We describe an update of MirGeneDB, the manually curated microRNA gene database. Adhering to uniform and consistent criteria for microRNA annotation and nomenclature, we substantially expanded MirGeneDB with 30 additional species representing previously missing metazoan phyla such as sponges, jellyfish, rotifers and flatworms. MirGeneDB 2.1 now consists of 75 species spanning over ∼800 million years of animal evolution, and contains a total number of 16 670 microRNAs from 1549 families. Over 6000 microRNAs were added in this update using ∼550 datasets with ∼7.5 billion sequencing reads. By adding new phylogenetically important species, especially those relevant for the study of whole genome duplication events, and through updating evolutionary nodes of origin for many families and genes, we were able to substantially refine our nomenclature system. All changes are traceable in the specifically developed MirGeneDB version tracker. The performance of read-pages is improved and microRNA expression matrices for all tissues and species are now also downloadable. Altogether, this update represents a significant step toward a complete sampling of all major metazoan phyla, and a widely needed foundation for comparative microRNA genomics and transcriptomics studies. MirGeneDB 2.1 is part of RNAcentral and Elixir Norway, publicly and freely available at http://www.mirgenedb.org/.

BackgroundThe genetic basis of muscle fat deposition in pigs is not well known. So far, we have only identified a limited number of genes involved in the absorption, transport, storage and catabolism of lipids. Such information is crucial to interpret, from a biological perspective, the results of genome-wide association analyses for intramuscular fat content and composition traits. Herewith, we have investigated how the ingestion of food changes gene expression in the gluteus medius muscle of Duroc pigs.ResultsBy comparing the muscle mRNA expression of fasted pigs (T0) with that of pigs sampled 5 h (T1) and 7 h (T2) after food intake, we have detected differential expression (DE) for 148 (T0-T1), 520 (T0-T2) and 135 (T1-T2) genes (q-value <0.05 and a |FC| > of 1.5). Many of these DE genes were transcription factors, suggesting that we have detected the coordinated response of the skeletal muscle to nutrient supply. We also found DE genes with a dual role in oxidative stress and angiogenesis (THBS1, THBS2 and TXNIP), two biological processes that are probably activated in the post-prandial state. Finally, we have identified several loci playing a key role in the modulation of circadian rhythms (ARNTL, PER1, PER2, BHLHE40, NR1D1, SIK1, CIART and CRY2), a result that indicates that the porcine muscle circadian clock is modulated by nutrition.ConclusionWe have shown that hundreds of genes change their expression in the porcine skeletal muscle in response to nutrient intake. Many of these loci do not have a known metabolic role, a result that suggests that our knowledge about the genetic basis of muscle energy homeostasis is still incomplete.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-017-3986-x) contains supplementary material, which is available to authorized users.

Background Feed efficiency (FE) has a major impact on the economic sustainability of pig production. We used a systems-based approach that integrates single nucleotide polymorphism (SNP) co-association and gene-expression data to identify candidate genes, biological pathways, and potential predictors of FE in a Duroc pig population. Results We applied an association weight matrix (AWM) approach to analyse the results from genome-wide association studies (GWAS) for nine FE associated and production traits using 31K SNPs by defining residual feed intake (RFI) as the target phenotype. The resulting co-association network was formed by 829 SNPs. Additive effects of this SNP panel explained 61% of the phenotypic variance of RFI, and the resulting phenotype prediction accuracy estimated by cross-validation was 0.65 (vs. 0.20 using pedigree-based best linear unbiased prediction and 0.12 using the 31K SNPs). Sixty-eight transcription factor (TF) genes were identified in the co-association network; based on the lossless approach, the putative main regulators were COPS5 , GTF2H5 , RUNX1 , HDAC4 , ESR1 , USP16 , SMARCA2 and GTF2F2 . Furthermore, gene expression data of the gluteus medius muscle was explored through differential expression and multivariate analyses. A list of candidate genes showing functional and/or structural associations with FE was elaborated based on results from both AWM and gene expression analyses, and included the aforementioned TF genes and other ones that have key roles in metabolism, e.g. ESRRG , RXRG , PPARGC1A , TCF7L2 , LHX4 , MAML2 , NFATC3 , NFKBIZ , TCEA1 , CDCA7L , LZTFL1 or CBFB . The most enriched biological pathways in this list were associated with behaviour, immunity, nervous system, and neurotransmitters, including melatonin, glutamate receptor, and gustation pathways. Finally, an expression GWAS allowed identifying 269 SNPs associated with the candidate genes’ expression (eSNPs). Addition of these eSNPs to the AWM panel of 829 SNPs did not improve the accuracy of genomic predictions. Conclusions Candidate genes that have a direct or indirect effect on FE-related traits belong to various biological processes that are mainly related to immunity, behaviour, energy metabolism, and the nervous system. The pituitary gland, hypothalamus and thyroid axis, and estrogen signalling play fundamental roles in the regulation of FE in pigs. The 829 selected SNPs exp...

Background: In this study, we aimed to investigate the molecular basis of lactation as well as to identify the genetic factors that influence milk yield and composition in goats. To achieve these two goals, we have analyzed how the mRNA profile of the mammary gland changes in seven Murciano-Granadina goats at each of three different time points, i.e. 78 d (T1, early lactation), 216 d (T2, late lactation) and 285 d (T3, dry period) after parturition. Moreover, we have performed a genome-wide association study (GWAS) for seven dairy traits recorded in the 1st lactation of 822 Murciano-Granadina goats. Results: The expression profiles of the mammary gland in the early (T1) and late (T2) lactation were quite similar (42 differentially expressed genes), while strong transcriptomic differences (more than one thousand differentially expressed genes) were observed between the lactating (T1/T2) and non-lactating (T3) mammary glands. A large number of differentially expressed genes were involved in pathways related with the biosynthesis of amino acids, cholesterol, triglycerides and steroids as well as with glycerophospholipid metabolism, adipocytokine signaling, lipid binding, regulation of ion transmembrane transport, calcium ion binding, metalloendopeptidase activity and complement and coagulation cascades. With regard to the second goal of the study, the performance of the GWAS allowed us to detect 24 quantitative trait loci (QTLs), including three genome-wide significant associations: QTL1 (chromosome 2, 130.72-131.01 Mb) for lactose percentage, QTL6 (chromosome 6, 78.90-93.48 Mb) for protein percentage and QTL17 (chromosome 17, 11.20 Mb) for both protein and dry matter percentages. Interestingly, QTL6 shows positional coincidence with the casein genes, which encode 80% of milk proteins. Conclusions: The abrogation of lactation involves dramatic changes in the expression of genes participating in a broad array of physiological processes such as protein, lipid and carbohydrate metabolism, calcium homeostasis, cell death and tissue remodeling, as well as immunity. We also conclude that genetic variation at the casein genes has a major impact on the milk protein content of Murciano-Granadina goats.

Background: The role of non-coding RNAs in the porcine muscle metabolism is poorly understood, with few studies investigating their expression patterns in response to nutrient supply. Therefore, we aimed to investigate the changes in microRNAs (miRNAs), long intergenic non-coding RNAs (lincRNAs) and mRNAs muscle expression before and after food intake. Results: We measured the miRNA, lincRNA and mRNA expression levels in the gluteus medius muscle of 12 gilts in a fasting condition (AL-T0) and 24 gilts fed ad libitum during either 5 h. (AL-T1, N = 12) or 7 h. (AL-T2, N = 12) prior to slaughter. The small RNA fraction was extracted from muscle samples retrieved from the 36 gilts and sequenced, whereas lincRNA and mRNA expression data were already available. In terms of mean and variance, the expression profiles of miRNAs and lincRNAs in the porcine muscle were quite different than those of mRNAs. Food intake induced the differential expression of 149 (AL-T0/AL-T1) and 435 (AL-T0/AL-T2) mRNAs, 6 (AL-T0/AL-T1) and 28 (AL-T0/AL-T2) miRNAs and none lincRNAs, while the number of differentially dispersed genes was much lower. Among the set of differentially expressed miRNAs, we identified ssc-miR-148a-3p, ssc-miR-22-3p and ssc-miR-1, which play key roles in the regulation of glucose and lipid metabolism. Besides, co-expression network analyses revealed several miRNAs that putatively interact with mRNAs playing key metabolic roles and that also showed differential expression before and after feeding. One case example was represented by seven miRNAs (ssc-miR-148a-3p, ssc-miR-151-3p, ssc-miR-30a-3p, ssc-miR-30e-3p, ssc-miR-421-5p, ssc-miR-493-5p and ssc-miR-503) which putatively interact with the PDK4 mRNA, one of the master regulators of glucose utilization and fatty acid oxidation. Conclusions: As a whole, our results evidence that microRNAs are likely to play an important role in the porcine skeletal muscle metabolic adaptation to nutrient availability.

Background Intramuscular fat (IMF) content and composition have a strong impact on the nutritional and organoleptic properties of porcine meat. The goal of the current work was to compare the patterns of gene expression and the genetic determinism of IMF traits in the porcine gluteus medius (GM) and longissimus dorsi (LD) muscles. Results A comparative analysis of the mRNA expression profiles of the pig GM and LD muscles in 16 Duroc pigs with available microarray mRNA expression measurements revealed the existence of 106 differentially expressed probes (fold-change > 1.5 and q-value < 0.05). Amongst the genes displaying the most significant differential expression, several loci belonging to the Hox transcription factor family were either upregulated ( HOXA9 , HOXA10 , HOXB6 , HOXB7 and TBX1 ) or downregulated ( ARX ) in the GM muscle. Differences in the expression of genes with key roles in carbohydrate and lipid metabolism (e.g. FABP3 , ORMDL1 and SLC37A1 ) were also detected. By performing a GWAS for IMF content and composition traits recorded in the LD and GM muscles of 350 Duroc pigs, we identified the existence of one region on SSC14 (110–114 Mb) displaying significant associations with C18:0, C18:1(n-7), saturated and unsaturated fatty acid contents in both GM and LD muscles. Moreover, we detected several genome-wide significant associations that were not consistently found in both muscles. Further studies should be performed to confirm whether these associations are muscle-specific. Finally, the performance of an eQTL scan for 74 genes, located within GM QTL regions and with available microarray measurements of gene expression, made possible to identify 14 cis -eQTL regulating the expression of 14 loci, and six of them were confirmed by RNA-Seq. Conclusions We have detected significant differences in the mRNA expression patterns of the porcine LD and GM muscles, evidencing that the transcriptomic profile of the skeletal muscle tissue is affected by anatomical, metabolic and functional factors. A highly significant association with IMF composition on SSC14 was replicated in both muscles, highlighting the existence of a common genetic determinism, but we also observed the existence of a few associations whose magnitude and significance varied between LD and GM muscles. Electronic supplementary material The online version of this article (10.1186/s12864-019-5557-9) contains supplementary material, which is available to authorized users.

Background Analyses of gut microbiome composition in livestock species have shown its potential to contribute to the regulation of complex phenotypes. However, little is known about the host genetic control over the gut microbial communities. In pigs, previous studies are based on classical “single-gene-single-trait” approaches and have evaluated the role of host genome controlling gut prokaryote and eukaryote communities separately. Results In order to determine the ability of the host genome to control the diversity and composition of microbial communities in healthy pigs, we undertook genome-wide association studies (GWAS) for 39 microbial phenotypes that included 2 diversity indexes, and the relative abundance of 31 bacterial and six commensal protist genera in 390 pigs genotyped for 70 K SNPs. The GWAS results were processed through a 3-step analytical pipeline comprised of (1) association weight matrix; (2) regulatory impact factor; and (3) partial correlation and information theory. The inferred gene regulatory network comprised 3561 genes (within a 5 kb distance from a relevant SNP–P < 0.05) and 738,913 connections (SNP-to-SNP co-associations). Our findings highlight the complexity and polygenic nature of the pig gut microbial ecosystem. Prominent within the network were 5 regulators, PRDM15, STAT1, ssc-mir-371, SOX9 and RUNX2 which gathered 942, 607, 588, 284 and 273 connections, respectively. PRDM15 modulates the transcription of upstream regulators of WNT and MAPK-ERK signaling to safeguard naive pluripotency and regulates the production of Th1- and Th2-type immune response. The signal transducer STAT1 has long been associated with immune processes and was recently identified as a potential regulator of vaccine response to porcine reproductive and respiratory syndrome. The list of regulators was enriched for immune-related pathways, and the list of predicted targets includes candidate genes previously reported as associated with microbiota profile in pigs, mice and human, such as SLIT3, SLC39A8, NOS1, IL1R2, DAB1, TOX3, SPP1, THSD7B, ELF2, PIANP, A2ML1, and IFNAR1. Moreover, we show the existence of host-genetic variants jointly associated with the relative abundance of butyrate producer bacteria and host performance. Conclusions Taken together, our results identified regulators, candidate genes, and mechanisms linked with microbiome modulation by the host. They further highlight the value of the proposed analytical pipeline to exploit pleiotropy and the crosstalk between bacteria and protists as significant contributors to host-microbiome interactions and identify genetic markers and candidate genes that can be incorporated in breeding program to improve host-performance and microbial traits.

Ancient DNA (aDNA) has played a major role in our understanding of the past. Important advances in the sequencing and analysis of aDNA from a range of organisms have enabled a detailed understanding of processes such as past demography, introgression, domestication, adaptation and speciation. However, to date and with the notable exception of microbiomes and sediments, most aDNA studies have focused on single taxa or taxonomic groups, making the study of changes at the community level challenging. This is rather surprising because current sequencing and analytical approaches allow us to obtain and analyse aDNA from multiple source materials. When combined, these data can enable the simultaneous study of multiple taxa through space and time, and could thus provide a more comprehensive understanding of ecosystem-wide changes. It is therefore timely to develop an integrative approach to aDNA studies by combining data from multiple taxa and substrates. In this review, we discuss the various applications, associated challenges and future prospects of such an approach.