Transcriptomics Reveals L‐Carnitine to Enhance Semen Quality in Malabari Bucks via Nutrigenomic Regulation of Key Biological Processes Associated With Male Fertility

ABSTRACT

Male infertility poses a significant challenge in animal breeding, impacting genetic progress and reproductive efficiency. This study investigated the effects of L‐carnitine supplementation (300 mg/kg basal diet for 105 days) on semen quality and underlying molecular mechanisms in Malabari bucks using a transcriptomic approach. Eight mature bucks (2–3 years) were randomly divided into control and treatment groups (n = 4 each). Semen parameters like semen volume (mL), concentration (10⁶/mL), viability (%), abnormality (%), acrosome integrity (%), plasma membrane integrity (%) and oxidative stress via the Nitro Blue Tetrazolium (NBT) assay were evaluated. For transcriptomic analysis, sperm RNA was isolated, sequenced on the Illumina NovaSeq 6000 platform (150 bp paired‐end), and differentially expressed genes (DEGs) were identified using DESeq2. Functional annotation was performed through GO enrichment and KEGG pathway analysis, whereas hub genes were identified via protein–protein interaction (PPI) analysis using STRING and Cytoscape. A total of 425 DEGs were identified, with 258 upregulated and 167 downregulated. Significant improvements were observed in acrosomal integrity, plasma membrane integrity, and oxidative stress markers following L‐carnitine supplementation. GO enrichment analysis suggested upregulation of biological processes associated with meiotic cell division, sperm structural integrity, DNA repair, and spermatogenesis, alongside downregulation of carbohydrate metabolism pathways and a possible shift toward fatty acid oxidation. KEGG pathway analysis indicated upregulated Polycomb repressive complex pathway, and downregulation of insulin resistance and oestrogen signalling pathways, potentially creating a favourable endocrinological environment for male fertility. The hub genes identified, namely PMS1, ZFAND4, MYSM1, EEFSEC and CEP126, were found to be associated with key processes in male fertility. These findings provide preliminary mechanistic insights into L‐carnitine's potential therapeutic role in small ruminant reproduction, and further functional validation of the identified hub genes is warranted.

1. Introduction

The Malabari goat is known for its adaptability to hot and humid climates, tolerance of diseases, and ability to thrive under low‐input farming systems. These qualities have made it an indispensable resource for smallholder farmers who depend on goats for meat, milk and income. Fertility is a lowly heritable trait, and conventional selective breeding alone is insufficient to achieve significant improvements. For this reason, researchers have been compelled to look beyond traditional breeding strategies and examine the role of nutrition, physiology, and molecular mechanisms in shaping fertility outcomes. In this context, male fertility takes on special importance, as a single buck can influence the genetic makeup and productivity of an entire herd.

Among the major economic traits of livestock, reproductive traits are extremely important; however, they are complex, quantitative, and lowly heritable traits involving multiple genes, loci and interactions (Ahlawat et al. 2012). These traits are influenced not only by genetics but also by non‐genetic factors such as environment, management and nutrition. Nutritional status is a critical modulator of reproduction in sheep and goats (Blache et al. 2008), and non‐genetic factors like nutrition, climate, and management practices significantly impact reproductive performance. This complexity makes the study of male fertility both a challenge and an opportunity in animal science. From the earliest stages of spermatogenesis to the final maturation of spermatozoa, the energy and nutrients available to an animal directly influence sperm quality, motility and functional competence. Over the last two decades, researchers have increasingly recognized that dietary supplementation with specific amino acids, vitamins, and bioactive molecules can enhance reproductive performance in livestock. Among these, L‐carnitine has drawn particular attention. Known primarily for its role in shuttling fatty acids into mitochondria for energy production (Virmani and Cirulli 2022), L‐carnitine also acts as an antioxidant (Jiang et al. 2025), protecting spermatozoa from oxidative stress, a major cause of reduced fertility. Studies in humans and other animals have shown that L‐carnitine supplementation improves sperm concentration, motility and morphology. In livestock species such as poultry, pigs and dairy cows, L‐carnitine supplementation has primarily led to benefits such as enhanced growth performance, improved feed conversion ratios, and reduced fat accumulation (Murali et al. 2015). Studies in roosters, boars and sheep have shown additional benefits, including higher fertility, improved sperm quality during cryopreservation, and greater artificial insemination efficiency (Sharafi et al. 2022). However, its precise influence on the molecular machinery of spermatozoa in goats remains underexplored.

This gap in knowledge becomes especially critical when considered in the context of advances in modern genomic technologies. Sperm cells, though transcriptionally silent after maturation, carry a unique transcriptome which is an ensemble of RNA molecules that are remnants of earlier spermatogenic activity and play critical roles in sperm function, fertilization, and early embryonic development (Guo et al. 2017). High‐throughput sequencing technologies have enabled mapping of these RNA populations with unprecedented depth, revealing not only the functional status of sperm but also potential biomarkers for fertility. By combining nutritional interventions with transcriptomic profiling, it becomes possible to connect diet, molecular signatures, and reproductive outcomes in a way that has never been fully investigated in goats. This study aimed to fill that gap by exploring the transcriptome profile of spermatozoa in bucks supplemented with L‐carnitine, in an attempt to elucidate the molecular mechanisms underlying the effects of L‐carnitine supplementation on male fertility.

2. Materials and Methods

2.1. Ethics

Malabari bucks maintained at the Goat and Sheep Unit, Instructional Livestock Farm Complex, College of Veterinary and Animal Sciences, Pookode, Kerala Veterinary and Animal Sciences University, India, were used for this study. The research work was approved by the university vide order no. KVASU/2023/65/MVP/ABT. Pure L‐carnitine was procured from Biovencer Healthcare Pvt. Ltd., India, and supplemented at the rate of 300 mg/kg basal diet. The animals were individually fed as per ICAR (2013) recommendations, and the feeding trial was continued for 105 days. During the study period, all experimental animals were kept under consistent management conditions with an ample supply of clean drinking water and green fodder.

2.2. Study Design

The study was conducted on eight mature Malabari bucks, aged 2–3 years, which were randomly assigned into two groups of four animals each, designated as control and treatment groups, based on age and body weight. A completely randomized design was employed, with the average body weight of each group being comparable prior to the commencement of the feeding trial. For the transcriptomic study, semen samples were collected from all eight bucks, four each from the control and treatment groups, at the end of the feeding trial. To create biological replicates, semen samples from two animals within the same group were pooled, yielding a total of four pooled samples: two control replicates and two treatment replicates, which were subsequently sequenced on the Illumina NovaSeq 6000 platform.

2.3. Fresh Semen Collection, Evaluation

Semen was collected using an artificial vagina designed for small ruminants (IMV Technologies, France). The artificial vagina was assembled 1 day prior to collection with a smooth neoprene liner, cone, and collection tube, and stored in a hot air oven at 42°C until use. During collection, the artificial vagina was maintained at 42°C with adequate pressure and lubrication using sterilized jelly to stimulate the buck's ejaculatory reflex. A total of 16 ejaculations were collected on Day 0 (prior to supplementation) and Day 105 (end of the feeding trial), with two ejaculates collected from each buck. The selected bucks from each group were allowed to mount a teaser twice for stimulation, and the artificial vagina was gently positioned to collect semen. Immediately after collection, semen samples were placed in a water bath at 37°C for macroscopic and microscopic evaluation. Fresh semen samples were subjected to macroscopic examination of volume, colour and density, and microscopic examination of mass activity, concentration, viability and abnormality (Campbell et al. 1953), plasma membrane integrity and acrosomal integrity (Selvaraju et al. 2008). The data were compared between Day 0 and Day 105 within the treated group, and between control and treated groups on Day 105.

Oxidative stress was assessed by the Nitro Blue Tetrazolium (NBT) assay, with comparison made between control and treated samples on Day 105. Briefly, a 0.1% NBT reagent was prepared by dissolving the powder in 1X PBS (Phosphate Buffered Saline) at pH 7.2. After 1 h of storage at room temperature, the solution was filtered using Whatman filter paper. A 2M solution of KOH (Potassium Hydroxide) in distilled water was prepared separately. The sperm pellet was obtained using gradient centrifugation and subsequently washed with 1 mL of PBS at 300 × g for 5 min. The washing procedure was repeated twice, and following removal of the supernatant, the sperm pellet was resuspended in 200 μL of PBS (pH 7.4). The suspension was divided into 100 μL aliquots, to which an equal volume of 0.1% working NBT reagent was added. The mixture was incubated at 37°C for 50–60 min, resulting in a colour change ranging from purple to light violet. The sample was then washed in 500 μL of PBS by centrifugation at 500 × g for 10 min to ensure complete removal of the remaining NBT solution, retaining only the sperm pellet. Subsequently, 150 μL each of 2M KOH and DMSO (Dimethyl Sulfoxide) were added to solubilize the intracellular formazan of the sperm pellet. The resulting dark blue gel suspension was vortexed and shaken thoroughly to enhance solubilization. The colour reaction was quantified spectrophotometrically at 655 nm, and optical density (OD) values were recorded. Formazan is a chromogenic compound, and an increase in formazan correlates with elevated absorbance, thereby signifying enhanced reactive oxygen species (ROS) generation. Statistical analyses were performed using R software version 4.5.1 (R Core Team 2025). Due to the small sample size, the non‐parametric Wilcoxon‐Mann–Whitney test was employed to compare. A p‐value < 0.05 was considered statistically significant.

2.4. RNA Isolation, Quantification, Quality Assessment and Library Preparation

Total RNA was isolated using TRI reagent (Sigma Aldrich, India) in combination with the RNeasy Mini Kit (Qiagen, India). Briefly, semen samples were vortexed thoroughly in TRI reagent and incubated for 10 min at room temperature, followed by the addition of 200 μL of chloroform. The samples were then centrifuged at 12,000 × g for 15 min at 4°C. The aqueous phase was carefully transferred into a fresh tube, and an equal volume of ice‐cold isopropanol was added, inverted, mixed, and incubated on ice for 10–15 min. The samples were then loaded onto the RNeasy Mini spin column provided in the kit for nucleic acid binding, following which on‐column DNase treatment was performed according to the manufacturer's instructions. RNA was eluted using 30 μL of nuclease‐free water.

RNA quality was assessed using the RNA ScreenTape System on a 2200 TapeStation System (Agilent, USA), and RNA integrity was determined by the RNA Integrity Number equivalent (RINe) values. RNA concentration was quantified using a Qubit 4 Fluorometer (ThermoFisher Scientific, USA) with the Qubit RNA BR Assay Kit. Total RNA samples were subjected to ribosomal RNA (rRNA) depletion using the QIAseq FastSelect rRNA HMR Kit, and sequencing libraries were prepared using the KAPA RNA HyperPrep Kit for Illumina Platforms. Library concentration was determined using a Qubit 4 Fluorometer (Life Technologies, USA) with the Qubit 1X dsDNA HS Assay Kit. Library quality was assessed using the Agilent D1000 ScreenTape and High Sensitivity D1000 ScreenTape Analysis on a 2200 TapeStation System (Agilent, USA).

2.5. Transcriptome Sequencing and Data Analysis

Qualified libraries underwent short‐read sequencing on the Illumina NovaSeq 6000 platform using 150 bp paired‐end (PE) chemistry. A total of 31 GB of raw data were generated from both control and treatment samples in duplicates as paired‐end FASTQ files, which were subjected to quality control (QC) processes to ensure the accuracy of downstream analysis steps. The average Phred score was above 30 for all samples, indicating high sequencing accuracy. The reads were processed with Trimmomatic v0.39 (Bolger et al. 2014) for adapter removal, length trimming and quality trimming. The trimmed reads were subsequently quality‐checked using FastQC (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Trimmed reads were aligned to the caprine reference genome, Capra hircus ARS 1.2 (GCA_001704415.2), using HISAT2 v2.2.1 (Kim et al. 2019). A count matrix file was generated from the aligned reads using featureCounts v2.0.1 (Liao et al. 2013).

2.6. Differential Expressed Genes (DEGs) Identification and Their Functional Annotation

Differentially expressed genes (DEGs) were identified from the count data using DESeq2 v1.40.2 (Love et al. 2014) in R v4.5.1 (R Core Team 2025). To generate more robust effect size estimates, the apeglm shrinkage method (Zhu et al. 2019) was applied to shrink the log₂ fold changes, reducing the variance of estimates for lowly expressed genes. Genes with an adjusted p‐value (p _adj) ≤ 0.1 and a log₂ fold change ≥ 0.5 were classified as upregulated, whereas those with a p _adj ≤ 0.1 and a log₂ fold change ≤ −0.5 were classified as downregulated. Additionally, differentially expressed genes were identified without applying any statistical cut‐off threshold, to capture the complete spectrum of transcriptomic changes associated with L‐carnitine supplementation. Functional annotation of the DEGs was performed using the DAVID bioinformatics resource (Sherman et al. 2022). For both GO terms and KEGG pathways, an EASE score ≤ 0.05 was set as the significance threshold. For the identification of hub genes, protein–protein interaction (PPI) analysis was performed using the STRING database (Szklarczyk et al. 2023), and the resulting network was visualized and analysed using Cytoscape v3.10.4 (Shannon et al. 2003).

2.7. Real Time PCR Validation

Quantitative real‐time PCR (qRT‐PCR) was employed to validate the RNA‐Seq data. Three samples per group were used for the qRT‐PCR study performed on a StepOnePlus real‐time PCR system (Applied Biosystems, USA). Relative quantification of two genes, namely Solute Carrier Family 9 Member C1 (SLC9C1) and Centrosomal Protein 70 (CEP70), was performed. Briefly, cDNA was synthesized using the PrimeScript 1st Strand cDNA Synthesis Kit (DSS Takara Bio, India) following the manufacturer's protocol. qRT‐PCR was performed using Maxima SYBR Green/ROX qPCR Master Mix (Thermo Scientific, USA) with custom‐designed primers (Table 1). Fold change was calculated using the $2^{-∆∆C_{\mathrm{T}}}$ method (Livak and Schmittgen 2001) with GAPDH as the reference gene. The statistical significance of the fold change values was determined using the Wilcoxon‐Mann–Whitney test in R 4.5.1 (R Core Team 2025).

TABLE 1.

Primer sequences used for qRT‐PCR validation of the target genes (SLC9C1 and CEP70) and reference gene (GAPDH).

Primer	Sequence	Amplicon (bp)	NCBI/Ensembl AN and primer location
SLC9C1_FP	TACTAAACTTGGTCTTCGTGATGT	103	XM_005674974.2/ENSCHIT00000029410.1 FP on exon 10 and 11 and RP on exon 11
SLC9C1_RP	GAGTGCAGAGGCTACAGATTT
CEP70_FP	CAGGAAGAAGAAGAACGCATTATC	88	XM_018049904.1/ENSCHIT00000003986.1 FP on exon 7 and RP on exon 7 and 8
CEP70_RP	ACTGTTTATCCAAGACGGTATGA
GAPDH_FP	CGCCTGGAGAAACCTGCCAAGTA	145	XM_005680968.3/ENSCHIT00000033836.1 FP on exon 8 and 9 RP on exon 10
GAPDH_RP	CGAAGGTAGAAGAGTGAGTGTCG

Note: Primers were designed based on sequences retrieved from the Ensembl and NCBI databases. Amplicon size is reported in base pairs (bp).

Abbreviations: AN, accession number; FP, forward primer; RP, reverse primer.

3. Results

3.1. Semen Parameter Evaluation

Fresh semen ejaculates were evaluated for semen quality parameters including semen volume, concentration, viability, abnormality, acrosomal integrity and plasma membrane integrity on Day 0 (prior to supplementation) and Day 105 (end of the feeding trial). No statistically significant differences were observed in the quantitative semen parameters, namely semen volume, sperm concentration, viability and abnormality, between Day 0 and Day 105 or between control and treated groups on Day 105. However, significant improvements were observed in the qualitative semen parameters following L‐carnitine supplementation. Acrosomal integrity and plasma membrane integrity showed statistically significant improvements both in the comparison between Day 0 and Day 105 within the treated group and in the comparison between control and treated groups on Day 105 (p < 0.05). The NBT assay, performed exclusively for the comparison between control and treated groups on Day 105, also showed a statistically significant reduction in oxidative stress following L‐carnitine supplementation (p < 0.05) (Table 2).

TABLE 2.

Comparison of fresh semen quality parameters between 0th and 105th day (within treated group) and between control and treated groups on the 105th day using the Wilcoxon–Mann–Whitney test.

S. no.	Parameter	0th vs. 105th day (treated)		Control vs. treated (105th day)
		W	p	W	p
1	Semen volume (mL)	6.5	0.7660	8.5	1.0
2	Concentration (106/mL)	1	0.0606	6	0.6650
3	Viability (%)	1	0.0591	3	0.1832
4	Abnormality (%)	11.5	0.3562	10.5	0.5516
5	Acrosome integrity (%)	0	0.0294*	0.5	0.0408*
6	Plasma membrane integrity (%)	0	0.0294*	0.5	0.0396*
7	Nitroblue tetrazolium test	—		16	0.0304*

Note: Parameters evaluated include semen volume (mL), sperm concentration (×10⁶/mL), viability (%), abnormality (%), acrosomal integrity (%), plasma membrane integrity (%) and nitroblue tetrazolium test. W: Wilcoxon test statistic; *: statistically significant bold values (p < 0.05). Acrosomal integrity, plasma membrane integrity and nitroblue tetrazolium assay showed statistically significant improvements in both comparisons (p < 0.05).

3.2. Sperm Transcriptome Profiling

RNA extracted from sperm samples was subjected to quality assessment and quantification using the Agilent TapeStation system, which revealed RINe values of 2.2 and 2.7 for the control samples and 2.9 and 2.2 for the treatment samples. Although these RINe values appear low by conventional standards, they are well accepted for sperm RNA samples, as the standard algorithm used to calculate RINe relies on the presence of intact 28S and 18S ribosomal RNA (rRNA) peaks, which are characteristically low in sperm RNA (Tiwari et al. 2023). The average sequencing depth was 26 million 150 bp paired‐end reads per sample. Of the 5648 genes detected across all samples, a total of 425 genes met the significance criteria (p _adj ≤ 0.1 and |log₂FC| ≥ 0.5) and were classified as DEGs, of which 258 were upregulated and 167 were downregulated in the treatment group compared to the control group (Data S1). The top upregulated genes identified were MSH4, uncharacterized gene (C5H12orf40), WDR78, NEBL, PIP5K1B, CEP126, uncharacterized gene (LOC102178878), INTS2, C2CD3 and TXNDC15, whereas SHC3, EBF2, MYO18B, TRNAD‐GUC6, MMRN2, HAUS8, CDCA4, ZIC4, DDB2 and EMX2 were among the top downregulated genes in the treatment group compared to the control group. The PCA plot shows control (C1, C2) and treatment (T1, T2) samples, with each point representing a pooled sample from two biological replicates (Figure 1). The pronounced separation along principal component 1 (PC1), which explains 81% of the total variance, demonstrates that the treatment is the dominant source of transcriptomic variation, and the tight clustering of replicates within each condition indicates high reproducibility and consistent biological responses. The MA plots depicted in Figure 2 show unshrunken (A) and shrunken (B) log₂ fold change estimates, illustrating the effect of apeglm shrinkage in reducing noise for low‐count genes while preserving strong biological effects. Hierarchical clustering of genes meeting the significance thresholds (p _adj < 0.1 and log₂FC > 0.5) showed a clear separation between control (C1, C2) and treatment (T1, T2) groups (Figure 3). The volcano plot demonstrated predominant upregulation, with many genes exhibiting large‐magnitude changes, notably MSH4, SON, SPATA18 and HTR1F (Figure 4).

FIGURE 1.

Principal component analysis (PCA) plot of sperm transcriptome profiles of Malabari bucks showing separation between control (C1, C2) and treatment (T1, T2) groups following L‐carnitine supplementation. Each data point represents a pooled sample derived from two biological replicates. The pronounced separation along principal component 1 (PC1, x‐axis) between the control and treatment groups indicates that L‐carnitine supplementation is the dominant source of transcriptomic variation. The treatment replicates (T1, T2) cluster closely together on the positive PC1 axis, whereas the control replicates (C1, C2) are more widely dispersed along both PC1 and PC2 axes, suggesting greater transcriptomic consistency in the treatment group. The separation between groups along PC1 supports the biological effect of L‐carnitine supplementation on the sperm transcriptome.

FIGURE 2.

MA plots comparing (A) unshrunken and (B) shrunken log₂ fold change estimates plotted against mean normalized counts in the sperm transcriptome of Malabari bucks following L‐carnitine supplementation. In panel (A), increased scatter at low expression levels reflects higher uncertainty in fold change estimation for low‐count genes, with out‐of‐range genes represented as triangles. Panel (B) shows the effect of apeglm shrinkage, where fold change estimates of low‐count genes are pulled toward zero whereas strong biological effects are preserved. Statistically significant DEGs are highlighted in blue and non‐significant genes in grey.

FIGURE 3.

Heat map showing hierarchical clustering of significant DEGs in the sperm transcriptome of Malabari bucks following L‐carnitine supplementation. The heat map demonstrates a clear separation between treatment (T1, T2) and control (C1, C2) groups, with two distinct gene clusters showing contrasting expression patterns between the groups. Red indicates higher expression and blue indicates lower expression relative to the mean normalized counts. Rows represent individual genes and columns represent individual pooled samples.

FIGURE 4.

Volcano plot of differential gene expression analysis between treatment and control groups in the sperm transcriptome of Malabari bucks following L‐carnitine supplementation. Each point represents a single gene plotted by log₂ fold change (x‐axis) against statistical significance (−log₁₀ adjusted p‐value, y‐axis). Grey points indicate non‐significant genes (NS); green points represent genes meeting the fold change threshold only (|log₂ FC| > 0.5); blue points represent genes meeting the p‐value threshold only (p _adj < 0.1); and red points represent genes meeting both criteria and are considered statistically significant DEGs. The plot demonstrates a pronounced rightward skew, indicating predominant upregulation in the treatment group, with notable genes including MSH4, HTR1F, SPATA18 and SON showing large‐magnitude fold changes. Vertical dashed lines indicate the log₂ fold change thresholds (|log₂ FC| = 0.5) and the horizontal dashed line indicates the significance threshold (p _adj < 0.1).

The GO terms observed for the upregulated genes were grouped into six categories, namely cell cycle and meiosis (CCMEIO), cilium and sperm structure (CSSTRU), DNA repair (DR), reproduction (REPRO), sperm‐related (SPMREL) and transport‐related (TRAN) (Figure 5). KEGG analysis identified six enriched pathways each for the upregulated and downregulated genes (Table 3). The PPI network was constructed using the STRING database and exported to Cytoscape using the CytoHubba plugin, with Degree and MCC ranking criteria applied to select the top interacting genes with connected internodes. This analysis identified five hub genes, namely PMS1, EEFSEC, ZFAND4, MYSM1 and PIK3R1, in the upregulated group (Figure 6), whereas no hub genes were identified in the downregulated group.

FIGURE 5.

Gene Ontology (GO) biological process enrichment analysis of upregulated DEGs in the sperm transcriptome of Malabari bucks following L‐carnitine supplementation. GO terms are grouped into six biological categories: cell cycle and meiosis (CCMEIO), cilium and sperm structure (CSSTRU), DNA repair (DR), reproduction (REPRO), sperm related (SPMREL) and transport related (TRAN). Each dot represents a specific GO term, with dot size proportional to the number of associated genes (gene count) and dot shade indicating the level of statistical significance (−log₁₀ FDR). The x‐axis represents fold enrichment. Only statistically significant GO terms (EASE score ≤ 0.05) are displayed.

TABLE 3.

KEGG pathway enrichment analysis of differentially expressed genes (DEGs) in the sperm transcriptome of Malabari bucks following L‐carnitine supplementation.

KEGG pathway	Count	p	Fold enrichment	Regulation
Polycomb repressive complex	4	2.93E‐02	5.89	Upregulated
Nucleocytoplasmic transport	5	1.33E‐02	5.38	Upregulated
Fc gamma R‐mediated phagocytosis	4	4.22E‐02	5.1	Upregulated
C‐type lectin receptor signalling pathway	4	4.89E‐02	4.8	Upregulated
Cellular senescence	5	4.33E‐02	3.72	Upregulated
Focal adhesion	6	2.28E‐02	3.65	Upregulated
Type II diabetes mellitus	3	4.21E‐02	9.04	Downregulated
Glioma	3	9.92E‐02	5.55	Downregulated
Insulin signalling pathway	5	1.69E‐02	4.99	Downregulated
FoxO signalling pathway	4	6.48E‐02	4.27	Downregulated
cGMP‐PKG signalling pathway	5	3.06E‐02	4.15	Downregulated
Oestrogen signalling pathway	4	7.21E‐02	4.08	Downregulated

Note: Six pathways were enriched among upregulated genes. Count refers to the number of DEGs mapped to each pathway. Only pathways with an EASE score ≤ 0.05 were considered statistically significant.

FIGURE 6.

Protein–protein interaction (PPI) network of upregulated DEGs in the sperm transcriptome of Malabari bucks following L‐carnitine supplementation, constructed using the STRING database and visualized in Cytoscape using the CytoHubba plugin. Hub genes identified based on Degree and MCC ranking criteria, namely ZFAND4, MYSM1, PMS1, EEFSEC and PIK3R1, are highlighted in warm colours (red to yellow) according to their interaction score, with red indicating the highest connectivity. Interacting genes are shown in blue. Solid lines represent direct protein–protein interactions and dashed lines represent indirect interactions, with edge labels indicating the interaction scores between connected nodes.

3.3. Real Time PCR Validation

The qRT‐PCR validation of two selected genes, SLC9C1 and CEP70, confirmed trends consistent with the RNA‐Seq data, with both genes showing upregulation in both RNA‐Seq and qRT‐PCR analyses. CEP70 showed a log₂ fold change of 0.40 (DESeq2) in RNA‐Seq with a corresponding fold change of 1.20 in qRT‐PCR, whereas SLC9C1 showed a log₂ fold change of 0.91 (DESeq2) in RNA‐Seq with a corresponding fold change of 2.18 in qRT‐PCR (Figure 7). Statistical analysis of the fold change values using the Wilcoxon‐Mann–Whitney test revealed no statistically significant differences between the control and treatment groups, which is consistent with the RNA‐Seq results. The genes were selected based on their biological importance and consistent expression in both control and treatment samples, as determined from the count matrix file generated by featureCounts 2.0.1. It is noteworthy that most of the statistically significant DEGs were exclusively expressed in the treatment samples with no detectable read counts in the control samples, making them unsuitable for fold change‐based qRT‐PCR validation.

FIGURE 7.

Comparison of fold change values obtained from DESeq2 RNA‐Seq analysis and qRT‐PCR validation for the two selected genes, CEP70 and SLC9C1, in the sperm transcriptome of Malabari bucks following L‐carnitine supplementation. Blue bars represent DESeq2 log₂ fold change (log₂FC) values and orange bars represent qRT‐PCR relative quantification (RQ) values calculated using the 2⁻^ΔΔCT method. Both genes showed consistent upregulation in RNA‐Seq and qRT‐PCR analyses, confirming the directional consistency between the two methods.

4. Discussion

Semen was collected from each buck in the morning hours using an artificial vagina with a dummy buck as the mount. Acrosomal integrity, plasma membrane integrity, and oxidative stress showed substantial improvements following L‐carnitine supplementation, whereas macroscopic semen parameters such as volume, colour, concentration, viability and morphology did not show any notable alterations. Evaluating acrosomal integrity is essential for ascertaining a sperm cell's fertilization capability. In the present study, acrosomal integrity showed a statistically significant improvement both within the treated group between Day 0 and Day 105 (W = 0, p = 0.0294) and between the control and treated groups on Day 105 (W = 0.5, p = 0.0408), as determined by the Wilcoxon‐Mann–Whitney test. These findings align with those reported by Heidari et al. (2022), who noted significantly higher acrosomal integrity in post‐thawed spermatozoa from bucks receiving 5 mM L‐carnitine compared to the control group (p ≤ 0.05). For the acrosome to function successfully, the integrity of the plasma membrane must be maintained through an efficient membrane repair mechanism. Similarly, plasma membrane integrity showed a statistically significant improvement both within the treated group between Day 0 and Day 105 (W = 0, p = 0.0294) and between the control and treated groups on Day 105 (W = 0.5, p = 0.0396), as determined by the Wilcoxon‐Mann–Whitney test. These results are consistent with the findings of Yadav (2021), who reported that supplementation with 5 mM carnitine at the pre‐freeze stage resulted in a significantly higher number of hypo‐osmotic swelling test (HOST)‐sensitive spermatozoa compared to the control and other carnitine‐treated groups (p < 0.01). Oxidative stress, characterized by an imbalance between reactive oxygen species (ROS) and antioxidants, can severely compromise sperm function and lead to male infertility. The NBT assay quantifies a cell's capacity to generate ROS, specifically superoxide anions, by measuring the reduction of the NBT molecule into insoluble blue formazan crystals. In the present study, the NBT assay revealed significantly lower oxidative stress in the treatment group compared to the control group on Day 105 (W = 16, p = 0.0304), indicating a marked reduction in ROS following L‐carnitine supplementation. Although specific data on L‐carnitine supplementation and the NBT assay in goats are currently unavailable, the indicative findings of Tunc et al. (2010) suggest that this assay holds promise as a biomarker for assessing sperm oxidative stress in livestock species.

The top upregulated genes, MSH4, uncharacterized gene (C5H12orf40), WDR78, NEBL, PIP5K1B, CEP126, uncharacterized gene (LOC102178878), INTS2, C2CD3 and TXNDC15, were found to be involved in diverse biological roles including regulation of chromosome pairing during meiosis (Krausz et al. 2020), motile cilia and flagella assembly for cell locomotion and beating (Zhang et al. 2019), actin filament binding (Millevoi et al. 1998), spermatogenesis (Hasegawa et al. 2012), cilium formation (Bonavita et al. 2014), transcription and processing of snRNA (Vassena et al. 2011), development and function of the sperm tail (Ye et al. 2014) and regulation of the redox state of cells (Smith et al. 2013). MSH4 (MutS Homologue 4) is a protein critical for the regulation of chromosome pairing during meiosis. Its upregulation suggests that L‐carnitine facilitates accurate chromosomal alignment, which is vital for generating genetically normal and viable sperm, thereby minimizing errors that could result in infertility. WDR78 (Dynein Axonemal Intermediate Chain 4) encodes a protein associated with motile cilia and flagella, which play a crucial role in cell locomotion and beating. The upregulation of WDR78 following L‐carnitine supplementation suggests an enhancement of flagellar function, which is directly linked to sperm motility. NEBL, PIP5K1B and CEP126 are involved in energy production and cytoskeletal organization, which are essential for the development of robust sperm flagella, thereby directly improving sperm motility and swimming ability, as well as supporting the structural integrity and shaping of sperm cells during development. The upregulation of genes associated with spermatogenesis suggests that L‐carnitine supports the highly energy‐intensive process of sperm cell creation and maturation within the testes. INTS2 (Integrator Complex Subunit 2) is involved in the transcription and processing of snRNA, supporting the efficient gene expression machinery required for the extensive protein synthesis involved in sperm cell development (Vassena et al. 2011). The upregulation of C2CD3 further supports sperm tail development and propulsive function by providing the structural components and metabolic energy required for centriolar distal appendage assembly and ciliary vesicle docking (Ye et al. 2014). Finally, TXNDC15, a thioredoxin domain‐containing protein involved in regulating the redox state of cells, was upregulated in the treatment group, suggesting that L‐carnitine enhances antioxidant defence mechanisms, protecting developing sperm from oxidative damage that can impair DNA integrity, membrane function, and motility, thereby preserving overall fertility (Smith et al. 2013).

The qRT‐PCR validated genes play significant roles in male reproduction. SLC9C1 has been reported to be essential for sperm fertility and motility in humans and mice (Cavarocchi et al. 2021; Iida‐Norita et al. 2025), and is involved in the hyperactivation of sperm flagella within the female reproductive tract (Pal and Chowdhury 2024). Additionally, SLC9C1 has been implicated in epigenetic regulation, further highlighting its multifaceted role in sperm function (Gardner et al. 2024). CEP70 is crucial for flagella formation and acrosome biogenesis (Liu et al. 2021), and biallelic mutations in CEP70 have been linked to male infertility in humans (Ruan et al. 2023). The upregulation of both SLC9C1 and CEP70 in the present study, as confirmed by qRT‐PCR, is consistent with the observed improvements in acrosomal integrity and plasma membrane integrity following L‐carnitine supplementation.

Among the top downregulated genes, the SHC3 gene has a limited specific role in sperm; however, based on curated database information, its biological process can be related to the tyrosine kinase signalling pathway, which is often activated under oxidative stress. Since L‐carnitine reduces ROS levels, the stimulus for activation of this signalling pathway is consequently reduced, suggesting that the downregulation of SHC3 reflects the antioxidant action of L‐carnitine. The majority of the downregulated genes are involved in transcription factor activity, regulating cell differentiation and identity; however, their direct role in sperm function is limited and mostly indirect, as they are not central players in the molecular processes of sperm maturation, motility or fertilization. The downregulation of DDB2, a testis tissue‐specific gene, suggests the presence of remnants of testicular transcriptional activity carried over during the spermatogenesis process. Similarly, the downregulation of EMX2, a gene responsible for early developmental growth, suggests a post‐transcriptional regulatory role for this RNA, the precise function of which in the context of zygote interaction remains to be fully elucidated. The downregulation of key glycolytic and autophagic genes in the current study suggests that L‐carnitine may shift the energy paradigm in sperm cells away from inefficient carbohydrate‐based metabolism toward the more efficient mitochondrial β‐oxidation of fatty acids for energy production. Furthermore, genes positively associated with low sperm motility were found to be downregulated, providing the most direct evidence that L‐carnitine supplementation may directly counter the molecular genetic signature associated with impaired sperm motility. The downregulation of certain testis‐specific genes may reflect a successful shift in the spermatogenic population toward more mature sperm forms, as the expression of many such genes is highest during the earlier stages of spermatogenesis such as in spermatocytes and spermatids, and progressively lower in fully matured spermatozoa. This suggests that the sperm population is becoming increasingly enriched with fully developed, functionally competent spermatozoa that express fewer development‐specific genes, resulting in improved overall efficiency of sperm maturation.

The significant number of GO terms observed across these categories indicates that L‐carnitine greatly influences biological processes directly related to meiosis and sperm quality. The enriched biological process (BP) terms from the cell cycle and meiosis (CCMEIO) group included homologous chromosome segregation, meiotic chromosome segregation, meiotic cell cycle, nuclear chromosome segregation, microtubule cytoskeleton organization and chromosome organization, which are critical elements ensuring normal spermatogenesis (Galander et al. 2019). Errors in meiotic segregation have been linked to male infertility and chromosomal aberrations (Brar and Amon 2008). A significant number of GO terms related to sperm structure and DNA repair were found to be upregulated in the present study, indicating a structured and coordinated molecular mechanism to support robust spermatogenesis following L‐carnitine supplementation. The GO terms observed for the cilium and sperm structure (CSSTRU) category included sperm flagellum assembly, cilium or flagellum‐dependent cell motility, cilium assembly, cilium movement involved in cell motility, and regulation of actin cytoskeleton organization. Actin filament organization is critical for the formation and integrity of the acrosomal cap, which enables sperm‐egg interaction during fertilization. These GO terms collectively point toward flagellum formation and development, which are critical for sperm motility, suggesting that L‐carnitine plays a significant role in supporting these structural processes. Two GO terms related to DNA repair mechanisms were found to be upregulated in the present study, namely DNA repair and DNA damage response. DNA repair mechanisms operate through multiple coordinated pathways, ensuring robust spermatogenesis and the production of healthy mature sperm. Antioxidants play a critical role in triggering DNA repair mechanisms, and in the present study, the NBT assay results demonstrated significantly reduced oxidative stress in the L‐carnitine‐supplemented treatment group, consistent with previous studies reporting the antioxidant properties of L‐carnitine (Gülçin 2006; Solarska et al. 2009). This reduction in oxidative stress is likely to trigger antioxidant responses in sperm cells, thereby activating DNA repair functions. Elevated ROS levels can result in DNA damage in sperm, adversely affecting morphology and motility (Alam et al. 2021). The remaining significant GO terms were related to reproduction, sperm‐related processes, and transport, with the sperm‐related terms specifically including spermatid differentiation, spermatogenesis, and sperm motility. Collectively, these GO terms indicate an orchestrated effect of L‐carnitine on sperm quality parameters and highlight the multifaceted molecular mechanisms through which this effect is achieved.

The analysis of downregulated GO terms revealed a coherent pattern of suppressed carbohydrate metabolism pathways including glycogen biosynthetic processes, polysaccharide metabolism and glucose utilization. This downregulation indicates a metabolic reprogramming characterized by a shift in cellular energy production from carbohydrate‐based metabolism toward enhanced fatty acid oxidation, which aligns with the primary pharmacological action of L‐carnitine as a facilitator of mitochondrial fatty acid import. The central theme emerging from the GO analysis is that L‐carnitine supplementation coordinately upregulates biological processes essential for robust meiosis and cell division, sperm structural integrity, DNA repair mechanisms, and spermatogenesis, whereas simultaneously driving a metabolic shift toward more efficient fatty acid oxidation, collectively creating a favourable molecular environment for enhanced male fertility.

The KEGG pathway enrichment analysis of upregulated genes revealed six enriched pathways, one of which was the Polycomb repressive complex pathway, suggesting possible epigenetic modulation by L‐carnitine, consistent with the reports of Heidari et al. (2022) and Oliviero et al. (2016). The KEGG pathway enrichment analysis of downregulated genes similarly revealed six enriched pathways, of which three warrant special attention, namely Type II diabetes mellitus, the insulin signalling pathway, and the oestrogen signalling pathway. Insulin resistance has been linked with male infertility (Leisegang et al. 2014; Mansour et al. 2017), and the observed downregulation of insulin resistance and diabetes‐related pathways in the present study suggests that L‐carnitine may ameliorate insulin resistance, thereby supporting better reproductive function. In addition, downregulation of the oestrogen signalling pathway may result in reduced estrogenic activity, potentially favouring androgen dominance and thereby exerting a positive effect on male fertility. This is particularly relevant given that excessive conversion of testosterone to estradiol can suppress the hypothalamic–pituitary‐gonadal (HPG) axis, leading to secondary hypogonadism (Michalakis et al. 2013). Collectively, these pathway alterations indicate that L‐carnitine supplementation promotes an endocrinological and metabolic environment conducive to enhanced male fertility.

Hub genes are defined as genes having a high number of interactions with other genes within a network, acting as key central players in biological processes. The upregulated hub genes identified in the present study highlight the multifaceted influence of L‐carnitine on sperm function, spanning chromatin remodelling, oxidative defence, DNA integrity and flagellar structure. MYSM1, a histone deubiquitinase, reflects the epigenetic regulation of chromatin organization, suggesting that L‐carnitine may support tighter DNA packaging and genomic stability during spermatogenesis. ZFAND4, a zinc finger domain‐containing protein, was identified as another hub gene in the present study. Zinc finger proteins have been implicated in critical steps of spermatogenesis and meiosis‐promoting functions (Ishizuka et al. 2016), and the upregulation of ZFAND4 suggests a role in maintaining the fidelity of meiotic progression following L‐carnitine supplementation. In terms of oxidative defence, EEFSEC, which mediates the incorporation of selenocysteine into selenoproteins (Qazi et al. 2019), indicates enhanced antioxidant capacity, aligning well with the established role of L‐carnitine in reducing reactive oxygen species. The upregulation of PMS1, a DNA mismatch repair protein (Zhu et al. 2022), further underscores the role of L‐carnitine in safeguarding sperm DNA from oxidative or replication‐associated damage. Notably, PMS1 showed the strongest interaction with MSH4, the most significantly upregulated gene in the present dataset, suggesting a coordinated activation of the DNA mismatch repair pathway following L‐carnitine supplementation. Finally, the upregulation of CEP126, a centrosomal protein critical for sperm flagellum assembly (Bonavita et al. 2014), points toward improved structural integrity and motility of spermatozoa, both of which are essential for successful fertilization.

5. Conclusion

This study investigated the potential role of L‐carnitine supplementation in enhancing male fertility in Malabari bucks through multifaceted molecular mechanisms. L‐carnitine supplementation was associated with significant improvements in acrosomal integrity, plasma membrane integrity, and reduced oxidative stress as evidenced by the NBT assay, whereas macroscopic semen parameters remained unaltered. Transcriptomic analysis identified 425 DEGs, of which 258 were upregulated and 167 were downregulated, suggesting a coordinated upregulation of key biological processes potentially essential for reproductive function, including meiosis, sperm structural integrity, DNA repair mechanisms and spermatogenesis. The observed downregulation of carbohydrate metabolism pathways may indicate a metabolic shift toward more efficient mitochondrial fatty acid oxidation, which is consistent with the known pharmacological action of L‐carnitine, though this requires further experimental validation. KEGG pathway analysis revealed upregulation of the Polycomb repressive complex pathway, which may suggest epigenetic modulation as a possible additional mechanism of action. Similarly, the downregulation of insulin resistance, type II diabetes mellitus, and oestrogen signalling pathways may indicate a tendency toward an endocrinological and metabolic environment potentially conducive to enhanced male fertility, although direct causal relationships cannot be established from transcriptomic data alone. The hub genes identified, namely PMS1, ZFAND4, MYSM1, EEFSEC and CEP126, appear to be associated with processes including chromatin remodelling, oxidative defence, DNA mismatch repair, selenoprotein‐mediated antioxidant capacity, and sperm flagellum assembly, and may represent potential targets for future functional validation. Although the limited number of biological replicates remains a limitation of the current study, the pooling strategy employed and the application of the apeglm shrinkage method within the DESeq2 pipeline helped to strengthen the statistical robustness of the findings. These results provide preliminary mechanistic insights into L‐carnitine's potential therapeutic role in small ruminant reproduction, and further validation through functional studies with larger sample sizes is warranted.

Author Contributions

Doddannavar Shashikiran: writing – original draft, data curation, investigation, methodology, software, visualization. Muhasin Asaf: conceptualization, data curation, formal analysis, funding acquisition, investigation, methodology, project administration, resources, software, supervision, validation, visualization, writing – review and editing. Bindya Liz Abraham: conceptualization, funding acquisition, methodology, project administration, resources. Lali F. Anand: formal analysis, methodology, resources. Senthil Murugan: conceptualization, data curation, investigation, methodology, resources. Kokkadath Naheef: data curation, methodology, resources. Gongale Tushar Surendra: data curation, investigation. Jaya Madhuri: methodology. Balamurali Vigneshwaran: investigation, methodology. Nisha TS: investigation. Kanjirakuzhiyil Promod: conceptualization, data curation, formal analysis, methodology, resources, validation.

Funding

This work was funded under state plan project ‘Nutritional and Genetic interventions for breed improvement of native Malabari goats of Kerala’ (RSP/25‐26/II‐5).

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Data S1: accompanies this article and contains three sheets listing: (i) all upregulated DEGs, (ii) all downregulated DEGs and (iii) all genes identified without applying a statistical cut‐off threshold.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.