Identifying key genes in milk fat metabolism by weighted gene co-expression network analysis

Mu, Tong; Hu, Honghong; Ma, Yanfen; Wen, Huiyu; Yang, Chaoyun; Feng, Xiaoran; Wan, Wen; Zhang, Juan; Gu, Ye

doi:10.1038/s41598-022-10435-1

Cited by 10 publications

(6 citation statements)

References 58 publications

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“…Weighted gene co-expression network analysis (WGCNA) is a valuable R tool that integrates gene expression data with phenotypic information to identify key modules and hub genes associated with target traits. This approach effectively clusters genes exhibiting similar expression patterns into distinct modules, which are characterized by shared functions or pathways [40]. By leveraging plant life activities and high-throughput sequencing technology, WGCNA enables the acquisition of multiple expression traits and facilitates the construction of a scale-free network topology centered around pivotal regulatory genes [41].…”

Section: Introductionmentioning

confidence: 99%

Integrated transcriptomic and WGCNA analyses reveal candidate genes regulating mainly flavonoid biosynthesis in Litsea coreana var. sinensis

Xie,

Guo,

et al. 2024

BMC Plant Biol

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Litsea coreana Levl. var. sinensis (Allen) Yang et P. H. Huang is a popular ethnic herb and beverage plant known for its high flavonoid content, which has been linked to a variety of pharmacological benefits and crucial health-promoting impacts in humans. The progress in understanding the molecular mechanisms of flavonoid accumulation in this plant has been hindered due to the deficiency of genomic and transcriptomic resources. We utilized a combination of Illumina and Oxford Nanopore Technology (ONT) sequencing to generate a de novo hybrid transcriptome assembly. In total, 126,977 unigenes were characterized, out of which 107,977 were successfully annotated in seven public databases. Within the annotated unigenes, 3,781 were categorized into 58 transcription factor families. Furthermore, we investigated the presence of four valuable flavonoids—quercetin-3-O-β-D-galactoside, quercetin-3-O-β-D-glucoside, kaempferol-3-O-β-D-galactoside, and kaempferol-3-O-β-D-glucoside in 98 samples, using high-performance liquid chromatography. A weighted gene co-expression network analysis identified two co-expression modules, MEpink and MEturquoise, that showed strong positive correlation with flavonoid content. Within these modules, four transcription factor genes (R2R3-MYB, NAC, WD40, and ARF) and four key enzyme-encoding genes (CHI, F3H, PAL, and C4H) emerged as potential hub genes. Among them, the R2R3-MYB (LcsMYB123) as a homologous gene to AtMYB123/TT2, was speculated to play a significant role in flavonol biosynthesis based on phylogenetic analysis. Our findings provided a theoretical foundation for further research into the molecular mechanisms of flavonoid biosynthesis. Additionally, The hybrid transcriptome sequences will serve as a valuable molecular resource for the transcriptional annotation of L. coreana var. sinensis, which will contribute to the improvement of high-flavonoid materials.

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Section: Introductionmentioning

confidence: 99%

Integrated transcriptomic and WGCNA analyses reveal candidate genes regulating mainly flavonoid biosynthesis in Litsea coreana var. sinensis

Xie,

Guo,

et al. 2024

BMC Plant Biol

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“…The most significant SNP, rs133231370, corresponded to a nearby hub gene, ATP8A2, known for its involvement in lipid metabolism. Previously, ATP8A2 has been discussed for its role in milk fat synthesis in Holstein cattle [48]. This gene produces an ATPase protein responsible for transferring, or flipping, phosphatidylserine (PS) and phosphatidylethanolamine from the ectoplasmic to the cytoplasmic layers of the cell membrane lipid bilayer.…”

Section: Discussionmentioning

confidence: 99%

Molecular Mechanisms Associated with the Development of the Metritis Complex in Dairy Cattle

Sanchez,

Campos-Chillon,

Sargolzaei

et al. 2024

Genes

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The metritis complex (MC), a group of post-partum uterine diseases, is associated with increased treatment costs and reduced milk yield and fertility. The goal of this study was to identify genetic variants, genes, or genomic regions that modulate MC disease. A genome-wide association study was performed using a single-locus mixed linear model of 1967 genotypes (624,460 SNPs) and metritis complex records. Then, in-silico functional analyses were performed to detect biological mechanisms and pathways associated with the development of MC. The ATP8A2, COX16, AMN, and TRAF3 genes, located on chromosomes 12, 10, and 21, were associated with MC at p ≤ 0.0001. These genes are involved in the regulation of cholesterol metabolism in the stromal tissue of the uterus, which can be directly associated with the mode of transmission for pathogens causing the metritis complex. The modulation of cholesterol abundance alters the efficiency of virulence factors and may affect the susceptibility of the host to infection. The SIPA1L1, DEPDC5, and RNF122 genes were also significantly associated with MC at p ≤ 0.0001 and are involved in the PI3k-Akt pathway, responsible for activating the autophagic processes. Thus, the dysregulation of these genes allows for unhindered bacterial invasion, replication, and survival within the endometrium.

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“…Palombo et al [14]discovered through GWAS analysis that PI4K2A is an important candidate gene for bovine milk fat metabolism. Mu et al [11] further identi ed the differential expression of the PI4K2A gene in high and low milk fat groups through transcriptomic analysis of BMECs. In this study, qRT-PCR detection revealed that the expression of the PI4K2A gene in cow mammary tissue was signi cantly higher than in other tissues, and the expression of the PI4K2A gene in both cow mammary tissue and BMECs was relatively constant.…”

Section: Discussionmentioning

confidence: 99%

“…Considering this, our group previously investigated the genomewide expression of mRNA transcripts in bovine mammary epithelial cells (BMECs) with high and low milk fat percentages by using comparative transcriptomics [10]. We performed a comprehensive analysis of mRNA expression pro le data using the weighted gene co-expression network analysis (WGCNA) and identi ed 15 candidate differential genes potentially regulating milk fat metabolism (Supplementary Table . 1) [11]. To further pinpoint and validate the most critical genes involved in milk fat synthesis in dairy cows, this study conducted tissue expression pro ling of the 15 candidate genes by using quantitative real-time PCR (qRT-PCR).…”

Section: Introductionmentioning

confidence: 99%

The PI4K2A positively regulates the synthesis of milk fat in cows, promotes the proliferation of bovine mammary epithelial cells, and inhibits their apoptosis

Mu,

Hu,

Feng

et al. 2023

Preprint

Self Cite

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Background: Milk fat is the most important and energy-rich substance in milk. It is crucial to study the theory and pathways of milk fat synthesis and its regulation in dairy cows for the study of lactation biology. However, the current identification of valuable candidate genes affecting milk fat is limited. Method: This study uses real-time quantitative PCR (qRT-PCR) technology to perform tissue expression profile analysis on 15 candidate differentially expressed genes related to milk fat metabolism obtained from our previous transcriptome sequencing and weighted gene co-expression network analysis (WGCNA), to determine the key candidate genes affecting milk fat synthesis in dairy cows. Investigate the specific regulatory mechanisms of key candidate genes in cow milk fat metabolism using overexpression (adenovirus) and interference techniques (lentivirus). Results: The results showed that the expression level of PI4K2A gene in milk gland tissue was significantly higher than that in small intestine, liver, kidney, heart, and ovary (P < 0.05). Compared with other genes, the expression of PI4K2A in mammary gland tissue and bovine mammary epithelial cells (BMECs) was also higher and more stable. Ultimately, we identified PI4K2A as the key candidate gene responsible for regulating milk fat synthesis in dairy cows, and it plays a vital role in the cytoplasm of BMECs. Afterwards, we constructed the adenovirus overexpression vector and lentivirus interference vector for the PI4K2A gene, and combined quantitative real-time PCR (qRT-PCR) and western blot (WB) techniques to detect the effects of overexpressing and interfering with the PI4K2A gene on lipid metabolism in BMEC. The results indicate that the PI4K2A gene plays a positive regulatory role in the fatty acid (FA) transport process involved in milk fat synthesis in cows (P < 0.05). Upon further examination of triglycerides (TAG), cholesterol, and lipid droplet content in BMECs, we found that PI4K2A also has a positive regulatory effect on bovine milk fat synthesis (P < 0.05). The results obtained from EdU and apoptosis kit detection indicated that the PI4K2A gene positively regulated BMECs proliferation (P < 0.05) while negatively regulating their apoptosis process (P < 0.05). Conclusions: This study offers valuable genetic marker information for precise molecular breeding of milk component traits in dairy cows, with potential implications for mammary gland wound healing and treatment of mammary gland-related diseases.

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Identifying key genes in milk fat metabolism by weighted gene co-expression network analysis

Cited by 10 publications

References 58 publications

Integrated transcriptomic and WGCNA analyses reveal candidate genes regulating mainly flavonoid biosynthesis in Litsea coreana var. sinensis

Integrated transcriptomic and WGCNA analyses reveal candidate genes regulating mainly flavonoid biosynthesis in Litsea coreana var. sinensis

Molecular Mechanisms Associated with the Development of the Metritis Complex in Dairy Cattle

The PI4K2A positively regulates the synthesis of milk fat in cows, promotes the proliferation of bovine mammary epithelial cells, and inhibits their apoptosis

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