LAILAPS: The Plant Science Search Engine

Abstract

With the number of sequenced plant genomes growing, the number of predicted genes and functional annotations is also increasing. The association between genes and phenotypic traits is currently of great interest. Unfortunately, the information available today is widely scattered over a number of different databases. Information retrieval (IR) has become an all-encompassing bioinformatics methodology for extracting knowledge from complex, heterogeneous and distributed databases, and therefore can be a useful tool for obtaining a comprehensive view of plant genomics, from genes to traits. Here we describe LAILAPS (http://lailaps.ipk-gatersleben.de), an IR system designed to link plant genomic data in the context of phenotypic attributes for a detailed forward genetic research. LAILAPS comprises around 65 million indexed documents, encompassing >13 major life science databases with around 80 million links to plant genomic resources. The LAILAPS search engine allows fuzzy querying for candidate genes linked to specific traits over a loosely integrated system of indexed and interlinked genome databases. Query assistance and an evidence-based annotation system enable time-efficient and comprehensive information retrieval. An artificial neural network incorporating user feedback and behavior tracking allows relevance sorting of results. We fully describe LAILAPS’s functionality and capabilities by comparing this system’s performance with other widely used systems and by reporting both a validation in maize and a knowledge discovery use-case focusing on candidate genes in barley.

Towards a whole‐genome sequence for rye (Secale cereale L.)

“…Comprehensive whole‐genome sequence information of the allogamous rye has been missing so far, whereas draft genome sequences of the related autogamous Triticeae species barley, bread wheat, Aegilops tauschii and T. urartu became available recently (Mayer et al ., , ; Jia et al ., ; Ling et al ., ). These genomic resources are indispensable tools for understanding the biology and evolution of major Triticeae species through comparative genomic approaches (Spannagl et al ., ) and for relating this knowledge to phenotypic traits (Esch et al ., ). As yet, rye is not well represented in public sequence databases, which prohibits large‐scale functional analyses in rye and genomics‐assisted genetic improvement of rye for sustainable crop production.…”

Editorial: Plant and Cell Physiology’s 2017 Database Issue

“…Therefore identification of experimental conditions that induce similar or opposite transcriptional changes can be used as a means of identifying which factors are potentially involved in the same biological process. Esch et al (2015) constructed LAILAPS (http://lailaps.ipkgatersleben.de) as an information retrieval system aiming to link plant genomic data in the context of phenotypic attributes in order to facilitate forward genetics approaches in plants. This online tool includes around 65 million indexed documents, covering over 13 major life science databases with around 80 million hyperlinks to plant science information resources.…”

transPLANT Resources for Triticeae Genomic Data

“…LAILAPS (Esch et al, 2014) is an integrated information retrieval system to link plant genomic data in the context of phenotypic traits for a detailed forward genetic research (Table 1.12; Fig. 6).…”