Abstract

   Early pregnancy in jennies is routinely determined by palpation per
   rectum or ultrasonography and also by detecting steroid hormone and
   chorionic gonadotropin levels in the blood, plasma, and serum. Herein
   we applied label-free mass spectrometry-based quantitative proteomics
   to identify serum proteins that were differentially expressed between
   early pregnant (day 45 after ovulation) and non-pregnant jennies.
   Bioinformatics analysis allowed illustration of pathways potentially
   involved in early pregnancy. We identified 295 proteins from a total of
   2,569 peptides. Twenty-five proteins (22 upregulated and three
   downregulated) were significantly differentially expressed between the
   early pregnant and non-pregnant groups. The majority of the
   differentially expressed proteins were involved in defense response,
   early embryonic development, and hormone signaling pathways.
   Furthermore, functional protein analyses suggested that proteins were
   involved in binding, enzyme inhibitor activity, and enzyme regulator
   activity. Five serum proteins—granulin precursor/acrogranin,
   transgelin-2, fibronectin, fibrinogen-like 1, and thrombospondin 1—can
   be considered as novel, reliable candidates to detect pregnancy in
   jennies. To the best of our knowledge, this is the first study to use
   label-free mass spectrometry-based quantitative proteomics to analyze
   serum proteins during early pregnancy in jennies. Our results should
   facilitate the identification of valuable pregnancy diagnostic markers
   in early pregnant jennies.

   Keywords: proteomics, jennies, early pregnancy, biomarkers, serum
   proteins

Introduction

   Donkey (Equus asinus), a member of the equids, provides substantial
   societal benefits to humans ([31]1). Considering its novel and evolving
   role in milk, meat, and skin production and in animal-assisted therapy,
   there has been a renewed interest in this species. A decline in donkey
   population and genetic diversity has become a global trend; thus,
   successful pregnancies are essential for maintaining effective
   population size and genetic diversity ([32]2). Pregnancy in jennies
   (female donkeys) can be determined by palpation per rectum at around 40
   days after ovulation ([33]3) or by ultrasonography at around 10 days
   after ovulation ([34]4). Steroid hormone variations in the blood of
   pregnant jennies have been previously investigated. Detecting
   progesterone and estradiol concentrations in the blood, plasma, and
   serum has become a method for pregnancy diagnosis in jennies ([35]5).

   There is a relatively high concentration of proteins present in the
   blood, plasma, and serum. The serum concentration of proteins in
   donkeys is 58–82 g/L ([36]6). Molecular events are regulated by the
   expression of proteins in the blood. Thus, blood proteome could be used
   to understand biological mechanisms at a molecular level. The blood,
   plasma, and serum are widely utilized for diagnostic purposes in
   clinical practice ([37]7) and for the discovery of novel biomarkers
   ([38]8).

   With the development of proteomics, different fractions of the blood
   proteome can now be analyzed in detail. Thus far, several proteomics
   approaches have been widely and effectively applied to explore the
   blood proteome of equids. Two-dimensional (2D) gel electrophoresis is
   routinely used for assessing quantitative changes in serum and/or
   plasma proteins of horses, such as for establishing the serum protein
   map ([39]9, [40]10), evaluating changes in plasma proteins after
   prolonged physical exercise ([41]11), and comparing differences in
   serum protein expression profiles between distinct breeds ([42]12).
   Henze et al. ([43]13) evaluated genetic differences in the serum
   proteome of horses, donkeys, and mules using surface-enhanced laser
   desorption–ionization time-of-flight mass spectrometry (MS), and they
   found considerable differences in the proteome of horses and donkeys
   and that the proteome of mules showed a higher similarity to donkeys
   than to that of horses.

   It is well-known that there is an increase in blood protein synthesis
   during pregnancy ([44]14). In several species, factors that help
   diagnose pregnancy have been subjected to in-depth research using
   proteomics. Some previous studies used high-resolution 2D gel
   electrophoresis in bovine ([45]15, [46]16) and buffaloes ([47]17) to
   identify potential pregnancy-specific markers in the serum and plasma.
   Furthermore, in pregnant women who delivered at term, Scholl et al.
   ([48]18) used two-dimensional difference in-gel electrophoresis as well
   as isotope tagging for relative and absolute quantitation to assess
   changes in relative protein abundance between paired serum samples
   collected in the first and third trimesters.

   A remarkable feature of equine pregnancy is the development of the
   invasive trophoblast of the chorionic girdle and its formation of
   gonadotrophin-secreting endometrial cup cells in early pregnancy.
   Equine chorionic gonadotropin, the main secretory product of the
   endometrial cups, is secreted during days 40–150 of pregnancy ([49]19).
   During this period, numerous proteins are involved in the process of
   fetomaternal interactions. To the best of our knowledge, there are no
   published data on serum proteins during early pregnancy in jennies.
   Thus, using label-free MS-based quantitative proteomics, we herein
   aimed to identify specific serum proteins during early pregnancy in
   jennies.

Materials and Methods

Animals and Sampling

   We used Liaoxi donkeys in this study ([50]20). Nine pregnant jennies at
   day 45 after ovulation and nine non-pregnant jennies (aged 4–8 years)
   were randomly chosen at a breeding farm in Liaoning Province, China.
   The animals were considered healthy based on veterinarian records,
   physical examination, and reproductive tract examination performed by
   transrectal palpation and ultrasonography. A “B mode” ultrasound
   scanner equipped with a 7.0 MHz linear array multi-frequency transducer
   (WED-3000, Shenzhen WELLD, China) was used to monitor ovarian and
   uterine activity during estrus and pregnancy. The presence of a
   preovulatory follicle (≥3.5 cm) indicated impending ovulation.
   Artificial insemination was performed on the day of ovulation, using
   fresh semen from the same fertile jack donkey. The animals were first
   examined for pregnancy 12–15 days after ovulation, and re-examined at
   40 and 45 days after ovulation to confirm the pregnancy status. Nine
   jennies that continued pregnancy to 45 days after ovulation were
   included into the “pregnant group” (P group). Further, nine jennies
   that repeated their cyclic estrous activity 21–22 days after the last
   estrus were included into the “non-pregnant group” (NP group). All
   jennies were maintained in a stable and outdoor paddock with ad libitum
   access to a mixture of cereal straw and grass hay, maize, bran, peas,
   minerals, vitamins, and water.

   Blood samples from the P and NP groups were collected at day 45 after
   ovulation, and obtained immediately after confirming the non-pregnant
   state, respectively. Blood samples were collected at 9–10 am. The blood
   was drawn from the jugular vein and dispensed into 10-mL disposable
   vacuum tubes (BD Vacutainer, USA) without an anticoagulant. Within 1 h
   of collection, the samples were centrifuged at 3,000 g for 10 min at
   4°C, and the serum thus obtained was stored at −80°C until needed. This
   study was conducted with the approval of Shenyang Agricultural
   University Animal Care and Use Committee (Permit no.: 201906025).

Protein Extraction and Digestion

   To avoid the influence of individual differences on serum proteins, the
   nine serum samples obtained from each group were randomly divided into
   three subgroups. The three serum samples (10 μL/sample) within each
   subgroup were equally pooled to obtain three biological replicates from
   each group. Proteins were extracted using SDT lysis buffer (4% SDS, 100
   mM DTT, 100 mM Tris-HCl, pH 8.0), and protein concentration was
   determined using the BCA protein assay kit (Bio-Rad, USA). The protein
   samples were digested with trypsin, in accordance with the filter-aided
   sample preparation method ([51]21). The digested peptides of each
   sample were desalted on C18 cartridges [Empore™ SPE C18 Cartridges
   (standard density), 7 mm bed I.D., 3 mL volume, Sigma], concentrated by
   vacuum centrifugation, and reconstituted in 40 μL of 0.1% (v/v) formic
   acid.

Liquid Chromatography (LC)–Electrospray Ionization (ESI)–Tandem MS (MS/MS)

   LC–ESI–MS/MS was performed on a Q-Exactive Plus mass spectrometer
   coupled with an EASY 1200 nano-LC System (Thermo Fisher Scientific,
   Bremen, Germany). LC–ESI–MS/MS settings were the same as those stated
   in a previous study ([52]22). Briefly, 3 μg of the peptide mixture was
   first loaded onto a trap column (100 μm inner diameter, 20 mm long, 5
   μm resin, C18, Dr. Maisch GmbH, Ammerbuch, Germany) in buffer A (0.1%
   formic acid in water). Reversed-phase high-performance LC was then
   performed with the EASY 1200 nano LC System (Thermo Fisher Scientific,
   Bremen, Germany) using a self-packed column (75 μm inner diameter, 150
   mm long, 3 μm ReproSil-Pur C18 beads, 120 Å, Dr. Maisch GmbH,
   Ammerbuch, Germany), and the peptide mixture was separated with a
   linear gradient of buffer B (0.1% formic acid in 85% acetonitrile) at a
   flow rate of 300 nL/min controlled by IntelliFlow for 120 min. MS/MS
   data were acquired using a data-dependent top 20 method by dynamically
   choosing the most abundant precursor ions. The survey scans were
   selected with an isolation window of 1.6 Thomson and fragmented by
   higher energy collisional dissociation with a normalized collision
   energy of 27 eV. The maximum ion injection times for the survey and
   MS/MS scans were 50 ms, and the ion target values were set to 1e6 and
   1e5, respectively. Selected sequenced ions were dynamically excluded
   for 60 s.

Sequence Database Searching and Protein Quantification

   Raw MS data were analyzed using MaxQuant v1.6.0.16 and searched against
   UniProtKB Equus (28,987 total entries, downloaded on 15/09/2019 from
   [53]http://www.uniprot.org). The initial search peptide tolerance and
   mass tolerance were set at 20 ppm for fragment ions. The main search
   peptide tolerance was 4.5 ppm. The search was performed based on an
   enzymatic cleavage rule of trypsin/P, and a maximum of two missed
   cleavage sites were allowed ([54]21). The carbamidomethylation of
   cysteine residues was defined as a fixed modification, while protein
   N-terminal acetylation and methionine oxidation were specified as
   variable modifications for database searching. The false discovery rate
   for both peptide and protein identification was set to be <0.01
   ([55]23). Protein identification was supported by at least one unique
   peptide identification.

Statistical and Bioinformatics Analysis

   Differential proteins were analyzed for significant up- or
   downregulation, which was assessed using the R statistical computing
   software (v 3.2.1). Protein abundance information was collected to have
   at least two valid expression values in each group. Normality was
   assessed using the Shapiro–Wilk test. This exploratory analysis of the
   dataset showed that the variables were normally distributed; thus, the
   independent samples t-test was used to determine statistical
   significance for comparison between the P and NP groups. The
   significantly differentially expressed proteins (DEPs) were further
   inspected and the ones with a differential expression ratio of
   ≥1.5-fold or ≤0.66-fold (P < 0.05) were retained.

   Analyses of bioinformatics data were performed with Perseus ([56]24),
   Microsoft Excel, and R statistical computing software. The protein
   sequences of selected DEPs were extracted from UniProtKB/Swiss-Prot
   ([57]25), gene ontology (GO) terms, and Kyoto Encyclopedia of Genes and
   Genomes (KEGG) database ([58]http://geneontology.org/). GO and KEGG
   enrichment analyses were applied on the basis of Fisher's exact test in
   which whole quantified protein annotations were considered as
   background dataset, and only functional categories and pathways with P
   < 0.05 were recognized as significant. The protein–protein interaction
   (PPI) information of DEPs was retrieved using the STRING
   ([59]http://string-db.org/) database and Cytoscape software ([60]26).

Results

Identification and Quantification of the Serum Proteome

   We herein used the label-free MS-based quantitative proteomics to
   investigate serum proteins in jennies, which led to the identification
   of 295 proteins ([61]Supplementary Table 1) in the serum of early
   pregnant and non-pregnant jennies with a high confidence level (≥1
   unique peptides with false discovery rate of <1%). Overall, 275
   proteins were common between the P and NP groups. Of the 295 proteins
   that were quantified, 27.1% (80/295) were inferred from one peptide,
   and 22.0% (65/295) were proteins with >11 unique peptides ([62]Figure
   1). The molecular weight of the identified proteins ranged from 1.53 to
   881.23 kDa. Albumin, α-2-macroglobulin, serotransferrin, apolipoprotein
   A1, and haptoglobin were the major serum proteins. Detailed information
   pertaining to the identified 2,569 peptides is shown in
   [63]Supplementary Table 2.

Figure 1.

   Figure 1
   [64]Open in a new tab

   Unique peptides for the identified proteins.

Differentially Expressed Serum Protein Profiles

   Twenty-five proteins (22 upregulated and three downregulated) were
   found to be significantly differentially expressed between the P and NP
   groups (≥1.5-fold, Student's t-test, P < 0.05) ([65]Table 1,
   [66]Supplementary Table 3). Among the 25 DEPs, 12 (10 upregulated and
   two downregulated) were common between the P and NP groups. According
   to the fold change and P-value between the groups, a volcano plot was
   drawn to illustrate significant differences ([67]Figure 2). In
   addition, among the 25 DEPs, there were 12 and one proteins that were
   uniquely expressed in the P and NP groups, respectively.

Table 1.

   Differentially expressed proteins in the serum of early pregnant (P
   group) and non-pregnant (NP group) jennies.
   UniProt accession Protein names Gene names Coverage (%)[68]^b Molecular
   weight (kDa) FC[69]^a P-value Change[70]^e
   F6YR34 Thrombospondin 1 THBS1 21.1 129.56 14.43 0.0432 ↑
   F7CN05 Fibronectin FN1 39.7 252.55 3.32 0.0045 ↑
   F6RMK1 C-X-C motif chemokine LOC100630489 31.5 11.835 2.92 0.0122 ↑
   F6ZRF6 Serpin family A member 7 SERPINA7 18.6 46.64 2.25 0.0346 ↑
   A0A0A1E971 Immunoglobulin lambda light chain variable region (Fragment)
   IGL 30.4 23.267 1.91 0.0363 ↑
   F7ATS5 Golgi membrane protein 1 GOLM1 12.5 41.218 1.87 0.0276 ↑
   [71]Q5IF07 Insulin-like growth factor binding protein-2 (Fragment)
   IGFBP-2 17.7 16.042 1.82 0.0014 ↑
   F6WA57 Lymphocyte cytosolic protein 1 LCP1 35.8 70.347 1.74 0.0409 ↑
   F6Y950 Chromosome 2 C4orf33 homolog C2H4orf33 6.5 23.394 1.64 0.0486 ↑
   F6Y2H3 Peptidase D PEPD 12.2 54.827 1.53 0.0061 ↑
   A0A0A1E3W4 Immunoglobulin lambda light chain variable region (Fragment)
   IGL 25.4 23.511 P[72]^c ↑
   F6VP61 Serpin family B member 10 SERPINB10 5.8 45.412 P[73]^c ↑
   F6QXN5 Transgelin2 TAGLN2 9.3 23 P[74]^c ↑
   F6RCZ8 Triggering receptor expressed on myeloid cells like 1 TREML1 5
   33.597 P[75]^c ↑
   F6RLT8 Calpain small subunit 1 CAPNS1 4.9 28.099 P[76]^c ↑
   F6RMQ1 GLI pathogenesis related 2 GLIPR2 17.2 16.905 P[77]^c ↑
   F6T962 EGF containing fibulin extracellular matrix protein 2 EFEMP2 6.5
   49.439 P[78]^c ↑
   F6ZEJ2 HGF activator HGFAC 7.2 55.76 P[79]^c ↑
   F7AB03 Granulin precursor GRN 6.6 63.195 P[80]^c ↑
   F7DIN1 Fibrinogen like 1 FGL1 4.4 36.475 P[81]^c ↑
   F7E2K1 Uncharacterized protein N/A 2.1 72.262 P[82]^c ↑
   [83]P19794 Lutropin/choriogonadotropin subunit beta LHB 10.1 17.943
   P[84]^c ↑
   F7BSN5 Uncharacterized protein N/A 7.6 59.264 0.51 0.0190 ↓
   F7DU87 Uncharacterized protein BPIFA2 39.8 26.915 0.28 0.0012 ↓
   F7ATL5 Keratin 14 KRT14 8.2 41.036 NP[85]^d ↓
   [86]Open in a new tab
   ^a

   FC, fold change, mean value of peak area obtained from the P group/mean
   value of peak area obtained from the NP group. If the fold-change value
   was >1.5, the relative content of serum proteins in the P group was
   higher that than in the NP group, and if the fold-change value was
   <0.67, the relative content of serum proteins in the P group was less
   than that in the NP group.
   ^b

   coverage (%) = percentage of the protein sequence covered by identified
   peptides.
   ^c

   uniquely expressed serum proteins in the P group.
   ^d

   uniquely expressed serum proteins in the NP group.
   ^e

   “↑” = upregulated serum proteins; “↓” = downregulated serum proteins.

Figure 2.

   [87]Figure 2
   [88]Open in a new tab

   A volcano plot of common proteins identified in the serum of early
   pregnant and non-pregnant jennies. This plot was drawn on the basis of
   the fold change and P-value between the P and NP groups. Red and green
   dots represent upregulated and downregulated common proteins,
   respectively (fold change ≥1.5 and P < 0.05). Gray dots represent
   proteins without any difference.

Bioinformatics Analysis of DEPs

   The 25 DEPs were classified into three distinctive functional sets
   through GO enrichment analysis, namely biological process (BP),
   cellular component (CC), and molecular function (MF) ([89]Figure 3),
   with a corrected statistically significant level (P < 0.05) based on
   Fisher's exact test. The most prevalent BPs were response to stimulus,
   regulation of cellular process, protein metabolic process, and
   proteolysis. The most enriched CCs were extracellular region, vesicle,
   extracellular organelle, and extracellular space, and in the MF
   category, DEPs were mainly involved in binding, enzyme inhibitor
   activity, and enzyme regulator activity.

Figure 3.

   [90]Figure 3
   [91]Open in a new tab

   GO enrichment analyses of DEPs identified in the serum of early
   pregnant and non-pregnant jennies. Most proteins could be divided into
   three major categories: biological process, cellular component, and
   molecular function.

   The 25 DEPs were related to 17 KEGG pathways; the first 10 pathways are
   shown in [92]Figure 4. The prevalent pathways related to DEPs were
   involved in bladder cancer, ovarian steroidogenesis, malaria, p53
   signaling, prolactin signaling, TGF-beta signaling, and GnRH signaling.
   Detailed information on the functional enrichment of DEPs is present in
   [93]Supplementary Table 4.

Figure 4.

   [94]Figure 4
   [95]Open in a new tab

   KEGG pathway enrichment analysis of DEPs identified in the serum of
   early pregnant and non-pregnant jennies.

PPI Analysis

   Color-coded networks were generated to represent different types of
   evidence for the biological crosslink between DEPs. The networks
   contained nine DEPs, and the core factors were fibronectin (FN1),
   fibrinogen-like 1 (FGL1), and thrombospondin 1 (THBS1). These three
   proteins were connected by 2–5 nodes ([96]Figure 5).

Figure 5.

   [97]Figure 5
   [98]Open in a new tab

   Protein–protein interaction network analysis based on DEPs in the P
   group vs. the NP group.

Discussion

   Serum proteins during early pregnancy in jennies have not been
   previously investigated. In this study, we generated proteome profiles
   of the serum obtained from jennies using label-free MS-based
   quantitative proteomics, which led to the identification of 25 DEPs.
   This is the first comprehensive study to explore the potential
   biological significance of DEPs between early pregnant and non-pregnant
   jennies, providing valuable insights into pregnancy-specific serum
   proteins that could be applied for developing pregnancy diagnostic
   markers in early pregnant jennies.

   The label-free MS-based quantitative proteomics method, i.e., spectral
   counting, compares the number of mass spectra assigned to each protein
   ([99]27). It offers several advantages such as high sensitivity,
   real-time measurements, rapid and multiplexed detection, larger
   quantification dynamic range, and improved reproducibility ([100]28),
   as compared with the low identification rate of the 2D gel
   electrophoresis method ([101]27). The label-free MS-based quantitative
   proteomics method has thus emerged as a promising technique for
   quantitative protein profiling of complex biological samples, such as
   serum ([102]29).

   Several proteomics-based studies involving various animal species have
   reported the identification of potential pregnancy-specific serum
   proteins. These studies have mostly used high-resolution 2D gel
   electrophoresis and MS for this purpose ([103]15–[104]17). Four
   differentially expressed serum proteins, namely transferrin, albumin,
   IgG2a heavy chain constant region, and immunoglobulin gamma heavy chain
   variable region, were identified as pregnancy-specific proteins in
   Holstein dairy cattle by 2D gel electrophoresis plus matrix-assisted
   laser desorption/ionization–time of flight (MALDI–TOF) MS ([105]15). In
   another study, 2D fluorescence difference gel electrophoresis plus
   MALDI-TOF MS were used to analyze serum proteins obtained from Holstein
   dairy cattle, which led to the identification of 16 DEPs spots; among
   them, upregulated proteins, such as conglutinin precursor, modified
   bovine fibrinogen, and IgG1, and downregulated proteins, such as
   hemoglobin, complement component 3, bovine fibrinogen, and IgG2a heavy
   chain constant region, were considered as pregnancy-specific proteins
   ([106]16). Further, upon exploration of serum pregnancy-specific
   proteins in Murrah buffaloes, synaptojanin-1, apolipoprotein a-1,
   apolipoprotein b, keratin 10, and von Willebrand factors were
   identified by 2D gel electrophoresis plus MALDI-TOF MS ([107]17). In
   this study, none of the DEPs identified by us using label-free MS-based
   quantitative proteomics have been reported in previous studies,
   indicating interspecific differences.

   So far, some pregnancy-specific proteins, such as pregnancy-specific
   glycoproteins, have been found in trophoblast cells of pregnant mares
   ([108]30); however, to the best of our knowledge, the identification of
   pregnancy-specific serum proteins based on proteomics has not been
   performed in horses. Further studies need to be conducted to reveal
   more biomarkers of early pregnancy and to compare differences among
   different Equus species.

   Herein many DEPs, such as FN1, FGL1, THBS1, granulin
   precursor/acrogranin (GRN), C-X-C motif chemokine, triggering receptor
   expressed on myeloid cells-1 (TREML1), and keratin 14 (KRT14), were
   identified in the serum obtained from early pregnant jennies, and these
   were mainly associated with defense response. FN1 usually exists as a
   dimeric glycoprotein and is a ubiquitous and abundant soluble
   constituent of the plasma and other body fluids; it is also a part of
   the insoluble extracellular matrix ([109]31). This extracellular
   fibronectin niche plays essential roles in wound healing, malignant
   transformation, inflammation, infection, hemostasis, and thrombosis
   ([110]32). FGL1 belongs to the fibrinogen family and is primarily
   secreted from hepatocytes. It is involved in the process of blood
   clotting ([111]33), and a study reported that recombinant human IL-6
   could induce FGL1 expression in Hep G2 cells and that serum FGL1 levels
   were also enhanced after induction of acute inflammation in rats by
   subcutaneous injection of turpentine oil ([112]34). THBS1 interacts
   with a cohort of target molecules through its multifunctional domains
   and participates in normal development and homeostasis maintenance
   ([113]35). It also plays an important role in the regulation of
   coagulation, antiangiogenesis, wound healing, and immune response
   ([114]36). The 6-kDa form of GRN has been invoked in wound repair
   ([115]37). GRN is also a potent inhibitor of the inflammatory cytokine
   tumor necrosis factor-α and regulate inflammation ([116]38). Both C-X-C
   motif chemokine and TREML1 are involved in platelet activation. KRT14,
   encoding a basal cell keratin, is expressed during the wound healing
   process and participates in cell morphogenesis and epidermis
   development ([117]39). Changes in the serum level of these proteins
   indicates the involvement of a regulatory mechanism of defense response
   during early pregnancy.

   The presence of many pregnancy-specific proteins associated with early
   embryonic development have been reported in the serum, other body
   fluids, and tissues of animals. We found that the expression of GRN and
   transgelin-2 (TAGLN2) was unique. GRN is an embryo-derived growth
   factor, which possesses growth regulatory activities principally toward
   epithelial cells. GRN has been reported to regulate the appearance of
   the epithelium in developing mouse blastocysts, growth of the
   trophectoderm, and/or function of the embryonic epithelium ([118]40).
   As a member of the transgelin family, TAGLN2 plays a significant role
   in the regulation of F-actin remodeling, which is important for
   trophoblast cell adhesion and invasion. TAGLN2 may be a potential
   target to improve embryo implantation rates in in vitro fertilization
   ([119]41). Furthermore, the significantly upregulated proteins FN1,
   FGL1, and THBS1 are also seemingly involved in the establishment and
   maintenance of pregnancy. FN1 plays major roles in cell adhesion,
   migration, growth, and differentiation. It also binds to a number of
   biologically important molecules ([120]42). Moreover, it is
   indispensable for embryogenesis; George et al. ([121]43) reported that
   FN1-deficient mice died around embryonic day 10.5 due to severe defects
   in mesoderm. FGL1 is also expressed in the placenta and increases the
   proliferation of trophoblasts through an ERK-dependent pathway
   ([122]44). THBS1 is reportedly involved in the organization of the
   cytoskeleton and in the process of adhesion ([123]45). It has also been
   reported to participate in the adhesiveness of the embryo during the
   peri-implantation period in pigs ([124]46). Considering our findings
   pertaining to the differential expression of GRN, TAGLN2, FN1, FGL1,
   and THBS1 in the serum of early pregnant jennies, which have been
   proved to play an important role in early embryonic development in
   other species, these five proteins seem to be novel, reliable
   candidates to detect pregnancy in jennies.

   Equine chorionic gonadotropin is a pregnancy-specific glycoprotein
   hormone produced by the placenta between day 40 and 150 of pregnancy,
   and it shows FSH- and LH-like biological activities ([125]19). Equids
   possess a single lutropin/choriogonadotropin subunit-β (LHB) gene,
   which confers specificity on the intact hormone ([126]47). In our
   study, LHB was noted to be uniquely expressed in the serum of pregnant
   jennies and was probably involved in ovarian steroidogenesis and
   prolactin signaling and GnRH signaling pathways, according to the KEGG
   pathway-based enrichment analysis. LHB has been identified as a marker
   of pregnancy in jennies, although it shows considerably lower FSH-like
   activity than horse LHB ([127]47).

Conclusion

   To summarize, this is the first study to report a comprehensive
   analysis of DEPs in the serum of early pregnant and non-pregnant
   jennies using label-free MS-based quantitative proteomics. Twenty-two
   upregulated and three downregulated proteins were significantly
   differentially expressed in the P group, and these were mainly
   associated with the defense response, early embryonic development, and
   hormone signaling pathways. The differences in the expression profiles
   helped identify candidate proteins to explore pregnancy diagnostic
   markers related to early pregnancy in jennies. Five serum proteins—GRN,
   TAGLN2, FN1, FGL1, and THBS1—appear to be novel, reliable candidates to
   detect pregnancy in jennies. Further studies should be conducted to
   elucidate their functions in jennies.

Data Availability Statement

   The datasets presented in this study can be found in online
   repositories. The names of the repository/repositories and accession
   number(s) can be found in the article/[128]Supplementary Material.

Ethics Statement

   The animal study was reviewed and approved by Shenyang Agricultural
   University Animal Care and Use Committee.

Author Contributions

   LD performed the experiments. YH and CT participated in data analysis.
   CT, QL, and ZL helped with sampling. LD and YH edited the manuscript.
   All authors read and approved the final manuscript.

Conflict of Interest

   The authors declare that the research was conducted in the absence of
   any commercial or financial relationships that could be construed as a
   potential conflict of interest.

Footnotes

   Funding. This study was supported by the National Natural Science
   Foundation, China (Grant no. 31501952) and the Foundation from the
   Department of Education of Liaoning Province, China (Grant no.
   LSNFW201904).

Supplementary Material

   The Supplementary Material for this article can be found online at:
   [129]https://www.frontiersin.org/articles/10.3389/fvets.2020.569587/ful
   l#supplementary-material
   [130]Click here for additional data file.^ (58.9KB, xlsx)
   [131]Click here for additional data file.^ (489.7KB, xlsx)
   [132]Click here for additional data file.^ (16KB, xlsx)
   [133]Click here for additional data file.^ (35.3KB, xlsx)
   [134]Click here for additional data file.^ (658.2KB, docx)

References