Pregled bibliografske jedinice broj: 796586
An effective approach for annotation of protein families with low sequence similarity and conserved motifs : identifying GDSL hydrolases across the plant kingdom
An effective approach for annotation of protein families with low sequence similarity and conserved motifs : identifying GDSL hydrolases across the plant kingdom // BMC bioinformatics, 17 (2016), 91-1 doi:10.1186/s12859-016-0919-7 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 796586 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
An effective approach for annotation of protein families with low sequence similarity and conserved motifs : identifying GDSL hydrolases across the plant kingdom
Autori
Vujaklija, Ivan ; Bielen, Ana ; Paradžik, Tina ; Biđin, Siniša ; Goldstein, Pavle ; Vujaklija, Dušica
Izvornik
BMC bioinformatics (1471-2105) 17
(2016);
91-1
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
motif-HMM ; annotation errors ; low sequence similarity ; GDSL family ; plant kingdom
Sažetak
The massive accumulation of protein sequences arising from the rapid development of high- throughput sequencing, coupled with automatic annotation, results in high levels of incorrect annotations. In this study, we describe an approach to decrease annotation errors of protein families characterized by low overall sequence similarity. The GDSL lipolytic family comprises proteins with multifunctional properties and high potential for pharmaceutical and industrial applications. The number of proteins assigned to this family has increased rapidly over the last few years. In particular, the natural abundance of GDSL enzymes reported recently in plants indicates that they could be a good source of novel GDSL enzymes. We noticed that a significant proportion of annotated sequences lack specific GDSL motif(s) or catalytic residue(s). Here, we applied motif- based sequence analyses to identify enzymes possessing conserved GDSL motifs in selected proteomes across the plant kingdom. Motif-based HMM scanning (Viterbi decoding-VD and posterior decoding-PD) and the here described PD/VD protocol were successfully applied on 12 selected plant proteomes to identify sequences with GDSL motifs. A significant number of identified GDSL sequences were novel. Moreover, our scanning approach successfully detected protein sequences lacking at least one of the essential motifs (171/820) annotated by Pfam profile search (PfamA) as GDSL. Based on these analyses we provide a curated list of GDSL enzymes from the selected plants. Clans clustering and phylogenetic analyses helped us to gain a better insight into the evolutionary relationship of all identified GDSL sequences. Three novel GDSL subfamilies as well as unreported variations in GDSL motifs were discovered in this study. In addition, analyses of selected proteomes showed a remarkable expansion of GDSL enzymes in the lycophyte, Selaginella moellendorffii. Finally, we provide a general motif- HMM scanner which is easily accessible through the graphical user interface (http://compbio.math.hr/). Conclusions Our results show that scanning with a carefully parameterized motif- HMM is an effective approach for annotation of protein families with low sequence similarity and conserved motifs. The results of this study expand current knowledge and provide new insights into the evolution of the large GDSL-lipase family in land plants.
Izvorni jezik
Engleski
Znanstvena područja
Matematika, Biologija
POVEZANOST RADA
Projekti:
MZOS-098-0982913-2877 - Temeljna molekularno-biološka istraživanja streptomiceta (Vujaklija, Dušica, MZOS ) ( CroRIS)
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb,
Prirodoslovno-matematički fakultet, Matematički odjel, Zagreb,
Prehrambeno-biotehnološki fakultet, Zagreb,
Institut "Ruđer Bošković", Zagreb,
Prirodoslovno-matematički fakultet, Zagreb
Profili:
Ivan Vujaklija
(autor)
Tina Paradžik
(autor)
Pavle Goldstein
(autor)
Dušica Vujaklija
(autor)
Ana Bielen
(autor)
Citiraj ovu publikaciju:
Časopis indeksira:
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus
- MEDLINE