Tag: ITS

Yesterday, Molecular Ecology Resources put online an unedited version of a recent paper which I co-authored. This time, Rodney Richardson at Ohio State University has made a tremendous work of evaluating three taxonomic classification software – the RDP Naïve Bayesian Classifier, RTAX and UTAX – on a set of DNA barcoding regions commonly used for plants, namely the ITS2, and the matK, rbcL, trnL and trnH genes.

In the paper (1), we discuss the results, merits and limitations of the classifiers. In brief, we found that:

• There is a considerable trade-off between accuracy and sensitivity for the classifiers tested, which indicates a need for improved sequence classification tools (2)
• UTAX was superior with respect to error rate, but was exceedingly stringent and thus suffered from a low assignment rate
• The RDP Naïve Bayesian Classifier displayed high sensitivity and low error at the family and order levels, but had a genus-level error rate of 9.6 percent
• RTAX showed high sensitivity at all taxonomic ranks, but at the same time consistently produced the high error rates
• The choice of locus has significant effects on the classification sensitivity of all tested tools
• All classifiers showed strong relationships between database completeness, classification sensitivity and classification accuracy

We believe that the methods of comparison we have used are simple and robust, and thereby provides a methodological and conceptual foundation for future software evaluations. On a personal note, I will thoroughly enjoy working with Rodney and Reed again; I had a great time discussing the ins and outs of taxonomic classification with them! The paper can be found here.

References and notes

1. Richardson RT, Bengtsson-Palme J, Johnson RM: Evaluating and Optimizing the Performance of Software Commonly Used for the Taxonomic Classification of DNA Sequence Data. Molecular Ecology Resources, Early view (2016). doi: 10.1111/1755-0998.12628 [Paper link]
2. This is something that several classifiers also showed in the evaluation we did for the Metaxa2 paper (3). Interestingly enough, Metaxa2 is better at maintaining high accuracy also as sensitivity is increased.
3. Bengtsson-Palme J, Hartmann M, Eriksson KM, Pal C, Thorell K, Larsson DGJ, Nilsson RH: Metaxa2: Improved identification and taxonomic classification of small and large subunit rRNA in metagenomic data. Molecular Ecology Resources, 15, 6, 1403–1414 (2015). doi: 10.1111/1755-0998.12399 [Paper link]

MycoKeys today put a paper online which I was involved in. The paper describes the results of a workshop in May, when we added and refined annotations for fungal ITS sequences according to the MIxS-Built Environment annotation standard (1). Fungi have been associated with a range of unwanted effects in the built environment, including asthma, decay of building materials, and food spoilage. However, the state of the metadata annotation of fungal DNA sequences from the built environment is very much incomplete in public databases. The workshop aimed to ease a little part of this problem, by distributing the re-annotation of public fungal ITS sequences across 36 persons. In total, we added or changed of 45,488 data points drawing from published literature, including addition of 8,430 instances of countries of collection, 5,801 instances of building types, and 3,876 instances of surface-air contaminants. The results have been implemented in the UNITE database and shared with other online resources. I believe, that distributed initiatives like this (and the ones I have been involved in in the past (2,3)) serve a very important purpose for establishing better annotation of sequence data, an issue I have brought up also for sequences outside of barcoding genes (4). The full paper can be found here.

References

1. Abarenkov K, Adams RI, Laszlo I, Agan A, Ambrioso E, Antonelli A, Bahram M, Bengtsson-Palme J, Bok G, Cangren P, Coimbra V, Coleine C, Gustafsson C, He J, Hofmann T, Kristiansson E, Larsson E, Larsson T, Liu Y, Martinsson S, Meyer W, Panova M, Pombubpa N, Ritter C, Ryberg M, Svantesson S, Scharn R, Svensson O, Töpel M, Untersehrer M, Visagie C, Wurzbacher C, Taylor AFS, Kõljalg U, Schriml L, Nilsson RH: Annotating public fungal ITS sequences from the built environment according to the MIxS-Built Environment standard – a report from a May 23-24, 2016 workshop (Gothenburg, Sweden). MycoKeys, 16, 1–15 (2016). doi: 10.3897/mycokeys.16.10000
2. Kõljalg U, Nilsson RH, Abarenkov K, Tedersoo L, Taylor AFS, Bahram M, Bates ST, Bruns TT, Bengtsson-Palme J, Callaghan TM, Douglas B, Drenkhan T, Eberhardt U, Dueñas M, Grebenc T, Griffith GW, Hartmann M, Kirk PM, Kohout P, Larsson E, Lindahl BD, Lücking R, Martín MP, Matheny PB, Nguyen NH, Niskanen T, Oja J, Peay KG, Peintner U, Peterson M, Põldmaa K, Saag L, Saar I, Schüßler A, Senés C, Smith ME, Suija A, Taylor DE, Telleria MT, Weiß M, Larsson KH: Towards a unified paradigm for sequence-based identification of Fungi. Molecular Ecology, 22, 21, 5271–5277 (2013). doi: 10.1111/mec.12481
3. Nilsson RH, Hyde KD, Pawlowska J, Ryberg M, Tedersoo L, Aas AB, Alias SA, Alves A, Anderson CL, Antonelli A, Arnold AE, Bahnmann B, Bahram M, Bengtsson-Palme J, Berlin A, Branco S, Chomnunti P, Dissanayake A, Drenkhan R, Friberg H, Frøslev TG, Halwachs B, Hartmann M, Henricot B, Jayawardena R, Jumpponen A, Kauserud H, Koskela S, Kulik T, Liimatainen K, Lindahl B, Lindner D, Liu J-K, Maharachchikumbura S, Manamgoda D, Martinsson S, Neves MA, Niskanen T, Nylinder S, Pereira OL, Pinho DB, Porter TM, Queloz V, Riit T, Sanchez-García M, de Sousa F, Stefaczyk E, Tadych M, Takamatsu S, Tian Q, Udayanga D, Unterseher M, Wang Z, Wikee S, Yan J, Larsson E, Larsson K-H, Kõljalg U, Abarenkov K: Improving ITS sequence data for identification of plant pathogenic fungi. Fungal Diversity, 67, 1, 11–19 (2014). doi: 10.1007/s13225-014-0291-8
4. Bengtsson-Palme J, Boulund F, Edström R, Feizi A, Johnning A, Jonsson VA, Karlsson FH, Pal C, Pereira MB, Rehammar A, Sánchez J, Sanli K, Thorell K: Strategies to improve usability and preserve accuracy in biological sequence databases. Proteomics, Early view (2016). doi: 10.1002/pmic.201600034

Some of you who think ITSx is running slowly despite being assigned multiple CPUs, particularly on datasets with only one kind of sequences (e.g. fungal) using the -t F option might be interested in trying out Andrew Krohn’s parallel ITSx implementation. The solution essentially employs a bash script spawning multiple ITSx instances running on different portions of the input file. Although there are some limitations to the script (e.g. you cannot select a custom name for the output and you will only get the ITS1 and ITS2 + full sequences FASTA files, as far as I understand the script), it may prove useful for many of you until we write up a proper solution to the poor multi-thread performance of ITSx (planned for version 1.1). In the coming months, I recommend that you check this solution out! See also the wiki documentation.

My speed tests shows the following (on a quite small test set of fungal ITS sequences):
ITSx parallel on 16 CPUs, all ITS types (option “-t all“):
3 min, 16 sec
ITSx parallel on 16 CPUs, only fungal ITS types (option “-t f“):
54 sec
ITSx native on 16 CPUs, all ITS types (options “-t all --cpu 16“):
4 min, 59 sec
ITSx native on 16 CPUs, only fungal types (options “-t f --cpu 16“):
5 min, 50 sec

Why fungal only took longer time in the native implementation is a mystery to me, but probably shows why there is a need to rewrite the multithreading code, as we did with Metaxa a couple of years ago. Stay tuned for ITSx updates!

A couple of days ago, a paper I have co-authored describing an ITS sequence dataset for chimera control in fungi went online as an advance online publication in Microbes and Environments. There are several software tools available for chimera detection (e.g. Henrik Nilsson‘s fungal chimera checker (1) and UCHIME (2)), but these generally rely on the presence of a chimera-free reference dataset. Until now, there was no such dataset is for the fungal ITS region, and we in this paper (3) introduce a comprehensive, automatically updated reference dataset for fungal ITS sequences based on the UNITE database (4). This dataset supports chimera detection throughout the fungal kingdom and for full-length ITS sequences as well as partial (ITS1 or ITS2 only) datasets. We estimated the dataset performance on a large set of artificial chimeras to be above 99.5%, and also used the dataset to remove nearly 1,000 chimeric fungal ITS sequences from the UNITE database. The dataset can be downloaded from the UNITE repository. Thereby, it is also possible for users to curate the dataset in the future through the UNITE interactive editing tools.

References:

1. Nilsson RH, Abarenkov K, Veldre V, Nylinder S, Wit P de, Brosché S, Alfredsson JF, Ryberg M, Kristiansson E: An open source chimera checker for the fungal ITS region. Molecular Ecology Resources, 10, 1076–1081 (2010).
2. Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics, 27, 16, 2194-2200 (2011). doi:10.1093/bioinformatics/btr381
3. Nilsson RH, Tedersoo L, Ryberg M, Kristiansson E, Hartmann M, Unterseher M, Porter TM, Bengtsson-Palme J, Walker D, de Sousa F, Gamper HA, Larsson E, Larsson K-H, Kõljalg U, Edgar R, Abarenkov K: A comprehensive, automatically updated fungal ITS sequence dataset for reference-based chimera control in environmental sequencing efforts. Microbes and Environments, Advance Online Publication (2015). doi: 10.1264/jsme2.ME14121
4. Kõljalg U, Nilsson RH, Abarenkov K, Tedersoo L, Taylor AFS, Bahram M, Bates ST, Bruns TT, Bengtsson-Palme J, Callaghan TM, Douglas B, Drenkhan T, Eberhardt U, Dueñas M, Grebenc T, Griffith GW, Hartmann M, Kirk PM, Kohout P, Larsson E, Lindahl BD, Lücking R, Martín MP, Matheny PB, Nguyen NH, Niskanen T, Oja J, Peay KG, Peintner U, Peterson M, Põldmaa K, Saag L, Saar I, Schüßler A, Senés C, Smith ME, Suija A, Taylor DE, Telleria MT, Weiß M, Larsson KH: Towards a unified paradigm for sequence-based identification of Fungi. Molecular Ecology, 22, 21, 5271–5277 (2013). doi: 10.1111/mec.12481

My colleague Henrik Nilsson has been interviewed by the ResearchGate news team about the recent effort to better annotate ITS data for plant pathogenic fungi. It’s an interesting read, and I think Henrik nicely underscores why large-scale efforts for improving and correcting sequence annotations are important. You can read the interview here, and the paper they talk about is referenced below.

Nilsson RH, Hyde KD, Pawlowska J, Ryberg M, Tedersoo L, Aas AB, Alias SA, Alves A, Anderson CL, Antonelli A, Arnold AE, Bahnmann B, Bahram M, Bengtsson-Palme J, Berlin A, Branco S, Chomnunti P, Dissanayake A, Drenkhan R, Friberg H, Frøslev TG, Halwachs B, Hartmann M, Henricot B, Jayawardena R, Jumpponen A, Kauserud H, Koskela S, Kulik T, Liimatainen K, Lindahl B, Lindner D, Liu J-K, Maharachchikumbura S, Manamgoda D, Martinsson S, Neves MA, Niskanen T, Nylinder S, Pereira OL, Pinho DB, Porter TM, Queloz V, Riit T, Sanchez-García M, de Sousa F, Stefaczyk E, Tadych M, Takamatsu S, Tian Q, Udayanga D, Unterseher M, Wang Z, Wikee S, Yan J, Larsson E, Larsson K-H, Kõljalg U, Abarenkov K: Improving ITS sequence data for identification of plant pathogenic fungi. Fungal Diversity, Volume 67, Issue 1 (2014), 11–19. doi: 10.1007/s13225-014-0291-8 [Paper link]

A minor bug in the “its1.full_and_partial.fasta” file has been fixed in a minor update to ITSx (1.0.11) released to day. The bug occasionally caused newline characters at the end of a sequence to be skipped and the next entry to begin at the same row. The bug only manifested itself when ITSx was used with the --partial option and only in the above mentioned FASTA file. If you have been affected by the bug, you should have noticed as the resulting FASTA file would be considered corrupted by most bioinformatics software. The updated version of ITSx can be downloaded here.

After a long delay-time in testing ITSx version 1.0.10 has been made public. The new version patches a bug causing the 3′ anchor not being properly written to file when using the “--anchor hmm” option. If a number was used for the “--anchor” option, this bug did not apply. Thus, if you have not been using the “--anchor” option together with “hmm”, you have not been affected in any way by this bug. Nevertheless, I encourage updating in case you would use the “--anchor hmm” option in the future. The update can be downloaded here. Happy barcoding!

Another paper I have made a contribution to have just recently been published in Molecular Ecology Resources. The paper (1), which is lead-authored by Xin-Cun Wang and Chang Liu at the Institute of Medicinal Plant Development in Beijing, investigates the usability of the ITS1 and ITS2 as separate barcodes across the Eukaryotes. The study is a large scale meta-analysis comparing available high-quality sequence data in as many taxonomic groups at possible from three different aspects: PCR amplification, DNA sequencing efficiency and species discrimination ability. Specifically, we have looked for the presence of DNA barcoding gaps, species discrimination efficiency, sequence length distribution, GC content distribution and primer universality, using bioinformatic approaches. We found that the ITS1 had significantly higher efficiencies than the ITS2 in 17 of 47 families and 20 of 49 investigated genera, which was markedly better than the performance of ITS2. We conclude that, in general, ITS1 represents a better DNA barcode than ITS2 for a majority of eukaryotic taxonomic groups. This of course doesn’t mean that using the ITS2 or the ITS region in its entirety should be dismissed, but our results can serve as a ground for making informed decisions about which region to choose for your amplicon sequencing project. The results complement what have previously been observed for e.g. fungi, where the difference between ITS1 and ITS2 were much less pronounced (2).

References:

1. Wang X-C, Liu C, Huang L, Bengtsson-Palme J, Chen H, Zhang J-H, Cai D, Li J-Q: ITS1: A DNA barcode better than ITS2 in eukaryotes? Molecular Ecology Resources. Early view. doi: 10.1111/1755-0998.12325 [Paper link]
2. Blaalid R, Kumar S, Nilsson RH, Abarenkov K, Kirk PM, Kauserud H: ITS1 versus ITS2 as DNA metabarcodes for fungi. Molecular Ecology Resources. Volume 13, Issue2, Page 218-224. doi: 10.1111/1755-0998.12065 [Paper link]

I and one of the other developers of ITSx had a discussion a while ago about that using the --anchor option should output the “anchor sequences” around the ITS regions also for the full-length output file (given that the --truncate option is activated). I have today changed ITSx to employ this behaviour, updating it to version 1.0.9. The update also improves sensitivity when using the --anchor HMM option slightly, and can be downloaded here. Happy barcoding!

ITSx has today been updated, bringing it to version 1.0.8. This update adds the “--only_full” option, which restricts output in the ITS1, 5.8S and ITS2 files to only the files that contain the full region, i.e. that both surrounding domains have been detected. The update also fixes a bug with the --anchor option, and can be downloaded here. Happy barcoding!