Meta-analysis of differentially-regulated hepatic microRNAs identifies candidate post-transcriptional regulation networks of intermediary metabolism in rainbow trout

https://doi.org/10.1016/j.cbd.2020.100750Get rights and content

Highlights

  • Several hepatic microRNAs are identified as commonly regulated in response to different experimental metabolic challenges

  • Diet and/or glucose-dependent regulation of several miRNAs families appears to be evolutionarily conserved

  • Predicted miRNA target transcripts suggest coordinated posttranscriptional regulation of metabolic enzymes and mitochondrial dynamics

  • Rewiring of miRNA-30 and miRNA-152 is predicted to target atypically regulated gluconeogenesis paralogues in rainbow trout

  • Evolutionary rewiring of miRNA regulation of gluconeogenic paralogues may contribute to ‘glucose intolerance’ in trout

Abstract

MicroRNAs (miRNAs) are small non-coding RNAs which act as post-transcriptional regulators by decreasing targeted mRNA translation and stability. Principally targeting small 3′ UTR elements of protein-coding mRNAs through complementary base-pairing, miRNAs are promiscuous regulators of the transcriptome. While potent roles for hepatic miRNAs in the regulation of energy metabolism have emerged in rodent models, comparative roles in other vertebrates remain largely unexplored. Indeed, while several miRNAs are deeply conserved among vertebrates, the acquisition of lineage- and species-specific miRNAs, as well as the rewiring between miRNA-mRNA target relationships beg the question of regulatory and functional conservation and innovation of miRNAs and their targets involved in energy metabolism. Here we provide a meta-analysis of differentially expressed hepatic miRNAs in rainbow trout, a scientifically and economically important teleost species with a ‘glucose-intolerant’ phenotype. Following exposure to nutritional and social context-dependent metabolic challenges, we analyzed differential miRNA expression from small-RNA-sequencing datasets generated with a consistent bioinformatics pipeline in conjunction with an in silico target prediction of metabolic transcripts and pathways. We provide evidence for evolutionary conserved (let-7, miRNA-27 family) and rewired (miRNA-30 family, miRNA-152, miRNA-722) miRNA-metabolic target gene networks in the context of the salmonid genome. These findings represent important first steps in our understanding of the comparative regulation and function of hepatic miRNAs in rainbow trout energy metabolism. We propose that the identified miRNA families should be prioritized for future comparative functional investigation in the context of hepatic energy- and glucose metabolism in rainbow trout.

Introduction

Since their discovery in C. elegans (Lee et al., 1993), microRNAs (miRNAs), a class of small non-coding RNA molecules which in their mature form exhibit a length of ~22 nt, have emerged as important post-transcriptional regulators of gene expression (O'Brien et al., 2018). In animals, miRNA-dependent regulation of targeted protein-coding mRNA transcripts is principally mediated via complementary base-pairing between the mature miRNA's seed region (comprised of nucleotides 2–7), and short elements within the targeted mRNA's 3′UTR sequence (McGeary et al., 2019). Initially considered an idiosyncrasy in C. elegans, it has rapidly become clear that miRNAs are deeply conserved in evolution, with few lineage-specific exceptions (Moran et al., 2017). Generally, increases in organismal complexity in animals are considered to scale with the quantity and complexity of the miRNA repertoire, and lineage-specific acquisition of novel miRNAs with losses of only a few specific miRNA families have been reported (Tarver et al., 2018). Functionally, miRNAs have, largely in rodent models and mammalian species in general, been linked to several key biological functions, including the regulation of energy metabolism (Rottiers and Näär, 2012; Hartig et al., 2015). However, in spite of the fact that the comparative investigation of the miRNA repertoire, its regulation, and the degree of conservation or evolutionary rewiring of targeted mRNA transcripts and pathways have the potential to help identify key conserved miRNA-target relationships on the one hand, and lineage-specific innovation on the other, very few studies have attempted to address these questions (Mennigen, 2016).

Since the advent of genome sequencing, major strides have been made in many traditional research models which previously lacked genomic resources to assess species-specific miRNA repertoires and predicted targets in a genome-wide context. This development has been true for teleost fishes and rainbow trout in particular (Mennigen, 2016), for which annotated miRNA repertoires (Juanchich et al., 2016) and in silico target prediction algorithms (Mennigen and Zhang, 2016) have been published following the sequencing of its genome (Berthelot et al., 2014). Because rainbow trout have been used as a comparative research model due to its ‘glucose-intolerant’ phenotype (Forbes et al., 2019), the evolution of its genome (Berthelot et al., 2014), and because of its economic importance in freshwater angling and aquaculture (Logan and Johnston, 1992; Crawford and Muir, 2008), significant research efforts have been geared towards the elucidation of molecular regulation of energy metabolism in this species (Panserat et al., 2012). It is therefore not surprising that with newly available genomic resources, comparative research of epigenetic molecular mechanisms involved in transcriptional and post-transcriptional control of energy metabolism has increased substantially over the last several years in this species (Best et al., 2018). As a major metabolic hub, the liver has been investigated in particular detail in this context: In addition to transcriptional level investigations which addressed potential roles of chromatin and DNA methylation level regulation of hepatic expression of genes with roles in energy metabolic pathways (Marandel et al., 2016), our group has conducted a range of studies to investigate regulation and potential post-transcriptional roles for miRNAs in hepatic energy metabolism in rainbow trout (Kostyniuk et al., 2019b, Kostyniuk et al., 2019a, Kostyniuk et al., 2018). We here use a meta-analytical approach to identify commonly regulated miRNAs in response to nutritional and social-status dependent metabolic challenges, as well as an in silico approach to address their possible function in rainbow trout hepatic energy metabolism. An overview of experimental designs which consisted of metabolic challenges in the form of changes of nutritional quantity and quality as a function of diet and/or social context is provided in Fig. 1 (Kostyniuk et al., 2019a, Kostyniuk et al., 2019b). In all experiments, changes of specific energy-metabolism related transcript steady-state abundances have been assessed, allowing correlative analysis between differentially-regulated miRNAs and their in silico predicted mRNA targets. Because rainbow trout experienced teleost-specific and salmonid-specific whole genome duplication events with consequences for the repertoire of energy metabolism transcripts (Marandel et al., 2019, Marandel et al., 2015), we attempt an initial in silico based investigation of potential paralogue-specific regulation by differentially regulated miRNA in this species, which forms an integral part of its comparative genomic context. Finally, as both differential miRNA abundance and specific DNA-level epigenetic molecular mechanisms have been quantified in the same liver tissue samples within specific experiments (Marandel et al., 2016; Kostyniuk et al., 2019a), we will discuss possible interaction of miRNA-dependent post-transcriptional and DNA-level epigenetic molecular mechanisms previously proposed in this species (Kuc et al., 2017).

Section snippets

Experimental design and analytical pipeline to determine differentially regulated hepatic miRNA abundances

The specific conditions for all rainbow trout experiments, as well as the processing and short RNA-sequencing analysis pipeline have been described in detail previously (Kostyniuk et al., 2019a, Kostyniuk et al., 2019b) and are summarized in Fig. 1 and Supplemental File S1, respectively. Briefly, sequences were initially filtered using the LCScience ACGT10-miR v4.2 pipeline to remove low-quality sequences, low-complexity sequences, and sequences corresponding to common RNA families (mRNA, RFam,

Differentially regulated hepatic miRNAs in short-term fasted rainbow trout

Of the overall ~69 M raw reads (Supplemental File S2), 39.76 M reads were excluded due a lack of a 3′adapter (3′ADT) (~32.16 M or 46.6%) and because of a nucleotide size outside the targeted range of 15–32 nt (~7.5 M or 11%) after 3′ADT sequence screening. This resulted in ~29.26 M mappable reads, of which 74% exhibit a size between 19 and 23 nt (Supplemental File S3). The Phred Score distribution of reads was larger than 30 (Supplemental File S4), indicating a probability of incorrect base

Rainbow trout strain and/or rearing temperature affect the hepatic miRNAome across experimental conditions

The current study used hepatic samples of rainbow trout exposed to different metabolic challenges in an effort to identify key miRNAs predicted to be involved in the regulation of rainbow trout hepatic metabolism. While the newly identified differentially regulated miRNAs in rainbow trout liver under conditions of short term fasting complement distinct hepatic miRNA profiles previously observed in juvenile rainbow trout under different metabolic challenges (Fig. 1), the current meta-analysis

Declaration of competing interest

The authors do not declare any conflict of interest.

Acknowledgements

We would like to thank Dr. Lucie Marandel and Dr. Stéphane Panserat (INRA NuMeA 1419/Université de Pau et Pays d'Adour, France), as well as Dr. Katie Gilmour (Department of Biology, University of Ottawa, Canada) for sharing tissue and/or RNA samples which form the basis for this meta-analysis. This research was supported through a MITACS Globalink Research/Campus France grant (#FR26557) awarded to DJK, as well as NSERC-DG (#147476) and CFI-JELF grants (#35859) awarded to JAM.

References (66)

  • L. Marandel et al.

    Pck-ing up steam: widening the salmonid gluconeogenic gene duplication trail

    Gene

    (2019)
  • J.A. Mennigen

    Micromanaging metabolism-a role for miRNAs in teleost energy metabolism

    Comp. Biochem. Physiol. B: Biochem. Mol. Biol.

    (2016)
  • J.A. Mennigen et al.

    MicroTrout: a comprehensive, genome-wide miRNA target prediction framework for rainbow trout, Oncorhynchus mykiss

    Comp. Biochem. Physiol. Part D Genomics Proteomics

    (2016)
  • S. Roush et al.

    The let-7 family of microRNAs

    Trends Cell Biol.

    (2008)
  • J. Sun et al.

    Potential regulation by miRNAs on glucose metabolism in liver of common carp (Cyprinus carpio) at different temperatures

    Comp. Biochem. Physiol. Part D Genomics Proteomics

    (2019)
  • R. Zhang et al.

    Caloric restriction induces microRNAs to improve mitochondrial proteostasis

    iScience

    (2019)
  • H. Zhu et al.

    The Lin28/let-7 axis regulates glucose metabolism

    Cell

    (2011)
  • C. Berthelot et al.

    The rainbow trout genome provides novel insights into evolution after whole-genome duplication in vertebrates

    Nat. Commun.

    (2014)
  • T.T. Bizuayehu et al.

    Temperature during early development has long-term effects on microRNA expression in Atlantic cod

    BMC Genomics

    (2015)
  • C. Castaño et al.

    Obesity-associated exosomal miRNAs modulate glucose and lipid metabolism in mice

    PNAS

    (2018)
  • T. Chen et al.

    MiR-27a promotes insulin resistance and mediates glucose metabolism by targeting PPAR-γ-mediated PI3K/AKT signaling

    Aging (Albany NY)

    (2019)
  • F. Christodoulou et al.

    Ancient animal microRNAs and the evolution of tissue identity

    Nature

    (2010)
  • S.S. Crawford et al.

    Global introductions of salmon and trout in the genus Oncorhynchus: 1870–2007

    Rev. Fish Biol. Fish.

    (2008)
  • S. Dias et al.

    MicroRNA expression varies according to glucose tolerance, measurement platform, and biological source [WWW document]

    Biomed. Res. Int.

    (2017)
  • H. Dweep et al.

    In-silico algorithms for the screening of possible microRNA binding sites and their interactions

    Curr Genomics

    (2013)
  • A.J. Enright et al.

    MicroRNA targets in Drosophila

    Genome Biol.

    (2003)
  • J.L.I. Forbes et al.

    Unexpected effect of insulin on glucose disposal explains glucose intolerance of rainbow trout

    Am. J. Phys. Regul. Integr. Comp. Phys.

    (2019)
  • R.J.A. Frost et al.

    Control of glucose homeostasis and insulin sensitivity by the Let-7 family of microRNAs

    PNAS

    (2011)
  • M.I. Hernández-Alvarez et al.

    Glucocorticoid modulation of mitochondrial function in hepatoma cells requires the mitochondrial fission protein Drp1

    Antioxid. Redox Signal.

    (2013)
  • S. Hsu et al.

    CREB-regulated miR-27b is linked to hepatic insulin resistance by targeting insulin/Akt signaling

    FASEB J.

    (2019)
  • C.W. Huang et al.

    Differential expression patterns of growth-related microRNAs in the skeletal muscle of Nile tilapia (Oreochromis niloticus)

    J. Anim. Sci.

    (2012)
  • R. Jagannathan et al.

    Translational regulation of the mitochondrial genome following redistribution of mitochondrial microRNA (MitomiR) in the diabetic heart

    Circ. Cardiovasc. Genet.

    (2015)
  • I.A. Johnston et al.

    Embryonic temperature affects muscle fibre recruitment in adult zebrafish: genome-wide changes in gene and microRNA expression associated with the transition from hyperplastic to hypertrophic growth phenotypes

    J. Exp. Biol.

    (2009)
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