Integrative study of diet-induced mouse models of NAFLD identifies PPARα as a sexually dimorphic drug target.

OBJECTIVE: We evaluated the influence of sex on the pathophysiology of non-alcoholic fatty liver disease (NAFLD). We investigated diet-induced phenotypic responses to define sex-specific regulation between healthy liver and NAFLD to identify influential pathways in different preclinical murine models and their relevance in humans. DESIGN: Different models of diet-induced NAFLD (high-fat diet, choline-deficient high-fat diet, Western diet or Western diet supplemented with fructose and glucose in drinking water) were compared with a control diet in male and female mice. We performed metabolic phenotyping, including plasma biochemistry and liver histology, untargeted large-scale approaches (liver metabolome, lipidome and transcriptome), gene expression profiling and network analysis to identify sex-specific pathways in the mouse liver. RESULTS: The different diets induced sex-specific responses that illustrated an increased susceptibility to NAFLD in male mice. The most severe lipid accumulation and inflammation/fibrosis occurred in males receiving the high-fat diet and Western diet, respectively. Sex-biased hepatic gene signatures were identified for these different dietary challenges. The peroxisome proliferator-activated receptor α (PPARα) co-expression network was identified as sexually dimorphic, and in vivo experiments in mice demonstrated that hepatocyte PPARα determines a sex-specific response to fasting and treatment with pemafibrate, a selective PPARα agonist. Liver molecular signatures in humans also provided evidence of sexually dimorphic gene expression profiles and the sex-specific co-expression network for PPARα. CONCLUSIONS: These findings underscore the sex specificity of NAFLD pathophysiology in preclinical studies and identify PPARα as a pivotal, sexually dimorphic, pharmacological target. TRIAL REGISTRATION NUMBER: NCT02390232.

LncRNAs in domesticated animals: from dog to livestock species.

Animal genomes are pervasively transcribed into multiple RNA molecules, of which many will not be translated into proteins. One major component of this transcribed non-coding genome is the long non-coding RNAs (lncRNAs), which are defined as transcripts longer than 200 nucleotides with low coding-potential capabilities. Domestic animals constitute a unique resource for studying the genetic and epigenetic basis of phenotypic variations involving protein-coding and non-coding RNAs, such as lncRNAs. This review presents the current knowledge regarding transcriptome-based catalogues of lncRNAs in major domesticated animals (pets and livestock species), covering a broad phylogenetic scale (from dogs to chicken), and in comparison with human and mouse lncRNA catalogues. Furthermore, we describe different methods to extract known or discover novel lncRNAs and explore comparative genomics approaches to strengthen the annotation of lncRNAs. We then detail different strategies contributing to a better understanding of lncRNA functions, from genetic studies such as GWAS to molecular biology experiments and give some case examples in domestic animals. Finally, we discuss the limitations of current lncRNA annotations and suggest research directions to improve them and their functional characterisation.

Multi-species annotation of transcriptome and chromatin structure in domesticated animals.

BACKGROUND: Comparative genomics studies are central in identifying the coding and non-coding elements associated with complex traits, and the functional annotation of genomes is a critical step to decipher the genotype-to-phenotype relationships in livestock animals. As part of the Functional Annotation of Animal Genomes (FAANG) action, the FR-AgENCODE project aimed to create reference functional maps of domesticated animals by profiling the landscape of transcription (RNA-seq), chromatin accessibility (ATAC-seq) and conformation (Hi-C) in species representing ruminants (cattle, goat), monogastrics (pig) and birds (chicken), using three target samples related to metabolism (liver) and immunity (CD4+ and CD8+ T cells). RESULTS: RNA-seq assays considerably extended the available catalog of annotated transcripts and identified differentially expressed genes with unknown function, including new syntenic lncRNAs. ATAC-seq highlighted an enrichment for transcription factor binding sites in differentially accessible regions of the chromatin. Comparative analyses revealed a core set of conserved regulatory regions across species. Topologically associating domains (TADs) and epigenetic A/B compartments annotated from Hi-C data were consistent with RNA-seq and ATAC-seq data. Multi-species comparisons showed that conserved TAD boundaries had stronger insulation properties than species-specific ones and that the genomic distribution of orthologous genes in A/B compartments was significantly conserved across species. CONCLUSIONS: We report the first multi-species and multi-assay genome annotation results obtained by a FAANG project. Beyond the generation of reference annotations and the confirmation of previous findings on model animals, the integrative analysis of data from multiple assays and species sheds a new light on the multi-scale selective pressure shaping genome organization from birds to mammals. Overall, these results emphasize the value of FAANG for research on domesticated animals and reinforces the importance of future meta-analyses of the reference datasets being generated by this community on different species.

Long noncoding RNAs in lipid metabolism: literature review and conservation analysis across species.

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.

A transcriptome multi-tissue analysis identifies biological pathways and genes associated with variations in feed efficiency of growing pigs.

BACKGROUND: Animal's efficiency in converting feed into lean gain is a critical issue for the profitability of meat industries. This study aimed to describe shared and specific molecular responses in different tissues of pigs divergently selected over eight generations for residual feed intake (RFI). RESULTS: Pigs from the low RFI line had an improved gain-to-feed ratio during the test period and displayed higher leanness but similar adiposity when compared with pigs from the high RFI line at 132 days of age. Transcriptomics data were generated from longissimus muscle, liver and two adipose tissues using a porcine microarray and analyzed for the line effect (n = 24 pigs per line). The most apparent effect of the line was seen in muscle, whereas subcutaneous adipose tissue was the less affected tissue. Molecular data were analyzed by bioinformatics and subjected to multidimensional statistics to identify common biological processes across tissues and key genes participating to differences in the genetics of feed efficiency. Immune response, response to oxidative stress and protein metabolism were the main biological pathways shared by the four tissues that distinguished pigs from the low or high RFI lines. Many immune genes were under-expressed in the four tissues of the most efficient pigs. The main genes contributing to difference between pigs from the low vs high RFI lines were CD40, CTSC and NTN1. Different genes associated with energy use were modulated in a tissue-specific manner between the two lines. The gene expression program related to glycogen utilization was specifically up-regulated in muscle of pigs from the low RFI line (more efficient). Genes involved in fatty acid oxidation were down-regulated in muscle but were promoted in adipose tissues of the same pigs when compared with pigs from the high RFI line (less efficient). This underlined opposite line-associated strategies for energy use in skeletal muscle and adipose tissue. Genes related to cholesterol synthesis and efflux in liver and perirenal fat were also differentially regulated in pigs from the low vs high RFI lines. CONCLUSIONS: Non-productive functions such as immunity, defense against pathogens and oxidative stress contribute likely to inter-individual variations in feed efficiency.

Long noncoding RNA repertoire in chicken liver and adipose tissue.

BACKGROUND: Improving functional annotation of the chicken genome is a key challenge in bridging the gap between genotype and phenotype. Among all transcribed regions, long noncoding RNAs (lncRNAs) are a major component of the transcriptome and its regulation, and whole-transcriptome sequencing (RNA-Seq) has greatly improved their identification and characterization. We performed an extensive profiling of the lncRNA transcriptome in the chicken liver and adipose tissue by RNA-Seq. We focused on these two tissues because of their importance in various economical traits for which energy storage and mobilization play key roles and also because of their high cell homogeneity. To predict lncRNAs, we used a recently developed tool called FEELnc, which also classifies them with respect to their distance and strand orientation to the closest protein-coding genes. Moreover, to confidently identify the genes/transcripts expressed in each tissue (a complex task for weakly expressed molecules such as lncRNAs), we probed a particularly large number of biological replicates (16 per tissue) compared to common multi-tissue studies with a larger set of tissues but less sampling. RESULTS: We predicted 2193 lncRNA genes, among which 1670 were robustly expressed across replicates in the liver and/or adipose tissue and which were classified into 1493 intergenic and 177 intragenic lncRNAs located between and within protein-coding genes, respectively. We observed similar structural features between chickens and mammals, with strong synteny conservation but without sequence conservation. As previously reported, we confirm that lncRNAs have a lower and more tissue-specific expression than mRNAs. Finally, we showed that adjacent lncRNA-mRNA genes in divergent orientation have a higher co-expression level when separated by less than 1 kb compared to more distant divergent pairs. Among these, we highlighted for the first time a novel lncRNA candidate involved in lipid metabolism, lnc_DHCR24, which is highly correlated with the DHCR24 gene that encodes a key enzyme of cholesterol biosynthesis. CONCLUSIONS: We provide a comprehensive lncRNA repertoire in the chicken liver and adipose tissue, which shows interesting patterns of co-expression between mRNAs and lncRNAs. It contributes to improving the structural and functional annotation of the chicken genome and provides a basis for further studies on energy storage and mobilization traits in the chicken.

Liver PPARα is crucial for whole-body fatty acid homeostasis and is protective against NAFLD.

OBJECTIVE: Peroxisome proliferator-activated receptor α (PPARα) is a nuclear receptor expressed in tissues with high oxidative activity that plays a central role in metabolism. In this work, we investigated the effect of hepatocyte PPARα on non-alcoholic fatty liver disease (NAFLD). DESIGN: We constructed a novel hepatocyte-specific PPARα knockout (Pparα(hep-/-)) mouse model. Using this novel model, we performed transcriptomic analysis following fenofibrate treatment. Next, we investigated which physiological challenges impact on PPARα. Moreover, we measured the contribution of hepatocytic PPARα activity to whole-body metabolism and fibroblast growth factor 21 production during fasting. Finally, we determined the influence of hepatocyte-specific PPARα deficiency in different models of steatosis and during ageing. RESULTS: Hepatocyte PPARα deletion impaired fatty acid catabolism, resulting in hepatic lipid accumulation during fasting and in two preclinical models of steatosis. Fasting mice showed acute PPARα-dependent hepatocyte activity during early night, with correspondingly increased circulating free fatty acids, which could be further stimulated by adipocyte lipolysis. Fasting led to mild hypoglycaemia and hypothermia in Pparα(hep-/-) mice when compared with Pparα(-/-) mice implying a role of PPARα activity in non-hepatic tissues. In agreement with this observation, Pparα(-/-) mice became overweight during ageing while Pparα(hep-/-) remained lean. However, like Pparα(-/-) mice, Pparα(hep-/-) fed a standard diet developed hepatic steatosis in ageing. CONCLUSIONS: Altogether, these findings underscore the potential of hepatocyte PPARα as a drug target for NAFLD.

Molecular alterations induced by a high-fat high-fiber diet in porcine adipose tissues: variations according to the anatomical fat location.

BACKGROUND: Changing the energy and nutrient source for growing animals may be an effective way of limiting adipose tissue expansion, a response which may depend on the genetic background of the animals. This study aims to describe the transcriptional modulations present in the adipose tissues of two pig lines divergently selected for residual feed intake which were either fed a high-fat high-fiber (HF) diet or an isocaloric low-fat high-starch diet (LF). RESULTS: Transcriptomic analysis using a porcine microarray was performed on 48 pigs (n = 12 per diet and per line) in both perirenal (PRAT) and subcutaneous (SCAT) adipose tissues. There was no interaction between diet and line on either adiposity or transcriptional profiles, so that the diet effect was inferred independently of the line. Irrespective of line, the relative weights of the two fat depots were lower in HF pigs than in LF pigs after 58 days on dietary treatment. In the two adipose tissues, the most apparent effect of the HF diet was the down-regulation of several genes associated with the ubiquitin-proteasome system, which therefore may be associated with dietary-induced modulations in genes acting in apoptotic and cell cycle regulatory pathways. Genes involved in glucose metabolic processes were also down-regulated by the HF diet, with no significant variation or decreased expression of important lipid-related genes such as the low-density lipoprotein receptor and leptin in the two fat pads. The master regulators of glucose and fatty acid homeostasis SREBF1 and MLXIPL, and peroxisome proliferator-activated receptor (PPAR)δ and its heterodimeric partner RXRA were down-regulated by the HF diet. PPARγ which has pleiotropic functions including lipid metabolism and adipocyte differentiation, was however up-regulated by this diet in PRAT and SCAT. Dietary-related modulations in the expression of genes associated with immunity and inflammation were mainly revealed in PRAT. CONCLUSION: A high-fat high-fiber diet depressed glucose and lipid anabolic molecular pathways, thus counteracting adipose tissue expansion. Interaction effects between dietary intake of fiber and lipids on gene expression may modulate innate immunity and inflammation, a response which is of interest with regard to chronic inflammation and its adverse effects on health and performance.

Thermal manipulation of the chicken embryo triggers differential gene expression in response to a later heat challenge.

BACKGROUND: Meat type chickens have limited capacities to cope with high environmental temperatures, this sometimes leading to mortality on farms and subsequent economic losses. A strategy to alleviate this problem is to enhance adaptive capacities to face heat exposure using thermal manipulation (TM) during embryogenesis. This strategy was shown to improve thermotolerance during their life span. The aim of this study was to determine the effects of TM (39.5 °C, 12 h/24 vs 37.8 °C from d7 to d16 of embryogenesis) and of a subsequent heat challenge (32 °C for 5 h) applied on d34 on gene expression in the Pectoralis major muscle (PM). A chicken gene expression microarray (8 × 60 K) was used to compare muscle gene expression profiles of Control (C characterized by relatively high body temperatures, Tb) and TM chickens (characterized by a relatively low Tb) reared at 21 °C and at 32 °C (CHC and TMHC, respectively) in a dye-swap design with four comparisons and 8 broilers per treatment. Real-time quantitative PCR (RT-qPCR) was subsequently performed to validate differential expression in each comparison. Gene ontology, clustering and network building strategies were then used to identify pathways affected by TM and heat challenge. RESULTS: Among the genes differentially expressed (DE) in the PM (1.5 % of total probes), 28 were found to be differentially expressed between C and TM, 128 between CHC and C, and 759 between TMHC and TM. No DE gene was found between TMHC and CHC broilers. The majority of DE genes analyzed by RT-qPCR were validated. In the TM/C comparison, DE genes were involved in energy metabolism and mitochondrial function, cell proliferation, vascularization and muscle growth; when comparing heat-exposed chickens to their own controls, TM broilers developed more specific pathways than C, especially involving genes related to metabolism, stress response, vascularization, anti-apoptotic and epigenetic processes. CONCLUSIONS: This study improved the understanding of the long-term effects of TM on PM muscle. TM broilers displaying low Tb may have lower metabolic intensity in the muscle, resulting in decreased metabolic heat production, whereas modifications in vascularization may enhance heat loss. These specific changes could in part explain the better adaptation of TM broilers to heat.

Transcriptome-wide investigation of genomic imprinting in chicken.

Genomic imprinting is an epigenetic mechanism by which alleles of some specific genes are expressed in a parent-of-origin manner. It has been observed in mammals and marsupials, but not in birds. Until now, only a few genes orthologous to mammalian imprinted ones have been analyzed in chicken and did not demonstrate any evidence of imprinting in this species. However, several published observations such as imprinted-like QTL in poultry or reciprocal effects keep the question open. Our main objective was thus to screen the entire chicken genome for parental-allele-specific differential expression on whole embryonic transcriptomes, using high-throughput sequencing. To identify the parental origin of each observed haplotype, two chicken experimental populations were used, as inbred and as genetically distant as possible. Two families were produced from two reciprocal crosses. Transcripts from 20 embryos were sequenced using NGS technology, producing ∼200 Gb of sequences. This allowed the detection of 79 potentially imprinted SNPs, through an analysis method that we validated by detecting imprinting from mouse data already published. However, out of 23 candidates tested by pyrosequencing, none could be confirmed. These results come together, without a priori, with previous statements and phylogenetic considerations assessing the absence of genomic imprinting in chicken.

The loss of adipokine genes in the chicken genome and implications for insulin metabolism.

Gene loss is one of the main drivers in the evolution of genomes and species. The demonstration that a gene has been lost by pseudogenization is truly complete when one finds the pseudogene in the orthologous genomic region with respect to active genes in other species. In some cases, the identification of such orthologous loci is not possible because of chromosomal rearrangements or if the gene of interest has not yet been sequenced. This question is particularly important in the case of birds because the genomes of avian species possess only about 15,000 predicted genes, in comparison with 20,000 in mammals. Yet, gene loss raises the question of which functions are affected by the changes in gene counts. We describe a systematic approach that makes it possible to demonstrate gene loss in the chicken genome even if a pseudogene has not been found. By using phylogenetic and synteny analysis in vertebrates, genome-wide comparisons between the chicken genome and expressed sequence tags, RNAseq data analysis, statistical analysis of the chicken genome, and radiation hybrid mapping, we show that resistin, TNFα, and PAI-1 (SERPINE1), three genes encoding adipokines inhibiting insulin sensitivity, have been lost in chicken and zebra finch genomes. Moreover, omentin, a gene encoding an adipokine that enhances insulin sensitivity, has also been lost in the chicken genome. Overall, only one adipokine inhibiting insulin sensitivity and five adipokines enhancing insulin sensitivity are still present in the chicken genome. These genetic differences between mammals and chicken, given the functions of the genes in mammals, would have dramatic consequences on chicken endocrinology, leading to novel equilibriums especially in the regulation of energy metabolism, insulin sensitivity, as well as appetite and reproduction.

Relationship between feed efficiency and gut microbiota in laying chickens under contrasting feeding conditions.

The gut microbiota is known to play an important role in energy harvest and is likely to affect feed efficiency. In this study, we used 16S metabarcoding sequencing to analyse the caecal microbiota of laying hens from feed-efficient and non-efficient lines obtained by divergent selection for residual feed intake. The two lines were fed either a commercial wheat-soybean based diet (CTR) or a low-energy, high-fibre corn-sunflower diet (LE). The analysis revealed a significant line x diet interaction, highlighting distinct differences in microbial community composition between the two lines when hens were fed the CTR diet, and more muted differences when hens were fed the LE diet. Our results are consistent with the hypothesis that a richer and more diverse microbiota may play a role in enhancing feed efficiency, albeit in a diet-dependent manner. The taxonomic differences observed in the microbial composition seem to correlate with alterations in starch and fibre digestion as well as in the production of short-chain fatty acids. As a result, we hypothesise that efficient hens are able to optimise nutrient absorption through the activity of fibrolytic bacteria such as Alistipes or Anaerosporobacter, which, via their production of propionate, influence various aspects of host metabolism.

Enriched atlas of lncRNA and protein-coding genes for the GRCg7b chicken assembly and its functional annotation across 47 tissues.

Gene atlases for livestock are steadily improving thanks to new genome assemblies and new expression data improving the gene annotation. However, gene content varies across databases due to differences in RNA sequencing data and bioinformatics pipelines, especially for long non-coding RNAs (lncRNAs) which have higher tissue and developmental specificity and are harder to consistently identify compared to protein coding genes (PCGs). As done previously in 2020 for chicken assemblies galgal5 and GRCg6a, we provide a new gene atlas, lncRNA-enriched, for the latest GRCg7b chicken assembly, integrating "NCBI RefSeq", "EMBL-EBI Ensembl/GENCODE" reference annotations and other resources such as FAANG and NONCODE. As a result, the number of PCGs increases from 18,022 (RefSeq) and 17,007 (Ensembl) to 24,102, and that of lncRNAs from 5789 (RefSeq) and 11,944 (Ensembl) to 44,428. Using 1400 public RNA-seq transcriptome representing 47 tissues, we provided expression evidence for 35,257 (79%) lncRNAs and 22,468 (93%) PCGs, supporting the relevance of this atlas. Further characterization including tissue-specificity, sex-differential expression and gene configurations are provided. We also identified conserved miRNA-hosting genes with human counterparts, suggesting common function. The annotated atlas is available at gega.sigenae.org.

Genome-wide interval mapping using SNPs identifies new QTL for growth, body composition and several physiological variables in an F2 intercross between fat and lean chicken lines.

BACKGROUND: For decades, genetic improvement based on measuring growth and body composition traits has been successfully applied in the production of meat-type chickens. However, this conventional approach is hindered by antagonistic genetic correlations between some traits and the high cost of measuring body composition traits. Marker-assisted selection should overcome these problems by selecting loci that have effects on either one trait only or on more than one trait but with a favorable genetic correlation. In the present study, identification of such loci was done by genotyping an F2 intercross between fat and lean lines divergently selected for abdominal fatness genotyped with a medium-density genetic map (120 microsatellites and 1302 single nucleotide polymorphisms). Genome scan linkage analyses were performed for growth (body weight at 1, 3, 5, and 7 weeks, and shank length and diameter at 9 weeks), body composition at 9 weeks (abdominal fat weight and percentage, breast muscle weight and percentage, and thigh weight and percentage), and for several physiological measurements at 7 weeks in the fasting state, i.e. body temperature and plasma levels of IGF-I, NEFA and glucose. Interval mapping analyses were performed with the QTLMap software, including single-trait analyses with single and multiple QTL on the same chromosome. RESULTS: Sixty-seven QTL were detected, most of which had never been described before. Of these 67 QTL, 47 were detected by single-QTL analyses and 20 by multiple-QTL analyses, which underlines the importance of using different statistical models. Close analysis of the genes located in the defined intervals identified several relevant functional candidates, such as ACACA for abdominal fatness, GHSR and GAS1 for breast muscle weight, DCRX and ASPSCR1 for plasma glucose content, and ChEBP for shank diameter. CONCLUSIONS: The medium-density genetic map enabled us to genotype new regions of the chicken genome (including micro-chromosomes) that influenced the traits investigated. With this marker density, confidence intervals were sufficiently small (14 cM on average) to search for candidate genes. Altogether, this new information provides a valuable starting point for the identification of causative genes responsible for important QTL controlling growth, body composition and metabolic traits in the broiler chicken.

Difference in Pap test uptake between women who have sex with women and other women in France: A comparative survey of 2032 women.

The elimination of cervical cancer has been a priority of the World Health Organization since 2018. The number of these cancers induced by the human papillomavirus (HPV) could be drastically reduced through vaccination and regularly screening by Pap tests. Guidelines for cervical cancer screening apply to all women, including those who have sexual relations with women (WSW), as HPV can be transmitted during sex between two women. As far as we know, our study is the first that compare the Pap test rate between WSW and other women in France. We developed an 18-item questionnaire available on the internet for 15 days and finally analyzed the responses of 2032 women. Based on their responses about their self-definition of their sexual orientation and their sexual behavior, we classified them into three groups of women: exclusive WSW, mixed WSW, and non-WSW. For each question, we tested the statistical differences in responses between these three groups. Our study shows in a large sample representative of the French population that exclusive WSW undergo Pap tests significantly less often than either mixed WSW or non-WSW. Among the exclusive WSW, 28.9 % had never had a Pap test, compared with 9 % of the mixed WSW and 3.1 % of non-WSW (p < 0,001). The responses to our questionnaire contribute to an understanding of this disparity and thus help to envision solutions for better care of all women, regardless of their sexual orientation; this point is crucial for prevention of cervical cancer.

Complex trait subtypes identification using transcriptome profiling reveals an interaction between two QTL affecting adiposity in chicken.

BACKGROUND: Integrative genomics approaches that combine genotyping and transcriptome profiling in segregating populations have been developed to dissect complex traits. The most common approach is to identify genes whose eQTL colocalize with QTL of interest, providing new functional hypothesis about the causative mutation. Another approach includes defining subtypes for a complex trait using transcriptome profiles and then performing QTL mapping using some of these subtypes. This approach can refine some QTL and reveal new ones.In this paper we introduce Factor Analysis for Multiple Testing (FAMT) to define subtypes more accurately and reveal interaction between QTL affecting the same trait. The data used concern hepatic transcriptome profiles for 45 half sib male chicken of a sire known to be heterozygous for a QTL affecting abdominal fatness (AF) on chromosome 5 distal region around 168 cM. RESULTS: Using this methodology which accounts for hidden dependence structure among phenotypes, we identified 688 genes that are significantly correlated to the AF trait and we distinguished 5 subtypes for AF trait, which are not observed with gene lists obtained by classical approaches. After exclusion of one of the two lean bird subtypes, linkage analysis revealed a previously undetected QTL on chromosome 5 around 100 cM. Interestingly, the animals of this subtype presented the same q paternal haplotype at the 168 cM QTL. This result strongly suggests that the two QTL are in interaction. In other words, the "q configuration" at the 168 cM QTL could hide the QTL existence in the proximal region at 100 cM. We further show that the proximal QTL interacts with the previous one detected on the chromosome 5 distal region. CONCLUSION: Our results demonstrate that stratifying genetic population by molecular phenotypes followed by QTL analysis on various subtypes can lead to identification of novel and interacting QTL.

Watch Out for a Second SNP: Focus on Multi-Nucleotide Variants in Coding Regions and Rescued Stop-Gained.

Most single-nucleotide polymorphisms (SNPs) are located in non-coding regions, but the fraction usually studied is harbored in protein-coding regions because potential impacts on proteins are relatively easy to predict by popular tools such as the Variant Effect Predictor. These tools annotate variants independently without considering the potential effect of grouped or haplotypic variations, often called "multi-nucleotide variants" (MNVs). Here, we used a large RNA-seq dataset to survey MNVs, comprising 382 chicken samples originating from 11 populations analyzed in the companion paper in which 9.5M SNPs- including 3.3M SNPs with reliable genotypes-were detected. We focused our study on in-codon MNVs and evaluate their potential mis-annotation. Using GATK HaplotypeCaller read-based phasing results, we identified 2,965 MNVs observed in at least five individuals located in 1,792 genes. We found 41.1% of them showing a novel impact when compared to the effect of their constituent SNPs analyzed separately. The biggest impact variation flux concerns the originally annotated stop-gained consequences, for which around 95% were rescued; this flux is followed by the missense consequences for which 37% were reannotated with a different amino acid. We then present in more depth the rescued stop-gained MNVs and give an illustration in the SLC27A4 gene. As previously shown in human datasets, our results in chicken demonstrate the value of haplotype-aware variant annotation, and the interest to consider MNVs in the coding region, particularly when searching for severe functional consequence such as stop-gained variants.

RNA-Seq Data for Reliable SNP Detection and Genotype Calling: Interest for Coding Variant Characterization and Cis-Regulation Analysis by Allele-Specific Expression in Livestock Species.

In addition to their common usages to study gene expression, RNA-seq data accumulated over the last 10 years are a yet-unexploited resource of SNPs in numerous individuals from different populations. SNP detection by RNA-seq is particularly interesting for livestock species since whole genome sequencing is expensive and exome sequencing tools are unavailable. These SNPs detected in expressed regions can be used to characterize variants affecting protein functions, and to study cis-regulated genes by analyzing allele-specific expression (ASE) in the tissue of interest. However, gene expression can be highly variable, and filters for SNP detection using the popular GATK toolkit are not yet standardized, making SNP detection and genotype calling by RNA-seq a challenging endeavor. We compared SNP calling results using GATK suggested filters, on two chicken populations for which both RNA-seq and DNA-seq data were available for the same samples of the same tissue. We showed, in expressed regions, a RNA-seq precision of 91% (SNPs detected by RNA-seq and shared by DNA-seq) and we characterized the remaining 9% of SNPs. We then studied the genotype (GT) obtained by RNA-seq and the impact of two factors (GT call-rate and read number per GT) on the concordance of GT with DNA-seq; we proposed thresholds for them leading to a 95% concordance. Applying these thresholds to 767 multi-tissue RNA-seq of 382 birds of 11 chicken populations, we found 9.5 M SNPs in total, of which ∼550,000 SNPs per tissue and population with a reliable GT (call rate ≥ 50%) and among them, ∼340,000 with a MAF ≥ 10%. We showed that such RNA-seq data from one tissue can be used to (i) detect SNPs with a strong predicted impact on proteins, despite their scarcity in each population (16,307 SIFT deleterious missenses and 590 stop-gained), (ii) study, on a large scale, cis-regulations of gene expression, with ∼81% of protein-coding and 68% of long non-coding genes (TPM ≥ 1) that can be analyzed for ASE, and with ∼29% of them that were cis-regulated, and (iii) analyze population genetic using such SNPs located in expressed regions. This work shows that RNA-seq data can be used with good confidence to detect SNPs and associated GT within various populations and used them for different analyses as GTEx studies.

A factor model to analyze heterogeneity in gene expression.

BACKGROUND: Microarray technology allows the simultaneous analysis of thousands of genes within a single experiment. Significance analyses of transcriptomic data ignore the gene dependence structure. This leads to correlation among test statistics which affects a strong control of the false discovery proportion. A recent method called FAMT allows capturing the gene dependence into factors in order to improve high-dimensional multiple testing procedures. In the subsequent analyses aiming at a functional characterization of the differentially expressed genes, our study shows how these factors can be used both to identify the components of expression heterogeneity and to give more insight into the underlying biological processes. RESULTS: The use of factors to characterize simple patterns of heterogeneity is first demonstrated on illustrative gene expression data sets. An expression data set primarily generated to map QTL for fatness in chickens is then analyzed. Contrarily to the analysis based on the raw data, a relevant functional information about a QTL region is revealed by factor-adjustment of the gene expressions. Additionally, the interpretation of the independent factors regarding known information about both experimental design and genes shows that some factors may have different and complex origins. CONCLUSIONS: As biological information and technological biases are identified in what was before simply considered as statistical noise, analyzing heterogeneity in gene expression yields a new point of view on transcriptomic data.

An integrative atlas of chicken long non-coding genes and their annotations across 25 tissues.

Long non-coding RNAs (LNC) regulate numerous biological processes. In contrast to human, the identification of LNC in farm species, like chicken, is still lacunar. We propose a catalogue of 52,075 chicken genes enriched in LNC ( http://www.fragencode.org/ ), built from the Ensembl reference extended using novel LNC modelled here from 364 RNA-seq and LNC from four public databases. The Ensembl reference grew from 4,643 to 30,084 LNC, of which 59% and 41% with expression ≥ 0.5 and ≥ 1 TPM respectively. Characterization of these LNC relatively to the closest protein coding genes (PCG) revealed that 79% of LNC are in intergenic regions, as in other species. Expression analysis across 25 tissues revealed an enrichment of co-expressed LNC:PCG pairs, suggesting co-regulation and/or co-function. As expected LNC were more tissue-specific than PCG (25% vs. 10%). Similarly to human, 16% of chicken LNC hosted one or more miRNA. We highlighted a new chicken LNC, hosting miR155, conserved in human, highly expressed in immune tissues like miR155, and correlated with immunity-related PCG in both species. Among LNC:PCG pairs tissue-specific in the same tissue, we revealed an enrichment of divergent pairs with the PCG coding transcription factors, as for example LHX5, HXD3 and TBX4, in both human and chicken.