Database construction and Peptide identification strategies for proteogenomic studies on sequenced genomes.

Since the advent of high-throughput DNA sequencing technologies, the ever-increasing rate at which genomes have been published has generated new challenges notably at the level of genome annotation. Even if gene predictors and annotation softwares are more and more efficient, the ultimate validation is still in the observation of predicted gene product( s). Mass-spectrometry based proteomics provides the necessary high throughput technology to show evidences of protein presence and, from the identified sequences, confirmation or invalidation of predicted annotations. We review here different strategies used to perform a MS-based proteogenomics experiment with a bottom-up approach. We start from the strengths and weaknesses of the different database construction strategies, based on different genomic information (whole genome, ORF, cDNA, EST or RNA-Seq data), which are then used for matching mass spectra to peptides and proteins. We also review the important points to be considered for a correct statistical assessment of the peptide identifications. Finally, we provide references for tools used to map and visualize the peptide identifications back to the original genomic information.

Broad-scale adaptive genetic variation in alpine plants is driven by temperature and precipitation.

Identifying adaptive genetic variation is a challenging task, in particular in non-model species for which genomic information is still limited or absent. Here, we studied distribution patterns of amplified fragment length polymorphisms (AFLPs) in response to environmental variation, in 13 alpine plant species consistently sampled across the entire European Alps. Multiple linear regressions were performed between AFLP allele frequencies per site as dependent variables and two categories of independent variables, namely Moran's eigenvector map MEM variables (to account for spatial and unaccounted environmental variation, and historical demographic processes) and environmental variables. These associations allowed the identification of 153 loci of ecological relevance. Univariate regressions between allele frequency and each environmental factor further showed that loci of ecological relevance were mainly correlated with MEM variables. We found that precipitation and temperature were the best environmental predictors, whereas topographic factors were rarely involved in environmental associations. Climatic factors, subject to rapid variation as a result of the current global warming, are known to strongly influence the fate of alpine plants. Our study shows, for the first time for a large number of species, that the same environmental variables are drivers of plant adaptation at the scale of a whole biome, here the European Alps.

Natural genetic variation in Arabidopsis: tools, traits and prospects for evolutionary ecology.

BACKGROUND: The model plant Arabidopsis thaliana (Arabidopsis) shows a wide range of genetic and trait variation among wild accessions. Because of its unparalleled biological and genomic resources, the potential of Arabidopsis for molecular genetic analysis of this natural variation has increased dramatically in recent years. SCOPE: Advanced genomics has accelerated molecular phylogenetic analysis and gene identification by quantitative trait loci (QTL) mapping and/or association mapping in Arabidopsis. In particular, QTL mapping utilizing natural accessions is now becoming a major strategy of gene isolation, offering an alternative to artificial mutant lines. Furthermore, the genomic information is used by researchers to uncover the signature of natural selection acting on the genes that contribute to phenotypic variation. The evolutionary significance of such genes has been evaluated in traits such as disease resistance and flowering time. However, although molecular hallmarks of selection have been found for the genes in question, a corresponding ecological scenario of adaptive evolution has been difficult to prove. Ecological strategies, including reciprocal transplant experiments and competition experiments, and utilizing near-isogenic lines of alleles of interest will be a powerful tool to measure the relative fitness of phenotypic and/or allelic variants. CONCLUSIONS: As the plant model organism, Arabidopsis provides a wealth of molecular background information for evolutionary genetics. Because genetic diversity between and within Arabidopsis populations is much higher than anticipated, combining this background information with ecological approaches might well establish Arabidopsis as a model organism for plant evolutionary ecology.

Le financement de la haute technologie dans le système de santé : le cas de la pharmacogénomique

L’exercice d’allocation de ressources en santé, relevant du Ministère de la santé, se voit fortement influencé autant par les besoins variés de la population que par les exigences des intervenants en santé. Quel rôle ces différents intérêts peuvent-ils jouer dans l’intégration de nouvelles technologies dans la distribution des soins de santé ? La pharmacogénomique, branche émergente de la pharmacologie intégrant les données issues du projet génome humain au processus de développement du médicament, est perçue comme une technologie qui permettrait de personnaliser la médecine. Son intégration aux processus de développement ou de prescription de médicaments promet de minimiser l’apparition d’effets secondaires néfastes découlant de la prise de médicaments. Serait-il alors judicieux pour le gouvernement du Québec, considérant la conjoncture actuelle d’allocation de ressources, d’investir dans la pharmacogénomique en tant que nouvel outil de développement du médicament ou nouveau mode pronostic de médication pour sa population ? Nous aborderons cette question à l’aide de critères de sélection dictés par Caulfield et ses collaborateurs (2001)[1] pour évaluer la pertinence de l’investissement public dans la mise sur pied d’un test génétique, soit l’acceptabilité, l’utilité, la non-malfaisance et la présence d’un bénéfice clair – à coût raisonnable – pour la population. La génomique avoisinant la génétique, ces facteurs s’avèrent applicables dans notre discussion.

Protein Microarray: "Theory" to "Real Practice"

Fueled by ever-growing genomic information and rapid developments of proteomics–the large scale analysis of proteins and mapping its functional role has become one of the most important disciplines for characterizing complex cell function. For building functional linkages between the biomolecules, and for providing insight into the mechanisms of biological processes, last decade witnessed the exploration of combinatorial and chip technology for the detection of bimolecules in a high throughput and spatially addressable fashion. Among the various techniques developed, the protein chip technology has been rapid. Recently we demonstrated a new platform called “Spacially addressable protein array” (SAPA) to profile the ligand receptor interactions. To optimize the platform, the present study investigated various parameters such as the surface chemistry and role of additives for achieving high density and high-throughput detection with minimal nonspecific protein adsorption. In summary the present poster will address some of the critical challenges in protein micro array technology and the process of fine tuning to achieve the optimum system for solving real biological problems.

Origin of avian genome size and structure in non-avian dinosaurs

Avian genomes are small and streamlined compared with those of other amniotes by virtue of having fewer repetitive elements and less non-coding DNA(1,2). This condition has been suggested to represent a key adaptation for flight in birds, by reducing the metabolic costs associated with having large genome and cell sizes(3,4). However, the evolution of genome architecture in birds, or any other lineage, is difficult to study because genomic information is often absent for long-extinct relatives. Here we use a novel bayesian comparative method to show that bone-cell size correlates well with genome size in extant vertebrates, and hence use this relationship to estimate the genome sizes of 31 species of extinct dinosaur, including several species of extinct birds. Our results indicate that the small genomes typically associated with avian flight evolved in the saurischian dinosaur lineage between 230 and 250 million years ago, long before this lineage gave rise to the first birds. By comparison, ornithischian dinosaurs are inferred to have had much larger genomes, which were probably typical for ancestral Dinosauria. Using comparative genomic data, we estimate that genome-wide interspersed mobile elements, a class of repetitive DNA, comprised 5 - 12% of the total genome size in the saurischian dinosaur lineage, but was 7 - 19% of total genome size in ornithischian dinosaurs, suggesting that repetitive elements became less active in the saurischian lineage. These genomic characteristics should be added to the list of attributes previously considered avian but now thought to have arisen in non-avian dinosaurs, such as feathers(5), pulmonary innovations 6, and parental care and nesting

Grid warehousing of molecular dynamics protein unfolding data

With the increasing awareness of protein folding disorders, the explosion of genomic information, and the need for efficient ways to predict protein structure, protein folding and unfolding has become a central issue in molecular sciences research. Molecular dynamics computer simulations are increasingly employed to understand the folding and unfolding of proteins. Running protein unfolding simulations is computationally expensive and finding ways to enhance performance is a grid issue on its own. However, more and more groups run such simulations and generate a myriad of data, which raises new challenges in managing and analyzing these data. Because the vast range of proteins researchers want to study and simulate, the computational effort needed to generate data, the large data volumes involved, and the different types of analyses scientists need to perform, it is desirable to provide a public repository allowing researchers to pool and share protein unfolding data. This paper describes efforts to provide a grid-enabled data warehouse for protein unfolding data. We outline the challenge and present first results in the design and implementation of the data warehouse.

Use of synteny to identify candidate genes underlying QTL controlling stomatal traits in faba bean (Vicia faba L.)

Key message We have identified QTLs for stomatal characteristics on chromosome II of faba bean by applying SNPs derived from M. truncatula , and have identified candidate genes within these QTLs using synteny between the two species. Abstract Faba bean (Vicia faba L.) is a valuable food and feed crop worldwide, but drought often limits its production, and its genome is large and poorly mapped. No information is available on the effects of genomic regions and genes on drought adaptation characters such as stomatal characteristics in this species, but the synteny between the sequenced model legume, Medicago truncatula, and faba bean can be used to identify candidate genes. A mapping population of 211 F5 recombinant inbred lines (Mélodie/2 × ILB 938/2) were phenotyped to identify quantitative trait loci (QTL) affecting stomatal morphology and function, along with seed weight, under well-watered conditions in a climate-controlled glasshouse in 2013 and 2014. Canopy temperature (CT) was evaluated in 2013 under water-deficit (CTd). In total, 188 polymorphic single nucleotide polymorphisms (SNPs), developed from M. truncatula genome data, were assigned to nine linkage groups that covered ~928 cM of the faba bean genome with an average inter-marker distance of 5.8 cM. 15 putative QTLs were detected, of which eight (affecting stomatal density, length and conductance and CT) co-located on chromosome II, in the vicinity of a possible candidate gene—a receptor-like protein kinase found in the syntenic interval of M. truncatula chromosome IV. A ribose-phosphate pyrophosphokinase from M. truncatula chromosome V, postulated as a possible candidate gene for the QTL for CTd, was found some distance away in the same chromosome. These results demonstrate that genomic information from M. truncatula can successfully be translated to the faba bean genome.

Label-free enrichment of avian Leucocytozoon using flow cytometric sorting

The group of haemosporidian parasites is of general interest to basic and applied science, since several species infect mammals, leading to malaria and associated disease symptoms. Although the great majority of haemosporidian parasites appear in bird hosts, as in the case of Leucocytozoon buteonis, there is little genomic information about genetic aspects of their co-evolution with hosts. Consequently, there is a high need for parasite-enrichment strategies enabling further analyses of the genomes, namely without exposure to DNA-intercalating dyes. Here, we used flow cytometry without an additional labelling step to enrich L. buteonis from infected buzzard blood. A specific, defined area of two-dimensional scattergramms was sorted and the fraction was further analysed. The successful enrichment of L. buteonis in the sorted fraction was demonstrated by Giemsa-staining and qPCR revealing a clear increase of parasite-specific genes, while host-specific genes were significantly decreased. This is the first report describing a labelling-free enrichment approach of L. buteonis from infected buzzard blood. The enrichment of parasites presented here is free of nucleic acid-intercalating dyes which may interfere with fluorescence-based methods or subsequent sequencing approaches.

How reliable is internet-based self-reported identity, socio-demographic and obesity measures in European adults?

In e-health intervention studies, there are concerns about the reliability of internet-based, self-reported (SR) data and about the potential for identity fraud. This study introduced and tested a novel procedure for assessing the validity of internet-based, SR identity and validated anthropometric and demographic data via measurements performed face-to-face in a validation study (VS). Participants (n = 140) from seven European countries, participating in the Food4Me intervention study which aimed to test the efficacy of personalised nutrition approaches delivered via the internet, were invited to take part in the VS. Participants visited a research centre in each country within 2 weeks of providing SR data via the internet. Participants received detailed instructions on how to perform each measurement. Individual’s identity was checked visually and by repeated collection and analysis of buccal cell DNA for 33 genetic variants. Validation of identity using genomic information showed perfect concordance between SR and VS. Similar results were found for demographic data (age and sex verification). We observed strong intra-class correlation coefficients between SR and VS for anthropometric data (height 0.990, weight 0.994 and BMI 0.983). However, internet-based SR weight was under-reported (Δ −0.70 kg [−3.6 to 2.1], p < 0.0001) and, therefore, BMI was lower for SR data (Δ −0.29 kg m−2 [−1.5 to 1.0], p < 0.0001). BMI classification was correct in 93 % of cases. We demonstrate the utility of genotype information for detection of possible identity fraud in e-health studies and confirm the reliability of internet-based, SR anthropometric and demographic data collected in the Food4Me study.

Implementation of DNA markers to produce genomically - Enhanced EPDs in nellore cattle

Background: The sequencing and publication of the cattle genome and the identification of single nucleotide polymorphism (SNP) molecular markers have provided new tools for animal genetic evaluation and genomic-enhanced selection. These new tools aim to increase the accuracy and scope of selection while decreasing generation interval. The objective of this study was to evaluate the enhancement of accuracy caused by the use of genomic information (Clarifide® - Pfizer) on genetic evaluation of Brazilian Nellore cattle. Review: The application of genome-wide association studies (GWAS) is recognized as one of the most practical approaches to modern genetic improvement. Genomic selection is perhaps most suited to the improvement of traits with low heritability in zebu cattle. The primary interest in livestock genomics has been to estimate the effects of all the markers on the chip, conduct cross-validation to determine accuracy, and apply the resulting information in GWAS either alone [9] or in combination with bull test and pedigree-based genetic evaluation data. The cost of SNP50K genotyping however limits the commercial application of GWAS based on all the SNPs on the chip. However, reasonable predictability and accuracy can be achieved in GWAS by using an assay that contains an optimally selected predictive subset of markers, as opposed to all the SNPs on the chip. The best way to integrate genomic information into genetic improvement programs is to have it included in traditional genetic evaluations. This approach combines traditional expected progeny differences based on phenotype and pedigree with the genomic breeding values based on the markers. Including the different sources of information into a multiple trait genetic evaluation model, for within breed dairy cattle selection, is working with excellent results. However, given the wide genetic diversity of zebu breeds, the high-density panel used for genomic selection in dairy cattle (Ilumina Bovine SNP50 array) appears insufficient for across-breed genomic predictions and selection in beef cattle. Today there is only one breed-specific targeted SNP panel and genomic predictions developed using animals across the entire population of the Nellore breed (www.pfizersaudeanimal.com), which enables genomically - enhanced selection. Genomic profiles are a way to enhance our current selection tools to achieve more accurate predictions for younger animals. Material and Methods: We analyzed the age at first calving (AFC), accumulated productivity (ACP), stayability (STAY) and heifer pregnancy at 30 months (HP30) in Nellore cattle fitting two different animal models; 1) a traditional single trait model, and 2) a two-trait model where the genomic breeding value or molecular value prediction (MVP) was included as a correlated trait. All mixed model analyses were performed using the statistical software ASREML 3.0. Results: Genetic correlation estimates between AFC, ACP, STAY, HP30 and respective MVPs ranged from 0.29 to 0.46. Results also showed an increase of 56%, 36%, 62% and 19% in estimated accuracy of AFC, ACP, STAY and HP30 when MVP information was included in the animal model. Conclusion: Depending upon the trait, integration of MVP information into genetic evaluation resulted in increased accuracy of 19% to 62% as compared to accuracy from traditional genetic evaluation. GE-EPD will be an effective tool to enable faster genetic improvement through more dependable selection of young animals.

Genome-wide association analysis of feed intake and residual feed intake in Nellore cattle

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Efeito da utilização de diferentes matrizes genômicas e parentesco na avaliação genética de bovinos de corte

Pós-graduação em Genética e Melhoramento Animal - FCAV

Análise da heterocedasticidade em bubalinos utilizando informações genômicas

Pós-graduação em Genética e Melhoramento Animal - FCAV

Building the sugarcane genome for biotechnology and identifying evolutionary trends

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)