Propensity weighted analysis of chemical venous thromboembolism prophylaxis agents in isolated severe traumatic brain injury: An EAST sponsored multicenter study.

Background: In patients with severe traumatic brain injury (TBI), clinicians must balance preventing venous thromboembolism (VTE) with the risk of intracranial hemorrhagic expansion (ICHE). We hypothesized that low molecular weight heparin (LMWH) would not increase risk of ICHE or VTE as compared to unfractionated heparin (UH) in patients with severe TBI.

Methods: Patients ≥ 18 years of age with isolated severe TBI (AIS ≥ 3), admitted to 24 level I and II trauma centers between January 1, 2014 to December 31, 2020 and who received subcutaneous UH and LMWH injections for chemical venous thromboembolism prophylaxis (VTEP) were included.

Predicting polymorphic EST-SSRs in silico.

The public availability of large quantities of gene sequence data provides a valuable resource of the mining of Simple Sequence Repeat (SSR) molecular genetic markers for genetic analysis. These markers are inexpensive, require minimal labour to produce and can frequently be associated with functionally annotated genes. This study presents the characterization of barley EST-SSRs and the identification of putative polymorphic SSRs from EST data.

Single nucleotide polymorphism discovery from wheat next-generation sequence data.

Single nucleotide polymorphisms (SNPs) are the most abundant type of molecular genetic marker and can be used for producing high-resolution genetic maps, marker-trait association studies and marker-assisted breeding. Large polyploid genomes such as wheat present a challenge for SNP discovery because of the potential presence of multiple homoeologs for each gene. AutoSNPdb has been successfully applied to identify SNPs from Sanger sequence data for several species, including barley, rice and Brassica, but the volume of data required to accurately call SNPs in the complex genome of wheat has prevented its application to this important crop.

Geneious Basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data.

Unlabelled: The two main functions of bioinformatics are the organization and analysis of biological data using computational resources. Geneious Basic has been designed to be an easy-to-use and flexible desktop software application framework for the organization and analysis of biological data, with a focus on molecular sequences and related data types. It integrates numerous industry-standard discovery analysis tools, with interactive visualizations to generate publication-ready images.

Bioinformatics tools and databases for analysis of next-generation sequence data.

Genome sequencing has been revolutionized by next-generation technologies, which can rapidly produce vast quantities of data at relatively low cost. With data production now no longer being limited, there is a huge challenge to analyse the data flood and interpret biological meaning. Bioinformatics scientists have risen to the challenge and a large number of software tools and databases have been produced and these continue to evolve with this rapidly advancing field.

WheatGenome.info: an integrated database and portal for wheat genome information.

Bread wheat (Triticum aestivum) is one of the most important crop plants, globally providing staple food for a large proportion of the human population. However, improvement of this crop has been limited due to its large and complex genome. Advances in genomics are supporting wheat crop improvement.

Sequencing and assembly of low copy and genic regions of isolated Triticum aestivum chromosome arm 7DS.

The genome of bread wheat (Triticum aestivum) is predicted to be greater than 16 Gbp in size and consist predominantly of repetitive elements, making the sequencing and assembly of this genome a major challenge. We have reduced genome sequence complexity by isolating chromosome arm 7DS and applied second-generation technology and appropriate algorithmic analysis to sequence and assemble low copy and genic regions of this chromosome arm. The assembly represents approximately 40% of the chromosome arm and all known 7DS genes.

Future tools for association mapping in crop plants.

Association mapping currently relies on the identification of genetic markers. Several technologies have been adopted for genetic marker analysis, with single nucleotide polymorphisms (SNPs) being the most popular where a reasonable quantity of genome sequence data are available. We describe several tools we have developed for the discovery, annotation, and visualization of molecular markers for association mapping.

Targeted identification of genomic regions using TAGdb.

Background: The introduction of second generation sequencing technology has enabled the cost effective sequencing of genomes and the identification of large numbers of genes and gene promoters. However, the assembly of DNA sequences to create a representation of the complete genome sequence remains costly, especially for the larger and more complex plant genomes.

Results: We have developed an online database, TAGdb, that enables researchers to identify paired read sequences that share identity with a submitted query sequence.

CMap3D: a 3D visualization tool for comparative genetic maps.

Unlabelled: Genetic linkage mapping enables the study of genome organization and the association of heritable traits with regions of sequenced genomes. Comparative genetic mapping is particularly powerful as it allows translation of information between related genomes and gives an insight into genome evolution. A common tool for the storage, comparison and visualization of genetic maps is CMap.

Single nucleotide polymorphism discovery in barley using autoSNPdb.

Molecular markers are used to provide the link between genotype and phenotype, for the production of molecular genetic maps and to assess genetic diversity within and between related species. Single nucleotide polymorphisms (SNPs) are the most abundant molecular genetic marker. SNPs can be identified in silico, but care must be taken to ensure that the identified SNPs reflect true genetic variation and are not a result of errors associated with DNA sequencing.

Discovering genetic polymorphisms in next-generation sequencing data.

The ongoing revolution in DNA sequencing technology now enables the reading of thousands of millions of nucleotide bases in a single instrument run. However, this data quantity is often compromised by poor confidence in the read quality. The identification of genetic polymorphisms from this data is therefore problematic and, combined with the vast quantity of data, poses a major bioinformatics challenge.

Genetic maps and the use of synteny.

Genetic linkage maps represent the order of known molecular genetic markers along a given chromosome for a given species. This provides an insight into the organisation of a plant genome. In comparative genomics, synteny is the preserved order of genes on chromosomes of related species which results from descent from a common ancestor.

AutoSNPdb: an annotated single nucleotide polymorphism database for crop plants.

Single nucleotide polymorphisms (SNPs) may be considered the ultimate genetic marker as they represent the finest resolution of a DNA sequence (a single nucleotide), are generally abundant in populations and have a low mutation rate. Analysis of assembled EST sequence data provides a cost-effective means to identify large numbers of SNPs associated with functional genes. We have developed an integrated SNP discovery pipeline, which identifies SNPs from assembled EST sequences.