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Related Concept Videos

Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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Eukaryotes have large genomes compared to prokaryotes. To fit their genomes into a cell, eukaryotic DNA is packaged extraordinarily tightly inside the nucleus. To achieve this, DNA is tightly wound around proteins called histones, which are packaged into nucleosomes that are joined by linker DNA and coil into chromatin fibers. Additional fibrous proteins further compact the chromatin, which is recognizable as chromosomes during certain phases of cell division.
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Rapid Amplification of cDNA Ends, or RACE, is one of the most effective methods to obtain a full-length cDNA from an mRNA sequence between a known internal region to the unknown sequence at the 5’ or 3’ end. The unknown region is cloned in the cDNA by a gene-specific primer that binds the known end, and a hybrid primer that attaches a predefined anchor sequence to the unknown end of the cDNA. The sequence in between is amplified by PCR with an anchor primer and a gene-specific...
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Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
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Related Experiment Video

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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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Biomartr: genomic data retrieval with R.

Hajk-Georg Drost, Jerzy Paszkowski

    Bioinformatics (Oxford, England)
    |January 23, 2017
    PubMed
    Summary

    The biomartr R package simplifies genomic data retrieval and functional annotation for metagenomics. It enhances analysis transparency and reproducibility, crucial for biological research.

    Area of Science:

    • Bioinformatics
    • Computational Biology
    • Genomics

    Background:

    • Reproducible retrieval and functional annotation of genomic data are essential in biological research.
    • Current methods often lack usability and transparency, hindering reproducibility.
    • Metagenomic approaches require efficient and reliable data handling frameworks.

    Purpose of the Study:

    • To present biomartr, an open-source R package for automating genomic data retrieval and functional annotation.
    • To provide a user-friendly framework that enhances clarity, transparency, and reproducibility in metagenomic analyses.
    • To facilitate the integration of data from major bioinformatics databases.

    Main Methods:

    • The biomartr package offers functions for bulk retrieval of genomic data, including genomes, proteomes, coding sequences, and annotation files.

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  • It interfaces with the National Center for Biotechnology Information (NCBI) and European Bioinformatics Institute (EMBL-EBI) databases.
  • The package utilizes the BioMart database for functional annotation of retrieved sequences.

    • Main Results:

    • biomartr provides straightforward functions for accessing comprehensive genomic datasets.
    • The package ensures high transparency and reproducibility in data retrieval and annotation processes.
    • Detailed documentation and tutorial vignettes guide users through reproducible analyses.

    Conclusions:

    • biomartr offers a robust and accessible solution for genomic data management in metagenomics.
    • The package significantly improves the usability and transparency of data retrieval and functional annotation.
    • It empowers researchers to conduct more reproducible and reliable biological analyses.