![]() ![]() One straightforward way of closing gaps is conducting wet lab experiments, that is, primer walking and Sanger sequencing. A complete genome is thus preferred or even required in a study. The presence of gaps often leads to errors in gene finding, annotation, and functional studies. Both of these scenarios result in underrepresentation of the affected sequences in the data set, and therefore, leave gaps. For example, some regions of the genome are inherently prone to physical degradation while some others are resistant to amplification due to secondary structures. ![]() Between them, the nature of DNA is more critical. Besides the limitations of assembling software, two other factors can lead to gaps: the nature of DNA templates and sequencing errors. CLC GENOMICS WORKBENCH ASSEMBLY SOFTWAREAs a consequence, despite the sheer volume of sequencing data and the highly sophisticated software dedicated to handling these types of data, gaps are commonly found in draft assemblies. In addition, software and hardware environment can also play a role. Nevertheless, no method is all-purpose, and the effectiveness of a method is often subject to constraints, such as genome size as well as the quality, length, and abundance of the reads. Methods for alignment and assembly and evaluations have also been developed. In recent years, encouraging progress has been made in de novo sequencing for both small (for example, bacteria ) and large (for example, mammalian ) genomes. A standard Illumina sequencing operation can easily generate enough data to cover the genome of a bacterium more than 100 times, which often results in a near-complete genome assembly in a single attempt. ![]() This is especially true for bacteria, whose genomes are typically less than 10 million base pairs (Mb). Next-generation sequencing technologies produce massive amount of data at greatly reduced costs, making it possible to routinely sequence the genomes of various organisms. The constituting principles and methods are applicable to similar studies on both prokaryotic and eukaryotic genomes. It highlights the complementary roles that in silico and wet lab methodologies play in bioinformatical studies. The developed pipeline provides an example of effective integration of computational and biological principles. The application of the pipeline is demonstrated by the completion of a bacterial genome, Thermotoga sp. It combines the strengths of de novo assembly, reference-based assembly, customized programming, public databases utilization, and wet lab experimentation. The pipeline alternates the employment of computational and biological methods in seven steps. The input of the pipeline is paired-end Illumina sequence reads, and the output is a high quality complete genome sequence. ResultsĪ pipeline was developed to assemble complete genomes primarily from the next generation sequencing (NGS) data. This study aims to identify a practical approach for biologists to complete their own genome assemblies using commonly available tools and resources. CLC GENOMICS WORKBENCH ASSEMBLY FULLThe existence of gaps compromises our ability to take full advantage of the genome data. Despite the large volume of genome sequencing data produced by next-generation sequencing technologies and the highly sophisticated software dedicated to handling these types of data, gaps are commonly found in draft genome assemblies. ![]()
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