emiRIT: a text-mining-based resource for microRNA information.

microRNAs (miRNAs) are essential gene regulators, and their dysregulation often leads to diseases. Easy access to miRNA information is crucial for interpreting generated experimental data, connecting facts across publications and developing new hypotheses built on previous knowledge. Here, we present extracting miRNA Information from Text (emiRIT), a text-miningbased resource, which presents miRNA information mined from the literature through a user-friendly interface. We collected 149 ,233 miRNA -PubMed ID pairs from Medline between January 1997 and May 2020. emiRIT currently contains 'miRNA -gene regulation' (69 ,152 relations), 'miRNA disease (cancer)' (12 ,300 relations), 'miRNA -biological process and pathways' (23, 390 relations) and circulatory 'miRNAs in extracellular locations' (3782 relations). Biological entities and their relation to miRNAs were extracted from Medline abstracts using publicly available and in-house developed text-mining tools, and the entities were normalized to facilitate querying and integration. We built a database and an interface to store and access the integrated data, respectively. We provide an up-to-date and user-friendly resource to facilitate access to comprehensive miRNA information from the literature on a large scale, enabling users to navigate through different roles of miRNA and examine them in a context specific to their information needs. To assess our resource's information coverage, we have conducted two case studies focusing on the target and differential expression information of miRNAs in the context of cancer and a third case study to assess the usage of emiRIT in the curation of miRNA information. Database URL: https://research.bioinformatics.udel.edu/emirit/.

Full gene HLA class I sequences of 79 novel and 519 mostly uncommon alleles from a large United States registry population.

HLA class I assignments were obtained at single genotype, G-level resolution from 98 855 volunteers for an unrelated donor registry in the United States. In spite of the diverse ancestry of the volunteers, over 99% of the assignments at each locus are common. Within this population, 52 novel alleles differing in exons 2 and 3 are identified and characterized. Previously reported alleles with incomplete sequences in the IPD-IMGT/HLA database (n = 519) were selected for full gene sequencing and, from this sampling, another 27 novel alleles are described.

[Genetic diversity of Pseudosciaena polyactis in Zhoushan based on mitochondrial DNA D-loop region sequences].

Pseudosciaena polyactis is an economically important species of marine fish in China that is currently declining due to overexploitation, environmental pollution and related factors. Research in to the genetic structure of Pseudosciaena polyactis populations plays a key role in protecting and promoting sustainable utilization. We collected 53 individuals of Pseudosciaena polyactis from Zhoushan, Zhejiang and sequenced and amplified the mitochondrial DNA (mtDNA) D-loop region using Polymerase Chain Reactions (PCR). The sequence length of the 53 individuals ranged from 795 to 801 bp. The sequences were analyzed by Clustal X1.83, MEGA3.1 and DnaSP4.0. The results showed that the average base content of T, C, A, G was 30.3%, 23.1%, 32.3% and 14.3%, respectively and there were 93 transition or transversion sites, including 53 single nucleotide mutation sites and 40 parsimony informative sites, which accounted for 11.6% of the length of the analyzed sequences. In total, we identified 52 haplotypes and found haplotype diversity (hd) of 0.9993, average number of nucleotide differences were 9.73875 (k), and nucleotide diversity (Π) of 0.01233. The average genetic distance of haplotypes was 0.012, and the average transition/transversion was 4.305. Based on mitochondrial DNA D-loop region sequences, these results indicate that the genetic diversity of the Pseudosciaena polyactis population in Zhoushan is currently at a medium level.