Comparative Analysis of the Liver Transcriptome among Cattle Breeds Using RNA-seq

Pareek, Chandra Shekhar; Sachajko, Mateusz; Jaśkowski, J. M.; Herudzińska, Magdalena; Skowroński, Mariusz T.; Domagalski, Krzysztof; Szczepanek, Joanna; Czarnik, Urszula; Sobiech, P.; Wysocka, Dominika; Pierzchała, Mariusz; Poławska, Ewa; Stepanow, Kamila; Ogłuszka, Magdalena; Juszczuk-Kubiak, Edyta; Feng, Yaping; Kumar, Dibyendu

doi:10.3390/vetsci6020036

Cited by 13 publications

(7 citation statements)

References 71 publications

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“…Though the library prep kit used is apt at maximizing sequencing depth when compared with other commercial solutions, we noticed that many transcripts with (typically) a relatively low expression were either not detected or detected at very low level, with zero-counts in most samples. Despite being able to detect >14,000 transcripts with a count>4 in at the least one sample, which is somewhat similar to what previously reported in RNAseq analysis of bovine liver ( 125 – 127 ), many transcripts with a relatively medium-low expression were either not detected or detected at very low level, with lack of detection in most samples. Most of the genes used for the RT-qPCR were in this category, such as all PPAR transcripts and LIPC .…”

Section: Limitationssupporting

confidence: 87%

Peroxisome Proliferator-Activated Receptor Activation in Precision-Cut Bovine Liver Slices Reveals Novel Putative PPAR Targets in Periparturient Dairy Cows

et al. 2022

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Metabolic challenges experienced by dairy cows during the transition between pregnancy and lactation (also known as peripartum), are of considerable interest from a nutrigenomic perspective. The mobilization of large amounts of non-esterified fatty acids (NEFA) leads to an increase in NEFA uptake in the liver, the excess of which can cause hepatic accumulation of lipids and ultimately fatty liver. Interestingly, peripartum NEFA activate the Peroxisome Proliferator-activated Receptor (PPAR), a transcriptional regulator with known nutrigenomic properties. The study of PPAR activation in the liver of periparturient dairy cows is thus crucial; however, current in vitro models of the bovine liver are inadequate, and the isolation of primary hepatocytes is time consuming, resource intensive, and prone to errors, with the resulting cells losing characteristic phenotypical traits within hours. The objective of the current study was to evaluate the use of precision-cut liver slices (PCLS) from liver biopsies as a model for PPAR activation in periparturient dairy cows. Three primiparous Jersey cows were enrolled in the experiment, and PCLS from each were prepared prepartum (−8.0 ± 3.6 DIM) and postpartum (+7.7± 1.2 DIM) and treated independently with a variety of PPAR agonists and antagonists: the PPARα agonist WY-14643 and antagonist GW-6471; the PPARδ agonist GW-50156 and antagonist GSK-3787; and the PPARγ agonist rosiglitazone and antagonist GW-9662. Gene expression was assayed through RT-qPCR and RNAseq, and intracellular triacylglycerol (TAG) concentration was measured. PCLS obtained from postpartum cows and treated with a PPARγ agonist displayed upregulation of ACADVL and LIPC while those treated with PPARδ agonist had increased expression of LIPC, PPARD, and PDK4. In PCLS from prepartum cows, transcription of LIPC was increased by all PPAR agonists and NEFA. TAG concentration tended to be larger in tissue slices treated with PPARδ agonist compared to CTR. Use of PPAR isotype-specific antagonists in PCLS cultivated in autologous blood serum failed to decrease expression of PPAR targets, except for PDK4, which was confirmed to be a PPARδ target. Transcriptome sequencing revealed considerable differences in response to PPAR agonists at a false discovery rate-adjusted p-value of 0.2, with the most notable effects exerted by the PPARδ and PPARγ agonists. Differentially expressed genes were mainly related to pathways involved with lipid metabolism and the immune response. Among differentially expressed genes, a subset of 91 genes were identified as novel putative PPAR targets in the bovine liver, by cross-referencing our results with a publicly available dataset of predicted PPAR target genes, and supplementing our findings with prior literature. Our results provide important insights on the use of PCLS as a model for assaying PPAR activation in the periparturient dairy cow.

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Section: Limitationssupporting

confidence: 87%

Peroxisome Proliferator-Activated Receptor Activation in Precision-Cut Bovine Liver Slices Reveals Novel Putative PPAR Targets in Periparturient Dairy Cows

et al. 2022

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“…Filters for differentially expressed genes between preadipocytes and mature adipocytes can promote further study of fat deposition in goats. Numerous studies have shown that RNA-seq helps reveal transcriptome differences in tissues and cells [29][30][31][32]. In this study, the DEG-Seq was used to analyse the DEGs in intramuscular preadipocytes and adipocytes.…”

Section: Resultsmentioning

confidence: 99%

Effects of the FHL2 gene on the development of subcutaneous and intramuscular adipocytes in goats

Li,

Wang,

Wang

et al. 2023

Preprint

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BackgroundAdipose tissue affects not only the meat quality of domestic animals, but also human health. Adipocyte differentiation is regulated by a series of regulatory genes and cyclins. Four and half LIM protein (FHL2) is positively correlated with the hypertrophy of fat cells and can cause symptoms such as obesity and diabetes. Result In the transcriptome sequencing analysis of intramuscular adipocytes after three days of differentiation, the differentially expressed gene FHL2 was found. To further explore the biological significance of the differentially expressed gene FHL2, which was downregulated in the mature adipocytes. We revealed the function of FHL2in adipogenesis through the acquisition and loss of function of FHL2. The results showed that the overexpression of FHL2 significantly increased the expression of adipogenic genes (PPARγ, C/EBPβ) and the differentiation of intramuscular and subcutaneous adipocytes. However, silencing FHL2 significantly inhibited adipocyte differentiation. The overexpression of FHL2 increased the number of adipocytes stained with crystal violet and increased the mRNA expression of proliferation marker genes such as CCNE, PCNA, CCND and CDK2. In addition, it significantly increased the rate of EdU positive cells. In terms of apoptosis, overexpression of FHL2 significantly inhibited the expression of P53and BAX in both intramuscular and subcutaneous adipocytes, which are involved in cell apoptosis. However, overexpression of FHL2 promoted the expression of BCL, but was rescued by the silencing of FHL2. Conclusions In conclusion, this study suggests that FHL2 promotes the differentiation, and proliferation and inhibited the apoptosis of both intramuscular and subcutaneous adipocytes. These findings elucidate the function of FHL2 in regulating the development of adipocytes.

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“…Furthermore, in the context of library complexity plot, duplicate reads are those that map to the same location with same orientation. However, in the post-alignment QC analysis (Figure 4), StrandNGS tool was successfully performed the alignment or mapping of the processed pre-alignment RNA-seq data on the Bos Taurus reference genome to identify the number of aligned reads, uniquely aligned reads, which was very critical and crucial for the genetic variants or single nucleotide polymorphisms (SNPs) discoveries [21,22] and identification of DEGs, gene network and metabolic pathways in bovine liver and pituitary tissues [23,24].…”

Section: Discussionmentioning

confidence: 99%

Quality control assessment of the RNA-Seq data generated from liver and pituitary transcriptome of Hereford bulls using StrandNGS software

Pareek

Sachajko

Szczepański

et al. 2019

TRVS

Self Cite

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Background: Quality control (QC) assessment is the most critical step in the high-throughput RNA-seq data analysis to characterize the in-depth understanding of genome and transcriptome assembling to a given reference genome. It provides not only a quick insight into the RNA-seq data quality to allow early identification of good or bad RNA-seq data samples, but also to verify the alignment QC checks for further essential high-throughput bioinformatics analysis such as, identification of novel genetic variants, differentially expressed genes (DEGs), gene network and metabolic pathways. Method: After isolation of total RNA from liver (n=15) and pituitary gland (n=15) tissues of young Hereford bulls, the pooled total RNA (n=30) were fragmented using GeneRead rRNA depletion kit (Qiagen, Hilden, Germany) and cDNA library preparation were preformed using ScriptSeq TM v2 RNA-Seq library preparation kit (Epicentre, illumina, USA), followed by high-throughput sequencing of combined liver and pituitary transcriptome using MiSeq reagent kit v2 (illumina, USA) to obtain high quality of paired-end RNAseq reads of 251 base-pairs (bps). In this paper, the QC assessment of obtained RNA-seq raw data as well as post-alignment QC of processed RNA-seq data of combined liver and pituitary transcriptome (n=30) of Hereford bulls were performed using the strand NGS software v1.3 (Agilent; http://www.strand-ngs.com/) data analysis package. The reads were aligned with Bowtie using default settings against both Bull and Cow genome assembly. Results: Using two runs of MiSeq platform, a total of over 60 million paired-end RNAseq reads were successfully obtained and submitted to NCBI SRA resources (https://www. ncbi.nlm.nih.gov/sra?linkname=bioproject_sra_all&from_uid=312148). Library complexity plot results revealed 72.02% of duplicate reads with a low library complexity value of 0.28. The pre-alignment QC analysis of raw RNA-seq data revealed the sequence read lengths ranged from 35-251 bp size with more than 50% of all reads with length over 200bp and 10% of reads below 100bp. Conclusion: By testing the RNA-seq methodology on Illumina platform, two MiSeq sequencing runs yielded significantly high quality of 30 million sequencing reads per single MiSeq run. Our initial pre-alignment and post-alignment analysis of RNA-seq data analysis revealed that mapping of the Hereford liver and pituitary gland transcriptome to reference Bos taurus genome was successfully performed, however, more than 50% of all reads with length over 200bp were recovered. Therefore, obtained results concludes that liver and pituitary transcriptome sequencing with rRNA depletion method is less effective than mRNA RNA-seq method.

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Comparative Analysis of the Liver Transcriptome among Cattle Breeds Using RNA-seq

Cited by 13 publications

References 71 publications

Peroxisome Proliferator-Activated Receptor Activation in Precision-Cut Bovine Liver Slices Reveals Novel Putative PPAR Targets in Periparturient Dairy Cows

Peroxisome Proliferator-Activated Receptor Activation in Precision-Cut Bovine Liver Slices Reveals Novel Putative PPAR Targets in Periparturient Dairy Cows

Effects of the FHL2 gene on the development of subcutaneous and intramuscular adipocytes in goats

Quality control assessment of the RNA-Seq data generated from liver and pituitary transcriptome of Hereford bulls using StrandNGS software

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