51]11]. This program runs on a VCF
file containing the studied pig breeds, with Duroc, Landrace, and Great
White pigs selected as outpopulations. Initially, we calculated allele
frequencies using VCF files and converted the files to TREEMIX format.
We set the parameter to -k 1000 since the TREEMIX runtime assumes that
SNPs are unchained to prevent starting the TREEMIX runtime with SD = 0.
TREEMIX runs with m values between 1 and 10, with five cycles per m
value. The OptM program was used to determine the optimal number of
migrated edges (m) [[52]12].
2.6. Analysis of Genetic Diversity Indices
To compare the genetic diversity of different pig populations, we
calculated the expected heterozygosity (He) for each of these breeds
using plinkV1.9, as well as the observed heterozygosity (Ho), minor
allele frequency (Maf), and inbreeding coefficient (Fis). The Fis for
each variety was calculated based on the observed homozygous genotype
and the expected number using the following formula [[53]13,[54]14]:
[MATH:
Fis=O<
/mi>HOM−E(HOM)NNM−E(HOM) :MATH]
where Fis is the inbreeding coefficient; O(HOM) is the observed number
of homozygotes; E(HOM) is the expected number of homozygotes; and N(NM)
is the number of non-missing genotypes.
2.7. Runs of Homozygosity Analysis
Plink (v1.90) software was used to detect the homozygous regions of a
certain number and density of SNPs in the genome, namely runs of
homozygosity (ROHs). The main parameters were as follows: The sliding
window was set as 20 SNPs along the chromosome, the number of
heterozygotes in each sliding window did not exceed one, the minimum
length was >1000 kb, the maximum distance between two SNPs was 100 kb,
the number of SNPs/ROH was >30, and the minimum density of SNPs was >50
kb/SNP [[55]15,[56]16]. R (v4.2) was used to calculate the inbreeding
coefficient (F[ROH]) based on ROHs, and the homozygosity measured from
genomic data based on ROHs (F[ROH]) was defined as the total length of
the genome covered by an ROH divided by the total length of the genome
covered by the SNP or sequence [[57]17], as shown below:
[MATH:
FROH=∑LROH<
mrow>LAUTO :MATH]
where ∑L[ROH] is the sum of the total length of all ROHs detected in an
individual, and L[AUTO] is the total length of the autosomal genome.
2.8. Selective Scan Analysis
Guizhou local pig breeds have a variety of coat color phenotypes.
JHBX’s coat color is two-end black; KL’s coat color is mostly black,
but a few are brown; and the coat color of JKLB and CJX is black. In
order to screen the genes affecting coat color phenotypes, we performed
the selective scanning of JHBX and KL with CJX and JKLB, who have black
coat color, respectively. We used the following strategies to conduct
the genome scanning of pig breeds in Guizhou province. We used
nucleotide diversity (θπ) to detect the selection characteristics of
local pig breeds in Guizhou province. By using vcftools, nucleotide
diversity was estimated using a 200 kb window and a 10 kb step size.
The regions with significantly high π values (the first 1% of π values
covered) were selected as candidate regions for genomic selection. R
software was used to visualize the π values at the whole genome level.
Referring to the pig reference genome (Sscrofa 11.1) on the Ensembl
website ([58]https://asia.ensembl.org/index.html, accessed on 27
October 2023), candidate genes were selected within a 100 KB range
upstream and downstream of the significant region. In order to better
understand the gene functions and signaling pathways of the identified
candidate genes, GO and KEGG pathway enrichment analyses were performed
using kobas. A p value of less than 0.05 indicated a significant
enrichment pathway.
3. Results
3.1. Phylogenetic Relationships and Genetic Differentiation
To compare the genome-wide genetic relationships and degrees of
differentiation between local pig breeds in Guizhou province and
European pig breeds, initially, we constructed adjacency
neighbor-joining (NJ) trees based on the identity-by-state (IBS)
distance matrix for all 283 pigs of the 10 Eurasian breeds ([59]Figure
1B). In general, Chinese local pig breeds and Western commercial breeds
were clustered on two sides of the evolutionary tree. Almost all breeds
were independently branched, and individuals of the same breed were
clustered together; BX had one individual clustered on the branch of
CJX, except KL. None of the KL individuals clustered into a single
branch, although they were dispersed among other Guizhou and European
pig breeds.
Figure 1.
[60]Figure 1
[61]Open in a new tab
Phylogeny and population structure of 283 pigs from 10 Eurasian breeds:
(A) The geographical location of seven indigenous pig breeds in Guizhou
province. The seven breeds included Baixi (BX), Congjiang Xiang (CJX),
Guanling (GL), Jianhe White Xiang (JHBX), Jiangkou Luobo (JKLB), Kele
(KL), and Qiandong Hua (QDH). (B) Neighbor-joining tree of 283 pigs
from the 10 breeds, including the 7 Guizhou breeds mentioned above, and
Duroc (DRC), Landrace (LR), and Large White (LW). (C) Principal
component (PC) plots of 283 pigs from the 10 pig breeds. The first
(PC1) and second component (PC2) are shown, and the percentage
represents the proportion of the corresponding principal component. (D)
Principal component (PC) plots of 193 pigs from the 7 pig breeds in
Guizhou province. (E) The ancestry of the 10 breeds was analyzed by
ADMIXTURE with the assumed number of ancestries (K) from 2 to 10 and
16. Each color represents one ancestral cluster. All breeds are
separated by dotted lines.
ADMIXTREE analyses were performed for the 10 Eurasian varieties, with K
values ranging from 2 to 10 and 16, to assess their evolutionary
origins in different populations in Guizhou province ([62]Figure 1E).
Chinese and Western pig breeds appeared as two distinct clusters with
different ancestral lineages when K = 2, as previously reported
[[63]9,[64]18]. However, the genetic background of some Guizhou pigs
was mixed with that of a small number of Western pig breeds. When K =
3, JHBX was separated from the other local varieties in Guizhou
province, indicating the unique genetic characteristics of JHBX. When
the K value was 6, BX was differentiated from the local pig breeds in
Guizhou province. Followed by K = 7, CJX and QDH had the same
differentiation cluster, and JKLB, GL, and KL were grouped in another
differentiation cluster; all breeds had different differentiation
clusters when K = 10. The lowest cross-validation error was observed
for K = 16. At the same time, KL pigs had the most mixed bloodlines,
which was consistent with the results of the NJ trees, and KL pigs did
not cluster into independent branches ([65]Figure 1E).
Principal component analysis was performed on local pig breeds in
Guizhou province and European pig breeds. The two largest principal
components, PC1 and PC2, were used to map the results ([66]Figure
1C,D). The Chinese breeds were clearly distinguished from the European
breeds according to PC1, as shown in [67]Figure 1C. Meanwhile, PC2
showed genetic differentiation between the DRC, LR, and LW breeds. PC1
and PC2 reflected the differences among the seven local varieties in
Guizhou province when European varieties were removed from the dataset
([68]Figure 1D). JHBX was distant from the other six varieties. This
further indicated the unique genetic characteristics of JHBX. CJX was
found to be closely related to QDH, and KL was found to be closely
related to BX. The distribution pattern of one BX individual was near
the CJX population, and the remainder clustered together. This agrees
with the results of the NJ and ADMIXTURE analyses. JHBX exhibited the
longest branch in the NJ tree. According to the results of the
ADMIXTURE analysis, JHBX had different differentiation clusters from
the other pig breeds in Guizhou province when K = 3.
We subsequently performed a TREEMIX analysis to identify the migration
events that occurred in all 10 species. The OptM package was used to
select the optimal number of migration edges (m value), and the optimal
m value was 2. Therefore, we set the migration event to 2. The
migration events that occurred in all 10 species were determined. Among
the 10 varieties, GL showed the infiltration characteristics of DRC,
and JKLB showed the infiltration characteristics of CJX ([69]Figure 2).
These migration events are consistent with the ADMIXTURE population
structure.
Figure 2.
[70]Figure 2
[71]Open in a new tab
Population splits and ADMIXTURE analysis of all 10 Eurasian pig breeds
were analyzed using TREEMIX. Arrows indicate migration events. A
spectrum of heat colors indicates different migration weights in the
migration event. Horizontal branch lengths are proportional to the
amount of genetic drift occurring on the branch. The scale bar shows 10
times the average standard error of the entries in the sample
covariance matrix. Refer to [72]Figure 1 for abbreviations.
3.2. Genetic Diversity Index
Five genetic diversity indices were calculated to compare the genetic
variability of these ten varieties: Ho, He, MAF, F[ROH], and FIS.
[73]Table 1 summarizes the genetic diversity parameters of the
varieties. Across all populations, the expected heterozygosity ranged
from 0.1342 (JHBX) to 0.3458 (KL), whereas the observed heterozygosity
ranged from 0.1501 (JHBX) to 0.3914 (JKLB). Ho and He were higher in
European pig breeds than in most Guizhou pig breeds, and Ho was higher
than He in all pig breeds. The inbreeding coefficients were negative
for all varieties, ranging from −0.26 (JKLB) to −0.05 (QDH) ([74]Figure
3).
Table 1.
Genetic diversity of the 10 Eurasian pig breeds in this study.
Breed Abbreviation Number of Individuals Ho He Maf F [ROH] Fis
Baixi BX 30 0.31 0.31 0.23 0.019 −0.02
Congjiang Xiang CJX 25 0.23 0.21 0.15 0.015 −0.09
Duroc DRC 30 0.31 0.29 0.22 0.023 −0.07
Guanling GL 30 0.28 0.27 0.19 0.009 −0.06
Jianhe White Xiang JHBX 40 0.15 0.13 0.10 0.038 −0.12
Jiangkou Luobo JKLB 16 0.39 0.31 0.24 0.009 −0.26
Kele KL 22 0.36 0.35 0.26 0.008 −0.05
Landrace LR 30 0.36 0.32 0.25 0.016 −0.12
Large White LW 30 0.34 0.34 0.26 0.021 −0.01
Qiandong Hua QDH 30 0.21 0.21 0.15 0.016 −0.01
[75]Open in a new tab
Figure 3.
[76]Figure 3
[77]Open in a new tab
Genetic diversity of 7 pig breeds in Guizhou province: The histograms
represent the inbreeding coefficients (Fis) of each breed. Pig breeds
were plotted along the X-axis, while Fis values were plotted along the
Y-axis. Green color represents local varieties in Guizhou Province and
red color represents foreign varieties.
The ROH length and frequency can reflect population history [[78]19].
The longer the ROH is, the closer the relatives are, and the longer the
ROH fragments are, the higher the possibility of inbreeding in the
family is [[79]15]. F[ROH] in these groups ranged from 0.008 (KL) to
0.038 (JHBX).
The Fst was used to estimate the values of all autosomal information
markers at a genome-wide level to determine the degree of
differentiation between Chinese and Western pig populations. The values
for all pairwise population comparisons of the Fst are shown in
[80]Table 2. DRC exhibited the highest Fst with JHBX compared to other
populations, and it also showed the greatest difference from JHBX. The
populations of Chinese pigs and European pigs were found to be very
different, with Fst values greater than 0.25. The Fst values of local
pig breeds in Guizhou province significantly varied, from the smallest
Fst value of 0.10 to the largest Fst value of 0.41.
Table 2.
Genetic differentiation index (Fst) of 10 Eurasian pig breeds in this
study.
CJX DRC GL JHBX JKLB KL LR LW QDH
BX 0.19 0.32 0.14 0.31 0.17 0.10 0.32 0.31 0.20
CJX 0.47 0.13 0.29 0.27 0.16 0.44 0.42 0.13
DRC 0.41 0.58 0.30 0.29 0.30 0.29 0.48
GL 0.25 0.21 0.10 0.38 0.35 0.12
JHBX 0.41 0.29 0.54 0.53 0.25
JKLB 0.14 0.31 0.29 0.28
KL 0.27 0.26 0.16
LR 0.24 0.45
LW 0.43
[81]Open in a new tab
Refer to [82]Table 1 for abbreviations.
3.3. Screening of Candidate Genes Affecting Pig Coat Color
We used nucleotide diversity analysis (θπ) to detect the candidate
genes affecting pig coat color phenotypes. We established two
comparison models. First, nucleotide diversity analysis was carried out
based on JHBX with CJX, and JKLB. The second model was based on
nucleotide diversity analysis of the presence of the brown coat
phenotypes of KL with CJX, and JKLB.
Firstly, based on the analysis of JHBX, 1566 significant intervals were
detected in JHBX, 796 genes were identified within these significant
intervals, and these candidate genes were analyzed with the KEGG
pathway enrichment analysis using kobas. The results of the enrichment
analysis showed that 284 KEGG signaling pathways were enriched, and of
those, 65 pathways were significantly enriched (p < 0.05). Among them,
four signaling pathways were enriched, namely the PI3K/Akt signaling
pathway, the MAPK signaling pathway, the Wnt signaling pathway, and the
melanoma signaling pathway, which may be involved in the process of
animal coat color generation. Notably, 43 genes were identified in
these four pathways, including PDGFRB, RB1, FGF7, BAD, DDB2, RAF1, etc.
Based on the KL analysis results, 2164 significant regions were
detected in KL, and 825 genes were identified within these significant
regions, which were analyzed using the KEGG pathway enrichment
analysis. The results showed that 284 KEGG signaling pathways were
enriched, and 95 of these pathways were significantly enriched (p <
0.05). Three signaling pathways were enriched, namely the MAPK
signaling pathway, the melanin generation pathway, and the PI3K/Akt
signaling pathway, which may be involved in the process of animal coat
color production. We identified 35 genes in these three signaling
pathways, including KIT, MAPK1, KRAS, PRKCG, etc.
4. Discussion
4.1. Historical Relatedness and ADMIXTURE Analysis
The historical correlation and mixability of seven Chinese breeds in
Guizhou and three European pig breeds were revealed through the
analysis of adjacent trees, PCA, ADMIXTURE, and TREEMIX results.
The local pig breeds in Guizhou province and the European pig breeds
were located in two large branches of the evolutionary tree in the NJ
tree constructed based on IBS values. Furthermore, the PCA diagram
proved that there was a significant difference between the Chinese and
European pig breeds. ADMIXTURE ancestry composition analysis showed
that the Chinese and Western pig breeds had two differentiated clusters
when K = 2, indicating different ancestral lineages. This is consistent
with previous reports indicating that European and Chinese pig breeds
have different ancestral origins [[83]8,[84]20]. Wang et al. [[85]8]
used a 60 K SNP chip to study three pig breeds in Jiangxi province and
found that Chinese and European pigs were clustered into two
independent branches, whereas the Chinese–European hybrid breed (Sutai)
was located in the middle between the European and Chinese branches in
the NJ tree; the obvious difference between Chinese and European pig
breeds was also reflected in the PCA diagram. Chen et al. [[86]4] also
found significant genetic differences between Chinese and European
domestic pigs based on the population genetic analysis of 266 Eurasian
wild pigs and domestic pigs. TREEMIX analysis showed that KL had the
infiltration characteristics of DRC, which was of certain confidence
because some KL had a brown coat color, consistent with the brown coat
color phenotype of DRC. There was a migration event from CJX to JKLB,
possibly owing to their proximity and the possibility of gene exchange.
4.2. Genetic Diversity
Chinese native pigs have richer genetic variability than European
commercial pigs [[87]18,[88]21]. Therefore, they are expected to have
higher Ho values than European commercial pigs. However, Ho levels in
the three European varieties were higher than those in CJX, GL, JHBX,
and QDH. The reason for the inconsistency with our expectations may be
the small effective population size of the current sample and the
underrepresentation of the sample. The degree of heterozygosity is an
indicator of genetic variation in a population. Inbreeding may occur in
the population when the observed heterozygosity is lower than the
expected heterozygosity. The population may have historically
differentiated when the observed heterozygosity is higher than the
expected heterozygosity. The observed heterozygosity of all the tested
sample groups was higher than their expected heterozygosity. This may
indicate that the sample groups were historically differentiated. Fis
represents the inbreeding coefficient of an individual relative to a
subpopulation, that is, the average inbreeding coefficient of a
subpopulation. Lower Fis values (including negative values) correlate
with higher heterozygosity; higher Fis values correlate with higher
homozygosity. In this study, the Fis values of all populations were
negative. This indicated that the degree of inbreeding in these
populations was low. The length and frequency of the ROH reflect the
history of population kinship, and the number of long ROH fragments is
positively proportional to the possibility of inbreeding within a
family. Higher numbers correlate with greater possibilities of
inbreeding [[89]22]. In this study, the F[ROH] in these populations
ranged from 0.008 (KL) to 0.038 (JHBX) in the inbreeding coefficients
calculated based on the ROH. The results of previous studies indicate
that the average inbreeding coefficient is 0.11 and 0.026 in a Licha
black pig population [[90]23] and a Liangshan pig population based on
the ROH [[91]24]. The degree of inbreeding in the JHBX population in
this study was higher than in the other breeds, but overall, all breeds
were less inbred. In addition, the JHBX breed had a larger F[ROH] than
the modern European breeds and had the most ROHs, perhaps due to
inbreeding in their ancestral populations, leading to a reduction in
genetic diversity, which was reflected in the breed’s much lower Ho
values. In contrast, the shorter ROHs and the lower degree of LD in KL
pigs reflect the richness of their genetic variability. This suggests
that the JHBX population needs further selection efforts to prevent
inbreeding decline.
4.3. Coat Color Candidate Gene Screening
Coat color is one of the important characteristics of animal breeds.
The head and tail of JHBX are black, and the middle is white, and some
KL breeds have brown coat phenotypes. Based on the difference in coat
color, the whole-genome nucleotide scanning analysis was performed on
the pigs with black coat color phenotypes, and four and three related
pathways were found to be involved in coat color formation for JHBX and
KL, respectively. Among them, the kinases MEK and ERK in the MAPK
signaling pathway are involved in the activation of melanocyte
receptors, and the ligands activate the complex mechanism
(Ras-Raf-MEK-ERK) by binding to the extracellular domain of the
receptor, resulting in the upregulation of MITF [[92]25]. Another
underlying mechanism of the activation of the MAPK pathway is the
interaction of endothelin (EDN) with its receptor. Zhou et al. reported
that Selaginellin (SEL) inhibited the mitogen-activated protein kinase
(MAPK) signaling pathway. Then, the expression of
microphthalmia-associated transcription factor (MITF) and the
downstream genes tyrosinase (TYR) and tyrosinase-associated protein 2
(TYRP2) were downregulated to inhibit melanin production [[93]26].
Interleukin-10 (IL-10) can activate the PI3K/Akt and JAK/Stat3
pathways, and the former leads to the activation of the classical NF-κB
pathway and the inactivation of GSK-3β, further upregulating melanin
production [[94]27]. Wnts is a cysteine-rich secreted glycoprotein, and
the Wnt signaling pathway is involved in cell migration, proliferation,
differentiation, and the self-renewal of stem cells [[95]28], including
neural crista-derived melanocyte development and migration [[96]29].
Among the selected candidate genes, SUN et al. used CRISPR/Cas9
technology to create two mouse models, KIT D17/+ to simulate splicing
mutations, and KIT Dup/+ to partially simulate KIT gene repeat
mutations in dominant white pigs. The combination of these two
mutations was found to reduce the phosphorylation of proteins
associated with the PI3K and MAPK pathways, which may be related to the
impaired melanoblast migration observed during embryonic development,
ultimately leading to a dominant white phenotype [[97]30]. In alpaca
melanocytes, IGF1 has been shown to improve melanin production via the
cyclic AMP (cAMP) pathway [[98]31]. Infarinato et al. [[99]32] found
that after the WNT-mediated activation of melanocyte stem cells, BMP
and WNT pathways synergically triggered the occurrence of proliferative
progeny by promoting LEF1- and MITF-dependent differentiation. Sastry
et al. showed that ERK1/2, AKT, PKA, and PKC are important kinases
responsible for melanocyte cell protection. Each of these
pathways/kinases is partially responsible for survival, and they
strictly regulate survival by inducing BAD phosphorylation. Melanocyte
survival is mediated by a complex network of Bad-dependent and
Bad-independent pathways [[100]33]. The candidate genes of the above
pathways can be used as candidate genes affecting coat color.
5. Conclusions
Our study revealed the genetic diversity, historical correlations, and
population structure of seven pig breeds in Guizhou in a more
comprehensive manner. In general, the genetic diversity of the six
Chinese native pig populations (except for JHBX in Guizhou province)
was at a medium level, while the genetic diversity of the JHBX
population was low. Further selection analysis should be performed to
strengthen the efforts toward preventing inbreeding decline; however,
the protective effects on the other six pig populations should be
further improved. At the same time, we identified a new set of
candidate genes that may have an impact on phenotypic differences in
coat color in pigs. In summary, we conducted a comprehensive
genome-wide survey of seven native Chinese pig populations in Guizhou
province. We believe that the results of this study will provide a good
basis to develop national programs for the conservation and utilization
of these pig populations. Furthermore, our findings will advance our
understanding of the genetic mechanisms underlying the germplasm
characteristics of these breeds.
Author Contributions
Conceptualization, L.Z. and Y.Z.; methodology, Z.H. and Y.S.; software,
Z.H.; validation, Z.H., Y.S. and L.Z.; formal analysis, Z.H.;
investigation, W.Z., N.N., R.Z., R.L. and L.W.; formal analysis, W.Z.,
N.N., R.Z., R.L. and L.W.; resources, L.Z. and Y.Z.; data curation,
Z.H.; writing—original draft preparation, Z.H.; writing—review and
editing, L.Z. All authors have read and agreed to the published version
of the manuscript.
Institutional Review Board Statement
All the animals used in this study were treated according to the
guidelines for experimental animals established by the Council of
China. Animal experiments were approved by the Science Research
Department of the Institute of Animal Science, Chinese Academy of
Agricultural Sciences (IAS2022-156; date: 25 January 2022, Beijing,
China).
Informed Consent Statement
Not applicable.
Data Availability Statement
The data presented in this study are available upon request from the
corresponding author.
Conflicts of Interest
The authors declare no conflicts of interest.
Funding Statement
This work was financially supported by the National Key R&D Program of
China (2021YFD1200303), the National Swine Industry Technology System
(CARS-35), and the Agricultural Science and Technology Innovation
Program (ASTIP-IAS02).
Footnotes
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References