Transcriptome Analysis of Intestinal Dysfunction in Newborn Piglets with Intrauterine Growth Restriction and Improve their Performance by Dimethylglycine Sodium Salt Supplementation after Weaning

Kaiwen Bai Nanjing Agricultural University Weigang Campus: Nanjing Agricultural University Luyi Jiang Zhejiang University Zijingang Campus: Zhejiang University Qiming Li Nanjing Agricultural University Weigang Campus: Nanjing Agricultural University Jingfei Zhang Nanjing Agricultural University Weigang Campus: Nanjing Agricultural University Lili Zhang Nanjing Agricultural University Weigang Campus: Nanjing Agricultural University Tian Wang (  tianwangnjau@163.com ) Nanjing Agricultural University https://orcid.org/0000-0002-9038-5009

piglets were allowed to suckle the sow naturally up to 21 days of weaning age and then randomly allocated to three treatments with ten replicates per treatment: N = NBW weaned piglets fed with common basal diets (Table S1); I = IUGR weaned piglets fed with common basal diets; ID = IUGR weaned piglets fed with common basal diets plus 0.1% DMG-Na (DMG-Na was obtained from Qilu Sheng Hua Pharmaceutical Co., Ltd., Shandong, China). All procedures were approved by the Institutional Animal Care and Use Committee of Nanjing Agricultural University, China. Piglets were housed individually in plastic oored pens (1 m × 0.6 m) at an ambient temperature of 28 °C in an environmentally controlled room and had free access to water. At 49 days of age, the piglets were weighed after feed deprivation for 12 h to calculate average daily weight gain (ADG), and feed consumption was recorded by using replicates to calculate average daily feed intake (ADFI) and feed conversion ratio (G:F). Then, blood and jejunum samples were obtained and stored at -80 °C for further study.

Construction of mRNA library and bioinformatic analysis
Total RNA was isolated from the jejunum samples using Trizol (Invitrogen, Carlsbad, CA, USA) according to manual instruction [13]. The double-stranded and single-stranded DNA in total RNA was removed by DNase I digesting, and RNase H or Ribo-Zero method (Illumina, USA) was used to remove the rRNA, and then puri ed mRNA was fragmented into small pieces with fragment buffer. The rst-strand and secondstrand cDNA was generated in First-Strand Reaction System by PCR. The reaction product was puri ed by magnetic beads, afterwards, A-Tailing Mix and RNA Index Adapters were added by incubating to carry out end repair. The cDNA fragments with adapters were ampli ed by PCR, and the products were puri ed by Ampure XP Beads. The library was validating on the Agilent Technologies 2100 bioanalyzer for quality control. The double-stranded PCR products above were heated denatured and circularized by the splint oligo sequence. The single-strand circle DNA (ssCir DNA) was formatted as the nal library. The nal library was ampli ed with phi29 (Thermo Fisher Scienti c, MA, USA) to make DNA nanoball (DNB) which had more than 300 copies of one molecular, DNBs were loaded into the patterned nanoarray and single end 50 bases reads were generated on BGISEQ500 platform (BGI-Shenzhen, China).
The sequencing data was ltered with SOAPnuke (v1.5.2) by removing reads of sequencing adapter, reads of low-quality base ratio more than 20%, reads of unknown base ('N' base) ratio more than 5%, afterward clean reads were stored in FASTQ format. The clean reads were mapped to the Sus_scrofa (NCBI_GCF_000003025.6_Sscrofa11.1) using HISAT2 (v2.0.4). Bowtie2 (v2.2.5) was applied to align the clean reads to the Sscrofa11.1, then the expression level of genes was calculated by RSEM (v1.2.12). The heatmap was drawn by pheatmap (v1.0.8) according to the gene expression in different samples. Essentially, differential expression analysis was performed using the DESeq2 (v1.4.5) with a q value lower than 0.05. To take an insight into the change of phenotype, Gene Ontology (GO) (http://geneontology.org/) and Kyoto Encyclopedia of Genes (KEGG) (https://www.kegg.jp/) enrichment analysis of annotated different expressed gene was performed by Phyper (https://en.wikipedia.org/wiki/Hypergeometric_distribution.) based on Hypergeometric test. The signi cant levels of terms and pathways using the corrected P-value < 0.05 as a threshold to nd signi cantly enriched KEGG terms in the input list of differential expression genes, comparing them to the whole genome background. The calculation formula of the P-value was as follows: N represented the number of KEGG annotated genes in jejunum samples, n represented the number of differentially expressed genes in N, M represented the number of particular KEGG annotated genes in a genome, and m represented the number of particular KEGG annotated genes expressed differentially in M. After correction for multiple testing, we chose pathways with a P-value < 0.05 to represent those signi cantly enriched in different expression genes.
Weighted gene co-expression network analysis (WGCNA) The WGCNA R package [14] was used in order to assess the relationships between clusters of coexpressed genes and phenotypes related to IUGR. At rst, the network was constructed grouping the functionally correlated genes into modules based on the pairwise correlations, corresponding to their similar gene expression level. To construct the network of co-expressed genes and to cluster genes that exhibit similar expression patterns, the WGCNA package built an adjacency matrix in which the nodes of the network correspond to gene expression pro les, and edges between genes are determined by the pairwise correlations between gene expressions, calculated using the Pearson's correlation. First, it was necessary to nd an optimal soft-thresholding power to transform the co-expression similarity into adjacency. Thus, after performing the analysis of network topology for several soft-thresholding parameters, power 12 was chosen as the soft-thresholding power to reach a scale-free topology index. Then, the gene network was constructed using the blockwiseModules function, and modules of coexpressed genes were detected by using hierarchical clustering. In the blockwiseModules function, we have chosen 30 for the minimum module size. Once identi ed groups of genes characterized by a similar trend of expression pro le, it was necessary to detect modules that were most signi cantly related to the measured traits of interest. In this regard, the association values between modules and traits were quanti ed using Pearson's correlation. In particular, to identify the module-trait relationship, the WGCNA package determined the expression value of each module using the principal component analysis. Indeed, the ME can be considered representative for the gene expression pro le of the corresponding module. This approach allowed us to calculate Pearson's correlations between each module eigengene and trait, and thus to identify the module-trait relationship. The most signi cantly correlated with the macro-trait (P < 0.01) were characterized by an absolute value of module-trait correlation higher than 0.8. Differential expression analysis was performed using the DEGseq, q value≤ 0.01, and the absolute value of Log2Ratio ≥ 1 as the default threshold to judge the signi cance of expression difference. To annotate gene functions, all target genes were aligned against the GO and KEGG database. GO enrichment analysis and KEGG enrichment analysis of target genes were performed using phyper [15], a function of R. The P-value was corrected using the Bonferroni method, and a corrected P-value ≤ 0.05 was taken as a threshold. GO terms or KEGG terms ful lling this condition were de ned as signi cantly enriched terms.

Histological study
Jejunum samples were xed in 1% (v/v) glutaraldehyde solution and stored in the same solution at 48 °C until processed. After post xation for 5 min in 2% (w/v) osmium tetroxide, samples were processed conventionally for transmission electron microscopy visualization and examined in a Philips 420 transmission electron microscope at 80 kV [2].
Jejunum samples xed in 4% buffered formaldehyde were dried up using a graded series of xylene and ethanol, after which they were embedded in para n for histological processing. The samples (8 microns in size) were then depara nized using xylene and rehydrated with graded dilutions of ethanol. The slides were stained with hematoxylin-eosin (HE). Ten slides for each sample (middle site of samples) were prepared, and the images were acquired using an optical binocular microscope. Values of villus length (L), crypt depth, and villus width (W) were measured ve times from different villus and crypts per slide [2]. Villus area (S) was calculated using the following formula: Jejunum samples were homogenized in 0.9% sodium chloride buffer on ice and then centrifuged at 2,800 × g at 4 °C for 15 min. The supernatant was used to measure the sIgA concentration with an ELISA assay kit (Nanjing Jiancheng Bioengineering Institute, Nanjing, Jiangsu, China) according to the method described by Hu et al [17].

Digestive enzyme activity
Jejunum samples were homogenized in 0.9% sodium chloride buffer on ice and then centrifuged at 2,800 × g at 4 °C for 15 min. The supernatant was used to measure the jejunum sucrase, maltase, and lactase level with corresponding assay kits (Nanjing Jiancheng Bioengineering Institute, Nanjing, Jiangsu, China).
Jejunum samples were homogenized in 0.9% sodium chloride buffer on ice and then centrifuged at 2,500 × g at 4 °C for 10 min. The supernatant was used to measure the intestinal amylase, lipase, and chymotrypsin level with corresponding assay kits (Nanjing Jiancheng Bioengineering Institute, Nanjing, Jiangsu, China).

Quantitative real-time PCR
Quantitative real-time PCR (qPCR) was performed as described by Mohamed et al. [13]. Total RNA was obtained from jejunum samples using Trizol Reagent (TaKaRa, Dalian, China) and then reversetranscribed using a commercial kit (Perfect Real Time, SYBR @ PrimeScript TM , TaKaRa) following the instructions of the manufacturer. The mRNA expression levels of speci c genes were quanti ed via realtime PCR, using SYBR @ Premix Ex Taq TM II (Tli RNaseH Plus) and an ABI 7300 Fast Real-Time PCR detection system (Applied Biosystems, Foster City, CA). The SYBR Green PCR reaction mixture consisted of 10 μL SYBR @ Premix Ex Taq (2X), 0.4 μl of the forward and reverse primers, 0.4 μL of ROX reference dye (50X), 6.8 μL of ddH 2 O, and 2 μL of cDNA template. Each sample was ampli ed in triplicate. The foldexpression of each gene was calculated according to the 2 -ΔΔCt method [13], in which the β -actin gene was used as an internal standard. The primer sequences used are given in Table S2.

Western blotting
Antibodies against related proteins were purchased from Cell Signaling Technology (Danvers, MA, USA). The protein content of samples was measured using the BCA Protein Assay Kit (Beyotime, Jiangsu, China). For western blotting analysis, 50 μg of protein from each jejunum sample was analyzed through sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). After SDS-PAGE, proteins were separated and transferred to polyvinylidene di uoride membranes. Membranes were blocked with blocking buffer (5% nonfat dry milk) for 12 h at 4 °C. Membranes were probed with appropriate primary and secondary antibodies (horseradish peroxidase-conjugated goat antirabbit immunoglobulin G, Cell Signaling Technology; 1:10,000 dilution in 1% milk). Blots were detected using enhanced chemiluminescence reagents (ECL-Kit, Beyotime, Jiangsu, China) followed by autoradiography. Photographs of membranes were taken using the Luminescent Image Analyzer LAS-4000 system (Fuji lm Co.) and quanti ed with ImageJ 1.42q software (NIH, Bethesda, MD, USA).

Statistical Analysis
Data are presented as the Mean ± SEM and were statistically analyzed by one-way analysis of variance (ANOVA) procedure of Statistical Analysis System (version 9.1; SAS Institute, Inc., Cary, Nc, USA). This was followed by Tukey's test when signi cant differences were found (P < 0.05). The signi cance was de ned as P < 0.05.

Results
In order to identify gene differentiation of jejunum between NBW newborn piglets and IUGR newborn piglets, NBW group (NBW1, NBW2, NBW3) and IUGR group (IUGR1, IUGR2, IUGR3) were constructed with total RNA and subjected to Illumina deep sequencing. Overviews of the sequencing and assembly results were shown in Table S3. After discarding the low-quality of raw reads, 276,210,270 clean reads remained. All the 19.935 assembled genes were referenced against Swiss-Prot, Nr, Pfam, KEGG, KOG, and GO databases, with the number of genes 12.630 (63.36%), 18.172 (91.16%), 16.602 (83.28%), 6.314 (31.67%), 10.976 (55.06%), and 7.487 (37.56%), respectively (Table S4). To explore the molecular mechanisms of jejunum in response to IUGR, RPKM method analysis was performed to determine the differential expression genes. We found that 14 mRNAs were up-regulated (P < 0.05), while 25 genes were down-regulated (P < 0.05) in response to IUGR (Table S5). We then made a hierarchical clustering of the different expression genes based on the six samples' log10 (RPKM + 1), with the results indicating that the samples could be sorted into two distinct groups (Fig. 1A). Overall, undergoing IUGR had a signi cant impact on the global gene expression pro le of jejunum in newborn piglets.
According to the GO classi cation system, genes involved in the "cellular process" (25 genes) and "metabolic process" (21 genes) were notably represented in the biological process category. Among the cellular components, "cell" (21 genes) was the most commonly represented, followed by "cell part" (21 genes) and "organelle" (15 genes). In the category of molecular function, a signi cant proportion of clusters were assigned to "binding" (21 genes) and "catalytic activity" (15 genes) (Fig S1). To classify orthologous gene products, the different expression genes were subdivided into 25 KOG classi cations.
By performing the KEGG pathway analyses, a total of 15 pathways that changed signi cantly (P < 0.05) in the IUGR newborn piglets in comparison to the NBW newborn piglets were identi ed (Fig. 1B). Among these pathways, "Bile secretion", "Pancreatic secretion", and "Salivary secretion" are included in the "Digestive system" sub-class. "Regulation of lipolysis in adipocytes" and "PPAR signaling pathway" are included in the "Endocrine system" sub-class. In addition, some important subclasses have also been signi cantly enriched, including "Signal transduction", "Nervous system", "Metabolism of cofactors and vitamins", "Substance dependence", "Membrane transport", "Nervous system", "Immune system", "Folding, sorting and degradation", "Environmental adaptation", and "Endocrine system". These results imply that the genes involved in these pathways may play crucial roles in newborn piglets' jejunum in response to IUGR.
As a result of network construction, the WGCNA analysis found 9 modules (power = 12) (Fig S4), identi ed by a different color. The 1159 gene modules identi ed by WGCNA are shown by cluster dendrogram (Fig S5), in which the branches correspond to modules and each leaf in the branch represents one probe. The WGCNA R package allowed us to quantify correlation values between the genes of each module and the considered phenotypes, assessing in this way the module-trait association. In this regard, Fig. 1C shows the associations between modules and traits using a heatmap plot, which graphically represents Pearson's correlation coe cients measured between every single module and trait (Table S6). From the data, the module yellow (P = 0.05, r = 0.81) exerted the most signi cantly correlated with the trait, which includes 254 genes. According to the GO classi cation system, 254 genes of the module yellow involved in "cellular process" (65 genes) and "single-organism process" (57 genes) were notably represented in the biological process category. Among the cellular components, "cell" (71 genes) and "cell part" (71 genes) were the most commonly represented, followed by "organelle" (50 genes). In the category of molecular function, a signi cant proportion of clusters were assigned to "binding" (73 genes) and "catalytic activity" (39 genes) (Fig S6). The KEGG classi cation was found for the 254 genes of MEyellow module that were further classi ed into 4 biochemical pathways ( Fig S7). Cellular Processes (25 genes), Environmental Information Processing (59 genes), Human Diseases (58 genes), and Organismal Systems (118 genes), respectively. A total of 13 hub genes was obtained from co-analysis of RNA-seq and WGCNA (Table S7).
Effects of DMG-Na on the growth performance of IUGR weaned piglets were shown in Table 1. Compared with N group, I group showed lower (P < 0.05) ADG, ADFI, IBW, and FBW values. The ADG, G:F, and FBW values of ID group were improved (P < 0.05) compared to that of I group. Effects of DMG-Na on jejunum villi, microvilli, and its structure of IUGR weaned piglets were revealed in Fig. 2. Compared with N group, jejunum villi of I group are more susceptible to oxidative damage, shorter, and with different lengths. Jejunum microvilli of I group were shorter and less frequent than those of N group. In addition, autophagosomes and mitochondrial swelling were observed in I group, and these features were not found in N group ( Fig. 2A). The jejunum villi, internal microvilli, and internal structure of ID group were improved compared to those of I group ( Fig. 2A). Histological morphology (villus length, crypt depth, villus width, and villus area) of jejunum deteriorated (P < 0.05) in I group compared to that in N group (Fig. 2B and Table 2). The ID group showed improvement (P < 0.05) in the histological morphology of their jejunum compared to that in I group (Fig. 2B, Table 2). Effects of DMG-Na on serum immunoglobulin and jejunum sIgA level of IUGR weaned piglets were observed in Table 3. Compared with N group, I group showed a decrease (P < 0.05) in serum IgA, IgG, and IgM, and jejunum sIgA levels. Serum IgA, IgG, and IgM, and jejunum sIgA levels of ID group were all improved (P < 0.05) compared to those in I group. Table 3 Effects of DMG-Na on serum immunoglobulin and jejunum sIgA level of IUGR weaned piglets 1  Table 4 Effects of DMG-Na on jejunum digestive enzyme activity of IUGR weaned piglets 1 Effects of DMG-Na on the redox status, such as SOD, GSH-Px, GSH, GR, CAT, and MDA, of serum and jejunum in IUGR weaned piglets were presented in Table 5 and Table 6. I group showed a lower (P < 0.05) antioxidant capacity and higher (P < 0.05) MDA concentration in serum and jejunum with respect to the values for these in N group. The ID group showed an increased (P < 0.05) antioxidant capacity and decreased (P < 0.05) MDA content in serum and jejunum compared to that in I group.  Effects of DMG-Na on jejunum mitochondrial MnSOD, GPx, GSH, GR, and γ-GCL activity of IUGR weaned piglets were shown in Table 7. It was indicated that I group showed a lower (P < 0.05) level of jejunum mitochondrial MnSOD, GPx, GSH, GR, and γ-GCL with respect to their levels in N group. Compared to I group, ID group showed higher (P < 0.05) levels of jejunum mitochondrial MnSOD, GPx, GSH, GR, and γ-GCL.   Effects of DMG-Na on jejunum redox status-related protein content (Nrf2, HO1, SOD, GSH-Px, Sirt1, and PGC1α) and mitochondrial function-related protein content (Cyt C, ERRα, mtTFA, NRF1, Mfn2, Drp1, and Fis1) of IUGR weaned piglets were presented in Fig. 5. Compared to N group, I group showed a lower (P < 0.05) level of SOD, GSH-Px, Sirt1, Cyt C, ERRα, mtTFA, NRF1, Mfn2, Drp1, and Fis1, along with a higher (P < 0.05) level of Nrf2, HO1, and PGC1α. The ID group presented a higher (P < 0.05) level of SOD, GSH-Px, Sirt1, Cyt C, ERRα, mtTFA, NRF1, Mfn2, Drp1, and Fis1, and lower (P < 0.05) level of Nrf2, HO1, and PGC1α compared to those in I group.
Discussion IUGR has received more attention from animal husbandry for its irreversible oxidative damage, delayed postnatal growth, and intestinal health [1,12,27]. Several studies used IUGR weaned piglets as a model to exhibit its poor performance [28,29], and these outcomes agree with our results, which demonstrate that the IUGR group exerts lower growth performance compared to the NBW group. As expected, supplemented with DMG-Na could improve the growth performance of IUGR weaned piglets, which might be explained based on its high radicals scavenging capacity and bene ts on intestinal health [30].
However, the effects of DMG-Na on improving the growth performance of IUGR weaned piglets remain to be further studied.
The small intestine is crucial in nutrient digestion, absorption, and metabolism. IUGR leads to intestinal diseases in the perinatal period and makes individuals prone to feeding intolerance and digestive diseases in the early postnatal period [31]. The movement of substances across the cell membrane depends on diffusion or active transport that is regulated by intestinal structure [32]. From the RNA-seq and WGCNA analysis in this work, we found ATP8 was the most signi cantly changed gene in jejunum between NBW and IUGR group that involved in maintaining mitochondrial function [33]. Thus, we hypothesis that the jejunum dysfunction in IUGR piglets might be related to the alteration of its mitochondrial function. Consistent with our results, studies indicated that IUGR leads to intestinal villus atrophy, mucosal oxidative damage, and intestinal dysfunction, thereby causing diarrhea and reduction of feed utilization in piglets [34,35]. This study also showed that autophagosomes and mitochondrial swelling appeared in the small intestine of the IUGR group, which may relate to their malnutrition in the uterus and is likely to be alleviated by replenishment of acquired nutrients [36]. A previous study suggested that DMG-Na acted as an antioxidant, protecting the small intestine from oxidative damage, maintaining its normal histological morphology [37]. Another study found that DMG-Na exerted a positive effect on cell protection from oxidative damage [38], and this might be one possible reason for the results seen in the histological analysis.
IUGR is a serious complication of the mammalian fetus during pregnancy, which limits fetal development and impair their immune function during the perinatal period. IgA, IgG, and IgM levels in the body are important because these re ect the immune status and their capacity of ghting against various infections. The IgA could turn to sIgA in cell gaps with secreted fragments produced by epithelial cells and then bind to the corresponding antigen in order to protect the intestine from oxidative damage [39]. It has been suggested that IUGR can damage the small intestine in piglets and lead to abnormalities in intestinal morphology and immune function [40]. DMG-Na increases serum immunoglobulin levels through its immunomodulatory function, which might represent one possible explanation for the results in this study [11].
Small intestinal digestive enzymes, cytokines, and immunoglobulins are related to its growth and immune function and have a role to prevent bacterial invasion. Consistent with our results, studies suggested that intestinal growth of IUGR weaned piglets is blocked, causing digestive enzyme secretion abnormalities, which may closely relate to intestinal epithelial cell apoptosis and proliferation imbalance and would lead to seriously affect the digestion and utilization of diets [41,42]. After adding 0.1% DMG-Na to the diet, results suggested that DMG-Na may improve the digestion and absorption of nutrients in the IUGR group because of its capacity of protecting the intestine from oxidative damage.
Oxidative damage could enhance the ROS level, decrease antioxidant capacity, and destroy the mitochondrial structure. Mitochondrial swelling of the IUGR group in the current study suggest a destroyed redox status of the small intestine [43]. Oxidative damage could be improved by the SOD enzyme, which catalyzes the conversion of endogenous superoxide anions to hydrogen peroxide through disproportionation, and nally neutralized by intracellular enzyme GSH-Px [44]. Meanwhile, MnSOD enzyme, GSH-related metabolic enzymes, and γ-GCL enzyme are crucial in suppressing oxidative damage in mitochondria [45,46]. A previous study found that DMG-Na could act as an antioxidant additive to improve body antioxidant capacity [30,37]. After adding 0.1% DMG-Na to the diet, these results suggested that DMG-Na could improve the antioxidant capacity through scavenging ROS generated excessively, so as to maintain the balance of the intracellular redox status.
The ROS level in cells maintains a dynamic balance with the antioxidant system. However, this balance will be disturbed if subjected to some environmentally-induced conditions, nally resulting in oxidative damage [47]. Excessive ROS could induce mitochondria and DNA structural damage, ultimately affecting antioxidant capacity [48,49]. IUGR is closely related to oxidative damage, mitochondrial dysfunction, high ROS level, and even the occurrence of metabolic syndrome [50]. From the RNA-seq and WGCNA analysis in this study, we found ATP8 was the most signi cantly changed gene in jejunum between NBW and IUGR group that involved in ROS generation [33]. It has been suggested that excessive ROS induces mitochondrial DNA (mtDNA) damage, whereas impaired mitochondrial function and produces more endogenous ROS [51]. The MMP level, negatively associated with ROS concentration, acts as an indicator of the beginning of mitochondria-dependent apoptosis [52]. Consistent with our results, a study indicated that IUGR reduces antioxidant enzyme activity and mtDNA level of weaned piglets [53]. Another study also found that IUGR piglets have reduced antioxidant capacity and are prone to suffer from oxidative damage [54,55]. It can be seen from the results that the reduction of antioxidant capacity in the IUGR group leads to impaired intestinal function. These results also suggested that DMG-Na could relieve oxidative damage due to the scavenging of excessive ROS, and different studies veri ed that natural antioxidants could protect cells from oxidative damage [37,56].
Activation of Nrf2 and HO1 is important in relieving oxidative damage by regulating antioxidant gene expression (SDO, GSH-Px, γ-GCL) [57,58]. Mitochondria are rich in Trx2, Trx-R2, and Prx3 proteins, which act together to prevent oxidative damage by scavenging free radicals and regulating mitochondria-dependent apoptotic pathways [59]. PGC1α is a coactivator with pleiotropic functions, which could regulate mitochondrial function gene expression (COX1, Cyt C, ERRα, MHC1, mtTFA, Ndufa2, NRF1, NRF2, UCP1, (mtDNA replication and repair (POLG1, POLG2, SSBP1) and mitochondrial ssion (Drp1, Fis1) and fusion (Mfn2)), as it induces mitochondrial genes both at the level of the nuclear and In conclusion, the present study demonstrated that DMG-Na could effectively improve small intestinal damage of IUGR weaned piglets. We speculated that DMG-Na could directly neutralize excessive free radicals, and indirectly improve redox status and inhibit abnormal expression of stress-related factors via the SIRT1/PGC1α network. Therefore, this suggests that DMG-Na can serve as a health-promoting substance and could be used in the eld of IUGR weaned piglets disorder prevention. Availability of data and materials The datasets produced and/or analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests
No potential con icts of interest relevant to this article were reported.  The RNA-seq analysis of jejunum of NBW and IUGR newborn piglets. The hierarchical clustering of the different expression genes from the RNA-seq analysis (n=3) (A), the KEGG pathway analyses (n=3) (B), the heatmap plot between modules and traits by WGCNA analysis (n=3) (C) of jejunum in NBW and IUGR newborn piglets. NBW, normal birth weight; IUGR, intrauterine growth retardation.

Figure 2
Effects of DMG-Na on jejunum histological morphology and its sub-organelle ultrastructure of IUGR weaned piglets. Jejunum mitochondrial swelling and microvilli (A). Scale bars represent 1 μm; Jejunum histological morphology (villus length, crypt depth, villus width, and villus area) (B). Scale bars represent 100 μm. N, NBW weaned piglets fed with common basal diets; I, IUGR weaned piglets fed with common basal diets; ID, IUGR weaned piglets fed with common basal diets plus 0.1% DMG-Na; NBW, normal birth weight; IUGR, intrauterine growth retardation. Effects of DMG-Na on jejunum redox status-related and mitochondrial function-related protein content of IUGR weaned piglets. Values are expressed as Mean ± SEM, n = 10. Values with different superscripts were signi cantly different (P < 0.05). The assays were conducted in triplicate. N, NBW weaned piglets fed with common basal diets; I, IUGR weaned piglets fed with common basal diets; ID, IUGR weaned piglets fed with common basal diets plus 0.1% DMG-Na; NBW, normal birth weight; IUGR, intrauterine