In vivo selection of engineered homing endonucleases using double-strand break induced homologous recombination

Homing endonucleases, endonucleases capable of recognizing long DNA sequences, have been shown to be a tool of choice for precise and efficient genome engineering. Consequently, the possibility to engineer novel endonucleases with tailored specificities is under strong investigation. In this report, we present a simple and efficient method to select meganucleases from libraries of variants, based on their cleavage properties. The method has the advantage of directly selecting for the ability to induce double-strand break induced homologous recombination in a eukaryotic environment. Model selections demonstrated high levels of enrichments. Moreover, this method compared favorably with phage display for enrichment of active mutants from a mutant library. This approach makes possible the exploration of large sequence spaces and thereby represents a valuable tool for genome engineering

The epigenomic landscape of African rainforest hunter-gatherers and farmers

International audienceThe genetic history of African populations is increasingly well documented, yet their patterns of epigenomic variation remain uncharacterized. Moreover, the relative impacts of DNA sequence variation and temporal changes in lifestyle and habitat on the human epigenome remain unknown. Here we generate genome-wide genotype and DNA methylation profiles for 362 rainforest hunter-gatherers and sedentary farmers. We find that the current habitat and historical lifestyle of a population have similarly critical impacts on the methylome, but the biological functions affected strongly differ. Specifically, methylation variation associated with recent changes in habitat mostly concerns immune and cellular functions, whereas that associated with historical lifestyle affects developmental processes. Furthermore, methylation variation—particularly that correlated with historical lifestyle—shows strong associations with nearby genetic variants that, moreover, are enriched in signals of natural selection. Our work provides new insight into the genetic and environmental factors affecting the epigenomic landscape of human populations over time

Genomewide and biochemical analyses of DNA-binding activity of Cdc6/Orc1 and Mcm proteins in Pyrococcus sp.

The origin of DNA replication (oriC) of the hyperthermophilic archaeon Pyrococcus abyssi contains multiple ORB and mini-ORB repeats that show sequence similarities to other archaeal ORB (origin recognition box). We report here that the binding of Cdc6/Orc1 to a 5 kb region containing oriC in vivo was highly specific both in exponential and stationary phases, by means of chromatin immunoprecipitation coupled with hybridization on a whole genome microarray (ChIP-chip). The oriC region is practically the sole binding site for the Cdc6/Orc1, thereby distinguishing oriC in the 1.8 M bp genome. We found that the 5 kb region contains a previously unnoticed cluster of ORB and mini-ORB repeats in the gene encoding the small subunit (dp1) for DNA polymerase II (PolD). ChIP and the gel retardation analyses further revealed that Cdc6/Orc1 specifically binds both of the ORB clusters in oriC and dp1. The organization of the ORB clusters in the dp1 and oriC is conserved during evolution in the order Thermococcales, suggesting a role in the initiation of DNA replication. Our ChIP-chip analysis also revealed that Mcm alters the binding specificity to the oriC region according to the growth phase, consistent with its role as a licensing factor

Blacklisting variants common in private cohorts but not in public databases optimizes human exome analysis

Computational analyses of human patient exomes aim to filter out as many nonpathogenic genetic variants (NPVs) as possible, without removing the true disease-causing mutations. This involves comparing the patient's exome with public databases to remove reported variants inconsistent with disease prevalence, mode of inheritance, or clinical penetrance. However, variants frequent in a given exome cohort, but absent or rare in public databases, have also been reported and treated as NPVs, without rigorous exploration. We report the generation of a blacklist of variants frequent within an in-house cohort of 3,104 exomes. This blacklist did not remove known pathogenic mutations from the exomes of 129 patients and decreased the number of NPVs remaining in the 3,104 individual exomes by a median of 62%. We validated this approach by testing three other independent cohorts of 400, 902, and 3,869 exomes. The blacklist generated from any given cohort removed a substantial proportion of NPVs (11-65%). We analyzed the blacklisted variants computationally and experimentally. Most of the blacklisted variants corresponded to false signals generated by incomplete reference genome assembly, location in low-complexity regions, bioinformatic misprocessing, or limitations inherent to cohort-specific private alleles (e.g., due to sequencing kits, and genetic ancestries). Finally, we provide our precalculated blacklists, together with ReFiNE, a program for generating customized blacklists from any medium-sized or large in-house cohort of exome (or other next-generation sequencing) data via a user-friendly public web server. This work demonstrates the power of extracting variant blacklists from private databases as a specific in-house but broadly applicable tool for optimizing exome analysis

Multiangle Light Scattering and Viscometric Detector for Size-Exclusion Chromatography

A new miniaturised Light Scattering (LS) apparatus coupled with a capillary viscometer has been developed which analyses sequentially small size fractions of eluent (1 cm$^3$). The apparatus can be used in an autonomous manner in order to obtain the weight-average molar mass ($M_{\rm w}$), the $z$-average radius of gyration ($R_{\rm g}$), the second virial coefficient ($A_2$), the intrinsic viscosity ([ $\eta$] ) and the Huggins constant ($k$) by analysing a given polymer sample at different concentrations. The device can be coupled to a standard Size-Exclusion Chromatography chain in which the detector not only provides mean values, but also the evolution of [ $\eta$] , $M_{\rm w}$ and $R_{\rm g}$. as a function of elution volume ($V_{\rm e}$). Specific calibration curves ($\log(M_{\rm w}) = f (V_{\rm e})$) can be constructed for any sample, and then be used without the combined detector. In this way the molecular weight dependence of [ $\eta$] and $R_{\rm g}$ is readily obtained. Moreover, the special design of the detector allows simple collection of fractions. A number of problems which need to be solved in order to allow an efficient use of the detector are discussed. Results on polystyrene standards illustrate the good performance of the apparatus

Comparison of roughness models to simulate overland flow and tracer transport experiments under simulated rainfall at the plot scale.

International audienceThe Saint-Venant equations have consistently proved capable of accurately simulating hydrographs at plot scale. However, recent works showed that even though the hydrograph is satisfyingly reproduced, the flow velocity field within the plot might be wrong, with the highest velocity largely underestimated. Moreover, the choice of roughness models to be used in the Saint-Venant equations is most often done in the purpose of increasing the hydrograph quality, while the actual travel time of water is ignored. This paper presents a tracer experiment made on a 10-m by 4-m rainfall simulation plot, where travel time and tracer mass recovery as well as local flow velocity have been measured. Four roughness models are tested: (i) Darcy-Weisbach's model, (ii) Lawrence's model, (iii) Manning's model with a constant roughness coefficient, and (iv) Manning's model with a variable roughness coefficient which decreases as a power law of the runoff water depth. Models with a constant friction factor largely underestimate high velocities. Moreover, they are not able to simulate tracer travel-times. Lawrence's model correctly simulates low and high velocities as well as tracer breakthrough curves. However, a specific set of parameters are required for each breakthrough curve from the same experiment. The best results are obtained with the Manning's model with a water-depth dependent roughness coefficient: simulated velocities are consistent with measurements, and a single set of parameters captures the entire set of breakthrough curves, as well as tracer mass recovery. The study reported here brings the following findings: (i) roughness coefficient is flow-dependent, (ii) faithful simulation of the velocity fields does not imply a good prediction of travel time and mass recovery, (iii) the best model is a Manning type model with a roughness coefficient which decreases as a power law of water depth. The full dataset used in this work is available on request. It can be used as benchmark for overland flow and transport models

Corrélations entre les paramètres biologiques et la composition corporelle dans la sclérose latérale amyotrophique

International audienceIntroduction et but de l’étudeAu cours de la sclérose latérale amyotrophique (SLA), la composition corporelle par impédancemétrie bioélectrique (BIA) ainsi que des paramètres biochimiques tels que la ferritine ou les marqueurs du bilan lipidique peuvent être associés à l’évolution et à la survie. Le but de notre travail était de déterminer la variation des paramètres biologiques, de BIA et cliniques au cours de la maladie, ainsi que le lien des données biologiques avec la BIA et les données cliniques.Matériel et méthodesLes données biologiques (albumine, lipides sériques, ferritine), la composition corporelle par BIA [masse maigre (MM), eau corporelle totale (ECT), eau intracellulaire (EIC)] et les données cliniques [poids, indice de masse corporelle (IMC), le score de l’ALS functional rating scale revised (ALSFRS-R) et la capacité vitale forcée (CVF)] des patients SLA ont été recueillies tous les 3 mois au cours des 12 mois (T1 à T4) suivant le diagnostic. Le test de Freidman a été utilisé pour étudier l’évolution des données au cours des quatre évaluations. Le test de Wilcoxon a été effectué pour comparer l’évolution des données entre la première évaluation (T1) et la dernière évaluation (T4). Le test de Spearman a été réalisé pour rechercher des corrélations des données biologiques avec la BIA et les données cliniques.Résultats et analyse statistiqueUn total de 42 patients atteints de SLA certaine ou probable, selon les critères de l’El Escorial révisés, ont été inclus dans cette étude. L’âge médian était de 70,7 ans (62,7–78,8) au moment du diagnostic. Le sex H/F ratio était de 1 et le site de début bulbaire dans 26,8 % des cas. Pendant le suivi, seul l’IMC a évolué au cours des quatre évaluations (p = 0,009). L’IMC, le score de l’ALSFRS-R et de la CVF ont diminué de manière significative (p = 0,01, p = 0,006, p < 0,0001 et p < 0,0001, respectivement) entre T1 à T4. La composition corporelle et les paramètres biologiques n’ont pas évolué pas au cours du suivi. Une corrélation positive entre les variations de l’albumine et de l’ALSFRS-R était observée (r = 0,48, p = 0,04). Plusieurs corrélations positives entre les variations du LDL-cholestérol et du poids, de la MM, de l’ECT et de l’EIC ont été observées (r = 0,46, p = 0,007 ; r = 0,53, p = 0,002 ; r = 0,51, p = 0,003 et r = 0,60, p = 0,004, respectivement). Des corrélations négatives ont aussi été retrouvées entre les variations de ferritine et de poids, de la MM, de l’ECT et de l’EIC (r = − 0,49, p = 0,002 ; r = − 0,58, p = 0,0002 ; r = − 0,51, p = 0,001 et r = − 0,53. p = 0,008, respectivement).ConclusionCette première étude permet d’objectiver des relations entre les biomarqueurs biochimiques, la composition corporelle et les données cliniques sur cette maladie. L’albumine pourrait permettre de suivre l’évolution fonctionnelle des patients atteints de SLA. La BIA peut donc constituer un outil précieux associé au bilan biologique pour la prise en charge nutritionnelle des patients atteints de SLA. Une confirmation sur une plus grande cohorte est nécessaire pour la confirmation de ces résultats

Ferritin and LDL-cholesterol as biomarkers of fat-free mass loss in ALS

International audienceThe availability of longitudinal clinical and biological data led us to wonder whether these parameters could be used to predict disturbances in body composition during ALS progression. Bioelectrical impedance analysis (BIA), as well as clinical and biological parameters (blood lipids and ferritin), were collected one year after diagnosis in ALS patients. The correlations were evaluated by the Spearman test. Performances to predict the evolution of BIA parameters during ALS evolution were evaluated by ROC analysis. Forty-two ALS patients were enrolled. Variations in FFM over one year were correlated to the variations in LDL-cholesterol (r = 0.53, p = 0.002) and ferritin (r = -0.58, p = 0.0002). To predict FFM loss, an increase in ferritin over 9 µg/L had a sensitivity of 90.0% and a specificity of 80.0% (p < 0.0001). Ferritine evolution would allow to easily follow the FFM without BIA during ALS. In addition, an adapted nutritional treatment based on this biological parameter might slow down ALS progression