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Effects of Intramuscular Administration of Folic Acid and Vitamin B12 on Granulosa Cells Gene Expression in Postpartum Dairy Cow

GSE72038 Bos taurus Expression microarray 6 samples Submitted 2015/09/15 Platform GPL13226
At a glance

Expression microarray · Bos taurus · 6 samples

What it is
Expression microarrayGene activity read on a chip (the older technology that RNA-seq replaced).
Organism
Bos taurus
Samples
6 samples
Data you can get
A processed expression table (series matrix) and the array files, from NCBI.
Summary (written by the submitters)
The fertility of dairy cows is challenged during early lactation and better nutritional strategies need to be developed to address this issue. Combined supplementation of folic acid and vitamin B12 improves energy metabolism in the dairy cow during early lactation. Therefore, the present study was undertaken to explore the effects of this supplement on gene expression in granulosa cells from the dominant follicle during the postpartum period.
Read the full summary ↓
Multiparous Holstein cows received weekly intramuscular injection of 320 mg folic acid and 10 mg vitamin B12 (treated group) beginning 24 (SD 4) d before calving until 56 d after calving, whereas the control group received saline. The urea plasma concentration was significantly decreased during the pre-calving period, and the concentration of both folate and vitamin B12 were increased in treated animals. Milk production and dry matter intake were not significantly different between the two groups. Plasma concentrations of folates and vitamin B12 were increased in vitamin-treated animals. Daily dry matter intake was not significantly different between the 2 groups before (13.5 kg SE 0.5) and after (23.6 kg SE 0.9) calving. Average energy-corrected milk tended to be greater in vitamin-treated cows, 39.7 (SE 1.4) and 38.1 (SE 1.3) kg/d for treated and control cows, respectively. After calving, average plasma concentration of BHBA tended to be lower in cows injected with the vitamin supplement, 0.47 (SE 0.04) vs. 0.55 (SE 0.03) for treated and control cows, respectively. The ovarian follicle ? 12 mm in diameter was collected by ovarian pick-up after estrus synchronization. Recovered follicular fluid volumes were greater in the vitamin-treated group. A microarray platform was used to investigate the impact of treatment on gene expression of granulosa cells. Lower expression of genes involved in the cell cycle and higher expression of genes associated with granulosa cell differentiation prior to ovulation were observed. Selected candidate genes were analyzed by reverse transcription quantitative polymerase chain reaction. Although the effects of intramuscular injections of folic acid and vitamin B12 on lactational performance and metabolic status of animals were limited, Ingenuity Pathway Analysis of gene expression in granulosa cells suggests a stimulation of cell differentiation in vitamin-treated cows, which may be the result of an increase in LH secretion.
This dataset
Download · which file do I need?

Direct links to NCBI, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need.

All supplementary files ↗
3 · The original raw files

Whole study · RAW.tar

Everything the authors deposited as one archive (GSE72038_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

What the files usually look like: For arrays the series matrix is normally the normalised expression table you want; the raw array files (CEL and similar) are in the RAW.tar.

Also filed as BioProject PRJNA292882. Searching any of these in the dataset finder brings you back here.

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