Background

The Importance of Shifting Ontology

The Gene Ontology [GO] provides a representation of biological knowledge through the use of precisely defined, interrelated terms [1, 2]. For GO to successfully underpin data-driven discovery and database searches, the definitions of the terms used, and their relations to each other, need to accurately portray existing biological knowledge about entities and processes. Thus, a key challenge for the long-term maintenance of GO consists of updating its contents to reflect new scientific developments that challenge established biological knowledge [3]. GO curators have been aware of this since the creation of GO [4] and have sought to establish mechanisms of feedback, so that users of GO could alert curators to any discrepancy between the understanding of given entities or processes routinely used within their own fields and the representation of that knowledge provided in the ontology [5]. Indeed, the capability of bio-ontologies such as GO to reflect new developments as they arise has been highlighted as key to their increasing popularity [6, 7].

GO was created in 1999 and is thus one of the longest-running ontologies within the Open Biomedical Ontologies (OBO). This paper explores how, in the course of its existence, GO has evolved to represent biological knowledge. We review the changes that have been applied to how GO terms are defined and related to each other, with a view to clarifying whether and how the content of GO has been modified to adequately fit new evidence. Reviewing how GO has been developed over the years is an important way for the users of GO and biologists in general to understand the processes involved in ontology development. This paper aims to provide biologists who are not normally involved in the development of ontologies with an understanding of the amount of conceptual and practical effort needed in this area, as well as the expertise involved. We therefore do not focus on changes implemented to improve the interoperability and internal coherence of GO, e.g. [2a). To address this, the existing term was renamed to add "mitochondrial", thus making information that was implicit in the ontology structure explicit in term names. Two new terms were then added, one of which uses the non-location-specific name, and is a descendant of "cytoplasm"; the second new term has a name and path specifying that the complex is located in the cytosol (Figure 2b).

Figure 2
figure 2

A shows the initial anomalous parentage of the term " 'tricarboxylic acid cycle enzyme complex " and B shows the corrected ontology structure in the current GO cellular component ontology hierarchy.

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Ontology shift 3: Dealing with diverging definitions across communities

A third type of ontology shift results from the need to deal with diverging definitions across research communities. Often, given the diversity and fragmentation typical of biological and biomedical research, the same phrase is used in different ways depending on the research context [3]. Maintaining univocity (a word or phrase having a single meaning) is essential in develo** unambiguous ontologies, so it is necessary to alter the structure of GO where cases of multiple meaning for a word or phrase arise. Not surprisingly, this type of ontology shift often coincides with ontology shifts of type three detailed above: divergence in the use of terms across communities are commonly discovered when new terminologies, fields or species are added to GO.

The 2001 transition to include plants in the ontology is a case in point. Early on, GO had only one term for gamete formation: "gametogenesis", which was defined as the "generation, maintenance, and proliferation of gametes". The meaning of "gamete" was not specified, but the term and definition were generated with animal gamete formation in mind. Plant biologists, however, use "gametogenesis" to refer to the generation of a gametophyte, that is, a plant in the haploid phase that can produce gametes. An extensive set of changes was required to remove ambiguity in the usage of "gametogenesis", and add terms to represent plant biology. The definition of "gametogenesis" was altered to define gamete as "a haploid reproductive cell" and to remove the mention of proliferation. For plant processes, a new term "gametophyte development" was added, its name and definition clearly referring to the relevant phase of a plant life cycle.

Ontology Shift 4: Mirroring scientific advance

A fourth type of ontology shift occurs in response to new evidence which changes the understanding of a given entity or process so that its definition and relations to other terms also need to change.

An example of this involves the term "cytoskeleton". For several decades, cytoskeletal structures such as microfilaments, microtubules, and intermediate filaments were observed only in eukaryotic cells, and were therefore thought to be absent from prokaryotic cells. Accordingly, the definition for the GO cellular component term "cytoskeleton" followed one of many dictionary and textbook definitions, beginning "Any of the various filamentous elements that form the internal framework of eukaryotic cells". In recent years, however, evidence has accumulated that bacterial cells do contain cytoskeletal structures [13, 14]. To accommodate these discoveries, and to facilitate annotation of bacterial cytoskeletal gene products the GO definition had to be broadened to remove the word "eukaryotic", and with it the restriction on species to which the term could be applied. Deletion of a single word from a term definition thus allowed GO to capture a revolutionary advance in the research community's understanding of both prokaryotic cell organization and the taxonomic distribution of cytoskeletal structures.

The definition of the term "conoid" is another example of how ontology can shift in response to scientific developments. The conoid is a cytoskeletal element that forms part of the apical complex, a distinctive and elaborate structure found in apicomplexan parasites [15]. Based on electron microscopic analysis, the conoid was known to consist of fibers; based on the prevailing hypothesis that the fibers were microtubules, GO included a cellular component term, "conoid", which was an is_a descendant of "microtubule". The definition was: "Coiled microtubules within both the polar and basal rings of the apical complex of an apicomplexan parasite." More recently, Hu et al. [16] showed that the conoid is indeed composed primarily of tubulin, but the tubulin structure differs markedly from that of typical microtubules. This improved understanding of conoid structure had two consequences for "conoid". First, the is_a relationship to "microtubule" was removed, because the conoid could no longer be considered a type of microtubule. Second, the text definition was changed to remove information now known to be false and to more accurately describe the structure of a conoid.

Ontology shift 5: Adding relations

One last type of ontology shift concerns changes to the type of relations deemed to hold between ontology terms. This shift is more complex than the previous four, since it potentially affects the whole ontology and requires a revision of the whole system in order to be implemented.

As originally used in GO, the part_of relationship was not rigorously defined. This led to a number of problems, one of the biggest ones being that the part_of relationship in GO was being used with different levels of stringency: in some cases all of the subclass is part of some of the superclass (all-some), while in others only some of the subclass is part of some of the superclass [17]. For example, the TRAMP complex is found only in the nucleus, while the exosome complex is found in both the cytoplasm and the nucleus yet in GO both complexes had the same part_of relation to nucleus, with the exosome complex having a further part_of relation to cytoplasm. To remedy this situation, the scope of the part_of relationship was limited to specifically refer to the all-some relationship, and the graph altered accordingly. Further, new relationship types have been introduced [18] to address other consistency issues with the use of part_of in GO:

• Regulation Relationships

Before the introduction of the regulation relationships, all regulatory processes in GO were made part_of the processes they regulated, which was insufficient to capture the biology because not all regulatory processes are integral to the processes they regulate. For example, a kinase which phosphorylates a transcription factor and thus regulates its translocation from the cytoplasm to the nucleus regulates transcription. However, the kinase is not part of the transcription machinery and thus does not itself play a direct role in the process of transcription.

• Has_part relationship

The use of the part_of relationship in the spliceosomal component terms led to a logical flaw, sometimes referred to as a true path violation, in the ontology. The term "U5 snRNP" was a part_of descendant of both the term "major (U2-dependent) spliceosome" and the term "minor (U12-dependent) spliceosome". Most eukaryotic organisms have two forms of spliceosomes, each of which contains five snRNP complexes, four which are unique to that type, and one which is found in both types of spliceosomes. While it is true biologically that both the major (U2) and the minor (U12) forms of the spliceosome contain the U5 snRNP, any specific U5 snRNP complex is not present in both forms of the spliceosome at the same time. Further, some organisms, e.g. S. cerevisiae, do not have the minor spliceosome. The "U5 snRNP" part_of the "minor (U12-dependent) spliceosome" relationship leads to the conclusion that the S. cerevisiae genes annotated to the term "U5 snRNP" are present in the minor spliceosome, which is not true. During a major revision of the spliceosomal complex terms, new terms were added to represent the different spliceosomal complexes that are recognized during various stages of the spliceosomal assembly/disassembly cycle. The has_part relationship was then used to capture the biological relationships between some of the large spliceosomal complexes and the smaller snRNP complexes, thus more accurately describing relationships between complexes and subcomplexes in the cellular component ontology (and similarly in the biological process ontology) that were either misrepresented or not represented previously.

Discussion

Like other ontologies in OBO, GO can be used as a platform for data sharing only insofar as it accurately captures current biological knowledge. GO terms are expected to refer to real biological entities and processes, and thus the definitions and relations used to characterise these terms need to reflect established knowledge about those entities and processes. OBO view this as a crucial principle underlying the development and use of ontologies in biology, and yet its application in practice is not straightforward. As illustrated by the cases discussed above, ontology shifts tend to happen for a variety of different reasons and to affect the ontology to varying degrees. Some shifts, such as the introduction of regulation and has_part relationships in GO (ontology shift 5), have a deep impact on the whole structure of the ontology; other shifts, such as the change in the GO terms related to serotonin secretion (ontology shift 1), have a more limited impact, affecting only a specific part of the ontology. Interestingly, in cases such as the term 'immune response' (ontology shift 3), a small shift in a definition or the choice of a term affects several of the related terms within the ontology. In all of these cases, the expert judgement and manual intervention by curators appears key to the appropriate development of an ontology. This is because carrying out these ontology shifts involves a complex set of skills. To effect the shifts illustrated above, curators are required to find and interpret new information coming from biological research to work out whether, and how, that affects the existing structure and content of GO; and to assess the representation of biological reality given within the GO, so as to judge how, if at all, it needs to be changed to accommodate new information. This means that in order to update GO, its curators need to be able to adequately understand and represent research carried out in contemporary experimental biology. As in the example of the cytoskeleton (ontology shift 4), they need to be able to spot discoveries relevant to how ontology terms are structured and defined, and work out how an ontology needs to change in response to new knowledge. On the one hand, this requires appropriate training in information technology and computer science, so as to be able to design, develop and modify ontologies. On the other hand, curators also need to be familiar with the scientific knowledge that their ontology aims to capture, the methods through which such knowledge is obtained, and the importance attached to specific discoveries and evidence by the relevant research communities.

Conclusion

The difficult judgments and decision-making processes involved in kee** an ontology up to date explain the relatively slow pace in implementing even well-circumscribed changes. This situation will certainly improve as ontology development becomes increasingly professionalised and automated. The OBO Foundry, for instance, is seeking to identify standard solutions that will hopefully enable the automation of at least some curatorial tasks [6]. Nevertheless, the examples above point to the difficulties involved in applying general standards to the development of a specific ontology. Ontology curation aims to produce a faithful representation of knowledge domains as they keep develo**, which requires the translation of general guidelines into specific representations of reality and an understanding of how scientific knowledge is produced and constantly updated. In this context, it is important that trained curators with technical expertise in the scientific field(s) in question are involved in supervising ontology shifts and identifying inaccuracies.

Methods

This is a qualitative study based on an in-depth analysis of specific examples of ontology shifts, each of which is discussed by the curator responsible for implementing it. The curators involved in this study were recruited by Sabina Leonelli via an email request for collaboration on exploring ontology shifts in GO, to which they freely responded by contributing what they saw as particularly interesting examples from their work. The selection of the examples used here is thus dependent on the specific expertise and interests of the authors of this paper, as usual in qualitative studies of this kind. The examples of ontology shifts are grouped into five categories, depending on the scientific circumstances that warranted them: (1) the emergence of anomalies; (2) the extension of the scope of GO; (3) divergence in how terminology is used across user communities; (4) new discoveries that change the meaning of the terms used and their relations to each other; and (5) the extension of the range of relations used to link entities or processes described by GO terms. Curators selected these specific cases on the basis of what they perceived as their typicality (how well they exemplify other cases within the same category); their intelligibility (the ease with which they could be explained within the word limits of this review); and their significance (the extent to which they impacted the structure and content of GO). A quantitative study would be needed to determine the frequency with which each type of ontology shift has appeared in GO (or any other bio-ontology). Due to the current lack of such quantitative data, there is no relation between the order in which the ontology shifts are listed in this paper and the frequency with which they occur in practice.