The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

Author:

Zhou Naihui,Jiang Yuxiang,Bergquist Timothy R.,Lee Alexandra J.,Kacsoh Balint Z.,Crocker Alex W.,Lewis Kimberley A.,Georghiou George,Nguyen Huy N.,Hamid Md Nafiz,Davis Larry,Dogan Tunca,Atalay Volkan,Rifaioglu Ahmet S.,Dalkıran Alperen,Cetin Atalay Rengul,Zhang Chengxin,Hurto Rebecca L.,Freddolino Peter L.,Zhang Yang,Bhat Prajwal,Supek Fran,Fernández José M.,Gemovic Branislava,Perovic Vladimir R.,Davidović Radoslav S.,Sumonja Neven,Veljkovic Nevena,Asgari Ehsaneddin,Mofrad Mohammad R.K.,Profiti Giuseppe,Savojardo Castrense,Martelli Pier Luigi,Casadio Rita,Boecker Florian,Schoof Heiko,Kahanda Indika,Thurlby Natalie,McHardy Alice C.,Renaux Alexandre,Saidi Rabie,Gough Julian,Freitas Alex A.,Antczak Magdalena,Fabris Fabio,Wass Mark N.,Hou Jie,Cheng Jianlin,Wang Zheng,Romero Alfonso E.,Paccanaro Alberto,Yang Haixuan,Goldberg Tatyana,Zhao Chenguang,Holm Liisa,Törönen Petri,Medlar Alan J.,Zosa Elaine,Borukhov Itamar,Novikov Ilya,Wilkins Angela,Lichtarge Olivier,Chi Po-Han,Tseng Wei-Cheng,Linial Michal,Rose Peter W.,Dessimoz Christophe,Vidulin Vedrana,Dzeroski Saso,Sillitoe Ian,Das Sayoni,Lees Jonathan Gill,Jones David T.,Wan Cen,Cozzetto Domenico,Fa Rui,Torres Mateo,Warwick Vesztrocy Alex,Rodriguez Jose Manuel,Tress Michael L.,Frasca Marco,Notaro Marco,Grossi Giuliano,Petrini Alessandro,Re Matteo,Valentini Giorgio,Mesiti Marco,Roche Daniel B.,Reeb Jonas,Ritchie David W.,Aridhi Sabeur,Alborzi Seyed Ziaeddin,Devignes Marie-Dominique,Koo Da Chen Emily,Bonneau Richard,Gligorijević Vladimir,Barot Meet,Fang Hai,Toppo Stefano,Lavezzo Enrico,Falda Marco,Berselli Michele,Tosatto Silvio C.E.,Carraro Marco,Piovesan Damiano,Ur Rehman Hafeez,Mao Qizhong,Zhang Shanshan,Vucetic Slobodan,Black Gage S.,Jo Dane,Suh Erica,Dayton Jonathan B.,Larsen Dallas J.,Omdahl Ashton R.,McGuffin Liam J.,Brackenridge Danielle A.,Babbitt Patricia C.,Yunes Jeffrey M.,Fontana Paolo,Zhang Feng,Zhu Shanfeng,You Ronghui,Zhang Zihan,Dai Suyang,Yao Shuwei,Tian Weidong,Cao Renzhi,Chandler Caleb,Amezola Miguel,Johnson Devon,Chang Jia-Ming,Liao Wen-Hung,Liu Yi-Wei,Pascarelli Stefano,Frank Yotam,Hoehndorf Robert,Kulmanov Maxat,Boudellioua Imane,Politano Gianfranco,Di Carlo Stefano,Benso Alfredo,Hakala Kai,Ginter Filip,Mehryary Farrokh,Kaewphan Suwisa,Björne Jari,Moen Hans,Tolvanen Martti E.E.,Salakoski Tapio,Kihara Daisuke,Jain Aashish,Šmuc Tomislav,Altenhoff Adrian,Ben-Hur Asa,Rost Burkhard,Brenner Steven E.,Orengo Christine A.,Jeffery Constance J.,Bosco Giovanni,Hogan Deborah A.,Martin Maria J.,O’Donovan Claire,Mooney Sean D.,Greene Casey S.,Radivojac Predrag,Friedberg IddoORCID

Abstract

Abstract Background The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Results Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory. Conclusion We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.

Funder

National Science Foundation

Publisher

Springer Science and Business Media LLC

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