Abstract
BackgroundAfter 10-year-use of AFLP (Amplified Fragment Length Polymorphism) technology for DNA fingerprinting and mRNA profiling, large repertories of genome- and transcriptome-derived sequences are available in public databases for model, crop and tree species. AFLP marker systems have been and are being extensively exploited for genome scanning and gene mapping, as well as cDNA-AFLP for transcriptome profiling and differentially expressed gene cloning. The evaluation, annotation and classification of genomic markers and expressed transcripts would be of great utility for both functional genomics and systems biology research in plants. This may be achieved by means of the Gene Ontology (GO), consisting in three structured vocabularies (i.e. ontologies) describing genes, transcripts and proteins of any organism in terms of their associated cellular component, biological process and molecular function in a species-independent manner. In this paper, the functional annotation of about 8,000 AFLP-derived ESTs retrieved in the NCBI databases was carried out by using GO terminology.ResultsDescriptive statistics on the type, size and nature of gene sequences obtained by means of AFLP technology were calculated. The gene products associated with mRNA transcripts were then classified according to the three main GO vocabularies. A comparison of the functional content of cDNA-AFLP records was also performed by splitting the sequence dataset into monocots and dicots and by comparing them to all annotated ESTs of Arabidopsis and rice, respectively. On the whole, the statistical parameters adopted for the in silico AFLP-derived transcriptome-anchored sequence analysis proved to be critical for obtaining reliable GO results. Such an exhaustive annotation may offer a suitable platform for functional genomics, particularly useful in non-model species.ConclusionReliable GO annotations of AFLP-derived sequences can be gathered through the optimization of the experimental steps and the statistical parameters adopted. The Blast2GO software was shown to represent a comprehensive bioinformatics solution for an annotation-based functional analysis. According to the whole set of GO annotations, the AFLP technology generates thorough information for angiosperm gene products and shares common features across angiosperm species and families. The utility of this technology for structural and functional genomics in plants can be implemented by serial annotation analyses of genome-anchored fragments and organ/tissue-specific repertories of transcriptome-derived fragments.
Highlights
After 10-year-use of AFLP (Amplified Fragment Length Polymorphism) technology for DNA fingerprinting and mRNA profiling, large repertories of genome- and transcriptome-derived sequences are available in public databases for model, crop and tree species
In the last ten years, the cDNA-AFLP mRNA profiling was largely adopted and considerable repertories of organ-specific and differentially expressed transcripts are available in public databases for model, crop and tree species
The evaluation, annotation and classification of AFLPderived sequences would become crucial for both functional genomics and systems biology research in plants
Summary
After 10-year-use of AFLP (Amplified Fragment Length Polymorphism) technology for DNA fingerprinting and mRNA profiling, large repertories of genome- and transcriptome-derived sequences are available in public databases for model, crop and tree species. The evaluation, annotation and classification of genomic markers and expressed transcripts would be of great utility for both functional genomics and systems biology research in plants This may be achieved by means of the Gene Ontology (GO), consisting in three structured vocabularies (i.e. ontologies) describing genes, transcripts and proteins of any organism in terms of their associated cellular component, biological process and molecular function in a speciesindependent manner. This, along with the availability of userfriendly bioinformatic tools, allows the feasible evaluation, functional annotation and classification of a high number of expressed sequences in a great variety of organisms Such characterization would be useful for functional genomics research in plants, in the emergent field of systems biology. Structured ontological terms can be adopted to query sequences and to describe genes and their products at different levels of knowledge and specificity [1]
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