Jordi Estellé

A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis

During the last 3 years, a number of approaches for the normalization of RNA sequencing data have emerged in the literature, differing both in the type of bias adjustment and in the statistical strategy adopted. However, as data continue to accumulate, there has been no clear consensus on the appropriate normalization method to be used or the impact of a chosen method on the downstream analysis. In this work, we focus on a comprehensive comparison of seven recently proposed normalization methods for the differential analysis of RNA-seq data, with an emphasis on the use of varied real and simulated datasets involving different species and experimental designs to represent data characteristics commonly observed in practice. Based on this comparison study, we propose practical recommendations on the appropriate normalization method to be used and its impact on the differential analysis of RNA-seq data.

Fast computation and applications of genome mappability.

We present a fast mapping-based algorithm to compute the mappability of each region of a reference genome up to a specified number of mismatches. Knowing the mappability of a genome is crucial for the interpretation of massively parallel sequencing experiments. We investigate the properties of the mappability of eukaryotic DNA/RNA both as a whole and at the level of the gene family, providing for various organisms tracks which allow the mappability information to be visually explored. In addition, we show that mappability varies greatly between species and gene classes. Finally, we suggest several practical applications where mappability can be used to refine the analysis of high-throughput sequencing data (SNP calling, gene expression quantification and paired-end experiments). This work highlights mappability as an important concept which deserves to be taken into full account, in particular when massively parallel sequencing technologies are employed. The GEM mappability program belongs to the GEM (GEnome Multitool) suite of programs, which can be freely downloaded for any use from its website (http://gemlibrary.sourceforge.net).

Tuning of Natural Killer Cell Reactivity by NKp46 and Helios Calibrates T Cell Responses

Natural Killer Controls Cytolytic natural killer (NK) cells participate in both antimicrobial and antitumor immunity. Their responsiveness is tuned through signals received through a variety of inhibitory and activating receptors expressed on their cell surface. Narni-Mancinelli et al. (p. 344) now show that signaling through the activating receptor NKp46 paradoxically keeps NK cell responses in check. NK cells from mice with disrupted NKp46 expression were hyperresponsive to stimulation and better protected against viral infection. NK cell responses, which are part of the early response to infection, may thus need to be carefully tuned to ensure optimal initiation of adaptive immunity and formation of protective long-lived memory cells. The activating receptor NKp46 is important for keeping the responses of natural killer cells in check. Natural killer (NK) cells are lymphocytes involved in antimicrobial and antitumoral immune responses. Using N-ethyl-N-nitrosourea mutagenesis in mice, we identified a mutant with increased resistance to viral infections because of the presence of hyperresponsive NK cells. Whole-genome sequencing and functional analysis revealed a loss-of-function mutation in the Ncr1 gene encoding the activating receptor NKp46. The down-regulation of NK cell activity by NKp46 was associated with the silencing of the Helios transcription factor in NK cells. NKp46 was critical for the subsequent development of antiviral and antibacterial T cell responses, which suggests that the regulation of NK cell function by NKp46 allows for the optimal development of adaptive immune responses. NKp46 blockade enhanced NK cell reactivity in vivo, which could enable the design of immunostimulation strategies in humans.

Chronic Trichuris muris Infection Decreases Diversity of the Intestinal Microbiota and Concomitantly Increases the Abundance of Lactobacilli.

The intestinal microbiota is vital for shaping the local intestinal environment as well as host immunity and metabolism. At the same time, epidemiological and experimental evidence suggest an important role for parasitic worm infections in maintaining the inflammatory and regulatory balance of the immune system. In line with this, the prevalence of persistent worm infections is inversely correlated with the incidence of immune-associated diseases, prompting the use of controlled parasite infections for therapeutic purposes. Despite this, the impact of parasite infection on the intestinal microbiota, as well as potential downstream effects on the immune system, remain largely unknown. We have assessed the influence of chronic infection with the large-intestinal nematode Trichuris muris, a close relative of the human pathogen Trichuris trichiura, on the composition of the murine intestinal microbiota by 16S ribosomal-RNA gene-based sequencing. Our results demonstrate that persistent T. muris infection dramatically affects the large-intestinal microbiota, most notably with a drop in the diversity of bacterial communities, as well as a marked increase in the relative abundance of the Lactobacillus genus. In parallel, chronic T. muris infection resulted in a significant shift in the balance between regulatory and inflammatory T cells in the intestinal adaptive immune system, in favour of inflammatory cells. Together, these data demonstrate that chronic parasite infection strongly influences the intestinal microbiota and the adaptive immune system. Our results illustrate the complex interactions between these factors in the intestinal tract, and contribute to furthering the understanding of this interplay, which is of crucial importance considering that 500 million people globally are suffering from these infections and their potential use for therapeutic purposes.

Early-life establishment of the swine gut microbiome and impact on host phenotypes

Early bacterial colonization and succession within the gastrointestinal tract has been suggested to be crucial in the establishment of specific microbiota composition and the shaping of host phenotype. Here, the composition and dynamics of faecal microbiomes were studied for 31 healthy piglets across five age strata (days 14, 36, 48, 60 and 70 after birth) together with their mothers. Faecal microbiome composition was assessed by 16S rRNA gene 454-pyrosequencing. Bacteroidetes and Firmicutes were the predominant phyla present at each age. For all piglets, luminal secretory IgA concentration was measured at day 70, and body weight was recorded until day 70. The microbiota of suckling piglets was mainly represented by Bacteroides, Oscillibacter, Escherichia/Shigella, Lactobacillus and unclassified Ruminococcaceae genera. This pattern contrasted with that of Acetivibrio, Dialister, Oribacterium, Succinivibrio and Prevotella genera, which appeared increased after weaning. Lactobacillus fermentum might be vertically transferred via breast milk or faeces. The microbiota composition coevolved with their hosts towards two different clusters after weaning, primarily distinguished by unclassified Ruminococcaceae and Prevotella abundances. Prevotella was positively correlated with luminal secretory IgA concentrations, and body weight. Our study opens up new possibilities for health and feed efficiency manipulation via genetic selection and nutrition in the agricultural domain.

Liver transcriptome profile in pigs with extreme phenotypes of intramuscular fatty acid composition

BackgroundNew advances in high-throughput technologies have allowed for the massive analysis of genomic data, providing new opportunities for the characterization of the transcriptome architectures. Recent studies in pigs have employed RNA-Seq to explore the transcriptome of different tissues in a reduced number of animals. The main goal of this study was the identification of differentially-expressed genes in the liver of Iberian x Landrace crossbred pigs showing extreme phenotypes for intramuscular fatty acid composition using RNA-Seq.ResultsThe liver transcriptomes of two female groups (H and L) with phenotypically extreme intramuscular fatty acid composition were sequenced using RNA-Seq. A total of 146 and 180 unannotated protein-coding genes were identified in intergenic regions for the L and H groups, respectively. In addition, a range of 5.8 to 7.3% of repetitive elements was found, with SINEs being the most abundant elements. The expression in liver of 186 (L) and 270 (H) lncRNAs was also detected. The higher reproducibility of the RNA-Seq data was validated by RT-qPCR and porcine expression microarrays, therefore showing a strong correlation between RT-qPCR and RNA-Seq data (ranking from 0.79 to 0.96), as well as between microarrays and RNA-Seq (r=0.72). A differential expression analysis between H and L animals identified 55 genes differentially-expressed between groups. Pathways analysis revealed that these genes belong to biological functions, canonical pathways and three gene networks related to lipid and fatty acid metabolism. In concordance with the phenotypic classification, the pathways analysis inferred that linolenic and arachidonic acids metabolism was altered between extreme individuals. In addition, a connection was observed among the top three networks, hence suggesting that these genes are interconnected and play an important role in lipid and fatty acid metabolism.ConclusionsIn the present study RNA-Seq was used as a tool to explore the liver transcriptome of pigs with extreme phenotypes for intramuscular fatty acid composition. The differential gene expression analysis showed potential gene networks which affect lipid and fatty acid metabolism. These results may help in the design of selection strategies to improve the sensorial and nutritional quality of pork meat.

Prediction of altered 3'- UTR miRNA-binding sites from RNA-Seq data: the swine leukocyte antigen complex (SLA) as a model region.

The SLA (swine leukocyte antigen, MHC: SLA) genes are the most important determinants of immune, infectious disease and vaccine response in pigs; several genetic associations with immunity and swine production traits have been reported. However, most of the current knowledge on SLA is limited to gene coding regions. MicroRNAs (miRNAs) are small molecules that post-transcriptionally regulate the expression of a large number of protein-coding genes in metazoans, and are suggested to play important roles in fine-tuning immune mechanisms and disease responses. Polymorphisms in either miRNAs or their gene targets may have a significant impact on gene expression by abolishing, weakening or creating miRNA target sites, possibly leading to phenotypic variation. We explored the impact of variants in the 3′-UTR miRNA target sites of genes within the whole SLA region. The combined predictions by TargetScan, PACMIT and TargetSpy, based on different biological parameters, empowered the identification of miRNA target sites and the discovery of polymorphic miRNA target sites (poly-miRTSs). Predictions for three SLA genes characterized by a different range of sequence variation provided proof of principle for the analysis of poly-miRTSs from a total of 144 M RNA-Seq reads collected from different porcine tissues. Twenty-four novel SNPs were predicted to affect miRNA-binding sites in 19 genes of the SLA region. Seven of these genes (SLA-1, SLA-6, SLA-DQA, SLA-DQB1, SLA-DOA, SLA-DOB and TAP1) are linked to antigen processing and presentation functions, which is reminiscent of associations with disease traits reported for altered miRNA binding to MHC genes in humans. An inverse correlation in expression levels was demonstrated between miRNAs and co-expressed SLA targets by exploiting a published dataset (RNA-Seq and small RNA-Seq) of three porcine tissues. Our results support the resource value of RNA-Seq collections to identify SNPs that may lead to altered miRNA regulation patterns.

Analysis of porcine adipose tissue transcriptome reveals differences in de novo fatty acid synthesis in pigs with divergent muscle fatty acid composition

BackgroundIn pigs, adipose tissue is one of the principal organs involved in the regulation of lipid metabolism. It is particularly involved in the overall fatty acid synthesis with consequences in other lipid-target organs such as muscles and the liver. With this in mind, we have used massive, parallel high-throughput sequencing technologies to characterize the porcine adipose tissue transcriptome architecture in six Iberian x Landrace crossbred pigs showing extreme phenotypes for intramuscular fatty acid composition (three per group).ResultsHigh-throughput RNA sequencing was used to generate a whole characterization of adipose tissue (backfat) transcriptome. A total of 4,130 putative unannotated protein-coding sequences were identified in the 20% of reads which mapped in intergenic regions. Furthermore, 36% of the unmapped reads were represented by interspersed repeats, SINEs being the most abundant elements. Differential expression analyses identified 396 candidate genes among divergent animals for intramuscular fatty acid composition. Sixty-two percent of these genes (247/396) presented higher expression in the group of pigs with higher content of intramuscular SFA and MUFA, while the remaining 149 showed higher expression in the group with higher content of PUFA. Pathway analysis related these genes to biological functions and canonical pathways controlling lipid and fatty acid metabolisms. In concordance with the phenotypic classification of animals, the major metabolic pathway differentially modulated between groups was de novo lipogenesis, the group with more PUFA being the one that showed lower expression of lipogenic genes.ConclusionsThese results will help in the identification of genetic variants at loci that affect fatty acid composition traits. The implications of these results range from the improvement of porcine meat quality traits to the application of the pig as an animal model of human metabolic diseases.

Phylogenetic network analysis applied to pig gut microbiota identifies an ecosystem structure linked with growth traits

The ecological interactions within the gut microbial communities are complex and far from being fully understood. Here we report the first study that aims at defining the interaction network of the gut microbiota in pigs and comparing it with the enterotype-like clustering analysis. Fecal microbiota of 518 healthy piglets was characterized by 16S ribosomal RNA gene sequencing. Two networks were constructed at the genus and operational taxonomic unit levels. Within-network interactions mirrored the human gut microbiota relationships, with a strong co-exclusion between Prevotella and Ruminococcus genera, and were consistent with the two enterotype-like clusters identified in the pig microbiota. Remarkably, the cluster classification of the individuals was significantly associated with the body weight at 60 days of age (P=0.005) and average daily gain (P=0.027). To the best of our knowledge, this is the first study to provide an integrated overview of the porcine gut microbiota that suggests a conservation of the ecological community interactions and functional architecture between humans and pig. Moreover, we show that the microbial ecosystems and porcine growth traits are linked, which allows us to foresee that the enterotype concept may have an important role in the animal production industry.

On growth, fatness, and form: A further look at porcine Chromosome 4 in an Iberian × Landrace cross

A crossed population between Iberian × Landrace pigs consisting of 321 F2, 87 F3, and 85 backcross individuals has been analyzed to refine the number and positions of quantitative trait loci (QTL) affecting shape, growth, fatness, and meat quality traits in SSC4. A multitrait multi-QTL approach has been used. Our results suggest that carcass length and shoulder weight are affected by two loci. The first one, close to the AFABP gene, has a very strong pleiotropic effect on fatness, whereas the second one, in the interval between S0073 and S0214, also affects live weight, although to a lesser extent. This latter QTL would correspond to the FAT1 locus described initially in pigs. It seems that SSC4’s loci play an important role in redistributing total weight, and the Landrace allele increases shoulder weight and carcass length much more than ham or total weight. Furthermore, there is also strong evidence of additional loci influencing pH and color in more distant, telomeric positions.