GRIL is a tool that automatically identifies collinear regions in bacterial-size genome sequences. GRIL uses three basic steps to identify and filter significant collinear regions. These regions then provide a basis for multiple genome alignment. The technique is especially useful for genome assembly. The application is, described in this article.
GRIL is a tool to automatically identify collinear regions in a set of bacterial-size genome sequences
Microbes with small genomes are a significant fraction of the biosphere and are of particular interest to researchers. The growing amount of data on these organisms requires complementary computational tools. The CoreGenesUniqueGenes tool finds a core set of genes that are, shared by two or five organisms. These core genes are likely to reflect similar niches or needs. The unique genes can then use in classification.
Genomic DNA is, fragmented into small fragments with an average length of two to five kb. DNA fragments are, often limited in length by shearing, which is a consequence of manipulation of the starting nucleic acid preparation. Shorter fragments may obtain using techniques that require more aliquots.
The annotation process results in a large amount of data. This information is, stored in a format called General Feature Format (GFF) file. For non-bioinformaticians, this format is difficult to read. Fortunately, there are tools for parsing GFF files. The GFFview web server parses this annotation information and generates a statistical description of six indices. It can also help evaluate the quality of a de novo assembled transcriptome.
Multiple displacement amplification is an effective technique for preparing these fragments. This method allows amplification products with dUTP or UTP substituted into specific points on each strand. This technique has the advantages and disadvantages of other enzymatic methods, such as the sensitivity of these methods to substrate concentrations and digestion time.
GRIL can use in a variety of situations. In some cases, a small number of genomic DNA sequences is sufficient to identify a heterozygous SNP in a bacterial genome. For example, the sequence of a single cell has an GC bias and amplification, but a small number of reads can lead to a confident heterozygous call.
GRIL can also use to identify specific sequences. Moreover, it can also be used for single nucleotide polymorphisms. In addition to identifying collinear regions, GRIL can be used to detect recombination events in genomic data.
Used to find maximal unique matches in a set of bacterial-size genome sequences
The genome sequence of M. tuberculosis is a large dataset that includes single-end and paired-end runs. The lengths of these sequences range from 51 to 108 bp. Unpaired data were, averaged at 26 k-mers, and paired-end data averaged at 35 k-mers. The dataset is, comprised of 171 genomes and labeled strains.
The GRIL method partitions M into collinear blocks called CB, where each block has its own weight (w(cb)). The length of a collinear block is defined by its length (SMi*L). In this method, overlapping matches are resolved in favor of the longer match.
This method identifies genes that are, highly conserved. The bacA gene is, conserved across 826 P. difficile genomes. The phyletic signature of these subclades can be seen by the SNP heatmap. The hpdBCA operon is, also highly conserved in the set.
Gril is a robust tool for finding maximal unique matches among bacterial-size genome sequences. It can perform complex analyses and has a high sensitivity rate. It also offers a flexible interactive visualization tool called Gingr. Gril is highly effective for high-quality genomes and has a favorable tradeoff between sensitivity and specificity. It is also cost-efficient for large strain collections.
The new algorithm has used to find multiple pairs of maximal unique matches in a set of microbial-size genome sequences. This method can use on a variety of genome sizes, and the current implementation is optimized for bacterial genomes. It requires 32 bytes for the reference genome construction, and 15 bp for the aligned genomes.
In a study of bacterial genomes, the algorithm is, compared with Mauve. Mauve shows better alignment accuracy than Shuffle-LAGAN, even at low substitution rates. It can also detect large-scale inversions and rearrangements. However, Mauve does not work well with large lineage-specific regions.
This method has applied to sequences of enterobacteria, which are, characterized by numerous horizontal transfers and genome rearrangements. However, these studies have been limited by the lack of effective tools to compare the large-scale evolutionary events that occur in these genomes. Because these events are, scattered throughout the genome, it is difficult to compare them.
Used to find collinear regions in a set of bacterial-size genome sequences
GRIL is a computer program for locating collinear regions in bacterial-size genome sequences. It relies on a three-step process to locate regions of high sequence identity. These regions are, filtered, based on user-specified criteria to identify significant collinear regions. GRIL is a powerful tool, used in genome analysis and multiple genome alignment. Several applications have developed on the basis of GRIL. Its web site includes a detailed description of its algorithms and an example of how to apply it to five genomes. It also includes a validation procedure to ensure that the results are accurate.
Using a set of genome sequences, Gril finds collinear regions by evaluating the extent of homology. To identify these regions, the algorithm first determines which region has the lowest identity. It then calculates the percent identity of each region in the collinear set. The identity value of each region is a legal number between 0 and 1, with 0.1 representing a minimum identity of 10%. Once the collinear set is, defined the program applies the filters in order.
Gril starts with an initial set of matching regions and represents them as connected blocks. These matches are, then partitioned into a minimum number of collinear blocks. Typically, each match contains identical-colored blocks. These are, then connected by connecting lines. Coalescence of adjacent collinear blocks may lead to elimination of a single or multiple breakpoints.
Mauve has used to align nine enterobacterial genomes and to find global rearrangement structures in three mammalian genomes. Results have shown that it is a robust method and consistently meets its accuracy goal of 98%.
Mauve is a fast genome alignment method that uses anchoring to determine the position of local collinear blocks. Mauve can also handle long genomes, as it can align genomes identically no matter the order of their inputs. In addition, Mauve can identify multi-MUMs and calculate a guide tree for progressive alignment. It can also identify unaligned regions of sequence that are lineage-specific.
Used to find unique matches in a set of bacterial-size genome sequences
GRIL is a program, used to identify unique matches in bacterial genome sequences. It uses 23-bp exact mers as seed matches. It also uses a generalized offset of 100000 to remove LCBs that span less than 10000 b.p. In this article, we describe how GRIL works and show how it is, used to identify enterobacterial genome sequences.
Gril is a fast and accurate method to find unique matches in a set of sequences of bacterial-size genomes. The method has been used in the field of genome analysis and bioinformatics. It has been successfully used to identify recurrent sequences, and it is particularly effective for identifying novel genes. It is also capable of analyzing genome sequences in a wide range of environments.
Single-stranded conformation polymorphism analysis (SSCP) is a popular microbial community analysis method. The technique provides a fast, easy, and inexpensive method of detecting genetic variation. It is also a powerful tool for microbial community diversity analysis. By analyzing PCR-amplified small-subunit rRNA gene sequences, SSCP can detect up to 80-90% of potential base exchanges.
