Bovine hepatic miRNAome profiling and differential miRNA expression analyses between beef steers with divergent feed efficiency phenotypes
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ABSTRACT:
PROVIDER: PRJNA603649 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR10983300.fastq.gz | Fastqsanger.gz | |||
| SRR10983301.fastq.gz | Fastqsanger.gz | |||
| SRR10983302.fastq.gz | Fastqsanger.gz | |||
| SRR10983303.fastq.gz | Fastqsanger.gz | |||
| SRR10983304.fastq.gz | Fastqsanger.gz |
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Project description:The aim of this study was to measure the effect of contrasting breed and dietary source on the skeletal muscle miRNA profile of beef cattle divergent for feed efficiency (RFI). Charolais (n=90) and Holstein-Fresian (N=77) steers) were offered two consecutive diets; namely a zero-grazed grass diet followed by a high concentrate diet. Dietary intakes were recorded for all steers throughout each dietary phase and residual feed intake values dertermined for each steer. At the end of each dietary phase the most efficient (Low-RFI; n=8) and least efficient (High-RFI; n=8) steers were selected across each breed for longissmus dorsi biopsy collection. RNA was isolated from all muscle tissue samples and subsequently used for small RNA sequencing. Ten miRNA were differentially expressed between the steers divergent for RFI across each diet and breed contrast. Biological pathway analyssi revealed enrichment of pathways related to both metabolic and growth processes.
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Project description:The objectives of the current study was to profile miRNA expression in the liver tissue of beef steers and consequently identify differentially expressed miRNAs between efficient and inefficient beef steers. Materials and Methods: In total 50 purebred Angus, 48 purebred Charolais and 158 Kinsella Composite breed steers were tested for individual feed intake using the GrowSafe system for an average period of 70 to 73 days. During the feedlot test animals were fed at ad libitum with a finishing diet composed of 75% barley grain, 20% barley silage and 5% rumensin pellet. Body weight of each animal was measured at an interval of 28days and ADG for each animal was obtained from a linear regression of serial body weight (BW) measurements (Kgs) on time (days). MWT was calculated as midpoint BW0.75, where midpoint BW was computed as the sum of initial BW of the animal and the product of its ADG multiplied by half the number test days. DMI of each animal was calculated as the average daily feed intake of the animals for the time during the feedlot test (days). The expected DMI for each animal was predicted using the regression intercept and regression coefficients of ADG and MWT on actual DMI, and RFI was computed as the difference between the standardized daily DMI and the expected DMI. At the end of the test, animals were slaughtered and liver tissue was collected immediately after slaughter separately bagged in plastic bags, labelled and flash frozen in liquid nitrogen. The frozen samples were transferred to the laboratory on ice and stored at -80C until RNA extraction. From the frozen samples, 20 samples (10 with positive and 10 with negative RFI phenotype values) of each breed were considered for total RNA extraction. Each of the selected liver tissue sample was pulverised into fine powder using liquid nitrogen and a pre-chilled mortar and pestle on dry ice. Total RNA containing small RNAs was then extracted using a Qiagen RNeasy Plus Universal Mini Kit (Qiagen, Toronto, ON). NanoDrop 2000 Spectrophotometer (Thermo Scientific, Wilmington, DE, USA) was used to quantify the RNA. We obtained total RNA of an average concertation of 1851.8ng/µl per sample, and with absorbance ratios (A260/280) ranging between 1.8 and 2.0 which were considered of high purity for downstream analyses. RNA integrity was confirmed using a TapeStation-Agilent instrument (Agilent Technologies Canada, Mississauga, ON), RNA integrity number (RIN) values for all samples were higher than 8 which deemed them of high quality for cDNA library preparation. In total 60 cDNA libraries were prepared and sequenced at Clinical Genomics Centre (Toronto, ON, Canada). The libraries were prepared using the Illumina Truseq Small RNA Library Prep Kit (Illumina, San Diego, CA, USA) from 1µg of each of total RNA samples we submitted. Firstly, an RNA 3’ adapter was ligated to the 3’ end of the RNAs in the total RNA sample using T4 RNA Ligase 2 enzyme, thereafter an RNA 5’ adapter was added to the 5’ end of the 3’ adaptor-ligated-RNAs using T4 RNA Ligase. The RNA 3’ and RNA 5’ adapters are designed to specifically target miRNAs and other small RNAs resulting from similar biogenic processing. The 5’ and 3’ adapter ligated RNA was then Reverse transcribed using SuperScript II Reverse Transcriptase (Thermo Fisher Scientific, San Jose, CA, USA) and the RNA RT primer to generate single stranded cDNA. The cDNA was then PCR amplified a common RNA PCR primer, and a second RNA PCR primer containing a six-nucleotide indexing sequence to allow multiplexed sequencing of multiple samples on the same flow cell lane. The cDNA libraries were purified via gel electrophoresis using a 6% PAGE Gel, and the 160bp and 145bp cDNA bands were used for sequencing. Four sequencing pools of 15 samples were constructed by pooling an average of 2nM cDNA of each sample. The pooled cDNA libraries were single end sequenced on two flow cells using the Illumina Hiseq 2500 sequencing platform under Rapid run mode, with expected read length of 50bp (1x50bp SR). After sequencing raw sequence data were demultiplexed into individual FASTQ file each sample using Illumina bcl2fastq-v2.17.1.14 conversion software (Illumina). Adaptors on the 3' end of the sequences were clipped of using Cutadapt version 1.16, and consquently filtered for other small RNA species using bowtie-1.1.1 short read aligner. Individual miRNA (including known and novel miRNAs) were profiled using the UMD3.1 bovine reference genome and the miRDeep2 package (version 2.0.0.8), Differential miRNA expression analyses within each breed was performed between six extreme low RFI and high RFI animals using edgeR package in R, at a threshold of P < 0.05 and Fold change > 1.5. We identified 588 miRNAs as expressed in the liver tissue of the studied animals of which 90% of these miRNAs were expressed in animals from all three breed populations. Ten previously identified (known) miRNAs including bta-miR-192, bta-miR-143, bta-miR-148a, bta-miR-26a, bta-miR-30a-5p, bta-miR-22-3p, bta-miR-27b, bta-let-7f, bta-miR-27a-3p, and bta-miR-101 showed exceptionally high expression in the liver tissue of all steers, accounting for over 78% of the aligned sequence reads. We also identified 241 novel bovine miRNAs, of which the majority (69%) were uniquely expressed in one of the three breed populations. We identified 12 (7 up- and 5 down- regulated in low-RFI animals), 18 (12 up- and 6 down- regulated in low-RFI animals), and 12 (8 up- and 4 down- regulated in low-RFI animals) DE miRNAs for Angus, Charolais, and KC steers, respectively. Most of the DE miRNAs were breed specific, with only bta-miR-449a being differentially expressed in all three breeds.
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Project description:We functionally analyzed the rumen epithelial transcriptomes from low- and high- feed efficient beef steers to identify differences that might contribute to variation in feed efficiency.
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Project description:Transcriptional profiling of bovine skeletal muscle comparing metabolically efficient steers to metabolically inefficient steers to ascertain what expression differences can be found in muscle tissue that might help explain differences in this economically significant phenotype. Two condition experiment, efficient versus inefficient animals. 8 efficient and 8 inefficient samples were used representing 16 unique individual animals.
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Project description:Transcriptional profiling of bovine skeletal muscle comparing metabolically efficient steers to metabolically inefficient steers to ascertain what expression differences can be found in muscle tissue that might help explain differences in this economically significant phenotype.
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Project description:The objective of this study was to identify differentially expressed genes in the liver of steers with divergent Residual Feed Intake (RFI). Methods:In total 50 purebred Angus, 48 purebred Charolais and 158 Kinsella Composite breed steers were tested for individual feed intake using the GrowSafe system for an average period of 70 to 73 days. During the feedlot test animals were fed at ad libitum with a finishing diet composed of 75% barley grain, 20% barley silage and 5% rumensin pellet. Body weight of each animal was measured at an interval of 28days and ADG for each animal was obtained from a linear regression of serial body weight (BW) measurements (Kgs) on time (days). MWT was calculated as midpoint BW0.75, where midpoint BW was computed as the sum of initial BW of the animal and the product of its ADG multiplied by half the number test days. DMI of each animal was calculated as the average daily feed intake of the animals for the time during the feedlot test (days). The expected DMI for each animal was predicted using the regression intercept and regression coefficients of ADG and MWT on actual DMI, and RFI was computed as the difference between the standardized daily DMI and the expected DMI. At the end of the test, animals were slaughtered and liver tissue was collected immediately after slaughter separately bagged in plastic bags, labeled and flash frozen in liquid nitrogen. The frozen samples were transferred to the laboratory on ice and stored at -80C until RNA extraction. From the frozen samples, 20 samples from each breed were selected for total RNA extraction including six samples with extreme high and six samples extreme low-RFI phenotypes for each breed. Complementary DNA (cDNA) libraries were constructed for each of the 60 animals and consequently single end sequenced using Illumina Hiseq 2500 sequencer. The raw reads were aligned and mapped to the bovine reference genome UMD 3.1 using Tophat2 aligner with default alignment parameters. Thereafter, reads aligned uniquely to each annotated transcript of gene in the bovine genome were counted using HTSeq-count package with default parameters. Read counts from HTSeq-count, sample information (sample id, sire, feed efficiency group and sequencing mode) and gene annotation table from ENSEMBL Biomart were used for differential expression analysis within each breed using the edgeR package in R for the six extreme low-RFI and six extreme high-RFI samples. Results: At a false discovery rate of 0.05 and fold change > 2 , we identified 72, 41 and 175 differentially expressed genes for Angus, Charolais and KC RFI divergent steers respectively.
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