Investigation of candidate genes for metabolic disorders expressed in liver and pituitary gland by comparing the RNA-seq data of Polish-HF and Polish-Red cattle

Wysocka, Dominika; Sobiech, Przemysław; Herudzińska, Magdalena; Sachajko, Mateusz; Pareek, Chandra Shekhar

doi:10.12775/trvs.2018.004

Cited by 2 publications

(2 citation statements)

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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

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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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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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“…Moreover, due to the NGS, the differentially expressed genes (DEGs) involved in crucial molecular processes can be recognized. The pituitary genes’ expression was examined in various contexts, such as carcinogenesis [9,10], the identification of pituitary stem cells [11], the interpretation of behaviour [12], and the explanation of metabolic disorder bases [13]. Because the pituitary is the predominant gland determining body growth, its transcriptome profiling also served to identify the candidate genes for postnatal development in miniature pigs [14].…”

Section: Introductionmentioning

confidence: 99%

The Pituitary Transcriptional Response Related to Feed Conversion in Pigs

Piórkowska

Żukowski

Tyra

et al. 2019

Genes

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Over the decades, pig breeding objectives have focused on improving the meat content in the carcass without taking into consideration the more effective fattening indicators that affect feed conversion. At present, pig growth traits associated particularly with animal feeding have become crucial due to their economic significance. This is especially evident in countries where pigs are maintained on large farms. The present study indicates that pituitary differentially expressed genes (DEGs) are activated in response to variable feed conversion (FC) in pigs. The experiment included two native Polish breeds: Puławska and Złotnicka White (ZW). The whole pituitary transcriptome was sequenced using next-generation sequencing (NGS) technology. The RNA-seq method identified over 500 and 300 DEGs in the pituitaries of the ZW and the Puławska pig populations, respectively, that were associated with hormonal regulation, notch signaling, and Wnt pathways. Lower FC in the ZW pigs favoured increased fat content in the body and significantly higher prolactin expression. The obtained results indicate that low FC values in pigs are related to slower growth or increased fat content, which suggests various pituitary responses. Therefore, the identified candidate genes were not directly associated with feed conversion values but with other factors. However, the present study delivers new insights into pituitary regulation in pigs.

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Investigation of candidate genes for metabolic disorders expressed in liver and pituitary gland by comparing the RNA-seq data of Polish-HF and Polish-Red cattle

Cited by 2 publications

References 32 publications

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

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

The Pituitary Transcriptional Response Related to Feed Conversion in Pigs

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