DNA annotation or genome annotation is the process of identifying the genes positions and all of the coding regions in a genome and assign functions to these genes.
Current eukaryotic genome annotations require various, abundant supporting data, such as species-specific and cross-species protein sequences, ESTs, cDNA and RNA-Seq data. Collecting such data sets and merging their analytical results to achieve a consistent complete annotation is a complex, time and cost consuming task.

• Custom Bioinformatics Data analysis
• Writing code or scripts for your project
• On premise or cloud optimal infrastructure for your institute
• Long term contracts for bioinformatics analysis

Here is a list of popular annotation tools available.

It predicts genes in bacteria, Archaea, metagenomes, metatranscriptomes, Eukaryotes, Viruses, phages and plasmids.
Novel genomes can be analyzed by the program GeneMark-ES utilizing unsupervised training. Note that GeneMark-ES has a special mode for analyzing fungal genomes. A semi-supervised version of GeneMark-ES, called GeneMark-ET uses RNA-Seq reads to improve training. For several species pre-trained model parameters are read QUAST —A quality assessment tool for evaluating and comparing genome assemblies. This tool improves on leading assembly comparison software with new ideas and quality metrics. QUAST can evaluate assemblies both with a reference genome, as well as without a reference. QUAST produces many reports, summary tables and plots to help scientists in their research and in their publications.
— using GeneMarkS. [2]
http://bioinf.spbau.ru/quast.
MetAMOS: MetAMOS, an open source and modular metagenomic assembly and analysis pipeline. MetAMOS represents an important step towards fully automated metagenomic analysis, starting with next-generation sequencing reads and producing genomic scaffolds, open-reading frames and taxonomic or functional annotations. MetAMOS can aid in reducing assembly errors, commonly encountered when assembling metagenomic samples, and improves taxonomic assignment accuracy while also reducing computational cost.
— using MetaGeneMark
https://github.com/treangen/MetAMOS.

Overview of the eukaryotic annotation process [1]

Gene prediction accuracy of BRAKER 1 and MAKER 2

AUGUSTUS
AUGUSTUS, a software for gene prediction in eukaryotic genomic sequences that is based on a generalized hidden Markov model, a probabilisticmodel of a sequence and its gene structure. The web server allows the user to impose constraints on the predicted gene structure. A constraint can specify the position of a splice site, a translation initiation site or a stop codon. Furthermore, it is possible to specify the position of known exons and intervals that are known to be exonic or intronic sequence. The number of constraints is arbitrary and constraints can be combined in order to pin down larger parts of the predicted gene structure.[4]
The web interface and the downloadable stand-alone program are available free of charge at
http://augustus.gobics.de/submission

mGene

mGene is a computational tool for the genome-wide prediction of protein coding genes from eukaryotic DNA sequences. It is based on recent advances in machine learning and uses discriminative training techniques, such as support vector machines (SVMs) and hidden semi-Markov support vector machines (HSMSVMs). Its excellent performance was proved in an objective competition based on the genome of the nematode Caenorhabditis elegans. The evaluated developmental version of mGene exhibited the best prediction performance (in terms of the average between sensitivity and specificity) for the multiple-genome prediction tasks on all four evaluation levels.[5]
Download is available at

http://mgene.org/download

PASA
PASA was originally developed at The Institute for Genomic Research in 2002 as an effort to automatically improve gene structures in Arabidopsis thaliana. Since then, it has been applied to numerous Eukaryotic genome annotation projects including Rice, Aspergillus species, Plasmodium falciparum, Schistosoma mansoni, Aedes aegypti, mouse, human, among others.

Functions of PASA include:

• • model complete and partial gene structures based on assembled spliced alignments.
  • automatically incorporate gene structures based on transcript alignments into existing gene structure annotations, thereby maintaining annotations consistent with experimental evidence. Annotation updates include
    • annotating untranslated regions (UTRs)
    • exon additions, deletions, boundary adjustments
    • addition of models for alternative splicing variants
    • merging genes
    • splitting genes
    • modeling novel genes
    • map polyadenylation sites to the genome
    • identify antisense transcripts
    • identify and classify all found splicing variations
    • report a likely set of partial and/or full-length protein-coding genes based on transcript alignments for training ab initio gene prediction tools.[11]

PASA can be obtained as:

https://pasapipeline.github.io/#A_obt_pasa

Ensemble

Ensembl is a genome browser for vertebrate genomes that supports research in comparative genomics, evolution, sequence variation and transcriptional regulation. Ensembl annotate genes, computes multiple alignments, predicts regulatory function and collects disease data. Ensembl tools include BLAST, BLAT, BioMart and the Variant Effect Predictor (VEP) for all supported species.[12]

Ensemble can be obtained as:

http://www.ensembl.org/downloads.html

GenScan

Identification of complete gene structures in genomic DNA[13]. It is online available at the following link:

http://genes.mit.edu/GENSCAN.html

 References

• • 1. The NCBI Eukaryotic Genome Annotation Pipeline. https://www.ncbi.nlm.nih.gov/genome/annotation_euk/process/
    2. QUAST: quality assessment tool for genome assemblies. Alexey Gurevich1,*, Vladislav Saveliev1 , Nikolay Vyahhi1 and Glenn Tesler2
    3. BRAKER1: Unsupervised RNA-Seq-Based Genome Annotation with GeneMark-ET and AUGUSTU. Katharina J. Hoff 1∗ , Simone Lange 1 , Alexandre Lomsadze 3 , Mark Borodovsky 2,3,4∗ and Mario Stanke 1
    4. AUGUSTUS: a web server for gene prediction in eukaryotes that allows user-defined constraints. Mario Stanke* and Burkhard Morgenstern
    5. mGene: Accurate SVM-based gene finding with an application to nematode genomes. Gabriele Schweikert,1,2,3 Alexander Zien,1,4,5 Georg Zeller,1,3,5 Jonas Behr,1 Christoph Dieterich,3,6 Cheng Soon Ong,1,2,7 Petra Philips,1 Fabio De Bona,1 Lisa Hartmann,1 Anja Bohlen,1 Nina Kru¨ger,1 So¨ren Sonnenburg,4,1 and Gunnar Ra¨tsch1,8
    6. http://www.softberry.com/berry.phtml?topic=fgenesh&group=help&subgroup=gfind
    7. https://blast.ncbi.nlm.nih.gov/Blast.cgi
    8. https://en.wikipedia.org/wiki/BLAT_(bioinformatics)
    9. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Cole Trapnell, Adam Roberts, Loyal Goff, Geo Pertea, Daehwan Kim, David R Kelley, lHarold Pimente, Steven L Salzberg, John L Rinn, Lior Pachter
    10. De novo transcript sequence reconstruction from RNA-Seq: reference generation and analysis with Trinity. Brian J. Haas#1,#, Alexie Papanicolaou#2, Moran Yassour1,3, Manfred Grabherr4, Philip D. Blood5, Joshua Bowden6, Matthew Brian Couger7, David Eccles8, Bo Li9, Matthias Lieber10, Matthew D. MacManes11, Michael Ott2, Joshua Orvis12, Nathalie Pochet1,13, Francesco Strozzi14, Nathan Weeks15, Rick Westerman16, Thomas William17, Colin N. Dewey9,18, Robert Henschel19, Richard D. LeDuc19, Nir Friedman3, and Aviv Regev1,20,#
    11. https://pasapipeline.github.io/
    12. http://www.ensembl.org/index.html

http://genes.mit.edu/GENSCAN.html