Skip to main content
NCBI home page
Journal of Animal Science logoLink to Journal of Animal Science
. 2023 Jun 27;101:skad218. doi: 10.1093/jas/skad218

Lnc-TRTMFS promotes milk fat synthesis via the miR-132x/RAI14/mTOR pathway in BMECs

Hongru Jia 1,1, Zhangqing Wu 2,1, Jianbing Tan 3, Silin Wu 4, Chaoqun Yang 5, Sayed Haidar Abbas Raza 6, Meng Wang 7, Guibing Song 8, Yujie Shi 9, Linsen Zan 10, Wucai Yang 11,✉
PMCID: PMC10414145  PMID: 37367933

Abstract

As an important index to evaluate the quality of milk, milk fat content directly determines the nutrition and flavor of milk. Recently, growing evidence has suggested that long noncoding RNAs (lncRNAs) play important roles in bovine lactation, but little is known about the roles of lncRNAs in milk fat synthesis, particularly the underlying molecular processes. Therefore, the purpose of this study was to explore the regulatory mechanism of lncRNAs in milk fat synthesis. Based on our previous lncRNA-seq data and bioinformatics analysis, we found that Lnc-TRTMFS (transcripts related to milk fat synthesis) was upregulated in the lactation period compared to the dry period. In this study, we found that knockdown of Lnc-TRTMFS significantly inhibited milk fat synthesis, resulting in a smaller amount of lipid droplets and lower cellular triacylglycerol levels, and significantly decreased the expression of genes related to adipogenesis. In contrast, overexpression of Lnc-TRTMFS significantly promoted milk fat synthesis in bovine mammary epithelial cells (BMECs). In addition, Bibiserv2 analysis showed that Lnc-TRTMFS could act as a molecular sponge for miR-132x, and retinoic acid induced protein 14 (RAI14) was a potential target of miR-132x, which was further confirmed by dual-luciferase reporter assays, quantitative reverse transcription PCR, and western blots. We also found that miR-132x significantly inhibited milk fat synthesis. Finally, rescue experiments showed that Lnc-TRTMFS could weaken the inhibitory effect of miR-132x on milk fat synthesis and rescue the expression of RAI14. Taken together, these results revealed that Lnc-TRTMFS regulated milk fat synthesis in BMECs via the miR-132x/RAI14/mTOR pathway.

Keywords: Lnc-TRTMFS, miR-132x, RAI14, mTOR signaling pathway, milk fat

The interference and overexpression of Lnc-TRTMFS can positively regulate the milk fat synthesis and mTOR pathway in BMECs, while the inhibition and mimics of miR-132x can negatively regulate the milk fat synthesis and mTOR pathway. It was found that Lnc-TRTMFS has a targeted binding relationship with miR-132x, and miR-132x has a targeted binding relationship with RAI14. A ceRNA network of Lnc-TRTMFS-miR-132x-RAI14 was further constructed

Introduction

The milk fat content directly determines the nutrition and flavor of milk and is often seen as one of the main indicators of milk quality (Bionaz and Loor, 2008; Ji et al., 2008). Milk fat consists mainly of triglycerides, accounting for approximately 98%, while other milk lipids are diacylglycerol (about 2% of the lipid fraction), cholesterol (less than 0.5%), phospholipids (about 1%) and free fatty acids (about 0.1%) (Jensen, 1973; Lindmar, 2008). Previous studies have shown that milk fat synthesis is influenced by many factors, such as the environment, genetics, hormones, and physiology, among which genetic factors are considered to be the most important (Zhang et al., 2020a,b; Yang et al., 2017). However, the mechanisms of the regulation of milk fat are poorly understood.

Long noncoding RNAs (LncRNAs) are usually noncoding RNAs longer than 200 nt and can be used as signal molecules, decoy molecules, guide molecules and scaffold molecules to participate in the regulation of development, differentiation, metabolism, and other biological processes (Rinn and Chang, 2012; Wang and Chang, 2011; Quinn and Chang, 2016). In addition, lncRNAs affect mammary gland development and lactation. Two of the earliest identified regulatory lncRNAs, H19 and SRA (steroid receptor RNA activator), may be beneficial for maintaining mammary epithelial cell proliferation, increasing ductal lateral branching, and inducing acinar differentiation (Lanz et al., 2003; Adriaenssens et al., 1999). With the continuous progress of whole genome sequencing technology, recent studies have shown that there are differentially expressed lncRNAs among different lactation stages of breast tissues (Ji et al., 2020; Yang et al., 2018; Mumtaz et al., 2022). Furthermore, previous studies found that lncRNA-ORA, H19, lncRNA-AK012226, and LINC00958 significantly promote lipid accumulation and protein secretion (Cai et al., 2019; Li et al., 2019; Chen et al., 2018a; Zuo et al., 2020), while lncRNA-Gm12664-001 and lncRNA-MEG3 inhibit lipid accumulation (Zhang et al., 2020; Zou et al., 2022).

With the in-depth study of microRNAs (miRNAs), the competing endogenous RNA mechanism (ceRNA) theory has been proposed, which indicated that lncRNAs could play a role by regulating target genes by sponging miRNAs (Smillie et al., 2018; Sen et al., 2014). Currently, the research scope of ceRNA networks composed of lncRNA-miRNA-mRNA is extremely extensive, and various cellular processes, such as cell proliferation, differentiation, programmed apoptosis and cell death, have been studied (Cai et al., 2021; Lv et al., 2022; Luo et al., 2022; Chen et al., 2022). Studies have also shown that lncRNAs, as a kind of ceRNA, could be involved in the regulation of milk fat metabolism. For example, the regulatory relationships of TCONS_0054231-bta-miR-455-3p-SYK, TCONS_00184575-bta-miR-455-3p-SYK and TCONS_00279006-bta-miR-331-3p-PPAP2C were formed by the target genes SYK and PPAP2C related to lipid metabolism, and affected milk fat contents (Mu et al., 2022a). Through weighted gene co-expression network analysis, they found that TCONS_00133813-bta-miR-2454-5p-TNFAIP3, TCONS_00133813-bta -miR-2454-5p-ARRB1, and TCONS_00133813-bta-miR-2454-5p-PIK3R1 are key candidate ceRNAs associated with milk fat metabolism (Mu et al., 2022b). Lnc-MPFAST regulated gene expression in the PI3K-AKT signaling pathway by sponging miR-103 and promoted the proliferation and synthesis of fatty acids in bovine mammary epithelial cells (BMECs; Liu et al., 2022). Although many studies have shown that lncRNAs play an important role in lactation, research on their function and molecular processes is still insufficient. Therefore, it is necessary to identify new important lncRNAs related to milk fat synthesis and explore their molecular mechanism.

In our previous study, we identified transcripts related to milk fat synthesis (Lnc-TRTMFS), which is differentially expressed in the mammary tissue of dairy cows during the lactation and dry periods, and found that Lnc-TRTMFS was mainly enriched in the mechanistic target of rapamycin kinase (mTOR) signaling pathway which plays a notable role in milk fat synthesis (Zhang et al., 2018; Zheng et al., 2018; Cai et al., 2020). These data suggested that Lnc-TRTMFS may be a potential biomarker for dairy cow breeding.

Materials and Methods

All experimental protocols in this study were approved by the Laboratory Animal Management Committee of Northwest A&F University (Yangling, Shaanxi, China).

Cell preparation

BMECs were isolated from mammary gland tissue of mid-lactation Holstein cows following previously published protocols (Hou et al., 2016; Lu et al., 2012). BMECs were cultured in complete growth medium containing 90% Dulbecco’s modified Eagle’s medium/F-12 (Sigma-Aldrich), 10% fetal bovine serum (Sigma Aldrich), and 100 μg/mL penicillin–streptomycin (Gibco) at 37 °C in a humidified incubator with 5% CO2. The cells were seeded in 12-well cell culture plates using 0.25% trypsin and grown to 80% confluence in 10-cm cell culture dishes. The medium was then discarded, and cells were cultured for 48 h in a lactogenic medium (complete medium supplemented with 5 μg/mL insulin, 100 ng/mL prolactin, and 1 μg/mL hydrocortisone).

To investigate the effect of Lnc-TRTMFS on milk fat synthesis, we designed a small interfering RNA (siRNA) of Lnc-TRTMFS, 100 nmol/L siRNA Lnc-TRTMFS-166 (F: GGAAGGACGGUGACUGUUATT, R: UAACAGUCACCG UCCUUCCTT) and siRNA Lnc-TRTMFS-222 (F: CCGGACCAAGAGUGAUCUU TT, R: AAGAUCACUCUUGGUCCGGTT) were transfected into BMECs, and 100 nmol/L siRNA NC was used as the negative control. The Lnc-TRTMFS full-length primer was inserted into the HindIII and KpnI sites of pcDNA3.1, and then transfected into BMECs at 1,000 ng/mL, 1,500 ng/mL, 2,000 ng/mL and 2,500 ng/mL, with the same amount of pcDNA3.1 vector as the control. All of the above reagents were synthesized by Sangon Biotech.

For analysis of the role of microRNA 132x (miR-132x) in milk fat synthesis in BMECs, a set of cells were treated with 50 nmol/L miR-132x mimic (S: ACCGUG CUUUCGAUUGUUACU, AS: UAACAAUCGAAAGCCACGGUUU) and 50 nmol/L mimic NC was used as its negative control. Correspondingly, the other set of cells was transfected with 200 nmol/L miR-132x inhibitor (S: AGUAACAAUCGAA AGCCACGGU) and 200 nmol/L inhibitor NC was used as its negative control. All miR-132x mimics/inhibitors and their respective negative controls were designed and compounded by Sangon Biotech. Three biological replicates for each treatment condition were used, and the cells of each treatment group were collected at 48 h post-treatment for further experiments.

Real-time PCR

Total RNA was extracted using TRIzol reagent (Invitrogen) and reverse-transcribed with a Reverse Transcription Kit (TransGen Biotech) or the PrimeScript RT Reagent Kit (TransGen Biotech) for subsequent analysis of miRNA and mRNA expression, respectively. Quantitative reverse transcription PCR was performed using the miRcute miRNA qPCR Detection Kit (Tiangen) and SYBR Premix ExTaq II (Tiangen) on a 7500 Real-Time PCR System (Applied Biosystems Inc., Foster City, CA, USA) to quantify miR-132x and mRNA levels, respectively. Ubiquitously expressed transcript 6 (U6) and ubiquitously expressed prefoldin like chaperone (UXT) were used as internal control genes for the quantitative analysis of miRNA and mRNA levels, respectively (Wang et al., 2019a). Primers (Tables 1 and 2) were purchased from TSINGKE Biological Technology (Xi’an, P.R. China). The relative expression of miR-132x and mRNA was calculated using the 2−ΔΔCT method.

Table 1.

Primers for mRNA quantitative real-time PCR

Gene Primer sequence Annealing temperature
Lnc-TRTMFS F:GTCCTGAGGTCTCCACCCAA
R:CCACTGCAGGCGGACAC		 61 °C
UXT F:GCGCTACGAGGCTTTCATCT
R:CCGAGTGGTTAGCTTCCTGG		 61 °C
HSL F:CGGGGAGCACTACAAACGAAAC
R:GTCAGAGGCATTTCAAAGGCGA		 61 °C
ATGL F:TGCTGATTGCTATGAGTGTGCC
R:CCTCTTTGGAGTTGAAGTGGGT		 61 °C
CEBPα F:ATCTGCGAACACGAGACG
R:CCAGGAACTCGTCGTTGAA		 61 °C
CEBPβ F:TTCCTCTCCGACCTCTTCTC
R:CCAGACTCACGTAGCCGTACT		 61 °C
PPARγ F:TGAAGAGCCTTCCAACTCCC
R:GTCCTCCGGAAGAAACCCTTG		 61 °C
FABP2 F:TTTCAGTTCCATCTGGGAGGC
R:GCACTTTCCATGGCATTTTGAC		 61 °C
ACACα F:CGGCTGACTGGAGTTGAAGAA
R:CGCGTATGGGAGGCAAAAAC		 61 °C
SREBP1 F: CTGACGACCGTGAAAACAGA 61 °C
R: AGACGGCAGATTTATTCAACTT
4EBP1 F: GTTCCTGATGGAGTGTCGGA 61 °C
R: AACTGTGACTCTTCACCGCCT
mTOR F: TGGACACCAACAAGGACGAC 61 °C
R: TCCCACTGACCTAAACCCCA
P70S6K F: ATCACCAAGGTCACGTCAAAC 61 °C
R: TGCTCCCAAACTCCACCAAT
RAI14 F: AAGCTCCACCACCTCCTATCA
R: GTATGGAACTAATCTCAGCCTTGAA		 61 °C
QSOX1 F: GTCCAGCCACAACAAGGTCA 61 °C
R: GGTAACATTTCCGGTTGCCAG
ACSL6 F: GCTGATTTCTCGGGCTTTCTG 61 °C
R: ACTGACTCTGGATGACTCTCTC
PLIN2 F: GTTATTTCTCTGTGGCCGTTCG 61 °C
R: GGTTGATGCCCTTGTAGAGC
ELOVL6 F: AAGGTTACGGGTTGTAGCCG 61 °C
R: ACTAGACCGAGGCTGTGCTA
PRKAG1 F: TCCTCTAATGCGAGTGGGGA 61 °C
R: CTCAGCTAACCACTCTGCCC
Open in a new tab

Table 2.

Primers for miRNA quantitative real-time PCR

Gene Primer sequence Annealing temperature
U6 F:GCTTCGGCAGCACATATACT 61 °C
R:TTCACGAATTTGCGTGTCA T
miR-132x F: ACCGTGGCTTTCGATTGTTACT 61 °C
R: CTCAACTGGTGTCGTGGAGTC
miR-1468-5p F: CCTCCGTTTGCCTGTTTCGCTG 61 °C
R: CTCAACTGGTGTCGTGGAGTC
miR-1206 F: ATCCCACCACTGCCACCA 61 °C
R: CTCAACTGGTGTCGTGGAGTC
bta-miR-1468 F: CTCCGTTTGCCTGTTTTGCTGA 61 °C
R: CTCAACTGGTGTCGTGGAGTC
bta-miR-21-5p F: CGGGCCTAGCTTATCAGACTGATGTTGA 61 °C
R: CTCAACTGGTGTCGTGGAGTC
Open in a new tab

Protein extraction and western blotting

BMECs were collected using 0.25% trypsin and lysed in RIPA buffer (Solarbio, China) supplemented with 1% ­phenylmethanesulfonyl fluoride (PMSF; Pierce, USA) and 1% phosphatase inhibitor cocktail (Roche). Western blotting was performed as previously described (Wang et al., 2019b), using primary antibodies against β-actin (Abcam 8226, 1:1,000, Abcam), peroxisome proliferator-activated receptor gamma (PPARγ; EP4394(N), 1:1,000, Abcam), fatty acid-binding protein 4 (FABP4, ab92501, 1:7,000, Abcam), Acetyl Coenzyme A Carboxylase Alpha (ACACA, ab109368, 1:500, Abcam), Sterol-regulatory element binding protein 1 (SREBP1, D151451, 1:500, Sangon Biotech), mTOR (5536 T, 1:1,500, Univ), pho-mTOR (5536 T, 1:1500, Univ), ribosomal protein S6 kinase B1 (P70S6K; 2708 T, 1:1,500, Univ), pho-P70S6K (9234 T, 1:1,500, Univ), Eukaryotic Translation Initiation Factor 4E-Binding Protein 1 (4EBP1; 9644 T, 1:1500, University), Pho-4EBP1 (2855 T, 1:1,500, Univ), and retinoic acid induced 14 (RAI14, EPR8518, 1:1,000, Abcam).

Oil red O staining

At 48 h post-treatment, BMECs were washed three times with phosphate-buffered saline (PBS) and then fixed using 4% paraformaldehyde. Lipid droplets were stained with Oil Red O. The cells were then washed and placed under a microscope to evaluate the number of lipid droplets following previously published methods (Yang et al., 2017).

Cellular triacylglycerol assay

BMECs were washed three times with PBS at 48 h post-treatment and then collected using 0.25% trypsin. The cells were then lysed with cell lysis buffer (Applygen Technologies Inc.), and the supernatant was collected and heated at 70 °C for 10 min. The mixture was then centrifuged at 5,000 rpm for 5 min, and the supernatant was used to determine the triacylglycerol (TAG) content according to the manufacturer’s recommended protocol (Applygen Technologies, Beijing, P.R. China).

Luciferase assay

TargetScan (http://www.targetscan.org) and Bibiserv2 (https://bibiserv.cebitec.uni-bielefeld.de/) were used to predict the biological target genes of miRNAs and miR-132x targeted by Lnc-TRTMFS. The target binding site of Lnc-TRTMFS and miR-132x was determined, and the mature sequence of miR-132x was compared with the 3ʹ noncoding region of RAI14 to determine the target gene of miR-132x. The wild-type, mutant (MUT) RAI14 and Lnc-TRTMFS were cloned into the CHECK2 double luciferase expression vector (Promega, Madison, WI, USA) by using XhoI and PmeI digestion. Then, 293A cells were cultured in 12-well petri dishes and transfected when they reached 70% confluence. After 24 h, according to the manufacturer’s instructions, the fluorescence intensity was measured by double luciferase detection system kit (PROMEGA). All experiments were conducted in triplicate. The firefly luciferase activity was normalized to the luciferase activity of the kidney worm.

Statistical analyses

Three replicate wells were used for each experiment, and each well is treated as a biological replicate. All statistical analyses and visualization were performed using GraphPad Prism 7.0 software. Significant differences between the two groups were assessed using a two-tailed Student’s t-test. All results are presented as mean ± standard deviation of the mean (SDM). Statistical significance was declared at P < 0.05 and P < 0.01.

Results

Lnc-TRTMFS promotes milk fat synthesis in BMECs

Lnc-TRTMFS was identified in our previous transcriptome sequencing of mammary tissue during the lactation and dry periods, and we found that it was differentially expressed in differentiated and undifferentiated BMECs (Figure 1A). Through the prediction of coding potential calculator 2(CPC2) and coding potential assessment tool(CPAT), we found that the coding ability of Lnc-TRTMFS was only 0.061862% and 0.0682856% (Figure 1B and C), and nuclear and cytoplasmic separation experiments showed that Lnc-TRTMFS mainly existed in the cytoplasm (Figure 1D).

Figure 1.

Figure 1.

Open in a new tab

Basic information about Lnc-TRTMFS (transcripts related to milk fat synthesis). (A) Relative expression of Lnc-TRTMFS in BMECs and undifferentiated BMECs; (B) and (C) coding ability of Lnc-TRTMFS predicted by CPC2 and CPAT; (D) subcellular localization of Lnc-TRTMFS, with electrophoresis map on the left and quantitative map on the right. Values are presented as the mean ± SDM. * P < 0.05; ** P < 0.01. BMECs, bovine mammary epithelial cells; CPC2, coding potential calculator 2; CPAT, coding potential assessment tool; N, nucleus; C, cytoplasm.

We used siRNA and pcDNA3.1 vectors to reveal the regulatory effect of Lnc-TRTMFS expression changes on BMECs. The interference efficiency of siRNA-Lnc-TRTMFS-166 was 35%, and that of siRNA-Lnc-TRTMFS-222 was 75% (Figure 2A). The overexpression efficiency increased with increasing plasmid concentration of OP-Lnc-TRTMFS, and was 1.5 times at 1,000 ng/mL, 3.3 times at 1,500 ng/mL, 5.8 times at 2,000 ng/mL and 19 times at 2,500 ng/mL (Figure 2B). Then, the groups with the best interference efficiency and overexpression efficiency were selected for follow-up experiments.

Figure 2.

Figure 2.

Open in a new tab

Effects of the Lnc-TRTMFS siRNA/ plasmid on milk fat synthesis in BMECs. (A) and (B) Lnc-TRTMFS relative expression levels. (C) and (D) Effects of the Lnc-TRTMFS siRNA/ plasmid on TAG accumulation. (E) and (F) Representative images of Oil Red O stained BMECs. Values are presented as the mean ± SDM. * P < 0.05; ** P < 0.01. BMECs, bovine mammary epithelial cells; TAG, triacylglycerol; plasmid is overexpression-Lnc-TRTMFS.

The cellular TAG assay and Oil Red O staining were used to assess the effect of Lnc-TRTMFS on milk fat synthesis in BMECs. Our results showed that siRNA-Lnc-TRTMFS decreased TAG content and the number of lipid droplets in BMECs, while treatment with the OP-Lnc-TRTMFS markedly increased TAG content and the amount of lipid droplets in BMECs when compared with their corresponding negative controls (NCs) (Figure 2C to F). Additionally, we investigated the effect of Lnc-TRRMFS on lipid synthesis-related genes by determining the mRNA expression levels of PPARγ, ACACA, FABP2, ATGL, HSL, SREBP1, CEBPα, and CEBPβ, as well as the protein expression levels of PPARγ, FABP4, CEBPβ, and ACACA. The results showed that the siRNA-Lnc-TRTMFS significantly decreased the mRNA expression levels of CEBPα (P < 0.01), CEBPβ (P < 0.01), FABP2 (P < 0.05), PPARγ (P < 0.01), SREBP1 (P < 0.05), and ACACA (P < 0.05), as well as suppressed CEBPβ, FABP4, PPARγ, and ACACA protein expression levels in BMECs (Figure 3A and B). In contrast, treatment with the OP-Lnc-TRTMFS significantly increased the mRNA expression levels of CEBPα (P < 0.01), CEBPβ (P < 0.01), FABP2 (P < 0.01), PPARγ (P < 0.01), ACACA (P < 0.01), and SREBP1 (P < 0.05), and elevated PPARγ, FABP4, CEBPβ, and ACACA protein expression levels in BMECs (Figure 3C and D). Taken together, these results indicated that Lnc-TRTMFS promoted milk fat synthesis in BMEC.

Figure 3.

Figure 3.

Open in a new tab

Effects of the Lnc-TRTMFS siRNA/plasmid on lipid synthesis-related genes in BMECs. (A) and (C) mRNA expression levels of ATGL, PPARγ, ACACA, CEBPα, CEBPβ, FABP2, HSL, SREBP1. (B) After Lnc-TRTMFS interference processing, protein expression levels of PPARγ, ACACA, CEBPβ, and FABP4. (D) After overexpression of Lnc-TRTMFS, protein expression levels of PPARγ, ACACA, CEBPβ, and FABP4. Values are presented as the mean ± SDM. * P < 0.05; ** P < 0.01. BMECs, bovine mammary epithelial cells; TAG, triacylglycerol; NC, negative control.

Lnc-TRTMFS acts as a molecular sponge of the miR-132x cluster

Through prediction software (Bibiserv2), we found that Lnc-TRTMFS had targeted binding sites with miR-1468-5p, bta-miR-1468, miR-1206, bta-miR-21-5p and miR-132x. Real-time fluorescence PCR showed that miR-132x was ­significantly upregulated after siRNA-Lnc-TRTMFS treatment and significantly downregulated after OP-Lnc-TRTMFS treatment (Figure 4A to C). Through the double luciferase reporter assay, we found that the intensity of fluorescence in the Lnc-TRTMFS-miR-132x group was significantly lower than that in the other three groups (Figure 4D). These results showed that there was a targeted binding relationship between Lnc-TRTMFS and miR-132x.

Figure 4.

Figure 4.

Open in a new tab

Lnc-TRTMFS had a targeted binding relationship with miR-132x. (A) After overexpression of Lnc-TRTMFS, the relative expression of related miRNAs was predicted. (B) After interfering with Lnc-TRTMFS, the relative expression amount of related miRNAs. (C) Target predicted by Lnc-TRTMFS and miR-132x. (D) Double Luciferase Reporter Assay in 293A cells. Values are presented as the mean ± SDM. * P < 0.05. ** P < 0.01. Rluc, Renilla luciferase; fluc, firefly luciferase; WT, wild-type; MUTA, mutation type, NC, negative control.

miR-132x inhibits the synthesis of milk fat in BMECs

A miR-132x mimic and inhibitor were used to enhance or inhibit the regulatory effect of miR-132x in BMECs. With regard to their overexpression and interference efficiency, the expression level of miR-132x in BMECs increased 900-fold after treatment with the miR-132x mimic, and decreased by 50% after treatment with the miR-132x inhibitor, compared with ­corresponding NCs (Fig. 5A and B). The cellular TAG assay and Oil Red O staining showed that the TAG content and the number of lipid droplets of BMECs decreased significantly after miR-132x-mimic treatment, and the opposite results were found after miR-132x-inhibitor treatment (Figure 5C to F).

Figure 5.

Figure 5.

Open in a new tab

Effects of the miR-132x mimic/inhibitor on milk fat synthesis in BMECs. (A) and (B) miR-132x relative expression levels. (C) and (D) Effects of the miR-132x mimic/inhibitor on TAG accumulation. (E) and (F) Representative images of Oil Red O stained BMECs. Values are presented as the mean ± SDM. * P < 0.05; ** P < 0.01. BMECs, bovine mammary epithelial cells; TAG, triacylglycerol; NC, negative control.

The results of the qPCR and western blot showed that the miR-132x mimic significantly decreased the mRNA expression levels of CEBPα (P < 0.01), CEBPβ (P < 0.01), and PPARγ (P < 0.05), increased HSL (P < 0.01) (Figure 6A), and suppressed CEBPβ, FABP4, PPARγ, and SREBP1 ­protein expression levels in BMECs (Figure 6B). Meanwhile, after miR-132x-inhibitor treatment, the levels of CEBPα (P < 0.01), FABP2 (P < 0.05), SREBP1 (P < 0.01), PPARγ (P < 0.01) significantly increased, and the level of HSL (P < 0.05) significantly decreased, and the protein expression showed consistent trend with mRNA expression (Figure 6C and D). These experiments showed that miR-132x played a negative regulation role in milk fat synthesis of BMECs.

Figure 6.

Figure 6.

Open in a new tab

Effects of the miR-132x mimic/inhibitor on lipid synthesis-related genes in BMECs. (A) and (C) mRNA expression levels of ATGL, PPARγ, ACACA, CEBPα, CEBPβ, FABP2, HSL, SREBP1. (B) After overexpression of miR-132x, protein expression levels of PPARγ, ACACA, CEBPβ, and FABP4. (D) After miR-132x interference processing, protein expression levels of PPARγ, ACACA, CEBPβ, and FABP4 Values are presented as the mean ± SDM. * P < 0.05; ** P < 0.01. BMECs, bovine mammary epithelial cells; TAG, triacylglycerol; NC, negative control.

Lnc-TRTMFS and miR-132x regulate milk fat synthesis by regulating the mTOR signaling pathway

Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses showed that Lnc-TRTMFS was enriched in the mTOR pathway. The mRNA, protein and phosphorylated protein levels of mTOR, 4EBP1, and P70S6K were detected. After Lnc-TRTMFS interference, mTOR (P < 0.01) and 4EBP1 (P < 0.05) were significantly downregulated, and the protein and phosphorylated protein expression levels of mTOR, 4EBP1, and P70S6K were significantly inhibited (Figure 7A and C). Conversely, mTOR (P < 0.01) and P70S6K (P < 0.05) were significantly upregulated after the overexpression of Lnc-TRTMFS, which promoted the protein and phosphorylated protein expression levels of mTOR, 4EBP1 and P70S6K (Figure 7B and C).

Figure 7.

Figure 7.

Open in a new tab

Effects of the Lnc-TRTMFS siRNA/plasmid on the mTOR signaling pathway in BMECs. (A) and (B) The relative mRNA expression level of mTOR, 4EBP1, and P70S6K. (C) The total protein and phosphorylated protein expression level of mTOR, 4EBP1, and P70S6K. Values are presented as the mean ± SDM. * P < 0.05; ** P < 0.01. BMECs, bovine mammary epithelial cells; NC, negative control.

Interestingly, overexpression of miR-132x markedly decreased mTOR and 4EBP1 mRNA, protein, and phosphorylated protein expression levels (Figure 8A and C). Conversely, miR-132x knockdown in BMECs significantly increased the mRNA, protein, and phosphorylated protein expression levels of mTOR, resulting in increased of phosphorylated 4EBP1 and P70S6K levels (Figure 8B and C). These results suggested that Lnc-TRTMFS and miR-132x regulated milk fat synthesis via the mTOR signaling pathway.

Figure 8.

Figure 8.

Open in a new tab

Effects of the miR-132x mimic/inhibitor on the mTOR signaling pathway in BMECs. (A) and (B) The relative mRNA expression level of mTOR, 4EBP1, and P70S6K. (C) The total protein and phosphorylated protein expression level of mTOR, 4EBP1, and P70S6K. Values are presented as the mean ± SDM. * P < 0.05; ** P < 0.01. BMECs, bovine mammary epithelial cells; NC, negative control.

miR-132x directly targets RAI14 in BMECs

The mRNAs targeted by miR-132x were predicted by the prediction software programs Bibiserv2 and TargetScan. QSOX1 (Geng et al., 2020), RAI14 (Shen et al., 2019), ACSL6 (Song., 2020), LPIN2 (Kaushik and Cuervo., 2016), ELOVL6 (Junjvlieke et al., 2020), and PRKAG1 (Puustinen et al., 2020) were the target genes of miR-132x. The overexpression of miR-132x in BMECs significantly downregulated QSOX1 (P < 0.01), ACSL6 (P < 0.01), RAI14 (P < 0.05), ELOVL6 (P < 0.05), and PRKAG1 (P <0.05). The mRNA expression of QSOX1 (P < 0.05), RAI14 (P < 0.05), and ACSL6 (P < 0.05) was significantly upregulated after miR-132x knockdown. Only RAI14 (P < 0.05) and ACSL6 (P < 0.05) mRNA expression was significantly downregulated after siRNA-Lnc-TRTMFS treatment, and significantly upregulated after overexpression of Lnc-TRTMFS (P < 0.05) (Figure 9A to D). These results indicated that Lnc-TRTMFS might regulate milk fat synthesis by regulating RAI14 or ACSL6 gene expression through competitive binding of miR-132x. The above studies showed that Lnc-TRTMFS and miR-132x regulated milk fat synthesis via the mTOR signaling pathway; RAI14 was an upstream regulator of the mTOR signaling pathway, so RAI14 was selected as a candidate target gene of miR-132x. Furthermore, the luciferase reporter assay was used to confirm whether RAI14 was a direct target gene of miR-132x. The results showed that the miR-132x mimic inhibited the standardized luciferase activity by 52.36% (P < 0.01), however, the activity returned to normal levels in the MUT group (Figure 9E and F). In addition, western blot analysis demonstrated that RAI14 protein also had the same trend after treatment (Figure 9G and H). These results indicated that miR-132x directly targeted RAI14 in BMECs.

Figure 9.

Figure 9.

Open in a new tab

RAI14 is one of the target genes of miR-132x. (A) and (B) Effect of miR-132x mimic/inhibitor on the mRNA level of predicted target genes. (C) and (D) Effect of Lnc-TRTMFS siRNA/ plasmid on the mRNA level of predicted target genes. (E) Double fluorescence reporter assay in 293A cells. (F) Report the experiment with double fluorescein in BMECs. (G) and (H) The protein expression level of RAI14. Values are presented as the mean ± SDM. * P < 0.05. ** P < 0.01. Rluc, Renilla luciferase; fluc, firefly luciferase; WT, wild-type; MUTA, mutation type; NC, negative control.

Lnc-TRTMFS regulated milk fat synthesis by regulating RAI14 targeted by miR-132x

Lnc-TRTMFS could indirectly regulate RAI14 expression as a ceRNA of miR-132x. To further explore the function of Lnc-TRTMFS in the lncRNA-miRNA-mRNA interaction network, we determine the effect of cotransfection of OP-Lnc-TRTMFS and miR-132x-mimics into BMECs on milk fat synthesis. We found that OP-Lnc-TRTMFS could alleviate the inhibitory effect of miR-132x-mimics on triglyceride content, the number of droplets, and RAI14 expression (Figure 10A to D). Moreover, siRNA-Lnc-TRTMFS and miR-132x inhibitor were cotransfected into BMECs, and the inhibitory effect of siRNA-Lnc-TRTMFS on milk fat synthesis could be reversed by the miR-132x inhibitor (Figure 11A to D).

Figure 10.

Figure 10.

Open in a new tab

OP-Lnc-TRTMFS and miR-132x-mimics were co-transfected into BMECs, and the effect on adipogenesis of BMECs was observed. (A) RAI14 relative expression levels. (B) The protein expression level of RAI14. (C) Effects of the co-transformation on TAG accumulation. (D) Representative images of Oil Red O stained BMECs. Values are presented as the mean ± SDM. * P < 0.05; ** P < 0.01. BMECs, bovine mammary epithelial cells; TAG, triacylglycerol; NC, negative control; OP-Lnc-TRTMFS, overexpression of Lnc-TRTMFS.

Figure 11.

Figure 11.

Open in a new tab

SiRNA-Lnc-TRTMFS and miR-132x-inhibitor were co-transfected into BMECs, and the effect on adipogenesis of BMECs was observed. (A) RAI14 (retinoic acid induced 14) relative expression levels. (B) The protein expression level of RAI14. (C) Effects of the co-transformation on TAG accumulation. (D) Representative images of Oil Red O stained BMECs. Values are presented as the mean ± SDM. * P < 0.05; ** P < 0.01. BMECs, bovine mammary epithelial cells; TAG, triacylglycerol; NC, negative control; siRNA-Lnc-TRTMFS, small interfering RNA of Lnc-TRTMFS.

To explore the relationship between Lnc-TRTMFS and RAI14, we cotransfected OP-Lnc-TRTMFS and siRNA-RAI14 into BMECs. The promotion effect of Lnc-TRTMFS overexpression on triglyceride content and droplet accumulation was significantly inhibited by siRNA-induced knockdown of RAI14 (Figure 12A to D). These results showed that Lnc-TRTMFS regulated milk fat synthesis through RAI14 targeted by miR-132x.

Figure 12.

Figure 12.

Open in a new tab

OP-Lnc-TRTMFS and siRNA-RAI14 were co-transfected into BMECs, and the effect on adipogenesis of BMECs was observed. (A) RAI14 relative expression levels. (B) The protein expression level of RAI14. (C) Effects of the co-transformation on TAG accumulation. (D) Representative images of Oil Red O stained BMECs. Values are presented as the mean ± SDM. * P < 0.05; ** P < 0.01. BMECs, bovine mammary epithelial cells; TAG, triacylglycerol; NC, negative control; OP-Lnc-TRTMFS, overexpression of Lnc-TRTMFS; siRNA-Lnc-TRTMFS, small interfering RNA of Lnc-TRTMFS.

Discussion

In recent years, an increasing number of studies have shown that lncRNAs play an important role in cell proliferation, differentiation, the cell cycle, and apoptosis. Therefore, more attention has been given to studies on lncRNAs. Focusing on the development of the mammary gland, a series of studies on lncRNAs have been conducted. For example, genetic ablation of Neat1 results in aberrant mammary gland morphogenesis and lactation defects (Standaert et al.,2014); lncRNA LOC102188416 acted as a sponge of miR-143-3p to regulate the expression of their mutual target gene MAPK1 in GMECs (Zhang et al., 2022). In a previous study, Lnc-TRTMFS was identified in our previous transcriptome sequencing of mammary tissue during lactation and dry periods.

In this study, we found that Lnc-TRTMFS significantly promoted the formation of lipid droplets and triglyceride accumulation and upregulated the genes related to milk fat synthesis (CEBPα, CEBPβ, PPARγ, SREBP1, and ACACA). PPARγ is a necessary gene for mitotic cloning and amplification during adipogenesis and plays a key role in milk fat synthesis (Xu et al., 2018). SREBP1 is a key factor in the regulation of milk lipids and can promote the synthesis of milk fat in breast epithelial cells (Xu et al., 2016; 2019). CEBP is an important transcription factor in milk fat synthesis, that can regulate lipid droplet formation by activating the expression of PPARγ (Fajas et al., 1998). ACC1 encoded by ACACA is involved in the first step of fatty acid synthesis and has been demonstrated to be a marker gene for milk fat synthesis (Mu et al., 2021). Therefore, our results revealed that Lnc-TRTMFS could control lipid accumulation and TAG content by affecting the expression of lipid metabolism-related genes in BMECs.

In this experiment, we found that Lnc-TRTMFS mainly exists in the cytoplasm, and lncRNAs located in the cytoplasm can act as miRNA sponges to regulate the target genes (Cai et al., 2021; Bridges et al., 2021). Through a double fluorescein report test and qPCR, we found that Lnc-TRTMFS may be the “sponge” molecule of miR-132x. MiR-132x has a negative regulatory effect on milk fat synthesis. Previous studies have found that miR-132x plays an important role in fat metabolism. Studies in mice have shown that miR-132 regulates SREBP-1c to improve liver lipid metabolism (Wang et al., 2022). In humans, miR-132x was shown to be negatively correlated with the content of body fat and cholesterol (Estep et al., 2010), and miR-132x is an important regulator of liver homeostasis and lipid metabolism (Eikelis et al., 2022). The results of this experiment are consistent with those of previous studies.

This study showed that Lnc-TRTMFS positively regulated the expression levels of the mTOR, 4EBP1, and P70S6K proteins and phosphorylated proteins, and miR-132x downregulated the expression of the mTOR, 4EBP1, and P70S6K proteins and phosphorylated proteins. In addition, we confirmed that RAI14 was a target gene of miR-132x. The mTOR pathway plays an important role in mammary gland development, milk protein generation and milk fat synthesis. Previous studies have shown that activation of the mTOR pathway can promote milk fat synthesis in mammary epithelial cells of pigs (Che et al., 2019), cattles (Li et al., 2022) and goats (Zhu et al., 2020). In addition, RAI14 is an important regulatory factor in the mTOR pathway. RAI14 increases the levels of pro-inflammatory cytokines, promotes gastric cell proliferation, and synthesizes bovine milk fat by mediating the mTOR pathway (Shen et al., 2019; Chen et al., 2018b; Wang et al.,2021).

Through the rescue test, we verified that Lnc-TRTMFS could weaken the inhibitory effect of miR-132x on RAI14 in mammary epithelial cells. Therefore, we concluded that the ceRNA network of Lnc-TRTMFS-miR-132x-RAI14 regulated milk fat synthesis in mammary epithelial cells via the mTOR pathway (Figure 13).

Figure 13.

Figure 13.

Open in a new tab

Schematic description of the Lnc-TRTMFS regulation of adipogenesis in bovine mammary epithelial cells. Lnc-TRTMFS targets miR-132x, and miR-132x targets RAI14, which further promotes milk fat synthesis by regulating the expression of genes associated with milk fat synthesis. In addition, RAI14 promotes fat production by regulating the phosphorylation of 4EBP1 and P70S6K proteins in the mTOR signaling pathway. The red arrow shows a positive correlation, while the green arrow shows a negative correlation.

Conclusion

This study revealed that Lnc-TRTMFS regulated the expression of RAI14 through competitive binding with miR-132x and thereby regulated the synthesis of milk fat, which provided a theoretical basis for further study on the molecular mechanism of fat synthesis in bovine mammary epithelial cells.

Acknowledgments

This work was supported by the National Key R&D Program of China (2022YFF1000100); the Key R&D Plan of Shaanxi Province (2022GD-TSLD-46-0104); and the National Technical System for Beef and Yak Industry (CARS-37).

Glossary

Abbreviations

4EBP1

eukaryotic translation initiation factor 4E binding protein 1

ACACA

acetyl-CoA carboxylase alpha

ACSL6

acyl-CoA synthetase long chain family member 6

ATGL

adipose triglyceride lipase

BMECs

bovine mammary epithelial cells

CEBP

CCAAT/enhancer binding protein

ceRNA

the competing endogenous RNA mechanism

ELOVL6

ELOVL fatty acid elongase 6

FABP

fatty acid binding protein

GO

gene ontology

HSL

hormone-sensitive lipase

KEGG

Kyoto Encyclopedia of Genes and Genomes

Lnc-TRTMFS

transcripts related to milk fat synthesis

LncRNA

long noncoding RNA

miR-132x

microRNA 132

miRNAs

microRNAs

mTOR

mechanistic target of rapamycin kinase

P70S6K

Ribosomal protein S6 kinase

PPARγ

peroxisome proliferator-activated receptor γ

PRKAG1

protein kinase Adenosine monophosphate (AMP)-activated noncatalytic subunit gamma 1

QSOX1

quiescin sulfhydryl oxidase 1

RAI14

retinoic acid induced 14

siRNA

small interfering RNA

SREBP1

sterol-regulatory element binding protein 1

TAG

triacylglycerol

U6

ubiquitously expressed transcript 6

UXT

ubiquitously expressed transcript

Contributor Information

Hongru Jia, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China.

Zhangqing Wu, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China.

Jianbing Tan, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China.

Silin Wu, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China.

Chaoqun Yang, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China.

Sayed Haidar Abbas Raza, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China.

Meng Wang, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China.

Guibing Song, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China.

Yujie Shi, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China.

Linsen Zan, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China.

Wucai Yang, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China.

Author Contributions

Yang Wucai designed and directed the experiment; Wang Meng, Song Guibing and Yang Chaoqun verified the accuracy of the preliminary sequencing results; Jia Hongru and Wu Zhangqing conducted the experimental work and data analysis; Yang Wucai, Jia Hongru,Shi Yujie and Wu Zhangqing wrote and revised the paper; Wu Sinlin and Tan Jianbing revised the paper; Sayed Haidar Abbas Raza and Linsen Zan: Data curation, Formal analysis, Investigation, Visualization Writing - review & editing. All authors have read and agreed to the published version of the manuscript.

Conflict of Interest Statement

The authors declare no conflicts of interest with regard to this study.

Data Availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Literature Cited

  1. Adriaenssens, E., S.  Lottin, T.  Dugimont, W.  Fauquette, J.  Coll, J. P.  Dupouy, B.  Boilly, and J. J.  Curgy. . 1999. Steroid hormones modulate H19 gene expression in both mammary gland and uterus. Oncogene. 18:4460–4473. doi: 10.1038/sj.onc.1202819. [DOI] [PubMed] [Google Scholar]
  2. Bionaz, M., and J. J.  Loor. . 2008. Gene networks driving bovine milk fat synthesis during the lactation cycle. BMC Genomics. 9:366. doi: 10.1186/1471-2164-9-366. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Bridges, M. C., A. C.  Daulagala, and A.  Kourtidis. . 2021. LNCcation: lncRNA localization and function. J. Cell Biol. 220:e202009045. doi: 10.1083/jcb.202009045. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Cai, R., G.  Tang, Q.  Zhang, W.  Yong, W.  Zhang, J.  Xiao, C.  Wei, C.  He, G.  Yang, and W.  Pang. . 2019. A novel lnc-RNA, named lnc-ORA, is identified by RNA-Seq analysis, and its knockdown inhibits adipogenesis by regulating the PI3K/AKT/mTOR signaling pathway. Cells. 8:477. doi: 10.3390/cells8050477. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Cai, J., D.  Wang, F. Q.  Zhao, S.  Liang, and J.  Liu. . 2020. AMPK-mTOR pathway is involved in glucose-modulated amino acid sensing and utilization in the mammary glands of lactating goats. J. Anim. Sci. Biotechnol. 11:32. doi: 10.1186/s40104-020-0434-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Cai, R., Q.  Zhang, Y.  Wang, W.  Yong, R.  Zhao, and W.  Pang. . 2021. Lnc-ORA interacts with microRNA-532-3p and IGF2BP2 to inhibit skeletal muscle myogenesis. J. Biol. Chem. 296:100376. doi: 10.1016/j.jbc.2021.100376. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Che, L., M.  Xu, K.  Gao, C.  Zhu, L.  Wang, X.  Yang, X.  Wen, H.  Xiao, Z.  Jiang, and D.  Wu. . 2019. Valine increases milk fat synthesis in mammary gland of gilts through stimulating AKT/MTOR/SREBP1 pathway. Biol. Reprod. 101:126–137. doi: 10.1093/biolre/ioz065. [DOI] [PubMed] [Google Scholar]
  8. Chen, X., Y.  Xu, D.  Zhao, T.  Chen, C.  Gu, G.  Yu, K.  Chen, Y.  Zhong, J.  He, S.  Liu, . et al. 2018a. LncRNA-AK012226 is involved in fat accumulation in db/db mice fatty liver and non-alcoholic fatty liver disease cell model. Front. Pharmacol. 9:888. doi: 10.3389/fphar.2018.00888. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Chen, C., A.  Maimaiti, X.  Zhang, H.  Qu, Q.  Sun, Q.  He, and W.  Yu. . 2018b. Knockdown of RAI14 suppresses the progression of gastric cancer. Onco Targets Ther. 11:6693–6703. doi: 10.2147/OTT.S175502. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Chen, F., X.  Chen, W.  Cai, H.  Ruan, and S.  Fang. . 2022. Mesenchymal stem cell-derived exosomal long noncoding RNA MALAT1-201 regulated the proliferation, apoptosis and migration of trophoblast cells via targeting miR-141. Ann. Clin. Lab. Sci. 52:741–752. doi: 10.1080/15384101.2021.2019411. [DOI] [PubMed] [Google Scholar]
  11. Eikelis, N., J. B.  Dixon, E. A.  Lambert, G.  Hanin, Y.  Tzur, D. S.  Greenberg, H.  Soreq, F. Z.  Marques, M. T.  Fahey, G. A.  Head, . et al. 2022. MicroRNA-132 may be associated with blood pressure and liver steatosis-preliminary observations in obese individuals. J. Hum. Hypertens. 36:911–916. doi: 10.1038/s41371-021-00597-2. [DOI] [PubMed] [Google Scholar]
  12. Estep, M., D.  Armistead, N.  Hossain, H.  Elarainy, Z.  Goodman, A.  Baranova, V.  Chandhoke, and Z. M.  Younossi. . 2010. Differential expression of miRNAs in the visceral adipose tissue of patients with non-alcoholic fatty liver disease. Aliment. Pharmacol. Ther. 32:487–497. doi: 10.1111/j.1365-2036.2010.04366.x. [DOI] [PubMed] [Google Scholar]
  13. Fajas, L., J. C.  Fruchart, and J.  Auwerx. . 1998. Transcriptional control of adipogenesis. Curr. Opin Cell Biol. 10:165–173. doi: 10.1016/s0955-0674(98)80138-5. [DOI] [PubMed] [Google Scholar]
  14. Geng, Y., C.  Xu, Y.  Wang, and L.  Zhang. . 2020. Quiescin sulfhydryl oxidase 1 regulates the proliferation, migration and invasion of human glioblastoma cells via PI3K/Akt pathway. Onco Targets Ther. 13:5721–5729. doi: 10.2147/OTT.S255941. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Hou, X., L.  Lin, W.  Xing, Y.  Yang, X.  Duan, Q.  Li, X.  Gao, and Y.  Lin. . 2016. Spleen tyrosine kinase regulates mammary epithelial cell proliferation in mammary glands of dairy cows. J. Dairy Sci. 99:3858–3868. doi: 10.3168/jds.2015-10118. [DOI] [PubMed] [Google Scholar]
  16. Jensen, R. G.  1973. Composition of bovine milk lipids. J. Am. Oil Chem. Soc. 50:186–192. doi: 10.1007/BF02640488. [DOI] [PubMed] [Google Scholar]
  17. Ji, H., N.  Erfani, B. J.  Tauro, E. A.  Kapp, H. J.  Zhu, R. L.  Moritz, J. W.  Lim, and R. J.  Simpson. . 2008. Difference gel electrophoresis analysis of Ras-transformed fibroblast cell-derived exosomes. Electrophoresis. 29:2660–2671. doi: 10.1002/elps.200800015. [DOI] [PubMed] [Google Scholar]
  18. Ji, Z., T.  Chao, Z.  Liu, L.  Hou, J.  Wang, A.  Wang, J.  Zhou, R.  Xuan, G.  Wang, and J.  Wang. . 2020. Genome wide integrated analysis demonstrates widespread functions of lncRNAs in mammary gland development and lactation in dairy goats. BMC Genom. 21:254. doi: 10.1186/s12864-020-6656-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Junjvlieke, Z., R.  Khan, C.  Mei, G.  Cheng, S.  Wang, S. H. A.  Raza, J.  Hong, X.  Wang, W.  Yang, and L.  Zan. . 2020. Effect of ELOVL6 on the lipid metabolism of bovine adipocytes. Genomics. 112:2282–2290. doi: 10.1016/j.ygeno.2019.12.024. [DOI] [PubMed] [Google Scholar]
  20. Kaushik, S., Cuervo, A. M.  2016. AMPK-dependent phosphorylation of lipid droplet protein PLIN2 triggers its degradation by CMA. Autophagy. 12:432–438. doi: 10.1080/15548627.2015.1124226. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Lanz, R. B., S. S.  Chua, N.  Barron, B. M.  Soder, F.  DeMayo, and B. W.  OMalley. . 2003. Steroid receptor RNA activator stimulates proliferation as well as apoptosis in vivo. Mol. Cell. Biol. 23:7163–7176. doi: 10.1128/MCB.23.20.7163-7176.2003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Li, X., H.  Wang, Y.  Zhang, J.  Zhang, S.  Qi, Y.  Zhang, and M. Q.  Gao. . 2019. Overexpression of lncRNA H19 changes basic characteristics and affects immune response of bovine mammary epithelial cells. PeerJ  7:e6715. doi: 10.7717/peerj.6715. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Li, F., G.  Hu, X.  Long, Y.  Cao, Q.  Li, W.  Guo, J.  Wang, J.  Liu, and S.  Fu. . 2022. Stearic acid activates the PI3K-mTOR-4EBP1/S6K and mTOR-SREBP-1 signaling axes through FATP4-CDK1 to promote milk synthesis in primary bovine mammary epithelial cells. J. Agric. Food Chem. 70:4007–4018. doi: 10.1021/acs.jafc.2c00208. [DOI] [PubMed] [Google Scholar]
  24. Lindmark Mansson, H.  2008. Fatty acids in bovine milk fat. Food Nutr. Res. 52:1821. doi: 10.3402/fnr.v52i0.1821. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Liu, L., B.  Sun, F.  Zhang, Z.  Zhong, Y.  Zhang, F.  Li, T.  Zhang, H.  Khatib, and X.  Wang. . 2022. lncRNA MPFAST promotes proliferation and fatty acid synthesis of bovine mammary epithelial cell by sponging miR-103 regulating PI3K-AKT pathway. J. Agric. Food Chem. 70:12004–12013. doi: 10.1021/acs.jafc.2c04789. [DOI] [PubMed] [Google Scholar]
  26. Lu, L., X.  Gao, Q.  Li, J.  Huang, R.  Liu, and H.  Li. . 2012. Comparative phosphoproteomics analysis of the effects of L-methionine on dairy cow mammary epithelial cells. Can. J. Anim. Sci. 92:433–442. doi: 10.4141/cjas2012-063. [DOI] [Google Scholar]
  27. Luo, Y., W.  Tang, S.  Xiang, J.  Feng, and X.  Zu. . 2022. Non-coding RNAs in breast cancer: implications for programmed cell death. Cancer Lett. 550:215929. doi: 10.1016/j.canlet.2022.215929. [DOI] [PubMed] [Google Scholar]
  28. Lv, W., W.  Jiang, H.  Luo, Q.  Tong, X.  Niu, X.  Liu, Y.  Miao, J.  Wang, Y.  Guo, J.  Li, . et al. 2022. Long noncoding RNA lncMREF promotes myogenic differentiation and muscle regeneration by interacting with the Smarca5/p300 complex. Nucleic Acids Res. 50:10733–10755. doi: 10.1093/nar/gkac854. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Mu, T., H.  Hu, Y.  Ma, X.  Feng, J.  Zhang, and Y.  Gu. . 2021. Regulation of key genes for milk fat synthesis in ruminants. Front. Nutr. 8:765147. doi: 10.3389/fnut.2021.765147. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Mu, T., H.  Hu, X.  Feng, Y.  Ma, Y.  Wang, J.  Liu, B.  Yu, W.  Wen, J.  Zhang, and Y.  Gu. . 2022a. Screening and conjoint analysis of key lncRNAs for milk fat metabolism in dairy cows. Front. Genet. 13:772115. doi: 10.3389/fgene.2022.772115. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Mu, T., H.  Hu, Y.  Ma, C.  Yang, X.  Feng, Y.  Wang, J.  Liu, B.  Yu, J.  Zhang, and Y.  Gu. . 2022b. Identification of critical lncRNAs for milk fat metabolism in dairy cows using WGCNA and the construction of a ceRNAs network. Anim. Genet. 53:740–760. doi: 10.1111/age.13249. [DOI] [PubMed] [Google Scholar]
  32. Mumtaz, P. T., B.  Bhat, E. M.  Ibeagha-Awemu, Q.  Taban, M.  Wang, M. A.  Dar, S. A.  Bhat, N.  Shabir, R. A.  Shah, N. A.  Ganie, . et al. 2022. Mammary epithelial cell transcriptome reveals potential roles of lncRNAs in regulating milk synthesis pathways in Jersey and Kashmiri cattle. BMC Genom. 23:176. doi: 10.1186/s12864-022-08406-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Puustinen, P., A.  Keldsbo, E.  Corcelle-Termeau, K.  Ngoei, S. L.  Sonder, T.  Farkas, K.  Kaae Andersen, J. S.  Oakhill, and M.  Jaattela. . 2020. DNA-dependent protein kinase regulates lysosomal AMP-dependent protein kinase activation and autophagy. Autophagy. 16:1871–1888. doi: 10.1080/15548627.2019.1710430. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Quinn, J. J., and H. Y.  Chang. . 2016. Unique features of long non-coding RNA biogenesis and function. Nat. Rev. Genet. 17:47–62. doi: 10.1038/nrg.2015.10. [DOI] [PubMed] [Google Scholar]
  35. Rinn, J. L., and H. Y.  Chang. . 2012. Genome regulation by long noncoding RNAs. Annu. Rev. Biochem. 81:145–166. doi: 10.1146/annurev-biochem-051410-092902. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Sen, R., S.  Ghosal, S.  Das, S.  Balti, and J.  Chakrabarti. . 2014. Competing endogenous RNA: the key to posttranscriptional regulation. Scientific World J. 2014:896206. doi: 10.1155/2014/896206. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Shen, X., J.  Zhang, X.  Zhang, Y.  Wang, Y.  Hu, and J.  Guo. . 2019. Retinoic acid-induced protein 14 (RAI14) promotes mTOR-mediated inflammation under inflammatory stress and chemical hypoxia in a U87 glioblastoma Cell Line. Cell. Mol. Neurobiol. 39:241–254. doi: 10.1007/s10571-018-0644-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Smillie, C. L., T.  Sirey, and C. P.  Ponting. . 2018. Complexities of post-transcriptional regulation and the modeling of ceRNA crosstalk. Crit. Rev. Biochem. Mol. Biol. 53:231–245. doi: 10.1080/10409238.2018.1447542. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Song, S. Y.  2020. The effect of ACSL6 on milk fat synthesis in mammary gland of dairy cow D. Northeast Agricultural University  4:1–53. doi: 10.27010/d.cnki.gdbnu.2020.000591. [DOI] [Google Scholar]
  40. Standaert, L., C.  Adriaens, E.  Radaelli, A.  Van Keymeulen, C.  Blanpain, T.  Hirose, S.  Nakagawa, and J. C.  Marine. . 2014. The long noncoding RNA Neat1 is required for mammary gland development and lactation. RNA  20:1844–1849. doi: 10.1261/rna.047332.114. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Wang, K. C., Chang, H. Y.  2011. Molecular mechanisms of long noncoding RNAs. J. Mol. Cell  43:904–914. doi: 10.1016/j.molcel.2011.08.018. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Wang, Y., W.  Guo, K.  Tang, Y.  Wang, L.  Zan, and W.  Yang. . 2019a. Bta-miR-34b regulates milk fat biosynthesis by targeting mRNA decapping enzyme 1A (DCP1A) in cultured bovine mammary epithelial cells1. J. Anim. Sci. 97:3823–3831. doi: 10.1093/jas/skz230. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Wang, Y., W.  Guo, H.  Xu, K.  Tang, L.  Zan, and W.  Yang. . 2019b. Melatonin suppresses milk fat synthesis by inhibiting the mTOR signaling pathway via the MT1 receptor in bovine mammary epithelial cells. J. Pineal Res. 67:e12593. doi: 10.1111/jpi.12593. [DOI] [PubMed] [Google Scholar]
  44. Wang, Y., X.  Wang, M.  Wang, L.  Zhang, L.  Zan, and W.  Yang. . 2021. Bta-miR-34b controls milk fat biosynthesis via the Akt/mTOR signaling pathway by targeting RAI14 in bovine mammary epithelial cells. J. Anim. Sci. Biotechnol. 12:83. doi: 10.1186/s40104-021-00598-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Wang, L., G.  Chen, S.  Wu, Y.  Xu, C.  Guo, M.  Wang, T.  Liang, Z.  Guo, H. J.  Di, and Z.  Hu. . 2022. Genipin improves lipid metabolism and sperm parametersin obese mice via regulation of miR-132 expression. Acta Biochim. Biophys. Sin. (Shanghai)  9: 1278–1288. doi: 10.3724/abbs.2022120. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Xu, H. F., J.  Luo, W. S.  Zhao, Y. C.  Yang, H. B.  Tian, H. B.  Shi, and M.  Bionaz. . 2016. Overexpression of SREBP1 (sterol regulatory element binding protein 1) promotes de novo fatty acid synthesis and triacylglycerol accumulation in goat mammary epithelial cells. J. Dairy Sci. 99:783–795. doi: 10.3168/jds.2015-9736. [DOI] [PubMed] [Google Scholar]
  47. Xu, L., X.  Ma, N. K.  Verma, D.  Wang, O.  Gavrilova, R. L.  Proia, T.  Finkel, and E.  Mueller. . 2018. Ablation of PPARγ in subcutaneous fat exacerbates age-associated obesity and metabolic decline. Aging Cell  17:e12721. doi: 10.1111/acel.12721. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Xu, H. F., J.  Luo, X. Y.  Zhang, J.  Li, and M.  Bionaz. . 2019. Activation of liver X receptor promotes fatty acid synthesis in goat mammary epithelial cells via modulation of SREBP1 expression. J. Dairy Sci. 102:3544–3555. doi: 10.3168/jds.2018-15538. [DOI] [PubMed] [Google Scholar]
  49. Yang, W. C., W. L.  Guo, L. S.  Zan, Y. N.  Wang, and K. Q.  Tang. . 2017. Bta-miR-130a regulates the biosynthesis of bovine milk fat by targeting peroxisome proliferator-activated receptor gamma. J. Anim. Sci. 95:2898–2906. doi: 10.2527/jas.2017.1504. [DOI] [PubMed] [Google Scholar]
  50. Yang, B., B.  Jiao, W.  Ge, X.  Zhang, S.  Wang, H.  Zhao, and X.  Wang. . 2018. Transcriptome sequencing to detect the potential role of long non-coding RNAs in bovine mammary gland during the dry and lactation period. BMC Genom. 19:605. doi: 10.1186/s12864-018-4974-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Zhang, M., D.  Chen, Z.  Zhen, J.  Ao, X.  Yuan, and X.  Gao. . 2018. Annexin A2 positively regulates milk synthesis and proliferation of bovine mammary epithelial cells through the mTOR signaling pathway. J. Cell. Physiol. 233:2464–2475. doi: 10.1002/jcp.26123. [DOI] [PubMed] [Google Scholar]
  52. Zhang, L., Z. Q.  Wu, Y. J.  Wang, M.  Wang, and W. C.  Yang. . 2020a. MiR-143 regulates milk fat synthesis by targeting Smad3 in bovine mammary epithelial cells. Animals (Basel). 10:1453. doi: 10.3390/ani10091453. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Zhang, Q., J.  Wang, H.  Li, Y.  Zhang, X.  Chu, J.  Yang, and Y.  Li. . 2020b. LncRNA Gm12664-001 ameliorates nonalcoholic fatty liver through modulating miR-295-5p and CAV1 expression. Nutr. Metab. (Lond.). 17:13. doi: 10.1186/s12986-020-0430-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Zhang, Y., J.  Zhou, S.  Liu, and Z.  Ji. . 2022. MAPK1 is regulated by LOC102188416/miR-143-3p axis in dairy goat mammary epithelial cells. Genes. 13:1013. doi: 10.3390/genes13061013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Zheng, X., C.  Ning, P.  Zhao, W.  Feng, Y.  Jin, L.  Zhou, Y.  Yu, and J.  Liu. . 2018. Integrated analysis of long noncoding RNA and mRNA expression profiles reveals the potential role of long noncoding RNA in different bovine lactation stages. J. Dairy Sci. 101:11061–11073. doi: 10.3168/jds.2018-14900. [DOI] [PubMed] [Google Scholar]
  56. Zhu, C., Y.  Jiang, J.  Zhu, Y.  He, H.  Yin, Q.  Duan, L.  Zhang, B.  Cao, and X.  An. . 2020. CircRNA8220 sponges MiR-8516 to regulate cell viability and milk synthesis via Ras/MEK/ERK and PI3K/AKT/mTOR pathways in goat mammary epithelial cells. Animals (Basel). 10:1347. doi: 10.3390/ani10081347. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Zou, D., L.  Liu, Y.  Zeng, H.  Wang, D.  Dai, and M.  Xu. . 2022. LncRNA MEG3 up-regulates SIRT6 by ubiquitinating EZH2 and alleviates nonalcoholic fatty liver disease. Cell Death Discov. 8:103. doi: 10.1038/s41420-022-00889-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Zuo, X., Z.  Chen, W.  Gao, Y.  Zhang, J.  Wang, J.  Wang, M.  Cao, J.  Cai, J.  Wu, and X.  Wang. . 2020. M6A-mediated upregulation of LINC00958 increases lipogenesis and acts as a nanotherapeutic target in hepatocellular carcinoma. J. Hematol. Oncol. 13:5. doi: 10.1186/s13045-019-0839-x. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Articles from Journal of Animal Science are provided here courtesy of Oxford University Press

RESOURCES