Restriction site-associated DNA sequencing, genotyping error estimation and de novo assembly optimization for population genetic inference.

Restriction site-associated DNA sequencing (RADseq) provides researchers with the ability to record genetic polymorphism across thousands of loci for nonmodel organisms, potentially revolutionizing the field of molecular ecology. However, as with other genotyping methods, RADseq is prone to a number of sources of error that may have consequential effects for population genetic inferences, and these have received only limited attention in terms of the estimation and reporting of genotyping error rates. Here we use individual sample replicates, under the expectation of identical genotypes, to quantify genotyping error in the absence of a reference genome. We then use sample replicates to (i) optimize de novo assembly parameters within the program Stacks, by minimizing error and maximizing the retrieval of informative loci; and (ii) quantify error rates for loci, alleles and single-nucleotide polymorphisms. As an empirical example, we use a double-digest RAD data set of a nonmodel plant species, Berberis alpina, collected from high-altitude mountains in Mexico.

Male dominance linked to size and age, but not to 'good genes' in brown trout (Salmo trutta).

BACKGROUND: Males that are successful in intra-sexual competition are often assumed to be of superior quality. In the mating system of most salmonid species, intensive dominance fights are common and the winners monopolise most mates and sire most offspring. We drew a random sample of mature male brown trout (Salmo trutta) from two wild populations and determined their dominance hierarchy or traits linked to dominance. The fish were then stripped and their sperm was used for in vitro fertilisations in two full-factorial breeding designs. We recorded embryo viability until hatching in both experiments, and juvenile survival during 20 months after release into a natural streamlet in the second experiment. Since offspring of brown trout get only genes from their fathers, we used offspring survival as a quality measure to test (i) whether males differ in their genetic quality, and if so, (ii) whether dominance or traits linked to dominance reveal 'good genes'. RESULTS: We found significant additive genetic variance on embryo survival, i.e. males differed in their genetic quality. Older, heavier and larger males were more successful in intra-sexual selection. However, neither dominance nor dominance indicators like body length, weight or age were significantly linked to genetic quality measured as embryo or juvenile survival. CONCLUSION: We found no evidence that females can improve their offspring's genetic viability by mating with large and dominant males. If there still were advantages of mating with dominant males, they may be linked to non-genetic benefits or to genetic advantages that are context dependent and therefore possibly not revealed under our experimental conditions - even if we found significant additive genetic variation for embryo viability under such conditions.

MR MAQ: algorisme de Read Mapping utilitzant la plataforma Hadoop

L’èxit del Projecte Genoma Humà (PGH) l’any 2000 va fer de la “medicina personalitzada” una realitat més propera. Els descobriments del PGH han simplificat les tècniques de seqüenciació de tal manera que actualment qualsevol persona pot aconseguir la seva seqüència d’ADN complerta. La tecnologia de Read Mapping destaca en aquest tipus de tècniques i es caracteritza per manegar una gran quantitat de dades. Hadoop, el framework d’Apache per aplicacions intensives de dades sota el paradigma Map Reduce, resulta un aliat perfecte per aquest tipus de tecnologia i ha sigut l’opció escollida per a realitzar aquest projecte. Durant tot el treball es realitza l’estudi, l’anàlisi i les experimentacions necessàries per aconseguir un Algorisme Genètic innovador que utilitzi tot el potencial de Hadoop.

Restriction site-associated DNA sequencing, genotyping error estimation and de novo assembly optimization for population genetic inference.

Restriction site-associated DNA sequencing (RADseq) provides researchers with the ability to record genetic polymorphism across thousands of loci for nonmodel organisms, potentially revolutionizing the field of molecular ecology. However, as with other genotyping methods, RADseq is prone to a number of sources of error that may have consequential effects for population genetic inferences, and these have received only limited attention in terms of the estimation and reporting of genotyping error rates. Here we use individual sample replicates, under the expectation of identical genotypes, to quantify genotyping error in the absence of a reference genome. We then use sample replicates to (i) optimize de novo assembly parameters within the program Stacks, by minimizing error and maximizing the retrieval of informative loci; and (ii) quantify error rates for loci, alleles and single-nucleotide polymorphisms. As an empirical example, we use a double-digest RAD data set of a nonmodel plant species, Berberis alpina, collected from high-altitude mountains in Mexico.

Programació d'aplicacions bioinformàtiques

Avui en dia la biologia aporta grans quantitats de dades que només la informàtica pot tractar. Les aplicacions bioinformàtiques són la més important eina d’anàlisi i comparació que tenim per entendre la vida i aconseguir desxifrar aquestes dades. Aquest projecte centra el seu esforç en l’estudi de les aplicacions dedicades a l’alineament de seqüències genètiques, i més concretament a dos algoritmes, basats en programació dinàmica i òptims: el Needleman&Wunsch i el Smith&Waterman. Amb l’objectiu de millorar el rendiment d’aquests algoritmes per a alineaments de seqüències grans, proposem diferents versions d’implementació. Busquem millorar rendiments en temps i espai. Per a aconseguir millorar els resultats aprofitem el paral·lelisme. Els resultats dels anàlisis de les versions els comparem per obtenir les dades necessàries per valorar cost, guany i rendiment.

Identifying genetic signatures of selection in a non-model species, alpine gentian (Gentiana nivalis L.), using a landscape genetic approach

It is generally accepted that most plant populations are locally adapted. Yet, understanding how environmental forces give rise to adaptive genetic variation is a challenge in conservation genetics and crucial to the preservation of species under rapidly changing climatic conditions. Environmental variation, phylogeographic history, and population demographic processes all contribute to spatially structured genetic variation, however few current models attempt to separate these confounding effects. To illustrate the benefits of using a spatially-explicit model for identifying potentially adaptive loci, we compared outlier locus detection methods with a recently-developed landscape genetic approach. We analyzed 157 loci from samples of the alpine herb Gentiana nivalis collected across the European Alps. Principle coordinates of neighbor matrices (PCNM), eigenvectors that quantify multi-scale spatial variation present in a data set, were incorporated into a landscape genetic approach relating AFLP frequencies with 23 environmental variables. Four major findings emerged. 1) Fifteen loci were significantly correlated with at least one predictor variable (R (adj) (2) > 0.5). 2) Models including PCNM variables identified eight more potentially adaptive loci than models run without spatial variables. 3) When compared to outlier detection methods, the landscape genetic approach detected four of the same loci plus 11 additional loci. 4) Temperature, precipitation, and solar radiation were the three major environmental factors driving potentially adaptive genetic variation in G. nivalis. Techniques presented in this paper offer an efficient method for identifying potentially adaptive genetic variation and associated environmental forces of selection, providing an important step forward for the conservation of non-model species under global change.

Genetic variability among populations of Lutzomyia (Psathyromyia) shannoni (Dyar 1929) (Diptera: Psychodidae: Phlebotominae) in Colombia

Polyacrylamide gel electrophoresis was used to elucidate genetic variation at 13 isozyme loci among forest populations of Lutzomyia shannoni from three widely separated locations in Colombia: Palambí (Nariño Department), Cimitarra (Santander Department) and Chinácota (Norte de Santander Department). These samples were compared with a laboratory colony originating from the Magdalena Valley in Central Colombia. The mean heterozygosity ranged from 16 to 22%, with 2.1 to 2.6 alleles detected per locus. Nei's genetic distances among populations were low, ranging from 0.011 to 0.049. The estimated number of migrants (Nm=3.8) based on Wright's F-Statistic, F ST, indicated low levels of gene flow among Lu. shannoni forest populations. This low level of migration indicates that the spread of stomatitis virus occurs via infected host, not by infected insect. In the colony sample of 79 individuals, the Gpi locus was homozygotic (0.62/0.62) in all females and heterozygotic (0.62/0.72) in all males. Although this phenomenon is probably a consequence of colonization, it indicates that Gpi is linked to a sex determining locus.

Genetic markers from Biomphalaria tenagophila (Gastropoda: Pulmonata: Planorbidae) obtained by the double stringency polymerase chain reaction technique

Biomphalaria tenagophila, one of the intermediate hosts of the trematoda Schistosoma mansoni, is a simultaneous hermafrodite snail species. In order to analyse the genetic structure of these populations, we performed a double-stringency PCR technique to obtain genetic markers with microsatellites and arbitrary primers in a single reaction.

Differentiation and genetic analysis of Rhodnius prolixus and Rhodnius colombiensis by rDNA and RAPD amplification

Domiciliated Rhodnius prolixus and sylvatic R. colombiensis were analyzed in order to confirm their genetic divergence and verify the risk that the latter represents in the domiciliation process, and to provide tools for identifying the sources of possible reinfestation by triatomines in human dwellings allowing control programs to be undertaken. Comparison of random amplified polymorphic DNA amplification patterns and cluster analysis suggests reproductive discontinuity between the two species. The calculated statistical F value of 0.24 and effective migration rate of 0.6 individuals per generation are insufficient to maintain genetic homogeneity between them and confirm the absence of present genetic flow. R. colombiensis presents higher intrapopulation variability. Polymerase chain reaction of ribosomal DNA supports these findings. The low genetic flow between the two species implies that R. colombiensis do not represent an epidemiological risk for the domiciliary transmission of Trypanosoma cruzi in the Tolima Department. The lower variability of the domiciliated R. prolixus could result in greater susceptibility to the use of pesticides in control programs.

Genetic epidemiology of fecal egg excretion during Schistosoma mansoni infection in an endemic area in Minas Gerais, Brazil

There is considerable variation in the level of fecal egg excretion during Schistosoma mansoni infections. Within a single endemic area, the distribution of egg counts is typically overdispersed, with the majority of eggs excreted coming from a minority of residents. The purpose of this study was to quantify the influence of genetic factors on patterns of fecal egg excretion in a rural study sample in Brazil. Individual fecal egg excretions, expressed in eggs per gram of feces, were determined by the Kato-Katz method on stool samples collected on three different days. Detailed genealogic information was gathered at the time of sampling, which allowed assignment of 461 individuals to 14 pedigrees containing between 3 and 422 individuals. Using a maximum likelihood variance decomposition approach, we performed quantitative genetic analyses to determine if genetic factors could partially account for the observed pattern of fecal egg excretion. The quantitative genetic analysis indicated that between 21-37% of the variation in S. mansoni egg counts was attributable to additive genetic factors and that shared environment, as assessed by common household, accounted for a further 12-21% of the observed variation. A maximum likelihood heritability (h²) estimate of 0.44 ± 0.14 (mean ± SE) was found for the 9,604 second- and higher-degree pairwise relationships in the study sample, which is consistent with the upper limit (37%) of the genetic factor determined in the variance decomposition analysis. These analyses point to the significant influence of additive host genes on the pattern of S. mansoni fecal egg excretion in this endemic area.

Biomphalaria tenagophila: dominant character of the resistance to Schistosoma mansoni in descendants of crossbreedings between resistant (Taim, RS) and susceptible (Joinville, SC) strains

The aim of the present work was to study parasitological, molecular, and genetic aspects in descendants of crossbreedings between a totally resistant Biomphalaria tenagophila strain (Taim, RS) and another one highly susceptible (Joinville, SC) to Schistosoma mansoni. Descendants F1 and F2 were submitted to S. mansoni infection (LE strain). The susceptibility rates for individuals from Group F1 were 0 to 0.6%, and from Group F2 was 7.2%. The susceptible individuals from Group F2 discharged a lower number of cercariae, when compared with the susceptible parental group, and in 2 out of 9 positive snails the cercarial elimination was discontinued. In order to identify genetic markers associated with resistance the genotype of parental snails and their offspring F1 and F2 were analyzed by means of the randomly amplified polymorphic DNA method. Nevertheless, it was not possible to detect any marker associated to resistance, but the results showed that in the mentioned species the resistance character is determined by two dominant genes.

Chagas disease in Mexico: an analysis of geographical distribution during the past 76 years - A review

Literature from 1928 through 2004 was compiled from different document sources published in Mexico or elsewhere. From these 907 publications, we found 19 different topics of Chagas disease study in Mexico. The publications were arranged by decade and also by state. This information was used to construct maps describing the distribution of Chagas disease according to different criteria: the disease, vectors, reservoirs, and strains. One of the major problems confronting study of this zoonotic disease is the great biodiversity of the vector species; there are 30 different species, with at least 10 playing a major role in human infection. The high variability of climates and biogeographic regions further complicate study and understanding of the dynamics of this disease in each region of the country. We used a desktop Genetic Algorithm for Rule-Set Prediction procedure to provide ecological models of organism niches, offering improved flexibility for choosing predictive environmental and ecological data. This approach may help to identify regions at risk of disease, plan vector-control programs, and explore parasitic reservoir association. With this collected information, we have constructed a data base: CHAGMEX, available online in html format.

An ecoregional classification for the state of Roraima, Brazil: the importance of landscape in malaria biology

Understanding the different background landscapes in which malaria transmission occurs is fundamental to understanding malaria epidemiology and to designing effective local malaria control programs. Geology, geomorphology, vegetation, climate, land use, and anopheline distribution were used as a basis for an ecological classification of the state of Roraima, Brazil, in the northern Amazon Basin, focused on the natural history of malaria and transmission. We used unsupervised maximum likelihood classification, principal components analysis, and weighted overlay with equal contribution analyses to fine-scale thematic maps that resulted in clustered regions. We used ecological niche modeling techniques to develop a fine-scale picture of malaria vector distributions in the state. Eight ecoregions were identified and malaria-related aspects are discussed based on this classification, including 5 types of dense tropical rain forest and 3 types of savannah. Ecoregions formed by dense tropical rain forest were named as montane (ecoregion I), submontane (II), plateau (III), lowland (IV), and alluvial (V). Ecoregions formed by savannah were divided into steppe (VI, campos de Roraima), savannah (VII, cerrado), and wetland (VIII, campinarana). Such ecoregional mappings are important tools in integrated malaria control programs that aim to identify specific characteristics of malaria transmission, classify transmission risk, and define priority areas and appropriate interventions. For some areas, extension of these approaches to still-finer resolutions will provide an improved picture of malaria transmission patterns.

Using 3D surface datasets to understand landslide evolution: From analogue models to real case study

Early detection of landslide surface deformation with 3D remote sensing techniques, as TLS, has become a great challenge during last decade. To improve our understanding of landslide deformation, a series of analogue simulation have been carried out on non-rigid bodies coupled with 3D digitizer. All these experiments have been carried out under controlled conditions, as water level and slope angle inclination. We were able to follow 3D surface deformation suffered by complex landslide bodies from precursory deformation still larger failures. These experiments were the basis for the development of a new algorithm for the quantification of surface deformation using automatic tracking method on discrete points of the slope surface. To validate the algorithm, comparisons were made between manually obtained results and algorithm surface displacement results. Outputs will help in understanding 3D deformation during pre-failure stages and failure mechanisms, which are fundamental aspects for future implementation of 3D remote sensing techniques in early warning systems.

Genetic diversity of Toscana virus

Distribution of Toscana virus (TOSV) is evolving with climate change, and pathogenicity may be higher in nonexposed populations outside areas of current prevalence (Mediterranean Basin). To characterize genetic diversity of TOSV, we determined the coding sequences of isolates from Spain and France. TOSV is more diverse than other well-studied phleboviruses (e.g.,Rift Valley fever virus).