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. 2026 Jun 23;27:738. doi: 10.1186/s12864-026-13071-5

Comparative transcriptome analysis of Qinchuan and Wagyu cattle reveals lnc11599 as a negative regulator of intramuscular fat deposition

Juntao Guo 1,#, Jiawei Du 1,#, Haobin Ma 1,#, Jianfang Wang 1, Abebe Belete Kuraz 1, Shengchen Yu 1, Ke Zhang 1, Haibing Liu 1, Diba Dedacha Jilo 1, Chugang Mei 1,3, Wucai Yang 1,2, Gong Cheng 1,2, Linsen Zan 1,2,✉
PMCID: PMC13548640  PMID: 42337409

Abstract

Background

Intramuscular fat (IMF) content is a critical factor determining beef quality, influenced by various factors including breed and age. However, the regulatory role of long non-coding RNAs (lncRNAs) in IMF deposition remains unclear.

Methods

This study investigated IMF deposition in the longissimus dorsi muscle of one- and two-year-old Qinchuan and Wagyu cattle through histological examination and fat content measurement. Based on transcriptome sequencing data of intramuscular fat tissue, differential expression analysis and weighted gene co-expression network analysis (WGCNA) were performed to identify lncRNAs associated with IMF deposition. The effects of a key candidate lncRNA on the adipogenic differentiation of cattle intramuscular preadipocytes were further examined.

Results

Results showed that Wagyu cattle exhibited stronger IMF deposition capacity than Qinchuan cattle across all age groups, with IMF content increasing with age in both breeds. We identified 7,910 lncRNAs from intramuscular fat tissue transcriptome data, including 6,455 novel lncRNAs. Through integrated differential expression analysis and WGCNA, 88 lncRNAs closely associated with IMF deposition were screened from two-year-old Qinchuan and Wagyu cattle. Notably, lnc11599 was significantly upregulated in Qinchuan cattle intramuscular fat tissue, but its expression decreased during intramuscular preadipocyte differentiation. Functional experiments demonstrated that lnc11599 knockdown enhanced adipogenic differentiation capacity, manifested as a highly significant increase in lipid accumulation, upregulation of key adipogenic genes at the mRNA level, together with increases in total fatty acid content and unsaturated fatty acid proportion.

Conclusions

This study established the lncRNA expression profiles in intramuscular fat tissue of Qinchuan and Wagyu cattle across different developmental stages, and demonstrated that lnc11599 acts as a negative regulator of intramuscular fat deposition. These findings provide new directions for elucidating the mechanisms of cattle IMF deposition and offer potential targets for genetic improvement of beef quality.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12864-026-13071-5.

Keywords: Qinchuan cattle, Wagyu cattle, Transcriptome, lncRNA, WGCNA, Intramuscular fat deposition

Background

Intramuscular fat (IMF), commonly referred to as marbling, is a critical characteristic of beef quality that affects tenderness, juiciness, flavor, and consumer preference. IMF deposition is influenced by multiple factors including genetics, nutrition, management, and age [14], among which breed and age are recognized as two of the primary intrinsic determinants [4, 48]. Current research indicates that Wagyu cattle exhibit significantly superior marbling compared to Chinese indigenous cattle [43, 46]. However, the molecular mechanisms underlying this difference, particularly the regulatory role of long non-coding RNAs (lncRNAs), remain incompletely understood.

Long non-coding RNAs (lncRNAs) are a class of RNA molecules longer than 200 nucleotides with limited coding potential [40, 49]. They are widely involved in various biological processes such as cell proliferation [15, 44], differentiation [12], adipogenesis [21], and lipid metabolism [41]. These molecules fine-tune gene expression through multi-layered mechanisms, including chromatin remodeling [25], transcriptional regulation [42], and post-transcriptional regulation [23]. Although the functions of many lncRNAs have been characterized in model organisms such as humans [22, 36, 37] and mice [13], their roles in IMF deposition in cattle remain insufficiently studied. Especially, research on lncRNA expression profiles in intramuscular fat tissue across different cattle breeds and age stages is still lacking, which limits our comprehensive understanding of the genetic and epigenetic mechanisms underlying valuable economic traits in Chinese local cattle.

To systematically identify key lncRNAs affecting IMF deposition in cattle, this study selected Qinchuan cattle and Wagyu cattle at different age stages as research subjects. We integrated histomorphological analysis, fat content measurement, and transcriptome sequencing to analyze the dynamics of IMF deposition and construct a global lncRNA expression profile. Using weighted gene co-expression network analysis (WGCNA), we identified key modules significantly associated with fat deposition phenotypes and selected a novel candidate lncRNA, lnc11599. Experimental validation confirmed the important regulatory role of lnc11599 in adipogenesis. This study provides new evidence from an epigenetic perspective for elucidating the molecular mechanisms underlying intramuscular fat traits. The key lncRNAs identified here not only offer a valuable theoretical foundation for the innovative utilization of genetic resources in Chinese indigenous cattle but also have practical significance for improving beef quality through molecular design breeding strategies.

Materials and methods

Tissue sample collection

In this study, 12 male Qinchuan and Wagyu cattle, raised under uniform feeding conditions at the National Beef Cattle Improvement Center of Northwest A&F University, were used. All animals were healthy and had similar body weights within the same age group. The cattle were divided into four groups based on breed and age: one-year-old Qinchuan cattle (QC1, n = 3), two-year-old Qinchuan cattle (QC2, n = 3), one-year-old Wagyu cattle (JB1, n = 3), and two-year-old Wagyu cattle (JB2, n = 3). After slaughter, tissue samples including the heart, liver, spleen, lungs, kidneys, perirenal fat, longissimus dorsi muscle, and intramuscular fat tissue from the longissimus dorsi muscle were collected and snap-frozen in liquid nitrogen. It is worth noting that samples of the longest dorsal muscle were collected from the 12th to 13th rib area on the left side of each cattle carcass.

Isolation of cattle intramuscular preadipocytes

Intramuscular preadipocytes were isolated and cultured from the longissimus dorsi muscle of three Qinchuan calves following a previously established method with minor modifications [18, 19]. Specifically, the longissimus dorsi muscle tissue was minced, and digested with 0.1% type I collagenase (Sigma-Aldrich, St. Louis, USA) at 30 °C for 1 h, followed by the addition of an equal volume of complete medium to terminate digestion. The complete medium consisted of 90% DMEM/F12 (Hyclone, Logan, USA), 10% fetal bovine serum (PAN Biotech, Aidenbach, Germany), 100 U/mL penicillin, and 100 μg/mL streptomycin (Hyclone, Logan, USA). The cell suspension was filtered through a 40 μm cell strainer and centrifuged to collect the cell pellet. The pellet was washed twice with serum-free DMEM/F12, resuspended in complete medium, and seeded into culture dishes. The cells were cultured at 37 °C in a 5% CO₂ atmosphere. After 2 h, the medium and non‑adherent cells were discarded, and the cells were washed three times with PBS. Fresh complete medium was added, and the medium was subsequently changed every 2 days. When cell confluence reached approximately 90%, the cells were digested with 0.25% trypsin (Sigma-Aldrich, St. Louis, USA), and an equal volume of complete medium was added to terminate digestion. The cells were collected by centrifugation, resuspended, and seeded into new culture dishes for subsequent interference and adipogenic differentiation experiments.

H&E staining

Samples of the longissimus dorsi muscle were fixed in 4% paraformaldehyde (Solarbio, Beijing, China) for 72 h, followed by dehydration using a graded ethanol series and clearing with xylene. The tissues were subsequently immersed in molten paraffin for embedding. The embedded blocks were sectioned into 4 μm thick slices utilizing a Leica microtome. Deparaffinization and rehydration were conducted using xylene and a series of graded ethanol solutions. Following staining with hematoxylin and eosin, the sections underwent dehydration via an ethanol gradient and were subsequently cleared in xylene. The samples were subsequently mounted with resin and examined under a microscope (Olympus, Tokyo, Japan).

Fat content detection

A 50 g sample of cattle longissimus dorsi muscle was collected, and surface connective tissue, fat, blood vessels, and fascia were removed. The sample was then thoroughly minced and homogenized using a meat grinder (Royalstar, Hefei, China) to achieve homogenization of the entire muscle. Fat content was determined according to the China National Determination of Fat in Foods Standards (GB 5009.6–2016) [8]. Each sample was measured in triplicate, and the arithmetic mean of the three independent measurements was taken as the final fat content value.

RNA-seq

Intramuscular fat tissue from one- and two-year-old Qinchuan and Wagyu cattle was ground in liquid nitrogen, and total RNA was isolated with TRIzol reagent (Invitrogen, CA, USA). The concentration, purity, and integrity of RNA were evaluated using the NanoDrop® spectrophotometer (Thermo Scientific, MA, USA) and the Agilent 2100 Bioanalyzer (Agilent Technologies, CA, USA), respectively. Ribosomal RNA was eliminated with the Ribo-Zero™ Kit (Illumina, CA, USA). The residual RNA was broken and reverse-transcribed into complementary DNA (cDNA). After synthesizing double-stranded cDNA, ligating adapters, and selecting fragment sizes, a strand-specific library was created and underwent paired-end sequencing (PE150) on the Illumina NovaSeqTM 6000 platform (Illumina, CA, USA).

Raw sequencing data were processed with Cutadapt (version 1.9.0) [28] to eliminate adapters and low-quality reads. Data quality was assessed using FastQC (version 0.10.1). High-quality clean reads were aligned to the bovine reference genome (ARS-UCD1.2) using HISAT2 (version 2.2.1) [16]. Transcript assembly was performed with StringTie (version 2.1.6) [30], after which known mRNAs and transcripts shorter than 200 bp were filtered out. Novel lncRNAs were predicted using CPC (version 0.9-r2) [14] and CNCI (version 2.0) [35]. Gene expression levels were quantified using FPKM values.

Differential expression analysis was conducted using DESeq2 (version 1.22.2) [24], with thresholds set at |log₂FC|> 1 and FDR-adjusted q-value < 0.05 after Benjamini‑Hochberg correction for multiple testing. Cis-target genes of differentially expressed lncRNAs were identified within 100 kb upstream and downstream regions. GO term annotation and KEGG pathway analysis were carried out using DAVID (https://davidbioinformatics.nih.gov/) and KOBAS (http://bioinfo.org/kobas), respectively, using a significance threshold of q-value < 0.05.

WGCNA analysis

To construct a weighted gene co-expression network, a screening of the lncRNA expression matrix was first performed, retaining the top 75% of genes with a median absolute deviation greater than 0.01 for subsequent analysis. The gene expression values were then transformed using log₂ (FPKM + 1), and the co-expression network was built based on the transformed data. All analyses were conducted in the RStudio environment (http://www.rstudio.org) using R 4.0.2 and the WGCNA (version 1.73) package from Bioconductor.

First, a weighted adjacency matrix was constructed according to the formula aₘₙ =|cor (m, n)|^β, where aₘₙ represents the connection strength between genes m and n, cor(m, n) denotes their Pearson correlation coefficient, and β is the soft threshold parameter. To enable a more precise assessment of gene similarity, the adjacency matrix was subsequently transformed into a Topological Overlap Matrix (TOM). Hierarchical clustering was performed based on the TOM to identify co-expression modules. The clustering parameters were set as follows: minModuleSize = 100, and a module merge threshold of 0.25 (i.e., modules with cor ≥ 0.75 were merged). Correlations between modules and samples were estimated based on the TOM, with screening criteria set at |cor|> 0.5 and P < 0.01. Genes within the same module generally exhibit high topological overlap.

To further evaluate the importance of genes within modules and in relation to phenotypes, this study incorporated gene significance (GS), which measures the correlation between a gene and a specific trait, and module membership (MM), which reflects the representativeness and contribution of a gene within its assigned module. Genes simultaneously satisfying MM > 0.8, GS > 0.7, and a weighted P-value (P.weighted) < 0.001 were identified as hub genes within the co-expression network.

RT-qPCR analysis

Total RNA was extracted from tissue samples and intramuscular preadipocytes using TRIzol reagent. The RNA was reverse-transcribed into cDNA using the Evo M-MLV RT Reaction Mix kit (Agbio, Hunan, China). Gene expression levels were quantified by quantitative PCR (qPCR) using PerfectStart Green qPCR SuperMix (TransGen Biotech, Beijing, China) on a CFX Connect Real-Time PCR Detection System, with cDNA as the template. The relative expression of target genes was calculated using the 2−ΔΔCT method, with β-actin serving as the internal reference gene. The primers used are listed in Additional file 3.

Prediction of lncRNA coding potential

The online tool CPC2.0 (http://cpc2.gao-lab.org) was used to assess the coding potential of lncRNA sequences.

Transient transfection and adipogenic differentiation induction of cattle intramuscular preadipocytes

When intramuscular preadipocytes reached approximately 50% confluence, siRNA was transfected into the cells using Lipofectamine 3000 reagent (Invitrogen, CA, USA) according to the manufacturer's instructions. Intramuscular preadipocytes were harvested 24 h post-transfection for evaluation of knockdown efficiency. The siRNA was synthesized by Sangon Biotech (Shanghai, China), and its sequence information is provided in Additional file 4.

Furthermore, after the intramuscular preadipocytes reached full confluence, they were induced to differentiate for two days using induction differentiation complete medium containing 0.5 mM 3-isobutyl-1-methylxanthine, 1 μM dexamethasone, and 10 μg/mL insulin (all from MedChemExpress, NJ, USA). Thereafter, the medium was replaced with a complete medium supplemented with 10 μg/mL insulin to support continued adipogenic differentiation, with the medium being refreshed every two days.

Assessment of adipogenic capacity of intramuscular preadipocytes

After 6 days of induction and differentiation of intramuscular adipocytes, the cells were washed three times with PBS and fixed with 4% paraformaldehyde for 30 min. The cells were then stained with Oil Red O, Bodipy, and Nile red, respectively. The Oil Red O staining was performed for 30 min, while Bodipy and Nile red staining were each carried out for 10 min. After staining, the cells were thoroughly washed three times with PBS, and images were acquired using an optical microscope (Olympus, Tokyo, Japan).

To further quantify lipid content, isopropanol was added to the Oil Red O-stained samples for extraction for 30 min. The absorbance was measured at a wavelength of 510 nm using an Infinite M200 PRO microplate reader (Tecan, Männedorf, Switzerland) to quantify the Oil Red O content.

Determination of fatty acid content in intramuscular preadipocytes

After intramuscular preadipocytes were cultured under adipogenic differentiation conditions for 6 days to become mature adipocytes, the cells were washed three with PBS and then lysed using 2 mL of a 2.5% sulfuric acid‑methanol solution. The cell suspensions were subjected to sonication, and fatty acids were methylated in a water bath at 80 °C for 1 h. Subsequently, 2 mL of 0.1 M hydrochloric acid and 800 μL of n-hexane were introduced to extract fatty acid methyl esters [38]. Extracts were desiccated using anhydrous sodium sulfate and then evaluated using gas chromatography employing an Agilent 7890B system with a flame ionization detector (FID).

Statistical analysis

All data are presented as the mean ± standard deviation (SD). Statistical analysis and graph generation were performed using GraphPad Prism 10 (GraphPad Software, CA, USA). Comparisons between two groups were performed using Student's t-test, while comparisons among multiple groups were performed using one-way ANOVA with Tukey's multiple comparison test. Each dataset was derived from at least three independent biological replicates. *P < 0.05 indicates a significant difference, and **P < 0.01 indicates a highly significant difference.

Results

Effects of breed and age on intramuscular fat deposition

To investigate the effects of breed and age on intramuscular fat deposition in cattle, this study conducted morphological cross-sectional observation, H&E staining analysis, and fat content measurement on the longissimus dorsi muscle of Qinchuan cattle and Wagyu cattle at different age stages. The results showed that the number, spatial distribution, and content of intramuscular adipocytes in the longissimus dorsi muscle of both cattle breeds increased significantly with age. Furthermore, at the same age stage, the longissimus dorsi muscle of Wagyu cattle exhibited a higher number of intramuscular adipocytes, a denser distribution, and a significantly higher fat content compared to Qinchuan cattle (P < 0.01) (Fig. 1A, B).

Fig. 1.

Fig. 1

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Comparison analysis of intramuscular fat distribution and content in the longissimus dorsi muscle of Qinchuan and Wagyu cattle at different ages. A H&E staining of the longissimus dorsi muscle; scale bar = 275 µm. B Intramuscular fat content of the longissimus dorsi muscle (n = 3). Data were analyzed by one-way ANOVA with Tukey's multiple comparison test. ** P < 0.01 indicates a highly significant difference

Characterization and identification of lncRNAs in cattle intramuscular fat tissue

Analysis of RNA-Seq data from the intramuscular fat tissue of one- and two-year-old Qinchuan and Wagyu cattle revealed that the raw reads ranged from 80,457,210 to 90,943,020. After quality control filtering, the clean reads ranged from 7,473,192 to 86,923,608, with an average valid read rate of 92.88%. The Q30 values for all samples were no less than 97.00% (Additional file 1). After alignment with the cattle reference genome, the mapping rate for each sample exceeded 95%, and over 93% of the high-quality clean reads were uniquely mapped to specific genomic regions (Additional file 2). These results indicate that the sequencing data are of high quality, meet the standards for transcriptome analysis, and are suitable for further in-depth research.

A total of 7,910 lncRNAs were discovered, including 1,455 known and 6,455 novel lncRNAs (Fig. 2A). Novel lncRNAs were categorised based on chromosomal position into intergenic, intronic, antisense, and other classifications. Among these, intronic lncRNAs were the most abundant, accounting for 43.21% of the total (Fig. 2B). In comparison to mRNAs, lncRNAs exhibited a reduced number of exons (Fig. 2C), abbreviated open reading frames (ORFs) (Fig. 2D), and shorter transcript lengths (Fig. 2E, F), aligning with the recognised structural characteristics of lncRNAs. These data support the reliability of the lncRNA identification result.

Fig. 2.

Fig. 2

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Characterization and identification of lncRNAs in cattle intramuscular fat tissue. A CPC and CNCI evaluate the coding ability of candidate lncRNAs. B Classification and proportions of lncRNAs. C The distribution of exon numbers for lncRNA and mRNA. D Length distribution of ORFs for lncRNA and mRNA. E Transcript length distribution of lncRNA. F Transcript length distribution of mRNA. i: intronic lncRNAs. u: intergenic lncRNAs. o: sense lncRNAs. x: antisense lncRNAs. j: at least one splice junction is shared with a reference transcript

Differentially expressed lncRNAs in cattle intramuscular fat tissue

Differentially expressed lncRNAs were identified using threshold criteria of |log2FC|≥ 1 and q-value < 0.05. In intramuscular fat tissue from cattle of different age groups, 777 differentially expressed lncRNAs were detected in QC2 vs. QC1 comparison, with 498 up-regulated and 279 down-regulated in QC2 cattle (Fig. 3A, E). Similarly, the JB2 vs. JB1 comparison revealed 510 differentially expressed lncRNAs, of which 236 were up-regulated and 274 were down-regulated in JB2 comparison (Fig. 3B, E).

Fig. 3.

Fig. 3

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Differential expression analysis of lncRNAs in cattle intramuscular fat tissue. A-D Differential expression analysis of lncRNAs in different groups. E The numbers of differentially expressed lncRNAs in different groups. F Differential expression lncRNA clustering heatmap

Comparative analysis of cattle breeds identified 545 differentially expressed lncRNAs in the QC2 vs. JB2 comparison, with 350 upregulated and 195 downregulated in Qinchuan cattle (Fig. 3E). In the QC1 vs. JB1 comparison, 590 differentially expressed lncRNAs were detected, of which 276 were upregulated and 314 were downregulated in Qinchuan cattle (Fig. 3D, E). Additionally, a clustering heatmap was generated to visualize the expression patterns of the top 100 most significantly differentially expressed lncRNAs based on q-value (Fig. 3F).

Quantitative validation of differentially expressed lncRNAs in cattle intramuscular fat tissue

Six differentially expressed LncRNAs were randomly selected for RT-qPCR validation (Fig. 4). The experimental results showed high consistency with the transcriptome sequencing data, providing additional evidence for the reliability of the sequencing data in this study.

Fig. 4.

Fig. 4

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RT-qPCR validation of differentially expressed lncRNAs in cattle intramuscular fat tissue. RT-qPCR results are shown as gray bars, and RNA-seq results are shown as red bars. *P < 0.05 indicates a significant difference, and **P < 0.01 indicates a highly significant difference

Screening of differentially expressed lncRNAs related to intramuscular fat deposition using WGCNA

To identify lncRNAs closely associated with intramuscular fat deposition, this study constructed a WGCNA based on the expression matrix of 7,910 lncRNAs identified from 12 samples. The optimal soft threshold was determined using the pickSoftThreshold function in the WGCNA package. When the scale-free topological fit index R2 reached 0.9, the corresponding soft threshold β was set to 9 (Fig. 5A). Gene modules were identified using a dynamic tree-cutting algorithm, and similar modules were merged with a merge threshold of 0.25, resulting in a total of 12 co-expression modules (Fig. 5B).

Fig. 5.

Fig. 5

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WGCNA analysis of lncRNA. A Determination of soft-thresholding power. When β = 9, R2 > 0.9, and mean connectivity < 500, the network was scale-free topology. B The Cluster dendrogram of co-expression network modules. C The module trait relationship heatmap displays the correlation coefficients between each module and the intramuscular fat content of cattle. D Scatter plot of the correlation between gene significance (GS) and module members (MM) in important modules

Correlation analysis between gene modules and sample groups revealed that the MEbrown module was significantly positively correlated with the JB1 (cor = 0.97, P = 2e-07), MEmagenta was significantly positively correlated with the JB2 (cor = 0.76, P = 0.004), MEred was significantly positively correlated with the QC1 group (cor = 0.94, P = 4e-06), MEgreenyellow was significantly positively correlated with the QC2 (cor = 0.99, P = 4e-09) (Fig. 5C). This study further investigated the correlation between gene significance (GS) and module membership (MM). The results revealed highly significant positive correlations between GS and MM across the modules, specifically in MEbrown (cor = 0.94, P < 1e-200), MEmagenta (cor = 0.52, P = 3.5e-22), MEred (cor = 0.87, P = 3.2e-105), and MEgreenyellow (cor = 0.97, P = 1.3e-182) (Fig. 5D). These findings indicate that the lncRNAs within these modules are strongly associated with intramuscular fat, further suggesting their important biological functions in regulating intramuscular fat deposition.

Given that two-year-old Wagyu and Qinchuan cattle exhibit significantly enhanced fat deposition capacity compared to one-year-old individuals, subsequent research prioritized the analysis of the MEmagenta and MEgreenyellow modules associated with these two-year-old cattle to identify differentially expressed lncRNAs related to intramuscular fat deposition. Through overlap analysis of the MEmagenta and MEgreenyellow modules with differentially expressed lncRNAs between two-year-old Qinchuan and Wagyu cattle, a total of 88 differentially expressed lncRNAs potentially highly associated with fat deposition were identified (Fig. 6A, B). Functional enrichment analysis showed that the target genes of these differentially expressed lncRNAs were mainly enriched in biological processes such as lipid localization and fatty acid transport, as well as pathways such as linoleic acid metabolism and glycerophospholipid metabolism (Fig. 6C, D). These findings suggest that these lncRNAs may play a critical role in intramuscular fat deposition in cattle by regulating lipid metabolism and transport processes.

Fig. 6.

Fig. 6

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Screening of lncRNAs related to intramuscular fat deposition. A Overlapping lncRNAs of differential lncRNAs (QC2 vs.JB2) and co expression modules (JB2-Magenta, QC2-greenwellow). B Cluster heatmap of lncRNAs associated with intramuscular fat deposition. C Functional enrichment analysis of target genes of lncRNAs associated with intramuscular fat deposition. D KEGG enrichment analysis of target genes of lncRNAs associated with intramuscular fat deposition

Identification and characterization of lnc11599

Compared to two-year-old Wagyu cattle, the expression of lncRNA MSTRG.11599.1 was significantly up-regulated in the intramuscular fat tissue of two-year-old Qinchuan cattle (P < 0.01), while no significant differences in expression were observed in subcutaneous fat, perirenal fat, or longissimus dorsi muscle (Fig. 7A). Multi-tissue expression profiling revealed that this lncRNA was expressed at relatively high levels in the longissimus dorsi muscle, heart, and intramuscular fat tissue of Qinchuan cattle (Fig. 7B). Notably, during the induced differentiation of intramuscular precursor adipocytes from Qinchuan cattle, the expression of MSTRG.11599.1 showed a gradual decreasing trend along with the differentiation process (Fig. 7C). Taken together, these results indicate that lncRNA MSTRG.11599.1 exhibits breed‑ and tissue‑specific expression patterns as well as dynamic changes during adipogenesis, suggesting a potential regulatory role in intramuscular adipocyte differentiation and lipid deposition in cattle. Therefore, this lncRNA was selected for subsequent functional studies.

Fig. 7.

Fig. 7

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Identification of lnc11599. A Relative expression levels of MSTRG.11599.1 in muscle and fat tissue of Qinchuan cattle and Wagyu cattle. B Expression profile of MSTRG.11599.1 in Qinchuan adult cattle tissues. C Temporal expression of MSTRG.11599.1 in cattle intramuscular preadipocytes. D Prediction of encoding potential for MSTRG.11599.1. E Localization of MSTRG.11599.1. F Knockdown efficiency of lnc11599. *P < 0.05 indicates a significant difference, and **P < 0.01 indicates a highly significant difference. Different letters indicate significant differences among groups

Coding potential prediction results indicated that the coding capacity of lncRNA MSTRG.11599.1 is lower than that of the protein-coding gene GAPDH and the known long non-coding RNA H19, further supporting its classification as a non-coding RNA (Fig. 7D). Subcellular localization analysis demonstrated that MSTRG.11599.1 is distributed in both the nucleus and cytoplasm of intramuscular preadipocytes (Fig. 7E). Based on these findings, we have officially designated this lncRNA as lnc11599. After 24 h of siRNA-mediated knockdown, the expression level of lnc11599 was significantly reduced by 50% (P < 0.01) (Fig. 7F).

Effects of lnc11599 knockdown on adipogenic differentiation of cattle intramuscular preadipocytes

Cattle intramuscular preadipocytes underwent siRNA-mediated knockdown of lnc11599 for 24 h, followed by 6 days of adipogenic induction. Oil Red O, BODIPY, and Nile Red staining demonstrated increased lipid droplet deposition in knockdown cells (Fig. 8A), corroborated by quantitative Oil Red O analysis (P < 0.01) (Fig. 8B).

Fig. 8.

Fig. 8

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Lnc11599 affects adipogenesis of cattle intramuscular preadipocytes. A Oil red O, BODPY, Nile red staining detection of lipogenic ability of cattle intramuscular preadipocytes. B Oil Red O staining quantitative detection. C RT-qPCR detection of differentiation related gene changes. D Changes in total fatty acid content. E Changes in fatty acid composition. *P < 0.05 indicates a significant difference, and **P < 0.01 indicates a highly significant difference

RT-qPCR analysis demonstrated a considerable overexpression of essential adipogenic genes, including C/EBPα (P < 0.05), DGAT1, and SCD1(P < 0.01) (Fig. 8C). Analysis of fatty acid composition revealed that the knockdown of lnc11599 increased total fatty acid content (P < 0.01) and the ratio of unsaturated fatty acids (Fig. 8D, E). The findings indicate that lnc11599 functions as a negative regulator of adipogenesis in cattle intramuscular preadipocytes by influencing the expression of genes, and lipid metabolism associated with adipogenesis.

Discussion

The quantity of intramuscular fat (IMF) is a crucial factor in determining beef quality, affecting marbling, flavour, and juiciness [10, 34]. In the present study, phenotypic analyses confirmed that both breed and age significantly influenced IMF deposition. At the same age, the longissimus dorsi of Wagyu cattle contained more intramuscular adipocytes with a denser distribution and a higher fat content than that of Qinchuan cattle. This finding is consistent with the view that Wagyu cattle have a stronger capacity for fat deposition and a greater potential for marbling formation. In addition, IMF deposition increased with age in both breeds, indicating that IMF formation follows a clear developmental pattern. As a dynamic and progressive process, IMF accumulation depends not only on the differentiation of precursor adipocytes into mature adipocytes, but also on subsequent triglyceride synthesis, lipid droplet expansion, and continuous lipid storage [9, 29].

Long non-coding RNAs (lncRNAs) have become essential regulators of adipogenesis and lipid metabolism, influencing preadipocyte proliferation, differentiation, and fat production via several molecular processes [17, 21, 39, 45, 47]. Although lncRNAs have been widely studied in various cattle fat tissues [31], including subcutaneous fat and perirenal fat, their expression profile and function in cattle intramuscular fat remain inadequately elucidated. This work used RNA-Seq analysis to identify 7,910 lncRNAs in intramuscular fat tissue, including 6,455 novel transcripts, substantially expanding the bovine non-coding RNA resource. Compared with mRNAs, these lncRNAs generally exhibited typical molecular features, including fewer exons, shorter transcript length, and shorter open reading frames, indicating that the identified transcripts were overall consistent with the defining characteristics of lncRNAs [26]. More importantly, large numbers of differentially expressed lncRNAs were found across both developmental stages and breeds, suggesting that IMF deposition is influenced by extensive changes in non-coding transcriptional regulation. Notably, during developmental stage comparisons, Qinchuan cattle (QC2 vs QC1, 777) showed a greater number of differentially expressed lncRNAs than Wagyu cattle (JB2 vs JB1, 510), suggesting that Qinchuan cattle may undergo more extensive transcriptional regulatory remodeling during the transition from IMF development to maturity. Moreover, interbreed differences in lncRNA expression were more pronounced at the juvenile stage (QC1 vs JB1, 590) than at the adult stage (QC2 vs JB2, 545), indicating that the influence of genetic background on lncRNA expression may be more prominent during early development. Collectively, these results indicate that lncRNA expression profiles are jointly regulated by genetic background (breed) and developmental stage (age).

WGCNA categorizes genes into several co-expression modules based on gene expression synergy and correlates them with target phenotypes, thereby identifying biologically significant gene clusters on the basis of dimensionality reduction [18, 19]. Given that the difference in IMF content between Qinchuan and Wagyu cattle was most pronounced at two years of age, this study focused on two-year-old Qinchuan and Wagyu cattle and employed an integrated strategy combining differential expression analysis with WGCNA, ultimately identifying 88 candidate lncRNAs potentially involved in IMF regulation. Compared with differential expression analysis or WGCNA alone, this integrative strategy simultaneously considers expression variation and phenotype association, thereby improving the biological relevance of the screened candidates [33]. Enrichment analysis of cis-target genes revealed their roles in lipid localisation, transport, and fatty acid metabolism, further indicating that these candidate lncRNAs may participate in the regulation of lipid synthesis, transport, and storage during intramuscular fat deposition.

In recent years, several lncRNAs involved in bovine fat deposition have been identified. For example, ADNCR and BADLNCR1 have been reported to inhibit adipogenic differentiation [6, 20], whereas lncFAM200B and BIANCR are associated with adipocyte proliferation or the promotion of adipogenesis [27, 44]. In the present study, MSTRG.11599.1, designated as lnc11599, was identified as a key candidate lncRNA for further validation. Compared with two-year-old Wagyu cattle, lnc11599 expression was significantly upregulated in the intramuscular fat tissue of two-year-old Qinchuan cattle, while its expression continuously decreased during adipogenic differentiation of cattle intramuscular preadipocytes in vitro. This expression pattern suggests that lnc11599 may act as a negative regulator during adipogenesis. Functional assays indicated that the knockdown of lnc11599 promoted adipogenic differentiation and lipid accumulation, as demonstrated by enhanced Oil Red O, BODIPY, and Nile red staining, upregulation of adipogenic genes (C/EBPα, DGAT1, SCD1), along with elevated total fatty acid content and a higher proportion of unsaturated fatty acids. Previous studies have shown that C/EBPα forms a positive feedback regulatory loop with PPARγ, synergistically activating the expression of multiple adipogenesis-related genes, thereby accelerating terminal adipocyte differentiation and lipid accumulation [32]. Additionally, SCD1 (stearoyl-CoA desaturase 1) catalyzes the conversion of saturated fatty acids to monounsaturated fatty acids, directly affecting adipocyte differentiation and lipid droplet formation [3, 45, 47]. FASN (fatty acid synthase) promotes de novo fatty acid synthesis, and its polymorphisms affect cattle fatty acid composition [5, 11]. FABP4 (fatty acid binding protein 4), as an adipokine, binds to long-chain fatty acids and promotes their transport across cell membranes [1, 2], and DGAT1 (diacylglycerol O-acyltransferase 1) directly participates in triglyceride synthesis and promotes lipid droplet expansion [7]. Therefore, the phenotype observed after lnc11599 knockdown suggests that this lncRNA may enhance adipogenic differentiation of bovine intramuscular preadipocytes by regulating adipogenic transcriptional programs, fatty acid desaturation, and triglyceride synthesis. Moreover, the increase in the proportion of unsaturated fatty acids suggests that lnc11599 may influence not only the overall level of lipid deposition, but also fatty acid composition, thereby potentially affecting meat quality-related traits.

Although this study systematically compared the differences in intramuscular fat deposition between Qinchuan cattle and Wagyu cattle at different age stages, identified key lncRNAs, and conducted preliminary functional validation, certain limitations remain. For instance, further studies are needed to elucidate the mechanism of lnc11599 and validate its function in vivo using animal models.

Conclusion

This study established the lncRNA expression profiles of intramuscular fat tissue in Qinchuan and Wagyu cattle at different developmental stages and revealed the dynamic expression patterns of lncRNAs during IMF formation. By integrating differential expression analysis and WGCNA, a total of 88 candidate lncRNAs potentially involved in IMF regulation were identified. Further functional validation suggested that lnc11599 is a candidate negative regulator of intramuscular fat deposition in cattle, and its knockdown significantly promoted adipogenic differentiation, lipid accumulation, and the proportion of unsaturated fatty acids. These findings provide new molecular evidence for elucidating the non-coding regulatory mechanisms underlying bovine IMF deposition.

Supplementary Information

Supplementary Material 1. (14KB, docx)
Supplementary Material 2. (14KB, docx)
Supplementary Material 3. (15.1KB, docx)
Supplementary Material 4. (13.1KB, docx)

Abbreviations

RNA-Seq

RNA sequencing

RT-qPCR

Reverse transcription quantitative PCR

GO

Gene Ontology

KEGG

Kyoto Encyclopedia of Genes and Genomes

H&E staining

Hematoxylin and eosin staining

WGCNA

Weighted gene co-expression network analysis

TOM

Topological overlap matrix

GS

Gene significance

MM

Module membership

IMF

Intramuscular fat

lncRNAs

Long non-coding RNAs

Authors’ contributions

GJT performed writing—original draft, validation, formal analysis, software operation, data curation. DJW, MHB carried out material preparation, validation, and formal analysis. WJF conducted material preparation, validation, software operation, and data curation. ABK, YSC, ZK, LHB, and DDJ was responsible for material preparation and validation. MCG was involved in methodology, investigation, and conceptualization. CC, YWC performed writing—review & editing, supervision. ZLS performed project administration, investigation, and conceptualization. All authors have read and approved the final manuscript.

Funding

This study was funded by the Natural Science Foundation of China (2023YFD1300101, 2023YFD1300103), Science and Technology Special Project of the Ministry of Agriculture and Rural Affairs (19240922, 22250059), Shaanxi Livestock and Poultry Breeding Double‐chain Fusion Key Project (2022GD‐TSLD‐46‐0102), Key Agricultural Technology Tackling Project of Shaanxi Province (K3031224096), the Construction of National Beef Cattle Yak Industry Technology System, China (CARS-37).

Data availability

The full set of raw data from this study was deposited in the National Center for Biotechnology Information’s Sequence Read Archive (SRA) and is accessible through the BioProject ID CRA031628. The link is https://ngdc.cncb.ac.cn/gsa/s/2S34vXAo.

Declarations

Ethics approval and consent to participate

All animal experiments in this study were approved by the Experimental Animal Management Committee (EAMC) of Northwest A&F University (Approval ID: DK2021042), and complied with the organization’s applicable rules and regulations.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Juntao Guo, Jiawei Du, and Haobin Ma contributed equally to this work.

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Associated Data

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

Supplementary Materials

Supplementary Material 1. (14KB, docx)
Supplementary Material 2. (14KB, docx)
Supplementary Material 3. (15.1KB, docx)
Supplementary Material 4. (13.1KB, docx)

Data Availability Statement

The full set of raw data from this study was deposited in the National Center for Biotechnology Information’s Sequence Read Archive (SRA) and is accessible through the BioProject ID CRA031628. The link is https://ngdc.cncb.ac.cn/gsa/s/2S34vXAo.

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