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Maternal nutrient restriction in mid-to-late gestation influences fetal mRNA expression in muscle tissues in beef cattle

Overview of attention for article published in BMC Genomics, August 2017
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Title
Maternal nutrient restriction in mid-to-late gestation influences fetal mRNA expression in muscle tissues in beef cattle
Published in
BMC Genomics, August 2017
DOI 10.1186/s12864-017-4051-5
Pubmed ID
Authors

Francois Paradis, Katie M. Wood, Kendall C. Swanson, Stephen P. Miller, Brian W. McBride, Carolyn Fitzsimmons

Abstract

Manipulating maternal nutrition during specific periods of gestation can result in re-programming of fetal and post-natal development. In this experiment we investigated how a feed restriction of 85% compared with 140% of total metabolizable energy requirements, fed to cows during mid-to-late gestation, influences phenotypic development of fetuses and mRNA expression of growth (Insulin-Like Growth Factor family and Insulin Receptor (INSR)), myogenic (Myogenic Differentiation 1 (MYOD1), Myogenin (MYOG), Myocyte Enhancer Factor 2A (MEF2A), Serum Response Factor (SRF)) and adipogenic (Peroxisome Proliferator Activated Receptor Gamma (PPARG)) genes in fetal longissimus dorsi (LD) and semitendinosus (ST) muscle. DNA methylation of imprinted genes, Insulin Like Growth Factor 2 (IGF2) and Insulin Like Growth Factor 2 Receptor (IGF2R), and micro RNA (miRNA) expression, were also examined as potential consequences of poor maternal nutrition, but also potential regulators of altered gene expression patterns. While the nutrient restriction impacted dam body weight, no differences were observed in phenotypic fetal measurements (weight, crown-rump length, or thorax circumference). Interestingly, LD and ST muscles responded differently to the differential pre-natal nutrient levels. While LD muscle of restricted fetal calves had greater mRNA abundances for Insulin Like Growth Factor 1 and its receptor (IGF1 and IGF1R), IGF2R, INSR, MYOD1, MYOG, and PPARG, no significant differences were observed for gene expression in ST muscle. Similarly, feed restriction had a greater impact on the methylation level of IGF2 Differentially Methylated Region 2 (DMR2) in LD muscle as compared to ST muscle between treatment groups. A negative correlation existed between IGF2 mRNA expression and IGF2 DMR2 methylation level in both LD and ST muscles. Differential expression of miRNAs 1 and 133a were also detected in LD muscle. Our data suggests that a nutrient restriction of 85% as compared to 140% of total metabolizable energy requirements during the 2nd half of gestation can alter the expression of growth, myogenic and adipogenic genes in fetal muscle without apparent differences in fetal phenotype. It also appears that the impact of feed restriction varies between muscles suggesting a priority for nutrient partitioning depending on muscle function and/or fiber composition. Differences in the methylation level in IGF2, a well-known imprinted gene, as well as differences in miRNA expression, may be functional mechanisms that precede the differences in gene expression observed, and could lead to trans-generational epigenetic programming.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 81 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 13 16%
Researcher 9 11%
Student > Ph. D. Student 8 10%
Student > Bachelor 5 6%
Student > Doctoral Student 5 6%
Other 13 16%
Unknown 28 35%
Readers by discipline Count As %
Agricultural and Biological Sciences 28 35%
Biochemistry, Genetics and Molecular Biology 6 7%
Medicine and Dentistry 5 6%
Veterinary Science and Veterinary Medicine 4 5%
Unspecified 2 2%
Other 4 5%
Unknown 32 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 August 2017.
All research outputs
#20,444,703
of 22,999,744 outputs
Outputs from BMC Genomics
#9,320
of 10,692 outputs
Outputs of similar age
#278,298
of 318,830 outputs
Outputs of similar age from BMC Genomics
#175
of 203 outputs
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