Coding and Noncoding Genes Involved in Atrophy and Compensatory Muscle Growth in Nile Tilapia

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2022-08-12

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Ali, A.; Shaalan, W.M.; Al-Tobasei, R.; Salem, M. Coding and Noncoding Genes Involved in Atrophy and Compensatory Muscle Growth in Nile Tilapia. Cells 2022, 11, 2504.

Abstract

Improvements in growth-related traits reduce fish time and production costs to reach market size. Feed deprivation and refeeding cycles have been introduced to maximize aquaculture profits through compensatory growth. However, the molecular compensatory growth signature is still uncertain in Nile tilapia. In this study, fish were subjected to two weeks of fasting followed by two weeks of refeeding. The growth curve in refed tilapia was suggestive of a partial compensatory response. Transcriptome profiling of starved and refed fish was conducted to identify genes regulating muscle atrophy and compensatory growth. Pairwise comparisons revealed 5009 and 478 differentially expressed (differential) transcripts during muscle atrophy and recovery, respectively. Muscle atrophy appears to be mediated by the ubiquitin-proteasome and autophagy/lysosome systems. Autophagy-related 2A, F-box and WD repeat domain containing 7, F-box only protein 32, miR-137, and miR-153 showed exceptional high expression suggesting them as master regulators of muscle atrophy. On the other hand, the muscle compensatory growth response appears to be mediated by the continuous stimulation of muscle hypertrophy which exceeded normal levels found in control fish. For instance, genes promoting ribosome biogenesis or enhancing the efficiency of translational machinery were upregulated in compensatory muscle growth. Additionally, myogenic microRNAs (e.g., miR-1 and miR-206), and hypertrophy-associated microRNAs (e.g., miR-27a-3p, miR-29c, and miR-29c) were reciprocally expressed to favor hypertrophy during muscle recovery. Overall, the present study provided insights into the molecular mechanisms regulating muscle mass in fish. The study pinpoints extensive growth-related gene networks that could be used to inform breeding programs and also serve as valuable genomic resources for future mechanistic studies.

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