Gene prediction

Structure of a eukaryotic gene

In computational biology, gene prediction or gene finding refers to the process of identifying the regions of genomic DNA that encode genes. This includes protein-coding genes as well as RNA genes, but may also include prediction of other functional elements such as regulatory regions. Gene finding is one of the first and most important steps in understanding the genome of a species once it has been sequenced.

In its earliest days, "gene finding" was based on painstaking experimentation on living cells and organisms. Statistical analysis of the rates of homologous recombination of several different genes could determine their order on a certain chromosome, and information from many such experiments could be combined to create a genetic map specifying the rough location of known genes relative to each other. Today, with comprehensive genome sequence and powerful computational resources at the disposal of the research community, gene finding has been redefined as a largely computational problem.

Determining that a sequence is functional should be distinguished from determining the function of the gene or its product. Predicting the function of a gene and confirming that the gene prediction is accurate still demands in vivo experimentation[1] through gene knockout and other assays, although frontiers of bioinformatics research [2] are making it increasingly possible to predict the function of a gene based on its sequence alone.

Gene prediction is one of the key steps in genome annotation, following sequence assembly, the filtering of non-coding regions and repeat masking.[3]

Gene prediction is closely related to the so-called 'target search problem' investigating how DNA-binding proteins (transcription factors) locate specific binding sites within the genome.[4][5] Many aspects of structural gene prediction are based on current understanding of underlying biochemical processes in the cell such as gene transcription, translation, protein–protein interactions and regulation processes, which are subject of active research in the various omics fields such as transcriptomics, proteomics, metabolomics, and more generally structural and functional genomics.

  1. ^ Sleator RD (August 2010). "An overview of the current status of eukaryote gene prediction strategies". Gene. 461 (1–2): 1–4. doi:10.1016/j.gene.2010.04.008. PMID 20430068.
  2. ^ Ejigu, Girum Fitihamlak; Jung, Jaehee (2020-09-18). "Review on the Computational Genome Annotation of Sequences Obtained by Next-Generation Sequencing". Biology. 9 (9): 295. doi:10.3390/biology9090295. ISSN 2079-7737. PMC 7565776. PMID 32962098.
  3. ^ Yandell M, Ence D (April 2012). "A beginner's guide to eukaryotic genome annotation". Nature Reviews. Genetics. 13 (5): 329–42. doi:10.1038/nrg3174. PMID 22510764. S2CID 3352427.
  4. ^ Redding S, Greene EC (May 2013). "How do proteins locate specific targets in DNA?". Chemical Physics Letters. 570: 1–11. Bibcode:2013CPL...570....1R. doi:10.1016/j.cplett.2013.03.035. PMC 3810971. PMID 24187380.
  5. ^ Sokolov IM, Metzler R, Pant K, Williams MC (August 2005). "Target search of N sliding proteins on a DNA". Biophysical Journal. 89 (2): 895–902. Bibcode:2005BpJ....89..895S. doi:10.1529/biophysj.104.057612. PMC 1366639. PMID 15908574.