Experiments were performed using pigs from two different populations: Tibetan pigs living in highlands (Linzhi, 3,000 m, TP), Yorkshire pigs that migrated from lowland (Beijing, 100 m) to highland (Linzhi, 3,000 m, YP) about 3 yr ago. TP and YP used were respectively raised in the Tibet Agricultural and Animal Husbandry University Farm (Linzhi, 3,000 m) and Tibet Linzhi ga ma breeding co. Ltd (Linzhi, 3,000 m), ten boars (1.5 years old, normal fertility and nutrition level) from each population were used in this study.
Semen collection and quality analysis
Twenty fresh semen samples, one per boar were respectively obtained from 10 TP and 10 YP by using the gloved-hand technique. After semen collection, there was no adverse effect noted on the health and growth of the pigs. Sperm quality were meautured by sperm motility parameters and ROS levels. Computer-assisted semen analysis (CASA) system (Hamilton Thorne Research, Beverly, MA, USA) was used to measure the sperm concentration, motility, VAP, and abnormality rate according to the manufacturer's instructions. In short, put the semen to incubation at 37 ℃ for 10 min, then 3 μL semen was dropped into the preheated (37 ℃) Makler sperm count board, sperm motility, etc. were assessed by using CASA system. Look at at least 3 visual fields to get the average. According to the manufacturer's protocol of ROS assay kit (S0033M, Shanghai Beyotime Biotechnology Co. Ltd, Shanghai, China), sperm ROS level was evaluated by using the probe 2′, 7′-dichlorodi-hydrofluorescein diacetate (DCFH-DA). Breifly, the semen samples were washed with PBS three times, resuspended and incubated with 10 μM DCFH-DA at 37 °C in the dark for 25 min. For intracellular DCFH-DA was deesterified to dichlorodihydrofluorescein which is oxidized by ROS to produce dichlorofluorescein with strong fluorescence, the fluorescence intensity could be conveniently monitored using a fluorescent microplate reader (Biotek Synergy, SynergyH4,USA) at an excitation wavelength of 488 nm and at an emission wavelength of 525 nm.
To remove seminal plasma and contamination (e.g., extender components and somatic cells such as leukocytes and testicular cells), semen samples were centrifuged at 500 × g for 20 min with a discontinuous (70% [v/v] and 35% [v/v]) Percoll gradient (Sigma, St Louis, MO, USA), and then the sperm pellets were washed 3 times with cold phosphate-buffered saline (PBS). For protein extraction, each sperm sample (3 × 108 spermatozoa) was resuspended in lysis buffer (8 M urea, 4% CHAPS, 50 mM DTT and protease inhibitor, pH 8.0) at 4°C. The lysates were centrifuged at 10,000 g for 30 min to remove insoluble material, and the supernatants were collected for further analysis. The protein content was measured with the Bradford protein assay kit (P0006C, Beyotime Institute of Biotechnology, Nanjing, China).
Protein labeling and LC-MS/MS
The proteins of the sperm samples and then digested using the filter-assisted sample preparation (FASP) as previously described . The resulting TP and YP peptides were labeled 116 (TP1), 121 (TP2), 113 (YP1) and 119 (YP2), according to the instructions supplied with the iTRAQ® Reagent-8PLEX Multiplex Kit (4381663, AB SCIEX, USA). The labeled samples were then loaded onto a high-pH reverse-phase liquid chromatography (RPLC) XBridge C18 column (Waters, Milford, MA, USA) connected to a liquid chromatography system (e2695, Waters, Milford, MA, USA). The column was eluted with a 51 min gradient of 0 ~ 5% buffer B (98% acetonitrile, pH 10.0) for 5 min, 5 ~ 35% buffer B for 45 min, and 35 ~ 50% buffer B for 10 min at a flow rate of 1 mL/min. The fractionated peptides were analyzed by LC-MS/MS using a nano-LC (Easy nLC 1000, Thermo Fisher Scientific, Odense, Demark) in tandem with an LTQ-Orbitrap Elite mass spectrometer (Thermo Fisher Scientific, Bremen, Germany). MS/MS scans in the range from m/z 350 to 1800 were recorded with a mass resolution of 70,000 at m/z 400. The LC-MS/MS data were acquired in a data-dependent mode, in which the ten most intense precursor ions were isolated and fragmented by collision-induced dissociation (CID) with 32% normalized collision energy. Dynamic exclusion was enabled (exclusion list size: 500, exclusion duration: 40 s).
Database search and bioinformatics
The MS/MS data were searched against the NCBI Sus_refesq_20180716.fasta (63,695 sequences) Fasta database for peptide identification and quantification using Mascot 2.5.1 and Proteome Discoverer 1.4 (Thermo). The search parameters were specified as follows: one missed enzymatic cleavage site was allowed, the mass tolerance was set at 10 ppm for precursor ions and ± 0.05 Da for fragment ions, carbamidomethylation was set as a fixed modification, oxidation and iTRAQ-4plex were set as variable modifications. The false-positive detection rate (FDR) was calculated using a decoy database search, with FDR < 1.0%, identifying each protein to at least 1 specific polypeptide, normalized by the median of the data. We compared the expression levels of all identified proteins between the TP and the YP groups to identify the proteins involved in reproduction traits in boars on plateaus. The Student’s t-test was used to compare differences in protein expression between the TP and YP groups and to calculate p values. p < 0.05 and a fold change ≥1.5 or ≤ 0.67 were set as the threshold to identify differentially expressed proteins (DEPs). The average of six labeled sample mixtures was used as reference (ref) based on the weighted average of the intensity of reported ions in each identified peptide. The final ratios of proteins were normalized according to the median average protein ratio for the mixtures of different labeled samples (TP1/ref, TP2/ref, YP1/ref, and YP2/ref).
The DEP data were analyzed using bioinformatics, while the UniProt IDs of the DEPs were converted to mouse UniProt IDs due to the small number of studies on gene function in pigs. Gene ontology (GO) annotation and enrichment of DEPs were analyzed using the GO consortium database for GO assignment (http://geneontology.org/). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein-protein interaction (PPI) analyses were performed using STRING online software (https://string-db.org/). The results of the GO analysis were mapped into a senior bubble map using the OmicShare tool, a free online platform for data analysis (http://www.omicshare.com/tools), which was also used to map the volcano figure and heatmap using the OmicShare tool. PPI networks were visualized and analyzed using Cytoscape 3.2.1 software .
Validation of DEPs by western blot
Cofilin-1 (CFL1), pro-epidermal growth factor (EGF), fibronectin 1 (FN1), and glutathione peroxidase 4 (GPX4) expression levels were determined by western blot analysis, using beta actin (β-actin) as a loading control. The bar line charts were created using Sigmaplot 10.0 (Systat Software, San Jose, CA, USA). In brief, denatured sperm proteins (30 µg) from TP and YP were separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE, 4% stacking gel and 12% separating gel) and transferred to polyvinylidene fluoride (PVDF) membranes using a Hoefer TE22 blotting instrument (Hoefer, Holliston, MA, USA). The membranes were blocked overnight in blocking buffer (P0071, Shanghai Beyotime Biotechnology Co. Ltd, Shanghai, China), incubated with the appropriate primary antibody (1:1000, ab42824, ab231103, ab32419, ab231174 or ab8227, Abcam, Cambridge, UK) and gently shaken at room temperature for 2 h. After three washes with phosphate-buffered saline containing 0.1% Tween 20 (PBST), the membranes were incubated with the appropriate secondary antibody (1:1000, A0208, Beyotime Ltd., Shanghai, China) for 1 h. After three washes in Tris-buffered saline with Tween 20 for 30 min, the immune complexes on the membranes were visualized using BeyoECL Plus (P0018S, A0216, Beyotime Ltd., Shanghai, China) following the manufacturer’s instructions. To determine the expression levels of CFL1, EGF, FN1 and GPX4 relative to β-actin, the gray value of the bands was analyzed using ImageJ 1.44 (NIH, Bethesda, MA, USA).
Statistical analyses were performed using IBM SPSS Statistics v17.0 (SPSS Inc. Released 2008. SPSS Statistics for Windows, Version 17.0. Chicago: SPSS Inc.). Graphs were prepared using SigmaPlot 10.0 (Systat Software, San Jose, CA, USA). One-way analysis of variance (ANOVA) was used to determine the significance of differences between the two groups. All quantitative data are presented as the mean ± standard deviation (S.D.). We considered P < 0.05 (*) as statistically significant and P < 0.01 (**) as extremely statistically significant.