Mathiesenzacho0665

We also demonstrate how computational modeling can help the experimental determination of RNA structure. #link# We highlight the recent advances in computational modeling which can offer reliable structure models using high-throughput experimental data.Pseudotaxus chienii (Taxaceae) is an endangered conifer species endemic to China. However, a lack of suitable molecular markers hinders the genomic and genetic studies on this species. Here, this website characterized and developed the microsatellite markers from a newly sequenced P. chienii transcriptome. A total of 21,835 microsatellite loci were detected from 161,131 non-redundant unigene sequences, and the frequency of SSRs was 13.55%, with an average of one SSR loci per 9.18 kb. Mono-nucleotide, di-nucleotide, and tri-nucleotide were the dominant repeat types, accounting for 50.06, 13.49, and 29.39% of the total SSRs, respectively. In terms of distribution location, the coding regions (CDS) with few microsatellites and mainly consisted of tri-nucleotides. There were significant differences in the length of microsatellite among genic regions and motif types. Functional annotation showed that the unigenes containing microsatellites had a wide range of biological functions, most of which were related to basic metabolism, and a few might be involved in expression regulation of gene and response to environmental stress. In addition, 375 primer pairs were randomly selected and synthesized for the amplification and validation of microsatellite markers. Seventy-seven primer pairs were successfully amplified and 40 primer pairs were found to be polymorphic. Finally, 20 pairs of primers with high polymorphism were selected to assess the genetic diversity in four P. chienii populations. In addition, the newly developed microsatellite markers exhibited high transferability (70%) in Amentotaxus argotaenia. Our study could enable further genetic diversity analysis and functional gene mining on Taxaceae.Transmembrane channel-like (TMC) genes encode a family of evolutionarily conserved membrane proteins. Mutations in the TMC1 and TMC2 cause deafness in humans and mice. However, their functions in insects are is still not well known. Here we cloned three tmc genes, Nltmc3, Nltmc5, and Nltmc7 from brown planthoppers. The predicted amino acid sequences showed high identity with other species homologs and have the characteristic eight or nine transmembrane domains and TMC domain architecture. We detected these three genes in all developmental stages and examined tissues. Interestingly, we found Nltmc3 was highly expressed in the female reproductive organ especially in the oviduct. RNAi-mediated silencing of Nltmc3 substantially decreased the egg-laying number and impaired ovary development. Our results indicate that Nltmc3 has an essential role in the ovary development of brown planthoppers.Motivation At present, a number of correlation analysis methods between SNPs and ROIs have been devised to explore the pathogenic mechanism of Alzheimer's disease. However, some of the deficiencies inherent in these methods, including lack of statistical efficacy and biological meaning. This study aims at addressing issues insufficient correlation by previous methods (relative high regression error) and the lack of biological meaning in association analysis. Results In this paper, a novel three-stage SNPs and ROIs correlation analysis framework is proposed. Firstly, clustering algorithm is applied to remove the potential linkage unbalanced structure of two SNPs. Then, the group sparse model is used to introduce prior information such as gene structure and linkage unbalanced structure to select feature SNPs. After the above steps, each SNP has a weight vector corresponding to each ROI, and the importance of SNPs can be judged according to the weights in the feature vector, and then the feature SNPs can be selected. Finally, for the selected feature SNPS, a support vector machine regression model is used to implement the prediction of the ROIs phenotype values. The experimental results under multiple performance measures show that the proposed method has better accuracy than other methods.Nitrite is a major environmental toxin in aquaculture systems that disrupts multiple physiological functions in aquatic animals. Although nitrite tolerance in shrimp is closely related to successful industrial production, few genetic studies of this trait are available. In this study, we constructed a high-density genetic map of Litopenaeus vannamei with 17,242 single nucleotide polymorphism markers spanning 6,828.06 centimorgans (cM), with an average distance of 0.4 cM between adjacent markers on 44 linkage groups (LGs). Using this genetic map, we identified two markers associated with nitrite tolerance. We then sequenced the transcriptomes of the most nitrite-tolerant and nitrite-sensitive individuals from each of four genetically distinct L. vannamei families (LV-I-4). We found 2,002, 1,983, 1,954, and 1,867 differentially expressed genes in families LV-1, LV-2, LV-3, and LV-4, respectively. By integrating QTL and transcriptomics analyses, we identified a candidate gene associated with nitrite tolerance. This gene was annotated as solute carrier family 26 member 6 (SLC26A6). RNA interference (RNAi) analysis demonstrated that SLC26A6 was critical for nitrite tolerance in L. vannamei. The present study increases our understanding of the molecular mechanisms underlying nitrite tolerance in shrimp and provides a basis for molecular-marker-assisted shrimp breeding.High-density single-nucleotide polymorphism (SNP) genotyping array is an essential tool for genetic analyses of animals and plants. Large yellow croaker (Larimichthys crocea) is one of the most commercially important marine fish species in China. Although plenty of SNPs have been identified in large yellow croaker, no high-throughput genotyping array is available. In this study, a high-throughput SNP array named NingXin-I with 600K SNPs was developed and evaluated. A set of 82 large yellow croakers were collected from different locations of China and re-sequenced. A total of 9.34M SNPs were identified by mapping sequence reads to the large yellow croaker reference genome. About 1.98M candidate SNPs were selected for further analyses by using criteria such as SNP quality score and conversion performance in the final array. Finally, 579.5K SNPs evenly distributed across the large yellow croaker genome with an average spacing of 1.19 kb were proceeded to array production. The performance of NingXin-I array was evaluated in 96 large yellow croaker individuals from five populations, and 83.