Pixel-Bit

Resumen basado en el de la publicaciónEl guión cinematográfico ha sido tratado de formas muy diferentes a lo largo de la historia. Si bien, las primeras películas carecían de guión y eran producciones sencillas de argumento y con escasez de medios, con la llegada de Méliès al mundo del cine el tema de la planificación de la producción adquirió cierto relieve e importancia. Sirviéndose de técnicas teatrales creó escenarios, trucos, hizo uso de la iluminación artificial, y utilizó la cámara de forma parecida a como es usada en el siglo XX. Los medios cinematográficos, televisivo, videográfico y los avances de la tecnología electrónica audiovisual han generado una dinámica de la producción en constante evolución y sometida a una constante revisión de métodos y medios. Por lo tanto, en la planificación de guiones lo definitivo, no existe.ES

Construction and Analysis of High-Density Linkage Map Using High-Throughput Sequencing Data

<div><p>Linkage maps enable the study of important biological questions. The construction of high-density linkage maps appears more feasible since the advent of next-generation sequencing (NGS), which eases SNP discovery and high-throughput genotyping of large population. However, the marker number explosion and genotyping errors from NGS data challenge the computational efficiency and linkage map quality of linkage study methods. Here we report the HighMap method for constructing high-density linkage maps from NGS data. HighMap employs an iterative ordering and error correction strategy based on a k-nearest neighbor algorithm and a Monte Carlo multipoint maximum likelihood algorithm. Simulation study shows HighMap can create a linkage map with three times as many markers as ordering-only methods while offering more accurate marker orders and stable genetic distances. Using HighMap, we constructed a common carp linkage map with 10,004 markers. The singleton rate was less than one-ninth of that generated by JoinMap4.1. Its total map distance was 5,908 cM, consistent with reports on low-density maps. HighMap is an efficient method for constructing high-density, high-quality linkage maps from high-throughput population NGS data. It will facilitate genome assembling, comparative genomic analysis, and QTL studies. HighMap is available at <a href="http://highmap.biomarker.com.cn/" target="_blank">http://highmap.biomarker.com.cn/</a>.</p></div

Oxygen-Vacancy-Induced Built-In Electric Field across MoCo Dual-Atomic Site Catalyst for Promoting Hydrogen Spillover in Hydrocracking and Hydrodesulfurization

The design and construction of highly efficient catalytic active sites for promoting hydrogen spillover are of great significance for improving hydrocracking (HCK) and hydrodesulfurization (HDS) performance in slurry-phase hydrogenation of vacuum residue (VR) but are still challenging. Herein, we report a carbon-supported MoCo dual-atomic site catalyst (MoCo DAC/C) and propose an oxygen-vacancy-induced built-in electric field (BIEF) regulation mechanism for promoting hydrogen spillover in HCK and HDS. It was found that the coordination structure of the MoCo dual-atomic was reconstructed and formed O vacancies in situ during hydrogenation process. The formation of O vacancies not only provided macromolecular adsorption sites but also broke the electronic balance and formed a weak BIEF between the Mo and Co atoms. Meanwhile, H2 was activated at the Mo sites to form active hydrogen species. The formation of BIEF promoted the active hydrogen spillover from Mo to Co sites by a Mo–C–Co bridging bond, thus improving the hydrogenation performance greatly. In HCK of VR, the MoCo DAC/C demonstrates remarkable catalytic hydrogenation activity with TOFT calculated for total metals up to 0.77 s–1 (two times enhancement than that of Mo single atoms (SAs)/C), the per pass conversion of VR of 76 wt %, liquid product yield of 92 wt %, and coke content of only 0.55 wt %. It also shows robust HDS performance with dibenzothiophene (DBT) conversion of 70 wt %. Density functional theory reveals that the formation of the O vacancies leads to the discrepancy of Bader charge between Mo and Co atoms, and the resulting local electric field can favor the diffusion of the positively charged (+0.10 e−) H atom. This work proposes an oxygen-vacancy-induced BIEF regulation mechanism from an atomic scale for enhancing the catalytic reaction process by promoting hydrogen spillover, which provided novel insights for the design and development of high-performance hydrogenation catalysts

Modules of HighMap algorithm.

<p>A: The single-linkage clustering algorithm was used to partition the marker loci into linkage groups based on a pairwise modified independence LOD score for the recombination frequency. B and B': The ordering module combines Gibbs sampling, spatial sampling, and simulated annealing algorithm to order markers and estimate map distances. C: The error correction module identified singletons according to parental contribution of genotypes and eliminated them from the data using <i>k</i>-nearest neighbor algorithm. To order markers correctly, the processes of ordering and error correction were carried out iteratively. D: Heat maps and haplotype maps were constructed to evaluate map quality.</p

Capability of missing imputation and error correction of HighMap.

<p>Capability of missing imputation and error correction of HighMap.</p

SLAF-seq: An Efficient Method of Large-Scale <em>De Novo</em> SNP Discovery and Genotyping Using High-Throughput Sequencing

<div><p>Large-scale genotyping plays an important role in genetic association studies. It has provided new opportunities for gene discovery, especially when combined with high-throughput sequencing technologies. Here, we report an efficient solution for large-scale genotyping. We call it specific-locus amplified fragment sequencing (SLAF-seq). SLAF-seq technology has several distinguishing characteristics: i) deep sequencing to ensure genotyping accuracy; ii) reduced representation strategy to reduce sequencing costs; iii) pre-designed reduced representation scheme to optimize marker efficiency; and iv) double barcode system for large populations. In this study, we tested the efficiency of SLAF-seq on rice and soybean data. Both sets of results showed strong consistency between predicted and practical SLAFs and considerable genotyping accuracy. We also report the highest density genetic map yet created for any organism without a reference genome sequence, common carp in this case, using SLAF-seq data. We detected 50,530 high-quality SLAFs with 13,291 SNPs genotyped in 211 individual carp. The genetic map contained 5,885 markers with 0.68 cM intervals on average. A comparative genomics study between common carp genetic map and zebrafish genome sequence map showed high-quality SLAF-seq genotyping results. SLAF-seq provides a high-resolution strategy for large-scale genotyping and can be generally applicable to various species and populations.</p> </div

SLAF-seq data summary for common carp F1 population.

<p>SLAF-seq data summary for common carp F1 population.</p

Pilot SLAF-seq data analysis using rice and soybeans.

<p>(a)and(b) Insert size distribution of SLAFs. SLAF length was found to cluster tightly around a mean of 430 bp, with 85% of SLAFs in the centermost 50 bp. (c) and (d)Distribution of SLAFs on the chromosomes. SLAFs were evenly distributed on the chromosomes in rice and soybeans. The gap in the middle was caused by the absence of centromere sequences. (e)and(f) Customized SLAF density design. In the rice pilot case, the density was designed using 20 kb per SLAF. In soybeans, 40 kb per SLAF was used. Both rice and soybean pilot SLAF data were found to be consistent with theoretical predictions.</p

Pilot SLAF-seq data summary in rice and soybeans.

<p>Pilot SLAF-seq data summary in rice and soybeans.</p

Genotyping quality in common F1 population.

<p>The genotyping quality score was used to select qualified markers and individuals for subsequent analysis. This is a dynamic optimization process. We counted low-quality markers for each SLAF marker and for each individual, and deleted the worst marker or individual. We repeated this process, deleting an individual or a marker each time until the average genotyping quality score of all SLAF markers reached the cutoff value, which was 13. (a)Detailed genotyping quality of SLAF-seqdata. (b) Cumulative quality score distribution of 7559 markers in 166 individuals.</p