Abstract
South China indigenous pigs are famous for their superior meat quality
and crude feed tolerance. Saba and Baoshan pigs without saddleback were
located in the high-altitude area of Yunnan Province, while Tunchang
and Ding’an pigs with saddleback were located in the low-altitude area
of Hainan Province. Although these pigs are different in appearance,
the underlying genetic differences have not been investigated. In this
study, based on the single-nucleotide polymorphism (SNP) genotypes of
124 samples, both the cross-population extended haplotype homozygosity
(XP-EHH) and the fixation index (F[ST]) statistic were used to identify
potential signatures of selection in these pig breeds. We found nine
potential signatures of selection detected simultaneously by two
methods, annotated 22 genes in Hainan pigs, when Baoshan pigs were used
as the reference group. In addition, eleven potential signatures of
selection detected simultaneously by two methods, annotated 24 genes in
Hainan pigs compared with Saba pigs. These candidate genes were most
enriched in GO: 0048015~phosphatidylinositol-mediated signaling and
ssc00604: Glycosphingolipid biosynthesis—ganglio series. These
selection signatures were likely to overlap with quantitative trait
loci associated with meat quality traits. Furthermore, one potential
selection signature, which was associated with different coat color,
was detected in Hainan pigs. These results contribute to a better
understanding of the underlying genetic architecture of South China
indigenous pigs.
Keywords: signatures of selection, South China indigenous pigs, SNP,
XP-EHH, F[ST]
1. Introduction
Pigs have been domesticated for 9000 years [[42]1]. During their long
history of evolution and breeding, pigs have been selected naturally or
artificially for specific traits, such as adaption to high temperature
and humidity in South China, coat color, body length, meat quality, and
so forth. Many genetic footprints, i.e., signatures of selection,
remain in the genome [[43]2,[44]3] and have been of interest for
evolutionary biologists and breeders. The study of signatures of
selection may provide some information about selection mechanisms and
benefit future pig breeding.
The regions of the genome where the signatures of selection can be
detected usually show long-range linkage disequilibrium (LD)
accompanied by a high population frequency [[45]2,[46]3,[47]4] and
these regions can be detected based on genomic data with the population
statistical method. Currently, detection approaches for signatures of
selection are based on single point frequencies of selected mutations,
LD, and population differentiation. Among these, single point
frequencies may produce high rates of false positives [[48]5].
Cross-population extended haplotype homozygosity (XP-EHH) [[49]6] is
based on the long-range haplotype (LRH) and the integrated haplotype
score (iHS) [[50]7], which was applied to identify signatures of
selection in cross-populations. The fixation index (F[ST]) statistic,
which is based on population differentiation, was first defined by
Lewontin and Krakauer [[51]8] based on coefficient F [[52]9] and was
then developed by Weir and Cockerham [[53]10], Akey et al. [[54]11],
and Gianola et al. [[55]12].
With the rapid developments in high-throughput sequencing and
genotyping, many signatures of selection have recently been detected in
the pig genome [[56]13,[57]14,[58]15,[59]16,[60]17]. The study of Rubin
et al. [[61]18] showed strong signatures of selection at three loci
which harbor NR6A1, PLAG1, and LCORL genes and are associated with the
elongation of the back and an increased number of vertebrae in European
domestic pigs. Additionally, using the F[ST] statistic, Ai et al.
[[62]19] found several genes, including ADAMTS12, SIMI, and NOS1, which
are likely associated with adaption to high altitude in Tibetan pigs.
Furthermore, some potential signatures of selection related to economic
traits, such as disease resistance, pork yield, fertility, tameness,
and body length, were found in Berkshire pigs [[63]20]. Compared with
Chinese indigenous breeds and commercial pig breeds, the results showed
that 81 candidate genes are associated with the development of tissues
and organs and the immune response [[64]21].
A few studies [[65]13,[66]21,[67]22,[68]23] have been carried out to
detect signatures of selection in Chinese indigenous pigs. Research
into breeding goals in Chinese and European domestic pig breeds showed
that they all concentrated on genes mostly related to muscle
development, the nervous system, and especially to metabolic diseases.
The Chinese tend to pay more attention to fat deposits, while Europeans
tend to concentrate more on leanness and body length for modern
commercial breeds [[69]24]. South China indigenous pig breeds are
distributed in the tropical and subtropical areas of South China. South
China indigenous pig breeds usually have a white coat with black spots,
a black head and haunch, and their body size is usually smaller than
other Chinese indigenous pig breeds. Moreover, the backfat of South
China pig breeds is thicker [[70]25,[71]26]. Tunchang pigs (a
subpopulation of Hainan pigs [[72]25]), Ding’an pigs (a subpopulation
of Hainan pigs [[73]25]), Baoshan pigs, and Saba pigs were domesticated
in a relatively isolated environment in Hainan Province and Yunnan
Province, South China. The long-term geographical and genetic isolation
caused differential appearance and potential genetic diversity. Saba
and Baoshan pigs, located in a high-altitude area of Yunnan Province
(>1500 m above sea level (a.s.l.)), have a black coat without
saddleback. Meanwhile, Hainan pigs, located in a low-altitude area,
have saddleback. Although the difference in appearance between these
two types of pig is easily observed, the underlying genetic differences
are yet to be discovered.
The aim of this study was to detect specific signatures of selection
associated with the genetic characteristics within the genomes of three
breeds of South China indigenous pigs. The XP-EHH test and the F[ST]
statistic were used to identify the signatures of selection in South
China indigenous pigs using genotype data from the Illumina
PorcineSNP60 BeadChip [[74]27] and the GeneSeek Genomic Profiler (GGP)
Porcine Chip ([75]https://genomics.neogen.com/en/ggp-porcine). Our
findings revealed important candidate functional genes that underwent
positive selection in South China indigenous pigs.
2. Materials and methods
2.1. Ethics Approval
This study was carried out in accordance with the recommendations of
the Animal Care Committee of the South China Agricultural University
(Guangzhou, People’s Republic of China). The protocol was approved by
the Animal Care Committee of the South China Agricultural University
(SCAU#2013-10).
2.2. DNA Sample Collection
A total of 124 individuals of three pig breeds (four populations) were
collected from four locations in South China. Specifically, 33 Baoshan
pigs (BS, 13 males, 20 females, collected from Shidian, Yunnan
Province, 16 July 2015), 23 Saba pigs (SB, nine males, 14 females,
collected from Chuxiong Yi Autonomous Prefecture, Yunnan Province, 22
July 2015), 34 Ding’an pigs (DA, a subpopulation of the Hainan pig
[[76]25], 34 females, collected from Ding’an, Hainan Province, 23
January 2016), and 34 Tunchang pigs (TC, a subpopulation of the Hainan
pig [[77]25], 10 males, 24 females, collected from Tunchang, Hainan
Province, 10 March 2016).
2.3. Single-Nucleotide Polymorphism (SNP) Genotyping and Data Quality Control
Genomic DNA samples from all three breeds of Chinese indigenous pig
were extracted from ear tissue using the E.Z.N.A.^®Tissue DNA Kit
(D3396-02, Omega Bio-tek, Norcross, GA, USA). The Illumina PorcineSNP60
BeadChip [[78]27], which contains 61,565 SNPs, was used for the SNP
genotyping of Baoshan pigs and Saba pigs, while the GGP Porcine Chip
([79]https://genomics.neogen.com/en/ggp-porcine), which contains 68,516
SNPs, was used for the SNP genotyping of Ding’an pigs and Tunchang
pigs. The SNP data of three South China pig breeds are available in the
figshare database ([80]https://doi.org/10.6084/m9.figshare.7588235.v1)
The quality control criteria for genotypic data were as follows: (1)
Retaining the mutual SNPs between two SNP chips (the alleles of each
SNP on two chips were unified according their SNP chip annotation file
while merging the genotype from different chips); (2) removing SNP loci
with a call rate of less than 0.90 and unknown position or located on
sex chromosomes; (3) filtering out individuals with call rates less
than 0.90; and (4) removing SNP loci with minor allele frequency (MAF)
less than 0.05. PLINK software [[81]28] was used to perform data
quality control. Following quality control, fastPHASE [[82]29] was used
to infer haplotypes for the haplotype-based method (XP-EHH) with the
parameters –KL10, –KU30, and –Ki5.
2.4. Principal Component Analysis
To investigate the pattern of genetic differentiation among breeds,
principal component analysis (PCA) was conducted with GCTA software
(Version 1.91.1) [[83]30]. Then, the figure of PCA was plotted using R
base package with plot function [[84]31]. The SNPs used in this
analysis were filtered for pairwise LD (r^2 < 0.5) with PLINK software
[[85]28] using the command indep-pairwise 50 5 0.5.
2.5. Phylogenetic Tree
In order to better understand the relationship between the three breeds
investigated in this study, a phylogenetic tree based on the pairwise
identical by state (IBS) was constructed. The average proportion of
alleles shared among all individuals (denoted as
[MATH: Dst :MATH]
) was calculated as follows:
[MATH:
Dst=(IBS2+0.5×<
/mo>IBS1)/N :MATH]
, where
[MATH:
IBS1
:MATH]
and
[MATH:
IBS2
:MATH]
are the number of loci which share either one or two alleles IBS of two
individuals, respectively, and
[MATH: N :MATH]
is the total number of SNPs. Then, 1-
[MATH:
Dst
:MATH]
is the genetic distance between all pairwise combinations of
individuals, as in Ai et al. [[86]19]. The
[MATH: Dst :MATH]
was calculated by PLINK software [[87]28]. A neighbor-joining (N-J)
tree [[88]32] based on genetic distance was constructed by MEGA
software (Version 7.0.14) [[89]33].
2.6. Identification of Signatures of Selection
Both the XP-EHH and the F[ST] were used for the detection of signatures
of selection in this study. The XP-EHH was needed to define test groups
and reference groups. In this study, XP-EHH [[90]34] was used to
calculate the XP-EHH scores. A chromosome segment of 1 Mb was directly
converted as 1 centiMorgan (cM) in Ma et al. [[91]23]. The Genepop R
package [[92]35] was used to calculate F[ST] statistics. The F[ST]
statistic indicated the population differentiation; however, it was
unable to indicate which population experienced selection.
In previous research, XP-EHH scores were reported to approximately
follow a normal distribution [[93]6]. In this study, the unstandardized
XP-EHH scores were transformed into a normal distribution. Then, the
p-values of standardized XP-EHH scores which were lower than 0.01 were
treated as significant SNPs detected by XP-EHH, as in Li et al.
[[94]13]. The distribution of F[ST] approximately followed a normal
distribution after the normalization of the square root of F[ST], as in
Gianola et al. [[95]12]. In this study, the p-values of standardized
F[ST] below 0.01 were treated as significant SNPs. F[ST] may produce
high rates of false positives compared with XP-EHH, as suggested by Ma
et al. [[96]36]. Therefore, the significant SNPs detected either both
methods or at least one method, which were treated as potential
signatures of selection in this study. In addition, this study focused
on the significant SNPs detected simultaneously by two methods.
2.7. Genome Annotation and Quantitative Trait Loci (QTL) Overlapping with
Potential Signatures of Selection
The potential selection regions were defined by extending 200 kb both
upstream and downstream of the potential signatures of selection in Liu
et al. [[97]37]. Genome annotation was based on the Sus scrofa 10.2
([98]https://www.animalgenome.org/blast/). Genes harbored in these
potential selection regions were treated as candidate genes and RNAs
and unconfirmed genes were filtered out. Additionally, the Animal
Quantitative Trait Loci (QTL) Database [[99]38] was used to annotate
potential traits related to the potential selection regions based on
QTL physical position intervals downloaded from the Animal QTL database
[[100]38].
2.8. Gene Ontology (GO) Terms and Kyoto Encyclopedia of Genes and Genomes
(KEGG) Pathway Enrichment Analysis
To further explore the function of these candidate genes, Kyoto
Encyclopedia of Genes and Genomes (KEGG) pathway [[101]39] and Gene
Ontology (GO) [[102]40] were used for enrichment analyses through the
Database for Annotation, Visualization, and Integrated Discovery
(DAVID) Version 6.8 ([103]https://david.ncifcrf.gov/)
[[104]41,[105]42]. The GO terms and KEGG pathways with p-values > 0.05
were filtered out.
3. Results
3.1. Genotypes and Population Structure
A total of 34,815 SNPs located on autosomes were common in the two SNP
chips. In quality control, 1833 and 9444 SNPs were filtered out for the
SNP call rate and MAF, respectively. The average individual call rate
was 0.9781 and no individual was removed. After quality control, 124
individuals and 23,538 SNPs were retained for further study.
A subset of 23,538 SNPs (18,994 LD-pruned SNPs) were retained to
conduct PCA. PCA1 and PCA2 explained 13.52% and 5.05% of the total
variation, respectively ([106]Figure 1). Individuals of two Hainan pig
subpopulations were clustered together, as also shown by the N-J tree
([107]Figure 2). Baoshan and Saba appeared as two separate groups. The
average genetic distance between Baoshan pigs (0.2775 ± 0.0042) was the
highest among the four pig populations (Saba: 0.2213 ± 0.0056; Ding’an:
0.2209 ± 0.0067; Tunchang: 0.2345 ± 0.0062). More details are shown in
[108]Table S1.
Figure 1.
[109]Figure 1
[110]Open in a new tab
Principal component analysis of 33 Baoshan pigs (red triangles), 23
Saba pigs (blue squares), 34 Ding’an pigs (purple triangles), and 34
Tunchang pigs (green targets). The principal component analysis was
conducted by GCTA software (Version 1.91.1) [[111]30], plotted with R
base package plot function [[112]31].
Figure 2.
[113]Figure 2
[114]Open in a new tab
Phylogenetic tree based on four pig populations. The polygenetic tree
was constructed based on data collected from 33 Baoshan pigs, 23 Saba
pigs, 34 Ding’an pigs, and 34 Tunchang pigs. Different colors represent
different pig populations. The phylogenetic tree was constructed by
MEGA software (Version 7.0.14) [[115]33].
3.2. Identification of Signatures of Selection
According to the result of the PCA ([116]Figure 1) and the N-J tree
([117]Figure 2), the two subpopulations of Hainan pigs (Ding’an pigs
and Tunchang pigs) were treated as test groups, while the Baoshan and
Saba populations were used as reference groups, respectively.
The distribution of unstandardized XP-EHH scores and standardized
XP-EHH scores are shown in [118]Figure 3b and [119]Figure 4b. The
distribution of F[ST] statistics and standardized F[ST] statistics are
shown in [120]Figure 5b and [121]Figure 6b. In the Ding’an and
Tunchang/Baoshan groups, 174 SNPs and 71 SNPs were treated as
significant through XP-EHH in Hainan pigs and Baoshan pigs ([122]Table
S2). Meanwhile, 445 SNPs were treated as significant using F[ST]
([123]Table S2). Similarly, in the Ding’an and Tunchang/Saba groups,
110 SNPs and 125 SNPs were treated as significant through XP-EHH in
Hainan pigs and Baoshan pigs ([124]Table S3). Meanwhile, 445 SNPs were
treated as significant using F[ST] ([125]Table S3).
Figure 3.
[126]Figure 3
[127]Open in a new tab
Cross-population extended haplotype homozygosity (XP-EHH) scores across
all autosomes in the Ding’an and Tunchang/Baoshan groups. (a)
Genome-wide distribution of signatures of selection detected by XP-EHH
across all autosomes in the Ding’an and Tunchang/Baoshan groups. The
SNPs shown as diamonds are the significant SNPs detected simultaneously
by two methods. The red lines show the threshold p-value (0.01). (b)
The distribution of unstandardized XP-EHH scores and standardized
XP-EHH scores across all autosomes in the Ding’an and Tunchang/Baoshan
groups.
Figure 4.
[128]Figure 4
[129]Open in a new tab
XP-EHH scores across all autosomes in the Ding’an and Tunchang/Saba
groups. (a) Genome-wide distribution of signatures of selection
detected by XP-EHH across all autosomes in the Ding’an and
Tunchang/Saba groups. The SNPs shown as diamonds are the significant
SNPs detected simultaneously by two methods. The red lines show the
threshold p-value (0.01). (b) The distribution of unstandardized XP-EHH
scores and standardized XP-EHH scores across all autosomes in the
Ding’an and Tunchang/Saba groups.
Figure 5.
[130]Figure 5
[131]Open in a new tab
F[ST] statistics across all autosomes in the Ding’an and
Tunchang/Baoshan groups. (a) Genome-wide distribution of signatures of
selection detected by F[ST] statistics across all autosomes in the
Ding’an and Tunchang/Baoshan groups. The SNPs shown as diamonds are the
significant SNPs detected simultaneously by two methods. The red line
shows the threshold p-value (0.01). (b) The distribution of
unstandardized F[ST] statistics and standardized F[ST] statistics
across all autosomes in the Ding’an and Tunchang/Baoshan groups.
Figure 6.
[132]Figure 6
[133]Open in a new tab
F[ST] statistics across all autosomes in the Ding’an and Tunchang/Saba
groups. (a) Genome-wide distribution of signatures of selection
detected by F[ST] statistics across all autosomes in the Ding’an and
Tunchang/Saba groups. The SNPs shown as diamonds are the significant
SNPs detected simultaneously by two methods. The red line shows the
threshold p-value (0.01). (b) The distribution of unstandardized F[ST]
statistics and standardized F[ST] statistics across all autosomes in
the Ding’an and Tunchang/Saba groups.
On one hand, nine and eleven potential signatures of selection were
detected simultaneously by two methods in Hainan pigs using Baoshan and
Saba pigs as the reference groups, respectively. Moreover, compared to
the reference group, three significant SNPs were detected
simultaneously by two methods in both of the two comparisons (Ding’an
and Tunchang/Baoshan, Ding’an and Tunchang/Saba), which were located on
Sus scrofa chromosome 2 (SSC2) (rs81360002) and SSC14 (rs81223780 and
rs80838751), respectively. Furthermore, rs81280567 was the only
significant SNP detected simultaneously by two methods in both Baoshan
and Saba pigs ([134]Table 1 and [135]Table 2). On the other hand, a
total of 680 potential signatures of selection were detected by at
least one method in Hainan pigs and Baoshan pigs ([136]Table S2). In
addition, the mean LD degree between pairs of significant SNPs detected
by at least one method was 0.1626; furthermore, a total of 35 pairs of
significant SNPs detected by at least one method (a majority of SNPs
located in SSC14) were in high LD (
[MATH:
r2> 0.
8 :MATH]
) ([137]Table S2 and [138]Figure S1). A total of 668 potential
signatures of selection were detected by at least one method in Hainan
pigs and Saba pigs ([139]Table S3). In addition, the mean LD degree
between pairs of significant SNPs detected by at least one method was
0.1665; furthermore, a total of 31 pairs of significant SNPs detected
by at least one method (a majority of SNPs located in SSC14) were in
high LD (
[MATH:
r2> 0.
8 :MATH]
) ([140]Table S3 and [141]Figure S2).
Table 1.
Summary of significant single-nucleotide polymorphisms (SNPs) detected
simultaneously by two methods in the Ding’an and Tunchang/Baoshan pig
groups.
Chr. ^1 ID Detected in iHH ^2 in Test ^3 iHH in Ref ^4 Standardized
XP-EHH ^5 Score F [ST] Genes QTL ^6 (Counts)
2 rs81360002 Test 3.2266 0.7763 2.7056 0.4685 BTF3, ANKRA2, UTP15,
ARHGEF28 Actinobacillus pleuropneumoniae susceptibility (7)
6 rs339432830 Test 3.9553 0.9181 2.8027 0.4726 MC5R, RNMT, FAM210A,
LDLRAD4, CEP192 Backfat at last rib (11)
6 rs81391982 Test 1.0048 0.1885 3.3794 0.5273 PIK3C3 Backfat at last
rib (9)
6 rs81392000 Test 0.9475 0.2324 2.6532 0.4930 – Backfat at last rib (9)
7 rs80899633 Test 1.3000 0.2568 3.2394 0.5677 GRM4, HMGA1, NUDT3,
RPS10, PACSIN1, SPDEF Average backfat thickness (20)
9 rs81224033 Test 1.7863 0.4160 2.7937 0.5233 PLEKHA6, PPP1R15B,
PIK3C2B, MDM4, LRRN2 Shoulder weight (3)
14 rs81223780 Test 2.4569 0.4583 3.3948 0.5498 NRG3 Fat androstenone
level (4)
14 rs80838751 Test 2.6767 0.5997 2.8987 0.5129 NRG3 Fat androstenone
level (4)
18 rs81470716 Test 0.7901 0.1880 2.7350 0.5564 – Actinobacillus
pleuropneumoniae susceptibility (3)
10 rs81280567 Ref 0.1573 0.3664 –3.4439 0.5492 FRMD3, RASEF Average
daily gain (4)
[142]Open in a new tab
^1 Chromosome; ^2 the integrated haplotype score; ^3 test group
(Ding’an and Tunchang pigs); ^4 reference group (Baoshan pigs); ^5
cross-population extended haplotype homozygosity (XP-EHH); ^6 QTL:
Quantitative trait loci—the traits with the highest QTL count are shown
here and all QTLs can be seen in [143]Table S4 and [144]Table S5.
Table 2.
Summary of significant SNPs detected simultaneously by two methods in
the Ding’an and Tunchang/Saba pig groups.
Chr. ^1 ID Detected in iHH ^2 in Test ^3 iHH in Ref ^4 Standardized
XP-EHH ^5 Score F [ST] Genes QTL ^6 (Counts)
1 rs80792171 Test 1.3676 0.5713 2.7257 0.5956 LRSAM1, FAM129B, STXBP1,
CFAP157, PTRH1, TTC16, TOR2A, SH2D3C, CDK9, FPGS, ENG, AK1, ST6GALNAC6,
ST6GALNAC4 Drip loss (15)
1 rs80943372 Test 4.5343 1.6659 3.1073 0.4985 – Drip loss (16)
1 rs80858349 Test 2.2043 0.9644 2.5884 0.5304 – Drip loss (16)
1 rs80819792 Test 0.9818 0.4111 2.7187 0.4975 – Drip loss (16)
2 rs81360002 Test 3.2297 1.0560 3.4540 0.4685 BTF3, ANKRA2, UTP15,
ARHGEF28 Actinobacillus pleuropneumoniae susceptibility (7)
3 rs81251364 Test 1.8817 0.7229 2.9747 0.5172 UXS1, C3H2orf40, NCK2
Average daily gain (6)
3 rs81251441 Test 1.8762 0.6455 3.3025 0.5333 UXS1, C3H2orf40, NCK2
Average daily gain (6)
12 rs81433573 Test 0.9817 0.4227 2.6354 0.5630 ANKFN1, NOG Muscle
moisture percentage (4)
13 rs80782255 Test 1.0648 0.4471 2.7108 0.4731 – Body weight (5 weeks)
(1)
14 rs81223780 Test 2.5220 0.9360 3.0773 0.5498 NRG3 Fat androstenone
level (4)
14 rs80838751 Test 2.7541 1.1181 2.8106 0.5129 NRG3 Fat androstenone
level (4)
10 rs81280567 Ref 0.1720 0.4522 –2.7414 0.5492 FRMD3, RASEF Average
daily gain
(4)
[145]Open in a new tab
^1 Chromosome; ^2 the integrated haplotype score; ^3 test group
(Dign’an and Tunchang pigs); ^4 reference group (Saba pigs); ^5
cross-population extended haplotype homozygosity (XP-EHH); ^6 the
traits with the highest QTL count are shown here and all QTLs can be
seen in [146]Table S6 and [147]Table S7.
3.3. Genome Annotation and QTL Overlapping with Potential Signatures of
Selection
Within the potential selection regions detected simultaneously by two
methods in the Ding’an and Tunchang groups, 22 and 24 candidate genes
were annotated in the National Coalition Building Institute database,
respectively. QTL overlapping with the potential selection regions
detected simultaneously by two methods was associated with backfat at
last rib, average backfat thickness, drip loss, and so on, as shown in
[148]Table 1 and [149]Table 2 and [150]Table S4 and [151]Table S6. More
details for each QTL trait are described in the animal QTL database
([152]https://www.animalgenome.org/QTLdb/). Two candidate genes were
annotated in the two reference groups (Baoshan and Saba). The one
potential selection region detected simultaneously by two methods
overlapped with QTLs related to average daily gain, dressing
percentage, percentage type I fibers, and so on (see [153]Table 1 and
[154]Table 2 and [155]Table S5 and [156]Table S7).
In addition, a total of 1349 candidate genes annotated in 680
significant SNPs detected by at least one method in Hainan pigs and
Baoshan pigs and the QTLs overlapping with these significant SNPs were
associated with meat quality, average backfat thickness, and so on
([157]Table S2), while 1267 candidate genes annotated in 668
significant SNPs detected by at least one method in Hainan pigs and
Saba pigs totally and the QTLs overlapping with these significant SNPs
were associated with meat quality, average daily gain, and so on
([158]Table S3).
3.4. GO Terms and KEGG Pathway Enrichment Analysis
Within the potential selection regions detected simultaneously by two
methods in the Ding’an and Tunchang groups, 41 candidate genes were
annotated in total ([159]Table 1 and [160]Table 2). One GO term and one
KEGG pathway were enriched and targeted, both of which involved two
candidate genes ([161]Table 3). The enriched KEGG pathway was ssc00604
(glycosphingolipid biosynthesis—ganglio series) and the enriched GO
term was GO: 0048015 (phosphatidylinositol-mediated signaling).
However, no GO term or KEGG pathway was enriched in the reference group
(Baoshan, Saba).
Table 3.
Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes
(KEGG) pathways enriched with candidate genes in Hainan pig
populations.
GO Terms and KEGG Pathways Count Genes p-Value Test/Ref ^1
GO: 0048015~phosphatidylinositol-mediated signaling 2 PIK3C2B, PIK3C3
0.0215 Ding’an and Tunchang/Baoshan
ssc00604: Glycosphingolipid biosynthesis—ganglio series 2 ST6GALNAC6,
ST6GALNAC4 0.0198 Ding’an and Tunchang/Saba
[162]Open in a new tab
^1 test/ reference group.
The 1349 candidate genes annotated in 680 significant SNPs detected by
at least one method in Hainan pigs and Baoshan pigs involved 22 GO
terms and 12 KEGG pathways ([163]Table S2) and 1267 candidate genes
annotated in 668 significant SNPs detected by at least one method in
Hainan pigs and Saba pigs involved 13 GO terms and 17 KEGG pathways
([164]Table S3).
4. Discussion
In this study, the potential signatures of selection in South China
indigenous pig populations were identified using two approaches. Nine
and eleven potential signatures of selection were detected
simultaneously by two methods in Hainan pigs with Baoshan and Saba pigs
as reference groups, respectively. Moreover, 22 and 24 candidate genes
were found to be enriched in Hainan pigs with Baoshan and Saba pigs as
reference groups, respectively. These selection regions were
overlapping with QTLs associated with meat quality, disease resistance,
and growth. In Baoshan and Saba pigs, only one potential signature of
selection was detected simultaneously by two methods was identified,
which overlapped with growth and meat quality traits. These results
together suggest the potential utility of the findings from the present
study.
In general, the signatures of selection revealed by the methods based
on population differentiation were associated with phenotypic changes
in morphology and behavior. Interestingly, there was a significant
difference in coat color between Hainan pigs and the reference
populations. Furthermore, a potential signature of selection on SSC14
(rs81223780) was detected in Hainan pigs with either Baoshan or Saba
pigs as the reference population. This region was reported by Wilkinson
et al. [[165]43] when black and partially black coat breeds (Large
Black, Berkshire, Hampshire, British Saddleback) were compared against
red coat breeds (Duroc). The results from the present study, together
with those of Wilkinson et al. [[166]43], suggest that a promising
functional candidate region for pig coat color has been identified and
that this region could be of research interest in the future.
Additionally, one candidate gene associated with coat color
(melanocortin 5 receptor, MC5R) was detected in this study. The MC5R
gene, a member of the melanocortin receptor gene family, has been
reported to create a ligand-dependent signal modulation with MC1R,
which may participate in physiological color change in flounder
[[167]44]. Moreover, another study reported that the MC5R gene
polymorphism (A303G) may affect the feed intake, feed conversion, and
other physicochemical characteristics in Large White x Landrace
crossbred pigs [[168]45].
The phenotypes of each individual were not included in most of the
signatures of selection detection analysis, hence the functional
explanation of significant signals was usually less conclusive.
Although a new methodology for the detection of signature of selection
for specific complex traits was recently proposed by Beissinger et al.
[[169]46], the phenotypic values were not always available in such
research. The reported QTLs could serve as a reference or potential
clue to understand the identified signatures of selection. In this
study, the Animal QTL database [[170]38] and enrichment analysis were
used to enhance our understanding of the detected signature of
selection. The QTLs overlapping with potential selection regions were
mainly related to traits of meat quality, disease resistance, and
growth. It is known that the meat quality of most Chinese indigenous
pigs is superior, especially for Ding’an and Tunchang pigs
[[171]25,[172]26]. Traditionally, the priorities of pig domestication
in China were fat deposit and reproduction, which was confirmed by Wang
et al. [[173]24]. From this perspective, the signatures of selection
detected in this study would be related to those traits annotated from
the above analysis. However, we should be sufficiently cautious to
conduct further specific functional research based solely on the
findings from signature detection. Pavlidis et al. [[174]47] reported
that annotation term enrichment is known to not perform well when
applied to selective sweeps.
Although some interesting findings were reported here, the limitations
of the present study should not be neglected. These include: (1) The
low density of markers. The average distance between adjacent SNPs is
100 kb and the average LD degree between pairs of SNPs with a distance
within 200 kb of each population is 0.201, 0.168, 0.151, and 0.188 in
Ding’an, Tunchang, Baoshan, and Saba pigs, respectively. This indicates
that the SNPs were not dense enough in the present study, although
similar SNP chips were used in other studies [[175]23]; (2) the
effectiveness of the two detection methods used in this study. The
F[ST]method may bring a higher false positive rate compared with
XP-EHH, as suggested by Ma et al. [[176]23]. Furthermore, the F[ST] is
suitable for the detection of genome regions that are differentially
fixed in different breeds, while XP-EHH is used in detecting variants
which are still segregating in populations and are a subject of ongoing
selection. In addition, focusing on SNPs detected by both methods, some
potential signatures of selection among breeds might be neglected and
the combination of significant SNPs detected by one method might cause
false positive results. To provide comprehensive and balanced results,
the significant SNPs detected by either two methods or at least one
method were provided and analyzed simultaneously in this study; (3) the
small size of the effective population of the three breeds might affect
the F[ST] statistic; and (4) the contrast between Yunnan and Hainan
pigs was insufficient. Although geographic isolation exists, the
direction of Chinese pig domestication was similar in different
regions. These limitations together might impact the observations of
this study and should be overcome in further investigations.
In conclusion, some potential signatures of selection that might be
functionally associated with meat quality, disease resistance, and
growth were detected in Hainan pig genomes. Moreover, potential
signatures of selection and two candidate genes were detected in Saba
and Baoshan pig populations. This study may provide knowledge for the
genetic foundation of adaptive evolution in three breeds of South China
indigenous pigs.
Acknowledgments