Transcription from a gene desert in a melanoma porcine model.

The genetic mechanisms underlying cutaneous melanoma onset and progression need to be further understood to improve patients' care. Several studies have focused on the genetic determinism of melanoma development in the MeLiM pig, a biomedical model of cutaneous melanoma. The objective of this study was to better describe the influence of a particular genomic region on melanoma progression in the MeliM model. Indeed, a large region of the Sus scrofa chromosome 1 has been identified by linkage and association analyses, but the causal mechanisms have remained elusive. To deepen the analysis of this candidate region, a dedicated SNP panel was used to fine map the locus, downsizing the interval to less than 2 Mb, in a genomic region located within a large gene desert. Transcription from this locus was addressed using a tiling array strategy and further validated by RT-PCR in a large panel of tissues. Overall, the gene desert showed an extensive transcriptional landscape, notably dominated by repeated element transcription in tumor and fetal tissues. The transcription of LINE-1 and PERVs has been confirmed in skin and tumor samples from MeLiM pigs. In conclusion, although this study still does not identify a candidate mutation for melanoma occurrence or progression, it highlights a potential role of repeated element transcriptional activity in the MeLiM model.

Characterization of Holstein and Normande whole milk miRNomes highlights breed specificities.

The concept of milk as a healthy food has opened the way for studies on milk components, from nutrients to microRNAs, molecules with broad regulatory properties present in large quantities in milk. Characterization of these components has been performed in several species, such as humans and bovine, depending on the stages of lactation. Here, we have studied the variation in milk microRNA composition according to genetic background. Using high throughput sequencing, we have characterized and compared the milk miRNomes of Holstein and Normande cattle, dairy breeds with distinct milk production features, in order to highlight microRNAs that are essential for regulation of the lactation process. In Holstein and Normande milk, 2,038 and 2,030 microRNAs were identified, respectively, with 1,771 common microRNAs, of which 1,049 were annotated and 722 were predicted. The comparison of the milk miRNomes of two breeds allowed to highlight 182 microRNAs displaying significant differences in the abundance. They are involved in the regulation of lipid metabolism and mammary morphogenesis and development, which affects lactation. Our results provide new insights into the regulation of molecular mechanisms involved in milk production.

KIRREL is differentially expressed in adipose tissue from 'fertil+' and 'fertil-' cows: in vitro role in ovary?

We have previously shown that dairy cows carrying the 'fertil-' haplotype for one quantitative trait locus affecting female fertility located on the bovine chromosome three (QTL-F-Fert-BTA3) have a significantly lower conception rate and body weight after calving than cows carrying the 'fertil+' haplotype. Here, we compared by Tiling Array the expression of genes included in the QTL-F-Fert-BTA3 in 'fertil+' and 'fertil-' adipose tissue one week after calving when plasma non-esterified fatty acid concentrations were greater in 'fertil-' animals. We observed that thirty-one genes were overexpressed whereas twelve were under-expressed in 'fertil+' as compared to 'fertil-' cows (P < 0.05). By quantitative PCR and immunoblot we confirmed that adipose tissue KIRREL mRNA and protein were significantly greater expressed in 'fertil+' than in 'fertil-'. KIRREL mRNA is abundant in bovine kidney, adipose tissue, pituitary, and ovary and detectable in hypothalamus and mammary gland. Its expression (mRNA and protein) is greater in kidney of 'fertil+' than 'fertil-' cows (P < 0.05). KIRREL (mRNA and protein) is also present in the different ovarian cells with a greater expression in granulosa cells of 'fertil+' than 'fertil-' cows. In cultured granulosa cells, recombinant KIRREL halved steroid secretion in basal state (P < 0.05). It also decreased cell proliferation (P < 0.05) and in vitro oocyte maturation (P < 0.05). These results were associated to a rapid increase in MAPK1/3 and MAPK14 phosphorylation in granulosa cells and to a decrease in MAPK1/3 phosphorylation in oocyte. Thus, KIRREL could be a potential metabolic messenger linking body composition and fertility.

Comparison of whole-genome (13X) and capture (87X) resequencing methods for SNP and genotype callings.

The number of polymorphisms identified with next-generation sequencing approaches depends directly on the sequencing depth and therefore on the experimental cost. Although higher levels of depth ensure more sensitive and more specific SNP calls, economic constraints limit the increase of depth for whole-genome resequencing (WGS). For this reason, capture resequencing is used for studies focusing on only some specific regions of the genome. However, several biases in capture resequencing are known to have a negative impact on the sensitivity of SNP detection. Within this framework, the aim of this study was to compare the accuracy of WGS and capture resequencing on SNP detection and genotype calling, which differ in terms of both sequencing depth and biases. Indeed, we have evaluated the SNP calling and genotyping accuracy in a WGS dataset (13X) and in a capture resequencing dataset (87X) performed on 11 individuals. The percentage of SNPs not identified due to a sevenfold sequencing depth decrease was estimated at 7.8% using a down-sampling procedure on the capture sequencing dataset. A comparison of the 87X capture sequencing dataset with the WGS dataset revealed that capture-related biases were leading with the loss of 5.2% of SNPs detected with WGS. Nevertheless, when considering the SNPs detected by both approaches, capture sequencing appears to achieve far better SNP genotyping, with about 4.4% of the WGS genotypes that can be considered as erroneous and even 10% focusing on heterozygous genotypes. In conclusion, WGS and capture deep sequencing can be considered equivalent strategies for SNP detection, as the rate of SNPs not identified because of a low sequencing depth in the former is quite similar to SNPs missed because of method biases of the latter. On the other hand, capture deep sequencing clearly appears more adapted for studies requiring great accuracy in genotyping.

Finding candidate genes under positive selection in Non-model species: examples of genes involved in host specialization in pathogens.

Numerous genes in diverse organisms have been shown to be under positive selection, especially genes involved in reproduction, adaptation to contrasting environments, hybrid inviability, and host-pathogen interactions. Looking for genes under positive selection in pathogens has been a priority in efforts to investigate coevolution dynamics and to develop vaccines or drugs. To elucidate the functions involved in host specialization, here we aimed at identifying candidate sequences that could have evolved under positive selection among closely related pathogens specialized on different hosts. For this goal, we sequenced c. 17,000-32,000 ESTs from each of four Microbotryum species, which are fungal pathogens responsible for anther smut disease on host plants in the Caryophyllaceae. Forty-two of the 372 predicted orthologous genes showed significant signal of positive selection, which represents a good number of candidate genes for further investigation. Sequencing 16 of these genes in 9 additional Microbotryum species confirmed that they have indeed been rapidly evolving in the pathogen species specialized on different hosts. The genes showing significant signals of positive selection were putatively involved in nutrient uptake from the host, secondary metabolite synthesis and secretion, respiration under stressful conditions and stress response, hyphal growth and differentiation, and regulation of expression by other genes. Many of these genes had transmembrane domains and may therefore also be involved in pathogen recognition by the host. Our approach thus revealed fruitful and should be feasible for many non-model organisms for which candidate genes for diversifying selection are needed.

Assessing the performance of single-copy genes for recovering robust phylogenies.

Phylogenies involving nonmodel species are based on a few genes, mostly chosen following historical or practical criteria. Because gene trees are sometimes incongruent with species trees, the resulting phylogenies may not accurately reflect the evolutionary relationships among species. The increase in availability of genome sequences now provides large numbers of genes that could be used for building phylogenies. However, for practical reasons only a few genes can be sequenced for a wide range of species. Here we asked whether we can identify a few genes, among the single-copy genes common to most fungal genomes, that are sufficient for recovering accurate and well-supported phylogenies. Fungi represent a model group for phylogenomics because many complete fungal genomes are available. An automated procedure was developed to extract single-copy orthologous genes from complete fungal genomes using a Markov Clustering Algorithm (Tribe-MCL). Using 21 complete, publicly available fungal genomes with reliable protein predictions, 246 single-copy orthologous gene clusters were identified. We inferred the maximum likelihood trees using the individual orthologous sequences and constructed a reference tree from concatenated protein alignments. The topologies of the individual gene trees were compared to that of the reference tree using three different methods. The performance of individual genes in recovering the reference tree was highly variable. Gene size and the number of variable sites were highly correlated and significantly affected the performance of the genes, but the average substitution rate did not. Two genes recovered exactly the same topology as the reference tree, and when concatenated provided high bootstrap values. The genes typically used for fungal phylogenies did not perform well, which suggests that current fungal phylogenies based on these genes may not accurately reflect the evolutionary relationships among species. Analyses on subsets of species showed that the phylogenetic performance did not seem to depend strongly on the sample. We expect that the best-performing genes identified here will be very useful for phylogenetic studies of fungi, at least at a large taxonomic scale. Furthermore, we compare the method developed here for finding genes for building robust phylogenies with previous ones and we advocate that our method could be applied to other groups of organisms when more complete genomes are available.

PERMANENT GENETIC RESOURCES: Isolation of 60 polymorphic microsatellite loci in EST libraries of four sibling species of the phytopathogenic fungal complex Microbotryum.

We report the development of 60 microsatellite markers on four species of the fungal complex Microbotryum, causing anther smut of the Caryophyllaceae. Microsatellites were found in four expressed sequence tag (EST) libraries, built from isolates of M. lychnis-dioicae, M. violaceum sensus stricto, M. lagerheimii and M. dianthorum, collected, respectively, from the plants Silene latifolia, S. nutans, S. vulgaris and Dianthus carthusianorum. Intrapopulation polymorphism was investigated using 24 isolates, and cross-amplification was explored using 23 isolates belonging to at least 10 different Microbotryum species. This study provides numerous microsatellite markers for population genetics and mapping studies.