Long noncoding RNAs in lipid metabolism: literature review and conservation analysis across species
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Abstract
Background
Lipids are important for the cell and organism life since they are major components of membranes, energy reserves and are also signal molecules. The main organs for the energy synthesis and storage are the liver and adipose tissue, both in humans and in more distant species such as chicken. Long noncoding RNAs (lncRNAs) are known to be involved in many biological processes including lipid metabolism.
Results
In this context, this paper provides the most exhaustive list of lncRNAs involved in lipid metabolism with 60 genes identified after an in-depth analysis of the bibliography, while all “review” type articles list a total of 27 genes. These 60 lncRNAs are mainly described in human or mice and only a few of them have a precise described mode-of-action. Because these genes are still named in a non-standard way making such a study tedious, we propose a standard name for this list according to the rules dictated by the HUGO consortium. Moreover, we identified about 10% of lncRNAs which are conserved between mammals and chicken and 2% between mammals and fishes. Finally, we demonstrated that two lncRNA were wrongly considered as lncRNAs in the literature since they are 3′ extensions of the closest coding gene.
Conclusions
Such a lncRNAs catalogue can participate to the understanding of the lipid metabolism regulators; it can be useful to better understand the genetic regulation of some human diseases (obesity, hepatic steatosis) or traits of economic interest in livestock species (meat quality, carcass composition). We have no doubt that this first set will be rapidly enriched in coming years.
Keywords
lncRNA Lipid metabolism Liver Evolution SyntenyAbbreviations
- 5-8F
Human nasopharyngeal carcinoma cell line
- ABCA1/ABCG5
ATP-Binding Cassette A1/G5
- ACACA/ACACB
Acetyl-CoA Carboxylase Alpha/Bêta
- ACADS/ACADVL
Acyl-CoA Dehydrogenase Short chain/Very Long chain
- ACAT2
Acetyl-CoA AcetylTransferase 2
- ACC1
Acetyl-CoA Carboxylase 1 (ACC1 – ACACA)
- ACLY
ATP Citrate LYase
- ACOT9
Acyl-CoA Thioesterase 9
- ACOX1
Acyl-CoA OXidase 1
- ACSL1
Acyl-CoA Synthetase Long chain 1
- Akt
PKB (Protein Kinase B)
- ANKHD1
Ankyrin repeat and KH Domain-containing protein 1
- ANRIL
Antisense Non-coding RNA in the INK4 Locus
- APO genes
APOlipoprotein genes
- AS
AntiSense
- ASC
Adipose Stromal Cells
- ATGL
Adipose triglyceride lipase
- B4GALT1
Beta-1,4-GALactosylTransferase 1
- BCL1/BCL2
B-Cell Lymphoma protein 1/2
- Blnc1
Brown fat LNCRNA 1
- CASIMO1
Cancer Associated Small Integral Membrane ORF 1
- CBRH-7919
Rat hepatocarcinoma cell line
- CD36
Cluster of Differentiation 36
- cDNA
complementary DNA
- CDS1
CDP-Diacylglycerol Synthase 1
- CEBPA
CCAAT/Enhancer-Binding Protein Alpha
- ceRNA
competing endogenous RNA
- ChIP
Chromatin ImmunoPrecipitation
- ChIRP
Chromatin Isolation by RNA Purification
- CNE2
Human nasopharyngeal carcinoma cell line
- CPT1A
Carnitine PalmitoylTransferase 1A
- CRNDE
ColoRectal Neoplasia Differentially Expressed
- CRP
C-Reactive Protein
- CYP51A1/7A1/8B1
Cytochrome P450 51A1/7A1/8B1
- DAG
DiAcylGlycerol
- DGAT2
DiGlyceride AcylTransferase 2
- DGKA
DiacylGlycerol Kinase Alpha
- DHCR24
24-DeHydroCholesterol Reductase
- DNA
DesoxyriboNucleic Acid
- DT
Divergent transcript
- EDF1
Endothelial Differentiation related Factor 1
- ELOVL6
ELongation Of Very Long chain fatty acids protein 6
- FA
Fatty Acid
- FABP4/5
Fatty Acid-Binding Protein 4/5
- FADS2
Fatty Acid DeSaturase 2
- FASN
Fatty Acid Synthase
- FDPS
Farnesyl DiPhosphate Synthase
- FLRL3/5/8
Fatty Liver Related LncRNA 3/5/8
- FXR
Farnesoid X Receptor; from NR1H4 gene
- GENE-AS#
Antisense of GENE
- GENE-DT
Divergent Transcript from GENE
- GPAT3
Glycerol-3-Phosphate AcylTransferase 3
- GPR119
G Protein-coupled Receptor 119
- GWAS
Genome-Wide Association Study
- H3K27
Histone 3, Lysine 27
- H3K27me3
trimethylation of H3K27
- HAGLR
HOXD Antisense Growth-associated Long non-coding RNA
- HCC
HepatoCellular Carcinoma
- HCT116, HCT 119, HT29
Human colorectal carcinoma cell line
- HDL
High-Density
- HEK-293 T
Human embryonic kidney cell line
- HeLa229
Human cervix adenocarcinoma cell line
- HEM-1
Human melanoma cell line
- HepG2
Human hepatocarcinoma cell line
- HMGCR
3-Hydroxy-3-Methylglutaryl-CoA Reductase
- HMGCS
3-Hydroxy-3-Methylglutaryl-CoA Synthase
- hnRNP
Heterogeneous Nuclear RiboNucleoProtein
- HOTAIR
HOX Transcript Antisense RNA
- HOXC6
Homeobox protein C6
- HSD17B7
17-beta-HydroxySteroid Dehydrogenase
- HUGO
HUman Genome Organisation
- Huh7
Human hepatocarcinoma cell line
- HULC
Highly Upregulated in Liver Cancer
- HUVEC
Human Umbilical Vein Endothelial Cells
- IDI1
Isopentenyl-diphosphate Delta Isomerase 1
- IGF2BP2
Insulin-like Growth Factor 2 Binding Protein 2
- IL-1β/6
Interleukin 1β/6
- INPP5D
INositol Polyphoshate-5-Phosphatase D
- IRX5
Iroquois Homeobox 5
- KD
Knockdown
- KO
Knockout
- LDL
Low-Density Lipoprotein
- LEP
Leptin
- LeXis
Liver-Expressed LXR-Induced Sequence
- linc-ADAL
lincRNA for ADipogenesis And Lipogenesis
- LINCADL
LincRNA for ADipogenesis And Lipogenesis
- lincRNA-DYNLRB2–2
linRNA-DYNein Light chain RoadBlock-type 2, transcript 2
- LINK-A
Long Intergenic Noncoding RNA for Kinase Activation
- LISPR1
Long Intergenic noncoding RNA antisense to S1PR1
- LIVAR
Liver cell Viability Associated lncRNA
- lncARSR
lncRNA Activated in RCC with Sunitinib Resistance
- lncHR1
lncRNA HCV Regulated 1
- lnc-KDM5D-4
lncRNA-Lysine DeMethylase 5D, transcript 4
- lncLSTR
lncRNA Liver-Specific Triglyceride Regulator
- lncRNA
long noncoding RNA
- lncSHGL
lncRNA Suppressor of Hepatic Gluconeogenesis and Lipogenesis
- LNMICC
lncRNA associated with Lymph Node Metastasis In Cervical Cancer
- LPCAT3
LysoPhosphatidylCholine AcylTransferase 3
- LPIN1/2
Lipin 1/2
- LPL
LipoProtein Lipase
- LSD1
Lysine (K)-Specific Demethylase 1; from KDM1A gene
- LSS
Lanosterol Synthase
- LXR
Liver X Receptor; from NR1H2/3 genes
- MALAT1
Metastasis Associated in Lung Adenocarcinoma Transcript 1
- MCF-7
Human breast cancer cell line
- MEG3
Maternally Expressed Gene 3
- MeXis
Macrophage-Expressed LXR-Induced Sequence
- MG-63
Human osteosarcoma cell line
- MGI
Mouse Genome Informatics
- miRNA
micro RNA
- MVD
MeValonate diphosphate Decarboxylase
- MVK
MeValonate Kinase
- NAFLD
Non-Alcoholic Fatty Liver Disease
- NASH
Non-Alcoholic Steato-Hepatitis
- NEAT1
Nuclear Enriched Abundant Transcript 1
- NF1
NeuroFibromin 1
- NFIA
Nuclear Factor I A
- NRF2
NFE2-Related Factor 2; from NFE2L2 gene
- NRON
Noncoding RNA Repressor Of NFAT
- NSCLC
Non-Small Cell Lung Cancer
- OLMALINC
OLigodendrocyte Maturation-Associated Long Intergenic NonCoding RNA
- ORF
Open Reading Frame
- Ov.
Overexpression
- Ox-LDL
Oxidized LDL
- PCR
Polymerase Chain Reaction
- PCSK9
Proprotein Convertase Subtilisin/Kexin Type 9
- PI4KB
Phosphatidylinositol 4-Kinase Beta
- PIP3
Phosphatidylinositol (3,4,5)-trisphosphate
- PL
Phospholipid
- PLA2G1B
PhosphoLipase A2, Group 1B
- PLCB3/G1
PhosphoLipase C Beta 3/Gamma 1
- PMVK
PhosphoMeValonate Kinase
- PNPLA2
PatatiN-like PhosphoLipase A2
- PPARA/G
Peroxisome Proliferator-Activated Receptors Alpha/Gamma
- PRC2
Polycomb Repressive Complex 2
- PTBP1
Polypyrimidine Tract Binding Protein 1
- PVT1
Plasmacytoma Variant Translocation 1
- qPCR
quantitative PCR
- RALY
hnRNP Associated with Lethal Yellow protein
- RIP
RNA ImmunoPrecipitation
- RNA
RiboNucleic Acid
- RNCR3
Retinal Non-Coding RNA 3
- RPKM
Reads Per Kilobase of transcript, per Million mapped reads
- RT-PCR
Reverse Transcription PCR
- S1PR1
Sphingosine-1-Phosphate Receptor 1
- SAF
Antisense of FAS (Fas Cell Surface Death Receptor)
- SCD
Stearoyl-CoA Desaturase
- SHP
Small Heterodimer Partner
- siRNA
small interfering RNA
- SMCR2
Smith-Magenis syndrome Chromosome Region, candidate 2
- SMIM22
SMall Integral Membrane protein 22
- SNHG16
Small Noncoding Host Gene 16
- SNP
Single Nucleotide Polymorphism
- SQLE
SQuaLene Epoxidase
- SRA1
Steroid Receptor RNA Activator 1
- SRAP
Steroid Receptor RNA Activator Protein
- SREBF1/2
Sterol Regulatory Element Binding transcription Factor 1/2
- SUZ12
SUppressor of Zeste 12
- TAG
TriAcylGlycerol
- TG
TriGlycerides
- THP-1
Human leukemic monocyte cell line
- TNBC
Triple-Negative Breast Cancer
- TNFa
Tumor Necrosis Factor
- TRIB1/3
TRIBbles homolog 1/3
- TRIBAL
TRIB1-Associated Locus
- U2OS
Human osteosarcoma cell line
- uc.372
ultra Conserved 372
- VLDL
Very Low-Density
Background
Lipids are found in all organisms and are essential for life [1, 2, 3]. They contribute to cell membrane constitution, acting as signaling molecules and as an important source of energy. In animal species, the deregulation of lipid homeostasis processes is responsible for dyslipidemia and many diseases of major importance in human health such as obesity, diabetes, non-alcoholic fatty liver disease (NAFLD) or cardiovascular diseases. The major site of lipid synthesis may differ from one species to another. Lipogenesis from carbohydrates sources occurs mainly in the liver in primates and rodents, and in adipose tissue in carnivores and ungulates (pig, cow, goat, dog) [1]. Note that for chicken [4, 5, 6] and many fishes [7], the major site of de novo fatty acid synthesis is the liver. The synthesis of cholesterol in mammals, birds and fish is more ubiquitous but predominates in the liver [5, 8, 9, 10]. The storage of fatty acids in triglycerides is the main animal’s energy reserve, which is constituted during periods of energy excess and mobilized during periods of energy deprivation. This storage mainly occurs in adipose tissue within the adipocytes. Energy homeostasis is regulated by hypothalamus which regulates food intake and energy expenditure [11], and involves many hormones and adipokines to organize the crosstalk between organs. Lipid metabolism is a complex process that involves a large variety of molecular pathways and different transcriptional regulators some of which have been described so far.
Since the 2000s, with the advent of whole-genome sequencing technologies, most genes coding essentially for proteins have gradually been identified. The databases reference nearly 20,000 genes in human [12] [Human GENCODE v.28–10 July 2018], 22,000 in mouse [13] [Mouse GENCODE v.M17–10 July 2018] and pig [Ensembl v.92–10 July 2018], 18,000 in chicken [Ensembl v.92–10 July 2018]. Small RNAs, such as miRNA that do not code for proteins, are also relatively well annotated today (from 1705 to 5531). In contrast, long noncoding RNA (lncRNA) are less described in the genomes: they are strictly defined as RNAs of more than 200 nt with no ORF long enough to be translated into a protein (< 150 nt) [14]. They have important roles since they control the regulation of gene expression via a large diversity of mechanisms as they can interact with DNA, RNA or proteins [15, 16]. The number of lncRNAs with a well-described functional role is now estimated at 1% [17]. lncRNA genes appear to be as numerous as or even more numerous than genes encoding proteins with 15,779 and 12,533 lncRNA referenced via the GENCODE projects [12, 13, 14] in human [Human GENCODE v.28] and mouse [Mouse GENCODE v.M17], respectively. Modeling of these gene entities structure is far from complete. In human, specialized databases such as NONCODE [18] or LNCipedia [19] announce even higher numbers than those referenced in Ensembl and NCBI databases. On the contrary, in less studied livestock species such as pig and chicken [Ensembl v.92], a very small fraction of lncRNA is referenced (361 and 4643, respectively). So far, most lncRNA and their underlying transcripts, are gene models predicted by bioinformatics pipelines from RNAseq data and in the majority of species have rarely been experimentally confirmed. The difficulty of lncRNA gene modeling and identification is due to different causes: 1. an expression 10 to 100 times weaker than the protein coding genes [14, 20, 21], which makes harder the identification of the different transcripts exon-intron structures and therefore of the gene locus; 2. the tissue-specificity of lncRNA expression [14, 20], requiring the use of many different tissues to establish an exhaustive catalogue; 3. the criteria used for lncRNA prediction that can be the presence of an ORF, a blast against a protein database, the size of transcripts and/or the composition in k-mers, depending on the bioinformatics tool used; the main tools being CPC [22, 23], CPAT [24], PhyloCSF [25], FEELnc [26] and the Ulitsky’s team pipeline PLAR [27]. 4. Finally, a last point concerns the low conservation of lncRNA sequences between species, especially for species that are evolutionary distant [14, 20, 27, 28, 29, 30]. All these drawbacks make it difficult to find orthologous long noncoding genes by sequence conservation analysis, as frequently done for protein-coding genes.
The first review about lncRNAs involved in lipid metabolism is very recent [31] (2016). Since then several other reviews and articles were published but none of them provided an exhaustive lipid-related lncRNA catalogue. The first objective of this study was to fill this gap providing an exhaustive catalogue of lncRNAs involved in lipid metabolism. An extensive analysis of the literature, generally focusing on human or mouse, allowed us to draw up a catalogue of 60 lncRNA genes related to lipid metabolism for which we report mechanisms of action when it is described This led us to highlight some spurious genes and therefore, to rename some lncRNAs in accordance to the rules published by the HUGO Gene Nomenclature Committee for long noncoding genes [32]. Second, we analyzed the conservation of these 60 lncRNA in chicken, which last shared common ancestor with mammal dates back to 300 M years ago, with the assumption that such a conservation would support an important role of these genes in the metabolism of interest. For this, an approach by synteny analysis was used, which highlighted 5 lncRNAs preserved between human/mouse and chicken. Finally, we have more precisely described their functional roles and analyzed their conservation between 8 species from mammals to zebrafish.
Results
60 lncRNA identified as involved in lipid metabolism by expert curation of the literature
The 60 genes involved in lipid metabolism and their associated publication
Name in article | Database name (feature) | Normalized name | Sp. | Experiment | Tissue/Cell type | Action | Ref. |
---|---|---|---|---|---|---|---|
ANRIL | CDKN2B-AS1 (h: 28tr; 3837 bp; 19ex) | ANRIL | h | Co-effects (6 yr-adiposity) | Umbilical cord | ↗lnc & ↗fat mass | [40] |
APOA1-AS | APOA1-AS (h: 2tr; 956 bp; 3ex) | APOA1-AS | h | KD (lnc) | HepG2 | ↗APO gene cluster: APOA1, APOC3, APOA4 | [41] |
APOA4-AS | Gm10680 (m: 1tr; 702 bp; 2ex) | APOA4-ASa | m | KD (lnc) | Liver | ↘APOA4 & ↘TG, Chol. | [42] |
FLRL5 | m | Co-effects (NAFLD) | Liver | ↗lnc, FADS2, ↘FABP5, LPL, ACMSD, | [43] | ||
AT102202 | – | HMGCR | h | KD (lnc) | HepG2 | ↗HMGCR | [39] |
AT115872 | SOD2-OT1 (h: 1tr; 1718 bp; 2ex) | SOD2-OT1a | h | KD (lnc) | HepG2 | ↘HMGCR | [39] |
Blnc1 | – | Blnc1a | m | Ov. (lnc) | Primary hepatocytes | ↗SREBP1c, FASN, SCD, DGAT2, FABP4, ABCA1, ABCG5, LPCAT3 | [44] |
CASIMO1 | SMIM22b | SMIM22a | h | Ov. (lnc) | MCF-7 | ↗Lipid droplet formation | [45] |
CRNDE | CRNDE (h: 24tr; 6325 bp; 2ex) | CRNDE | h | KD (lnc) | HCT116, HT29 | ↘FASN, DGKA, CDS1, PLCB3, PLCG1, ↗ACADVL, ACOT9, PI4KB | [46] |
ORat7 | c | Co-effects (Se-deficient diet) | Vein | ↗lnc, ↘ACADS | [47] | ||
E330013P06 | Carmn (m: 2tr; 1778 bp; 3ex) | CARMN | m | Ov. (lnc) | RAW 264.7 | ↗lipid uptake | [48] |
FLRL3 | Gm11832 (m: 1tr; 432 bp; 3ex) | RAD54B-AS1a | m | Co-effects (NAFLD) | Liver | ↗lnc, FADS2, ↘FABP5, LPL, ACMSD, | [43] |
FLRL8 | 1700067K01Rikb | -a | m | Co-effects (NAFLD) | Liver | ↗lnc, FADS2, ↘FABP5, LPL, ACMSD, | [43] |
Gm16551 | Gm16551 (m: 5tr; 3162 bp; 3ex) | LINCxxxxa | m | KD (lnc) | Liver | ↗ACLY, FASN, SCD & ↗TG | [49] |
H19 | H19 (m: 7tr; 2286 bp; 5ex) | H19 | m | Co-effects (FA) | Liver | ↗lnc, PTBP1 | [50] |
HAGLR | HAGLR (h: 17tr; 4095; 3ex) | HAGLRa | h | KD (lnc) | NSCLC cells | ↘FASN & ↘FA | [51] |
HOTAIR | HOTAIR (h: 5tr; 2421 bp; 7ex) | HOTAIRa | h | KD (lnc) | CNE2, 5-8F | ↘FASN & ↘FA | [52] |
HOXC-AS1 | HOXC-AS1 (h: 2tr; 548 bp; 2ex) | HOXC-AS1a | h | Ov. (lnc) | THP-1 | ↗HOXC6 & ↘Chol. | [53] |
HULC | – | HULC | h | Co-effects (HCC) | HepG2 | ↗lnc, ACSL1, PPARA & ↗TG, Chol. | [54] |
LeXis | 4930412L05Rik (m: 2tr; 1241 bp; 8ex) | LeXis | m | KO, KD, Ov. (lnc) | Liver | ↘CYP51A1, FDPS, MVK, MVD, SQLE, IDI1, LSS, PMVK & ↘Chol. | [55] |
LINC01138 | LINC01138 (h: 14tr; 2212 bp; 4ex) | LINC01138a | h | KD, Ov. (lnc) | Renal cell carcinoma | ↗SREBP1 activity & ↗lipid desaturation | [56] |
linc-ADAL | LINCADL (h: 1tr; 521 bp; 2ex) | LINCADLa | h | KD (lnc) | ASC | ↘PPARG, CEBPA, SREBF1, FASN, ELOVL6, ATGL & ↘TG | [57] |
lincRNA-DYNLRB2–2 | LINC01228 (h:1tr; 623 bp; 2ex) | LINC01228 | h | Co-effects (Ox-LDL) | THP-1 | ↗lnc, GPR119, ABCA1 & ↘Chol., ↗Efflux | [58] |
LINK-A | LINC01139 (h: 7tr; 1579; 2ex) | LINK-Aa | h | Co-effects (lipid-binding) | TNBC | ↗lnc with highest lipid enrichment | [59] |
LISPR1 | – | S1PR1-DTa | h | KD (lnc) | HUVEC | ↗S1PR1 | [60] |
lnc_DHCR24 | DHCR24-DT (h: 4tr; 440 bp; 2ex)c | DHCR24-DTa | c | Co-effects (fat line) | Liver | ↗lnc, DHCR24 | [20] |
lnc18q22.2 | LIVAR (h: 1tr; 384 bp; 2ex) | LIVAR | h | Co-effects (NASH) | Liver | ↗lnc, anti-apoptotic genes | [61] |
lncACACA | – | LINCxxxxa | h | Co-effects (LXR agonist) | THP-1 | ↗lnc | [62] |
lncARSR | LNCARSR d (h: 10tr; 2932 bp;2ex) | lncARSRa | m | Ov. (lnc) | Liver | ↗SREBP1c, FASN, ACC1, SCD, ↘CPT1A | [63] |
m | Ov. (lnc) | Liver | ↗HMGCR, HMGCS, SQLE, ↘CYP7A1 & ↗Chol. | [64] | |||
lncFASN | LINC01970 (h: 1tr; 1810 bp; 2ex) | LINC01970a | h | Co-effects (LXR agonist) | THP-1 | ↗lnc | [62] |
lnc-HC | – | lnc-HC | r | KD, Ov. (lnc) | Liver, CBRH-7919 | ↘CYP7A1, ABCA1 & ↘TG, Chol. | [65] |
lncHR1 | AC023161.1 d (h: 1tr; 420 bp; 2ex) | lncHR1 | m | Ov. (lnc) | Liver | ↘SREBP1c, FASN, ACACA & ↘TG | [66] |
lnc-KDM5D-4 | – | LINCxxxxa | h | KD (lnc) | HepG2 | ↗LPIN2 & ↗Lipid droplet formation | [67] |
lnc-leptin | – | lnc-leptina | m | KD (lnc) | Primary adipocyte | ↘LEP | [68] |
lncLSTR | C730036E19Rik (m: 1tr; 1102 bp; 5ex) | lncLSTR | m | KD (lnc) | Liver | ↗APOC2, ↘CYP8B1 & ↘TG, Glucose | [69] |
lncLTR | NONGGAG001747.2 (c: 1tr; 776 bp; NA) | lncLTRa | c | GWAS (serum TG content) | – | SNP in lncLTR locus | [70] |
lncSHGL | B4GALT1-AS1 d (h: 3tr; 3752 bp; 4ex) | lncSHGLa | m | KD, Ov. (lnc) | Liver | ↗ACACB, ↘FASN, SREBP1 & ↘FA, lipolyse | [71] |
lncSREBF1 | SMCR2 (h:1tr; 564 bp; 4ex) | SMCR2a | h | Co-effects (LXR agonist) | THP-1 | ↗lnc | [62] |
LNMICC | AC009902.2 (h: 2tr; 620 bp; 2ex) | LNMICCa | h | KD, Ov. (lnc) | HeLa229 | ↗ACACA, FASN, FABP5, ↘ACOX1, CPT1A & ↗TG, PL | [72] |
LOC100506036 | CNNM3-DT (h: 1tr; 415 bp; 2ex) | CNNM3-DT | h | KD (lnc) | Jurkat cells | ↘SMPD1, NFAT1 | [73] |
LOC157273 | AC022784.6 (h: 1tr; 559 bp; 1ex) | LINCxxxxa | h | GWAS (lipid-traits) | – | ↗lnc / SNP in the lncRNA locus | [74] |
MALAT1 | MALAT1 (h: 17tr; 1519 bp; 2ex) | MALAT1 | h | KD (lnc) | HepG2 | ↗SREBP1c & ↗TG, Chol. | [75] |
MEG3 | MEG3 (h: 50tr; 4867 bp; 2ex) | MEG3 | h,m | Ov. (lnc) | Liver HEK-293 T | ↗CYP7A1, CYP8B1, FXR, SREBP1c, ↘SHP | [76] |
m | KD (lnc) | Liver | ↘TG | [77] | |||
m | Co-effects (NAFLD) | Liver | ↗lnc, NRF2, ↘miR-136 & ↘serum lipid | [78] | |||
MeXis | AI427809 (m: 4tr; 2033 bp; 2ex) | MeXis | m | KO, Ov. (lnc) | Liver, Macrophage | ↗ABCA1 & ↗Chol. efflux | [37] |
NEAT1 | NEAT1 (h: 9tr; 3341 bp; 2ex) | NEAT1 | h | KD (lnc) | THP-1 | ↘TNFa, ↗CD36, OLR1 & ↗lipid uptake | [79] |
h | KD (lnc) | HCC | ↘ATGL, PPARa, ↗miR-124-3p | [80] | |||
OLMALINC | OLMALINC (h: 36tr; 5893 bp; 5ex) | OLMALINCa | h | Co-effects (obesity) | Adipose | ↘lnc, ↗lipid metabolism genes | [81] |
h | KD (lnc) | HepG2 | ↗SREBP2-dependent gene, ↘SREBP1 pathway genes | [82] | |||
PLA2G1Bat1 | ENSGALG00000041755 (c: 3tr; 2101 bp; 3ex) | LINCxxxxa | c | Co-effects (Se-deficient diet) | Vein | ↘lnc, ↗PLA2G1B | [47] |
PVT1 | PVT1 (h:182tr; 1699 bp; 8ex) | PVT1a | h | KD (lnc) | U2OS MG-63 | ↗miR-195, ↘FASN | [83] |
RNCR3 | Mir124a-hg (m: 4tr; 4103 bp; 4ex) | RNCR3a | m | KD (lnc) | Plasma | ↗TG, Chol. | [84] |
RP1-13D10.2 | AL021407.3 (h: 1tr; 486 bp; 1ex) | LINCxxxxa | h | Ov. (lnc) | Huh7, HepG2 | ↗LDLR & ↗LDL, ↘ApoB | [85] |
RP5-833A20.1 | NFIA-AS1 (h: 7tr; 384 bp; 4ex) | NFIA-AS1 | h | KD, Ov. (lnc) | THP-1 | ↗miR-382, ↘NFIA & ↗Chol. | [86] |
SNHG14 | Snhg14 (m: 15tr; 6861 bp;1 2ex) | SNHG14 | m | KD, Ov. (lnc) | BV-2 | ↘PLA2G4A | [87] |
SNHG16 | SNHG16 (h: 13tr; 3607 bp; 3ex) | SNHG16a | h | KD (lnc) | HCT119 | ↘SCD, PCSK9, SQLE, ACLY, INPP5D, HSD17B7 | [88] |
SPRY4-IT1 | SPRY4-AS1 (h: 7tr; 1293 bp; 5ex) | SPRY4-IT1a | h | KD (lnc) | HEM-1 | ↘DGAT2, GPAT3 & ↘Acyl Carnitine, FA, TG | [89] |
SRA | Sra1b (m: 2tr; 1299 bp; 4ex) | SRA1 | m | KO (lnc) | Liver | ↗ATGL | [90] |
m | KO (lnc) | Liver | ↘PPARA, PPARG, FABP4, SCD & ↘TG, FA | [91] | |||
TRIBAL | AC091114.1 (h: 2tr; 1272 bp; 3ex) | TRIBAL | h | GWAS (TG) | – | SNP in TRIBAL locus | [92] |
uc.372 | – | RALGAPA1-AS1a | h,m | Ov. (lnc) | Liver, HepG2 | ↗ACACA, FASN, SCD, CD36 & ↗TG, Chol. | [93] |
XLOC_011279 | – | LINCxxxxa | p | Co-effects (fat line) | Adipose | ↗lnc, LPIN1 | [94] |
XLOC_013639 | – | LINCxxxxa | p | Co-effects (fat line) | Adipose | ↗lnc, SCD | [94] |
XLOC_014379 | – | NF1-IT1a | p | Co-effects (fat line) | Adipose | ↗lnc, SCD | [94] |
XLOC_019518 | – | RNF7-DTa | p | Co-effects (fat line) | Adipose | ↗lnc, SCD | [94] |
XLOC_064871 | – | LINCxxxxa | p | Co-effects (fat line) | Adipose | ↗lnc, TRIB3 | [94] |
Mechanisms of action of lncRNAs
Mechanisms of action reported for 25 lncRNAs
Name | Sp. | LncRNA action | Ref. |
---|---|---|---|
APOA1-AS | h | Histone mark modification via LSD1 et SUZ12 (PRC2) | [41] |
APOA4-AS | m | Complex lnc:HuR et APOA4 mRNA | [42] |
Blnc1a | m | Complex lnc:hnRNPU / Complex lnc:EDF1, lnc:LXRa | [95] |
CASIMO1a | h | Small protein CASIMO1 interacts with SQLE protein | [45] |
H19 | m | Complex lnc:PTBP1 which targets SREBP1c mRNA and protein stability and transcriptional activity | [50] |
LeXis | m | Complex lnc:RALY (hnRNP) which targets SREBP2, HMGCR, CYP51A1, FDPS promoters | [55] |
LINC01138 | h | Comple lnc:PRMT5 which targets SREBP1 in order to regulate its arginine methylation and to stabilize SREBP1 mRNA | [56] |
linc-ADALa | h | Complex lnc:IGF2BP2 and hnRNPU | [57] |
LINK-Aa | h | Complex lnc:PIP3 increases interaction with Akt | [59] |
lnc-HC | r | Complex lnc:hnRNPA2B1 which targets CYP7A1/ABCA1 mRNAs | [65] |
Lnc-leptina | m | Loop between LEP and its enhancer (near lnc:leptin locus) | [68] |
lncLGRa | m | Complex lnc:hnRNPL which targets GCK promoter | [96] |
lncLSTR | m | Complex lnc:TDP-43 which targets CYP8B1 promoter | [69] |
lncSHGLa | m | Complex lnc:hnRNPA1 which targets CALM mRNA to increase its translation | [71] |
LNMICCa | h | Complex lnc:NPM1 which targets FABP5 promoter | [72] |
MALAT1 | h | Complex lnc:SREBP1c which stabilizes nuclear SREBP1c protein | [75] |
MEG3 | h,m | Complex lnc:PTBP1 which targets SHP mRNA for its decay | [76] |
MeXis | m | Complex lnc:DDX17 which targets ABCA1 promoter | [37] |
NEAT1 | h | Complex lnc:NONO:CD36 mRNA | [79] |
h | ceRNA (miR-124-3p which targets ATGL) | [80] | |
PVT1a | h | ceRNA (miR-195 which targets FASN) | [83] |
RALGAPA1-AS1a | h,m | Stop maturation of pri-miRNA (pri-miR-195/pri-miR-4668) | [93] |
S1PR1-DTa | h | Complex lnc:ZNF354C which inhibits its repressive activity | [60] |
SNHG14 | m | ceRNA (miR-145-5p which targets PLA2G4A) | [87] |
SNHG16a | h | ceRNA (multiple miRNA which target SCD) & Complex lnc:HuR | [88] |
SPRY4-IT1a | h | Complex lnc:Lipin2 | [89] |
The different mechanisms of action of lncRNAs. a Mechanisms with effect at transcriptional level, b at post-transcriptional level and (c) on proteins. d LncRNAs with a role as small noncoding RNA host. e LncRNAs with translational activity through a small ORF. In red, lncRNA; in green, mRNA; in blue, miRNA; the green, yellow and blue oval spheres are proteins. The genes in bold are those mentioned in this review, the others are examples from research fields other than lipid metabolism: SAF66 and NRON [97]
Other studies have shown an action of lncRNAs on the transcription. For example, APOA1-AS seems to inhibit the transcription of the APO gene cluster (APOA1, APOC3, APOA4, APOA5) that codes for protein components of lipoproteins, by DNA compaction through epigenetics mark modulation [41] (Fig. 1a, left part). This mechanism seems to require the recruitment of the LSD1 protein known to induce gene silencing through the removal of active methyl marks, and of the SUZ12 protein, a key component of the polycomb recessive complex (PRC2) known to mediate chromatin silencing through H3K27 trimethylation [41]. Indeed, the APOA1-AS depletion in HepG2 cells increased the active histone H3K4me3 marks at the APOA1 promoter in parallel to a significant decrease of LSD1 occupancy. APOA1-AS depletion also decreased the repressive histone H3K27me3 marks at the APOA1 promoter that coincided with a marked reduction of SUZ12 occupancy in this region [41]. A second example of lncRNA action on DNA compaction is Lnc-leptin [68] (Fig. 1a, middle part). By using chromatin conformation capture experiments, a direct interaction was detected between lnc-leptin and the LEP (leptin) gene, which codes for a major adipokine secreted by white adipocytes and functioning as an energy sensor to regulate energy homeostasis. This “lnc-leptin – leptin promoter” interaction occurred at the enhancer region of LEP and it was diminished upon lnc-leptin knockdown in mature adipocytes.
At the post-transcriptional level, some lncRNAs seem to play a role in the maturation of RNAs such as lncRNA uc.372 (Fig. 1b, left part) which prevents the maturation of a pri-miRNA by camouflaging the area targeted by the Drosha protein [93]. On mature RNAs, the so called “competing endogenous RNA (ceRNA)” role of lncRNAs resembles that of a sponge for small RNAs regulating the mRNA target of small RNAs (Fig. 1b, middle part). Among the lncRNAs involved in lipid metabolism, NEAT1 [80], SNHG16 [88] and PVT1 [83] are endogenous competitors of ATGL, SCD and FASN transcripts, respectively. Sometimes, lncRNA-protein complexes target a mRNA and thus regulate its stability (lnc-HC [65], H19 [50], MEG3 [76], NEAT1 [79], APOA4-AS [42]) or its translation (lncSHGL [71]) (Fig. 1b, right part). LncRNAs can bind via their three-dimensional conformation, involving one or more proteins in the structure (Fig. 1c). They can bind via their sequence RNA of hnRNP such as SPRY4-IT1 [89] (Fig. 1c, left part). They can also form protein scaffolds such as Blnc1 which associates with EDF1, LXRα and hnRNPU [95] or linc-ADAL which associates with IGF2BP2 and hnRNPU [57] (Fig. 1c, left part). These protein scaffolds do not yet have a well-defined mechanism of action. Some publications have gone further by highlighting the interest of this complex. For example, lncRNA protein complexes can modulate the half-life of the proteins involved in the complex, such as MALAT1 which binds to SREBP1c in order to stabilize it [75] (Fig. 1c, middle part), or they can modulate its function, such as LINK-A which binds to PIP3 and intensifies its interaction with Akt [59] (Fig. 1c, right part) or modify its cell location as illustrated by NRON [97]. Another role of lncRNA [99] is that of hosting small RNAs (Fig. 1d). SNHG16 [88] illustrates very well this role because it hosts 3 small nucleolar RNAs (snoRNA) SNORD1A, SNORD1B and SNORD1C which are positioned within the introns in the sense direction of the lncRNA, thus benefiting from the co-transcription with the host lncRNA. Finally, lncRNAs can also host small ORFs (Fig. 1e) allowing the translation of small peptides. CASIMO1 is a perfect example, lncRNA CASIMO1 hosts the sequence of a small transmembrane peptide that interacts directly with the SQLE protein and modulates the formation of lipid droplets [45].
New names proposed for misnamed lncRNAs
HGNC decision tree for naming lncRNAs according to the Wright’s schema [32], here updated by including divergent lncRNA and lncRNA hosting small noncodingRNA
We propose to rename some lncRNAs according to the HGNC rules whatever the species (Table 1, column 3). Seven lncRNA have been renamed according to the nearby protein-coding gene: lnc_DHCR24 [20] in DHCR24-DT, AT115872 [39] in SOD2-OT1, XLOC_014379 [94] in NF1-IT1, FLRL3 [43] in RAD54B-AS1, XLOC_019518 [94] in RNF7-DT. We have also renamed two other genes: LISPR1 (long intergenic noncoding RNA antisense to S1PR1) [60] in S1PR1-DT, and uc.372 (ultra-conserved 372) [93] which has a generic name and should be rather called RALGAPA1-AS1. We have restored the official and standardized names, LINC01970 and SMCR2 (Smith-Magenis syndrome Chromosome Region, candidate 2), for the two lncFASN and lncSREBF1 genes [62] respectively. All other XLOC_013639, XLOC_011279, XLOC_064871 [94], lncACACA [62], LOC157273 [74], Gm16551 [49], PLA2G1Bat1 [47] and lnc-KDM5D-4 [67] genes should have a standard name of the type LINC#####. Finally, the lncRNA AT102202 has several common splice junctions with the HMGCR protein-coding gene and should therefore be considered as a HMGCR isoform rather than a lncRNA new gene. Note that the knockdown of this isoform in HepG2 cells was described by Liu et al. to increase the expression level of the gene encoding HMGCR due to the presence of several HMGCR isoforms with different expression patterns [39]; although the authors missed to specify which isoform was targeted by siRNAs and which one was up-regulated (see Additional file 1). According to this figure, the knockdown of the AT102202 isoform should lead to an absence of HMGCR functional protein.
In some cases, a gene is named with several aliases between species. This is the case for lncSHGL in mouse known as B4GALT1-AS1 in human which were both mentioned in Wang et al. [71]. Naming problems also exist within the same species. For example, the NCBI mouse gene named Gm30838 by the MGI (Mouse Genome Informatics), is double named in Lo et al. lnc-ORIA9 and lnc-leptin [68]. Similarly, the human ENSG00000266304 lincRNA gene, firstly known as RP11-484 N16.1, was named lnc18q22.2 by Atanasovska et al. [61] and finally officially renamed LIVAR. Due to their recent studies, we found some genes in databases with an “ID” name instead of its common names used in the literature (e.g. AC023161.1 instead of lncHR1 [66]). Other problems are due to some articles that use lncRNA gene names without referring to any database: the most classical examples are XLOC/TCONS names reflecting experiment-dependent naming from Cufflinks (e.g. pig new genes in Huang et al. [94]) but other names exist such as AT102202 [39] which does not refer to any easily detectable source because it is a contraction of the NONCODE ID NONHSAT102202.
Detailed examination of model architecture
Verification of the ALDBGALG00000000505049 and FLRL7 gene models with their neighboring SCD and FADS2 genes in chicken and mouse. a, d Model of protein-coding genes are from Ensembl v.92 and models of lncRNA are from the article of Fan et al. [101] that used ALDB v1.0, a lncRNA database (a for ALDBGALG00000000505049) and from the article of Chen et al. [43] that used their own models (d for FLRL7). Primers (black arrows) were design in order to amplify a fragment (red line) specific of lncRNA gene (I), of coding-protein gene (IV), of intergenic region (III) and of a fragment linking both genes (II). The expected sizes have been specified (black for RNA; red for DNA) according to the models. b, e Electrophoretic gels with the lengths of the amplicons, showing the existence of a unique gene, the lncRNA being an extension of the protein-coding gene. c, f New experimentally corrected models for the protein-coding gene
Conservation between phylogenetically distant species
Gene conservation during evolution, especially between phylogenetically distant species suggests an important functional role for these genes. Conservation of function of lncRNA across species was tested in some studies, showing a function retained despite a minor sequences conservation [29]. However the task remains difficult because of the poor conservation of lncRNA sequences between phylogenetically distant species as opposed to protein-coding genes, suggesting a more rapid evolution of lncRNA during evolution [14, 20, 27]. Therefore, we propose here to carry out orthologous lncRNA searches between phylogenetically distant species (chicken and mammals) using an approach based on the genome synteny as already presented in Muret et al. [20] and Foissac et al. [28] (see Materials & Methods). Even if this manual approach is time-consuming, we investigated the whole 60 long noncoding genes involved in lipid metabolism.
The 10 lncRNAs potentially conserved between human/mouse and chicken genomes
LncRNA | Hsa.ID | Hsa.position | Mmu.ID | Mmu.position | Gga.ID | Gga.position |
---|---|---|---|---|---|---|
CRNDE | ENSG00000245694 | 16:54845189–54,929,189(−) | ENSMUSG00000031736 | 8:92326033–92,356,120(−) | XLOC_003575 [47] | 11:4285705–4,316,300(+) |
DHCR24-DT | ENSG00000233203 | 1:54887563–54,888,850(+) | – | – | ENSGALG00000035342 | 8:25343117–25,344,661(+) |
PVT1 | ENSG00000249859 | 8:127794533–128,101,253(+) | ENSMUSG00000097039 | 15:62037986–62,378,096(+) | ENSGALG00000033453 | 2:139905946–139,947,148(+) |
NFIA-AS1 | ENSG00000237853 | 1:61248945–61,253,510(−) | RefSeq:102637398 | 4:98018556–98,024,773(−) | NONGGAG010741 | 8:27269736–27,278,903(−) |
SRA1 | ENSG00000213523 | 5:140537340–140,558,252(−) | ENSMUSG00000006050 | 18:36666681–36,679,366(−) | ENSGALG00000040453 | 13:1649170–1,650,955(−) |
DYNLRB2–2 | ENSG00000261082 | 16:79798050–79,827,150(−) | ENSMUSG00000110620 | 8:115971635–115,972,071(−) | Mult. ALDB Models | ~ 11:14928493–15,189,801(−) |
lncACACA | Unknown | 17:36810109–36,810,324(−) | – | – | Mult Ens. Models | ~ 19:8345185–8,375,056(−) |
MeXis | TCONS_00016111 [55] | ~ 9:105092000–105,108,500(+) | ENSMUSG00000086712 | 4:53261356–53,270,232(−) | Mult. ALDB Models | ~Z:54833466–54,863,390(−) |
PLA2G1Bat1 | – | – | ENSMUSG00000087292 | 5:115359078–115,422,863(+) | ENSGALG00000041755 | 15:9358431–9,366,570(+) |
TRIBAL | ENSG00000253111 | 8:125466939–125,541,373(+) | – | – | Mult. ManyDB Models | ~ 2:138972973–138,996,132(+) |
CRNDE (ColoRectal Neoplasia Differentially Expressed) is a lncRNA divergent with respect to the IRX5 gene, at 2 kb and 1.2 kb in human and chicken, respectively. In chicken, it has been described as ORat7 [47] (ALDBGALT0000001763). Composed of 6 to 9 exons in chicken and 6 exons in human, CRNDE is mainly noncoding but some isoforms are known in human to code for small proteins [102]. In human, CRNDE knockdown by siRNA in colorectal cancer cell lines leads to an under-expression of FASN, and an overexpression of ACADVL and ACOT9, two genes involved in lipid catabolism [46].
Lnc_DHCR24, renamed in DHCR24-DT (Table 1), is a lncRNA divergent with respect to the DHCR24 gene coding for a key enzyme of the cholesterol synthesis. We have modelled this transcript for the first time in 2017 in chicken and located a possible orthologue in human [20]. The intergenic region is very small, i.e., 200 bp in human and 300 bp in chicken [20]. In a previous study, we have suggested that these two genes are likely to be co-regulated by a bi-directional promoter, because of their high hepatic co-expression in several chicken lines (layers and broilers) analysed at different ages (young and, adult stage) [20].
NFIA-AS1 is an intronic antisense lncRNA of the NFIA gene (Nuclear Factor I A). Composed of 4 to 7 exons, it is found on the second intron of NFIA gene in human as well as in chicken. It negatively regulates in THP-1 cells the expression of the NFIA gene by a negative feedback mechanism with the transcription factor NF1A binding the promoter of NFIA-AS1 to activate it [86]. LncRNA NFIA-AS1 (also called RP5-833A20.1) is induced by a high level of oxidized and acetylated LDL [86]. These two genes (NFIA-AS1 and NFIA) appear to regulate the homeostasis of cholesterol (LDL, HDL, VLDL) and inflammatory cytokines (IL-1β/6, TNF-α and CRP) in Apo−/− mice [86].
PVT1 (Plasmacytoma Variant Translocation 1) is a same strand lncRNA with respect to the MYC nearest protein-coding gene. Modelled in the NCBI databases of human, mouse and rat, the two genes are separated by 50-60 kb in these three species. In the chicken, we also found it at the same distance (56 kb) of the MYC gene. PVT1 in human is a competitive endogenous lncRNA by acting as a sponge of MIR-195 in osteosarcoma cells [83]. It upregulates BCL1 and BCL2, two genes playing roles in the control of cell cycle and apoptosis, but also FASN, one of the key lipogenic enzymes.
SRA1, better known by its first name SRA (Steroid Receptor Activator), is one of the first lncRNA described in human (1999) [103]. Its functional RNA acts as a steroid receptor coactivator. It can coactivate androgen receptor (AR), estrogen receptors (ERα, ERβ), progesterone receptor (PR), glucocorticoid receptor (GR), thyroid hormone receptor (TR) and retinoic acid receptor (RAR) [104]. As early as 2003, it was demonstrated that its codes for a functional SRAP protein improving the trans-activation of PPARG and genes coding for AR and GR [105]. In Human, as in mouse or other species, this double “protein coding-lncRNA” classification exists [106]. In this review, we are only interested in its noncoding isoform. SRA1 is an antisense exonic lncRNA of the gene coding for ANKHD1 in human. Currently, we do not know if SRA1 has noncoding isoforms in chicken but a coding isoform is present in Ensembl database (ENSGALG00000040453). Using a mouse SRA1 KO, the noncoding SRA1 isoform seems to regulate in the liver the expression of genes involved in lipid metabolism as PPARA, PPARG, FABP4 and SCD by a mechanism still unknown [91]. In 2016, the same team showed that in liver, the noncoding SRA1 isoform positively regulates the expression of PNPLA2. PNPLA2 codes for an enzyme that plays a role in lipid hydrolysis that if under expressed leads to the progressive fatty liver steatosis [90].
Genomic conservation in 8 species of the five lncRNA previously found as conserved between human and chicken. a Tree of genome evolution in vertebrates based on Kumar and Hedges studies [107, 108]. b Conservation of the five lncRNA (yellow) through the animal kingdom in relation to their genomic environment: protein-coding gene (blue). The distances between the intergenic entities are in bases
Expression of lncRNA in embryo, liver, adipose tissue and hypothalamus in human and chicken. a Expression of the 5 lncRNA conserved between human and chicken. b Expression of all lncRNAs (pale colors) in the different tissues against all the 5 lncRNA studied here. Embryo (E), liver (L), adipose tissue (A), hypothalamus (H). Top: expression in human with n = 3 (embryo not represented), bottom: expression in chicken with n = 16. **: p value< 5% ***: p value< 1%
Discussion
To our knowledge, previous reviews taken together described 27 lncRNAs involved in lipid metabolism. An extensive research has allowed us to report 33 additional lncRNAs, the majority of which identified in human or mouse, resulting in a total of 60 long noncoding genes having a role in lipid metabolism. Such a research has to be meticulous because of the multiple aliases intra and between species and is tedious and time-consuming.
In addition to gathering these 60 genes as related to the lipid metabolism, we demonstrated experimentally that two lncRNA close and on same strand with the SCD and FADS2 protein-coding genes and called by the authors as ALDBGALG00000000505049 and FLRL7 related to the lipid metabolism, were spurious. We also made a lncRNA nomenclature revision and propose to rename some genes according to the official rules of the HUGO gene nomenclature committee [32].
We then performed a comparative analysis to identify orthologous genes between phylogenetically distant species. Such a approach allows to make use of the knowledge obtained in one species to infer the presence on lncRNAs in other species not examined so far. In particular, it facilitates the understanding of the biological role by working on species in which gene manipulations are easier. Unfortunately, this research is difficult for lncRNAs because these genes are very poorly conserved in sequence between relatively distant species; such research required synteny approaches to study the conservation of the local genomic structure around the gene of interest. We identified, out of the 60 lncRNAs, 5 lncRNAs conserved within amniotes (320Myr), including two conserved within vertebrates (440Myr). Such results are consistent with other studies; some articles reported less than 20% of lncRNAs conserved across mammals [114, 115]. Interestingly, we showed that lncRNAs described so far are more expressed compared to the whole lncRNAs present in the gene databases; the reason is likely technical since it is easier to work on lncRNAs that are more expressed.
Conclusions
Such a catalogue of 60 genes is interesting, first, by providing new regulators of a complex lipid metabolism known to be highly regulated at the mRNA levels [42, 76]. Second, because the lipid metabolism is particularly important in human health through the numerous diseases related to this metabolism (obesity, cardiovascular diseases, hepatic steatosis ...). Third, because this metabolism is also important in livestock species where it is linked to economically important traits, such as intramuscular fat content, meat quality traits [116, 117, 118] and ectopic fat deposition and economic carcass values. It should be noted that more than 2/3 of the 60 lncRNAs reported in this review were discovered in the last 2 years and we have no doubt that this first set will be rapidly enriched in the coming years.
Methods
Literature review
The state of the art regarding lncRNA potentially involved in lipid metabolism was obtained by expert curation of the literature database Pubmed. In this way, lipid metabolism was defined as the including synthesis, degradation and transport of different types of lipids, with a particular interest for fatty acids and cholesterol. The keyword literature search was therefore conducted by combining the terms “lncRNA” and one of the following terms associated to apolipoprotein or to the 8 lipid classes: sterol (cholesterol), prenol, fatty acid, acylglycerol (triglyceride), phosphoglyceride, glycolipids, polyketides and sphingolipids.
Syntenic conservation between the chicken and the species where the lncRNA was discovered
The syntenic conservation analysis was performed for all 60 lncRNA genes identified in the first step, using the following annotation reference databases: Ensembl v.92, NCBI release 109, NONCODEv5 [18], ALDB v1.0 [119], completed by the new lncRNA models that we have previously published for chicken [20, 28]. Long noncoding gene conservation by synteny analysis between human/mouse and chicken was performed according to three criteria used in the following order of priority: 1. the lncRNA in human/mouse genome is surrounded by two neighboring protein-coding genes for which a 1-to-1 orthologous gene is available in the chicken genome. We considered the lncRNA as syntenically conserved if this lncRNA was also found in chicken between these two orthologous protein-coding genes, in the same orientation and order and same relative position and/or intron-exon structure. 2. The lncRNA in human/mouse genome is a close divergent lncRNA (< 1 kb) or antisense from a protein-coding gene with a 1-to-1 orthologous gene in the chicken genome; 3. the lncRNA in human/mouse genome is hosting small noncoding genes. Such a lncRNA was syntenically conserved if a lncRNA in chicken is hosting small noncoding genes with the same numbered-names.
Syntenic conservation between eight species
The syntenic conservation analysis was further performed across eight species (human, mouse, goat, cattle, pig, chicken, xenope and zebrafish) for the subset of 5 lncRNA genes, which were found conserved between the chicken and the human/mouse. We used the same three criteria aforementioned, taking the lncRNA reference databases in the following order: Ensembl v.92, NCBI annotation release 109, and the new lncRNA catalogue that we have previously published for livestock species (goat, cattle, pig) [28]. The phylogenetic tree was performed with the phyloT v2018.3 tool (https://phylot.biobyte.de/), which generates phylogenetic trees based on NCBI species names and taxonomy. The tree visualization was carried out with the iTOL v4.2.3 tool [120].
Tissue expression analysis in chicken and human
The human expression raw data from liver, white adipose tissue and brain were obtained from RNAseq data (2 × 100 bp) from three subjects (approximatively 18 M read-pairs per sample) chosen from the NCBI BioProject accession number PRJEB4337 [110]. The aim of Fagerberg et al. was to study tissue-specific expression of genes from 27 healthy human tissues. The chicken liver and abdominal adipose tissue expression data were obtained from RNAseq data (2 × 100 bp) from 16 animals (about 55 M read-pairs per sample for liver and 70 M for adipose tissue) extracted from our PRJNA330615 project [20]. The aim of Muret et al. was to model new lncRNA in chicken in these two tissues. For the hypothalamus and the embryo in chicken, the raw data used correspond to RNAseq data (2 × 150 bp) from 16 individuals (approximately 50 M read-pairs per sample - PRJEB28745). For these 2 species and all the tissues mentioned, normalized RPKM data were used.
RT-PCR for remodeling gene structure
Total RNAs was extracted from the liver of 48 chickens (from 9-weeks broilers) and mice (C57BL/6) as described by Desert et al. [4] and reverse-transcribed using High-Capacity cDNA Reverse Transcription kit (Applied Biosystems, Foster City, CA) following manufacturer’s instructions. cDNAs was treated with DNAseI (kit Ambion – RNAse-free) and diluted 1:10 for specific PCR amplification using the primers defined in Additional file 2. The amplification specificity was confirmed by sequencing. The amplification fragment lengths were verified on 2% agarose gel using the marker SmartLadder (Eurogentec MW1700_10).
Notes
Acknowledgements
We thank Christine Kervarrec from the UMR 1085 IRSET-INSERM (Rennes, France) for murine genomic DNA.
Authors’ contributions
KM and SL carried out the state of the art about lncRNAs involved in lipid metabolism. KM performed lncRNAs conservation across species and expression analyses. LL, MB and CD carried out RNA extraction and lncRNA model validations. SL conceived the project. KM, SL, FG and TZ contributed to the writing of this article. All authors read and approved the final manuscript.
Funding
KM is a Ph.D. fellow supported by the Brittany region (France) and the INRA’s Animal Genetics division. The animal experimental designs and RNA-Seq data were funded by the French National Agency of Research (FatInteger Project, ANR-11-SVS7 and ChickStress Project, ANR-13-ADAP).
Ethics approval and consent to participate
All experiments were conducted following the French National Guidelines for the care and use of animals in research edited by the French Ministries of Higher Education and Scientific Research, and of Agriculture and Fisheries (http://ethique.ipbs.fr/charteexpeanimale.pdf). The protocol was also approved by the local Ethics Committee of Val de Loire, France (authorization to experiment on living animals n°7740, 30/03/2012). The human tissue samples from which RNAseq data were collected and used in this study were approved by the Uppsala Ethical Review Board (Reference #2011/473) according to Fagerberg et al. [110].
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Supplementary material
References
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