An improved pig reference genome sequence to enable pig genetics and genomics research.

Background: The domestic pig (Sus scrofa) is important both as a food source and as a biomedical model given its similarity in size, anatomy, physiology, metabolism, pathology, and pharmacology to humans. The draft reference genome (Sscrofa10.2) of a purebred Duroc female pig established using older clone-based sequencing methods was incomplete, and unresolved redundancies, short-range order and orientation errors, and associated misassembled genes limited its utility.

Next-Generation Sequencing of Haematococcus lacustris Reveals an Extremely Large 1.35-Megabase Chloroplast Genome.

is an industrially relevant microalga that is used for the production of the carotenoid astaxanthin. Here, we report the use of PacBio long-read sequencing to assemble the chloroplast genome of strain UTEX:2505. At 1.

Complete Genome Sequence of the Model Oleaginous Alga CCMP1894.

The model oleaginous alga was completely sequenced using a combination of optical mapping and next-generation sequencing technologies to generate one of the most complete eukaryotic genomes published to date. The assembled genome is 30.7 Mb long.

Lipid production in Nannochloropsis gaditana is doubled by decreasing expression of a single transcriptional regulator.

Lipid production in the industrial microalga Nannochloropsis gaditana exceeds that of model algal species and can be maximized by nutrient starvation in batch culture. However, starvation halts growth, thereby decreasing productivity. Efforts to engineer N.

Phylogenetic Distribution of CRISPR-Cas Systems in Antibiotic-Resistant Pseudomonas aeruginosa.

Unlabelled: Pseudomonas aeruginosa is an antibiotic-refractory pathogen with a large genome and extensive genotypic diversity. Historically, P. aeruginosa has been a major model system for understanding the molecular mechanisms underlying type I clustered regularly interspaced short palindromic repeat (CRISPR) and CRISPR-associated protein (CRISPR-Cas)-based bacterial immune system function.

The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line.

Using deep sequencing (deepCAGE), the FANTOM4 study measured the genome-wide dynamics of transcription-start-site usage in the human monocytic cell line THP-1 throughout a time course of growth arrest and differentiation. Modeling the expression dynamics in terms of predicted cis-regulatory sites, we identified the key transcription regulators, their time-dependent activities and target genes. Systematic siRNA knockdown of 52 transcription factors confirmed the roles of individual factors in the regulatory network.

Cost-effective strategies for completing the interactome.

Comprehensive protein-interaction mapping projects are underway for many model species and humans. A key step in these projects is estimating the time, cost and personnel required for obtaining an accurate and complete map. Here we modeled the cost of interaction-map completion for various experimental designs.

Analyses of deep mammalian sequence alignments and constraint predictions for 1% of the human genome.

A key component of the ongoing ENCODE project involves rigorous comparative sequence analyses for the initially targeted 1% of the human genome. Here, we present orthologous sequence generation, alignment, and evolutionary constraint analyses of 23 mammalian species for all ENCODE targets. Alignments were generated using four different methods; comparisons of these methods reveal large-scale consistency but substantial differences in terms of small genomic rearrangements, sensitivity (sequence coverage), and specificity (alignment accuracy).

Multiple alignment by sequence annealing.

Motivation: We introduce a novel approach to multiple alignment that is based on an algorithm for rapidly checking whether single matches are consistent with a partial multiple alignment. This leads to a sequence annealing algorithm, which is an incremental method for building multiple sequence alignments one match at a time. Our approach improves significantly on the standard progressive alignment approach to multiple alignment.

Tools for loading MEDLINE into a local relational database.

Background: Researchers who use MEDLINE for text mining, information extraction, or natural language processing may benefit from having a copy of MEDLINE that they can manage locally. The National Library of Medicine (NLM) distributes MEDLINE in eXtensible Markup Language (XML)-formatted text files, but it is difficult to query MEDLINE in that format. We have developed software tools to parse the MEDLINE data files and load their contents into a relational database.

A simple algorithm for identifying abbreviation definitions in biomedical text.

The volume of biomedical text is growing at a fast rate, creating challenges for humans and computer systems alike. One of these challenges arises from the frequent use of novel abbreviations in these texts, thus requiring that biomedical lexical ontologies be continually updated. In this paper we show that the problem of identifying abbreviations' definitions can be solved with a much simpler algorithm than that proposed by other research efforts.