Literature DB >> 30417039

Data on transcriptome profiling of circulating microRNAs in dairy cattle.

Kesavan Markkandan1, Hyun-Joo Lim2, Dong Jin Lee1, In-Gang Shin1, Seung-Il Yoo1, Changgwon Dang2, Chang Pyo Hong1, Kung Ahn1.   

Abstract

MicroRNA (miRNA) are found in numerous biofluids including blood and are considered a new class of biomarkers. The data presented here are related to the research article entitled "Profiling and identification of pregnancy-associated circulating microRNAs in dairy cattle" (Markkandan et al. 2018). In the cited article, we sequenced the circulating microRNAs of the three healthy dairy cows of normal and 30 days of pregnancy (DOP) using Illumina RNA-Seq. Differentially expressed genes (DEG) analysis between normal and pregnant samples showed perturbations in miRNA expression. Herein, we made a comparison of DEGs at normal and 60 DOP libraries. The analysis results showed that 147 known miRNAs were differently expressed at 60 DOP groups when compared to the normal group. In addition, stage specific miRNAs were also predicted.

Entities:  

Keywords:  Circulating microRNA; Exosome; Holstein; MiRNA-sequencing; Pregnancy

Year:  2018        PMID: 30417039      PMCID: PMC6216090          DOI: 10.1016/j.dib.2018.09.038

Source DB:  PubMed          Journal:  Data Brief        ISSN: 2352-3409


Specifications table Value of the data The differentially expressed miRNAs could serve as potential biomarkers for not only early diagnosis of pregnancy but also for livestock health and disease. Pregnancy-associated microRNA profiling at 60 DOP in bovine was described for the first time and can be used for comparative studies. These miRNAs may have similar function in mammalian species and can be potential molecular markers for evolution.

Data

Data shown in this article are related to the research article entitled “Profiling and identification of pregnancy-associated circulating microRNAs in dairy cattle” [1]. The exosomal miRNA extracted from the serum blood of normal and 60 DOP samples were analyzed. The quality of sequencing reads was assessed by the read length (Fig. 1, Supplementary Table 1). Table 1 describes the number of differentially expressed miRNAs at 60 days of pregnant cows. The target gene prediction for those differentially expressed miRNAs revealed that, 21,801 genes were regulated by 147 differentially expressed miRNAs (Supplementary Table 2).
Fig. 1

Length distribution of miRNA sequences in normal and 60 days of pregnancy samples by Illumina small RNA deep sequencing. Sequence length distribution of clean reads based on the abundance and distinct sequences; the most abundant size class was 22 nt, followed by 21 and 23 nt.

Table 1

Differential miRNA profile expression between normal and 60 days of pregnancy groups (p-value < 0.05).

Differentially expressed miRNAs60 days of pregnancy groups (This study)30 days of pregnancy groups [1]
Up8821
Down598
Length distribution of miRNA sequences in normal and 60 days of pregnancy samples by Illumina small RNA deep sequencing. Sequence length distribution of clean reads based on the abundance and distinct sequences; the most abundant size class was 22 nt, followed by 21 and 23 nt. Differential miRNA profile expression between normal and 60 days of pregnancy groups (p-value < 0.05).

Experimental design, materials and methods

Animals and collection of samples

The whole blood samples of before and 60 DOP were collected from three individual healthy Holstein cow. Briefly, about 10 mL whole blood was collected in EDTA tubes, and then the samples were incubated at room temperature for 1 h. The whole blood samples were centrifuged at 4 °C (1900×g, 10 min), followed by a second centrifugation at 4 °C (16,000×g, 10 min). After this step, the circulating cell-free nucleic acid were in the supernatant (sera) and then the sera were transferred into a fresh 2.0 mL tube and stored at −80 °C for further analysis.

Extraction total RNA, Illumina sequencing and data analysis

Before RNA isolation, the exosomes in sera was firstly isolated using Total Exosomes Isolation kit (Invitrogen, Carlsbad, CA). Exosomal total RNA was isolated using miRNeasy Mini Kit (Qiagen) following manufacturer׳s protocols. The concentration of RNA was determined using the Qubit microRNA assay kit (Invitrogen, Carlsbad, CA). The RNA samples were stored at −80 °C for further analysis. Total RNA (5 µL) from each sample was used to construct miRNA library using the NEXTflex Small RNA Sequencing Kit (Illumina, San Diego, CA) according to the manufacturer׳s instruction. Small RNA libraries were then pooled together in equal volumes for gel purification. The pooled library was sequenced using the HiSeq. 2500 system (Illumina) as 50 bp single reads. Read quality (adaptor removal, and size selection) was assessed using FastQC v0.11.5 (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) and cutadapt [2]. The sequences with read length larger than 18 nucleotides (nt) were aligned against bovine miRNA database (miRBase, release version 21) with the default parameters to identify known miRNAs using Bowtie2 [3]. Each library was processed separately. The expression level of miRNAs in each library was estimated by sRNAbench, which normalized reads count number of each miRNA reads per million (RPM) by the following formula: RPM=(miRNA reads number/total mapped reads per library)×1,000,000. The DE miRNAs were determined by Log2 fold change (FC) >1 or <−1 and false discovery rate (FDR) < 0.05 based on counting reads using HTSeq [4]. Briefly, target genes of selected miRNAs were commonly predicted by TargetScan [5] and miRanda (http://www.microrna.org/microrna/home.do).
Subject areaBiology
More specific subject areaTranscriptomics
Type of dataTable, figure
How data was acquiredIllumina HiSeq. 2500
Data formatRaw (FASTQ)
Experimental factorsBlood samples of normal and 60 days of pregnancy were collected from three Holstein dairy cattle
Experimental featuresDEGs of normal and 60 days of pregnancy
Sample source locationNational Institute of Animal Science (NIAS), Cheonan, Republic of Korea
Data accessibilityData is available in the article and at: https://www.ncbi.nlm.nih.gov/Traces/study/?acc=SRP151837
  4 in total

1.  Fast gapped-read alignment with Bowtie 2.

Authors:  Ben Langmead; Steven L Salzberg
Journal:  Nat Methods       Date:  2012-03-04       Impact factor: 28.547

2.  Profiling and identification of pregnancy-associated circulating microRNAs in dairy cattle.

Authors:  Kesavan Markkandan; Kung Ahn; Dong Jin Lee; Tae Il Kim; Changgwon Dang; Song-Eui Hong; Ho-Baek Yoon; Hyun-Joo Lim; Chang Pyo Hong
Journal:  Genes Genomics       Date:  2018-02-23       Impact factor: 1.839

3.  Prediction of mammalian microRNA targets.

Authors:  Benjamin P Lewis; I-hung Shih; Matthew W Jones-Rhoades; David P Bartel; Christopher B Burge
Journal:  Cell       Date:  2003-12-26       Impact factor: 41.582

4.  HTSeq--a Python framework to work with high-throughput sequencing data.

Authors:  Simon Anders; Paul Theodor Pyl; Wolfgang Huber
Journal:  Bioinformatics       Date:  2014-09-25       Impact factor: 6.937

  4 in total

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