Notes

Utilization of infographics as being a health-related expertise translation tool: method to get a scoping review.
MicroRNAs (miRNAs) and RNA-binding proteins (RBPs) regulate gene expression at the post-transcriptional level, but the extent to which these key regulators of gene expression coordinate their activities and the precise mechanisms of this coordination are not well understood. RBPs often have recognizable RNA binding domains that correlate with specific protein function. Recently, several RBPs containing K homology (KH) RNA binding domains were shown to work with miRNAs to regulate gene expression, raising the possibility that KH domains may be important for coordinating with miRNA pathways in gene expression regulation. To ascertain whether additional KH domain proteins functionally interact with miRNAs during Caenorhabditis elegans development, we knocked down twenty-four genes encoding KH-domain proteins in several miRNA sensitized genetic backgrounds. Here, we report that a majority of the KH domain-containing genes genetically interact with multiple miRNAs and Argonaute alg-1. Interestingly, two KH domain genes, predicted splicing factors sfa-1 and asd-2, genetically interacted with all of the miRNA mutants tested, whereas other KH domain genes showed genetic interactions only with specific miRNAs. Our domain architecture and phylogenetic relationship analyses of the C. elegans KH domain-containing proteins revealed potential groups that may share both structure and function. Collectively, we show that many C. elegans KH domain RBPs functionally interact with miRNAs, suggesting direct or indirect coordination between these two classes of post-transcriptional gene expression regulators.Several Candida species can undergo a heritable and reversible transition from a 'white' state to a mating proficient 'opaque' state. This ability relies on highly interconnected transcriptional networks that control cell-type-specific gene expression programs over multiple generations. Candida albicans, the most prominent pathogenic Candida species, provides a well-studied paradigm for the white-opaque transition. In this species, a network of at least eight transcriptional regulators controls the balance between white and opaque states that have distinct morphologies, transcriptional profiles, and physiological properties. Given the reversible nature and the high frequency of white-opaque transitions, it is widely assumed that this switch is governed by epigenetic mechanisms that occur independently of any changes in DNA sequence. However, a direct genomic comparison between white and opaque cells has yet to be performed. Here, we present a whole-genome comparative analysis of C. albicans white and opaque cells. This analysis revealed rare genetic changes between cell states, none of which are linked to white-opaque switching. This result is consistent with epigenetic mechanisms controlling cell state differentiation in C. albicans and provides direct evidence against a role for genetic variation in mediating the switch.Evaluating the quality of a de novo annotation of a complex fungal genome based on RNA-seq data remains a challenge. In this study, we sequentially optimized a Cufflinks-CodingQuary-based bioinformatics pipeline fed with RNA-seq data using the manually annotated model pathogenic yeasts Cryptococcus neoformans and Cryptococcus deneoformans as test cases. Our results show that the quality of the annotation is sensitive to the quantity of RNA-seq data used and that the best quality is obtained with 5-10 million reads per RNA-seq replicate. We also showed that the number of introns predicted is an excellent a priori indicator of the quality of the final de novo annotation. We then used this pipeline to annotate the genome of the RNAi-deficient species Cryptococcus deuterogattii strain R265 using RNA-seq data. Dynamic transcriptome analysis revealed that intron retention is more prominent in C. deuterogattii than in the other RNAi-proficient species C. neoformans and C. deneoformans. In contrast, we observed that antisense transcription was not higher in C. deuterogattii than in the two other Cryptococcus species. Comparative gene content analysis identified 21 clusters enriched in transcription factors and transporters that have been lost. Interestingly, analysis of the subtelomeric regions in these three annotated species identified a similar gene enrichment, reminiscent of the structure of primary metabolic clusters. Our data suggest that there is active exchange between subtelomeric regions, and that other chromosomal regions might participate in adaptive diversification of Cryptococcus metabolite assimilation potential.While maize with anthocyanin-rich pericarp (purple corn) is rising in popularity as a source of natural colorant for foods and beverages, information on color range and stability-factors associated with anthocyanin decorations and compositional profiles-is currently limited. Furthermore, to maximize the scalability and meet growing demands, both anthocyanin concentrations and agronomic performance must improve in purple corn varieties. Bevacizumab research buy Using the natural anthocyanin diversity present in a purple corn landrace, Apache Red, we generated a population with variable flavonoid profiles-flavanol-anthocyanin condensed forms (0-83%), acylated anthocyanins (2-72%), pelargonidin-derived anthocyanins (5-99%), C-glycosyl flavone co-pigments up to 1904 µg/g, and with anthocyanin content up to 1598 µg/g. Each aspect of the flavonoid profiles was found to play a role in either the resulting extract hue or intensity. With genotyping-by-sequencing of this population, we mapped aspects of the flavonoid profile. Major quantitativmining anthocyanin profile in pericarp.Polyploidy poses several problems for parentage analysis. We present a new polysomic inheritance model for parentage analysis based on genotypes or allelic phenotypes to solve these problems. The effects of five factors are simultaneously accommodated in this model (1) double-reduction, (2) null alleles, (3) negative amplification, (4) genotyping errors and (5) self-fertilization. To solve genotyping ambiguity (unknown allele dosage), we developed a new method to establish the likelihood formulas for allelic phenotype data and to simultaneously include the effects of our five chosen factors. We then evaluated and compared the performance of our new method with three established methods by using both simulated data and empirical data from the cultivated blueberry (Vaccinium corymbosum). We also developed and compared the performance of two additional estimators to estimate the genotyping error rate and the sample rate. We make our new methods freely available in the software package polygene, at http//github.com/huangkang1987/polygene.
Here's my website: https://www.selleckchem.com/products/bevacizumab.html