Tag: DNA sequencing

Another paper I have co-authored related to the UNITE database for fungal rDNA ITS sequences is now published as an Online Early article in Fungal Diversity. The paper describes an effort to improve the annotation of ITS sequences from fungal plant pathogens. Why is this important? Well, apart from fungal plant pathogens being responsible for great economic losses in agriculture, the paper is also conceptually important as it shows that together we can accomplish a substantial improvement to the metadata in sequence databases. In this work we have hunted down high-quality reference sequences for various plant pathogenic fungi, and re-annotated incorrectly or insufficiently annotated ITS sequences from the same fungal lineages. In total, the 59 authors have made 31,954 changes to UNITE database data, on average 540 changes per author. While one, or a few, persons could not feasibly have made this effort alone, this work shows that in larger consortia vast improvements can be made to the quality of databases, by distributing the work among many scientists. In many ways, this relates to proposals to “wikify” GenBank, and after Rfam and Pfam it might now be time to take the user-contribution model to, at least, the RefSeq portion of GenBank, which despite its description as being “comprehensive, integrated, non-redundant, [and] well-annotated” still contains errors and examples of non-usable annotation. More on that at a later point…

Paper reference:

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 Online early (2014). doi: 10.1007/s13225-014-0291-8 [Paper link]

Science for Life Laboratories (SciLifeLab) in Stockholm will host a metagenome data analysis workshop on May 21-23, in which I will participate as a tutorial assistant. Additionally, our group leader Joakim Larsson will be giving a lecture about how we use metagenomics to assess the environmental reservoir of antibiotic resistance genes (much of my recent work will likely go into that). I hope to meet you there, so don’t forget to register!

Confirmed speakers:
Lex Nederbragt, Oslo University, Norway
Saskia Smits, Erasmus University Rotterdam, Netherlands
Joakim Larsson, Göteborg University, Sweden
Paul Wilmes, University of Luxembourg, Luxembourg
Anders Andersson, SciLifeLab, Sweden
Noan Le Bescot, UPMC (Tara expedition), France

The workshop is part of the AllBio Bioinformatics initiative.

If you are thinking about doing a PhD and think that bioinformatics and antibiotic resistance is a cool subject, then now is your chance to come and join us for the next four years! There is a PhD position open i Joakim Larsson’s group, which means that if you get the job you will work with me, Joakim Larsson, Erik Kristiansson, Ørjan Samuelsen and Carl-Fredrik Flach on a super-interesting project relating to discovery of novel beta-lactamase genes (NoCURE). The project aims to better understand where, how and under what circumstances these genetic transfer events take place, in order to provide opportunities to limit or delay resistance development and thus increase the functional lifespan of precious antibiotics. The lion’s share of the work will be related to interpreting large-scale sequencing data generated by collaborators within the project; both genome sequencing and metagenomic data.

This is a great opportunity to prove your bioinformatics skills and use them for something urgently important. Full details about the position can be found here.

It’s been a while since the PETKit got any attention from me. Partially, that has been due to a nasty bug that could produce no output for one of the read files in Pefcon when using FASTA input files, but mostly it has simply been due to lack of time to continue development on the package. Now, I have finally put all threads together (bug fixes, new features, documentation) and today the 1.1 version is released! The new features are:

• A new tool has been added – peacat – that can be used to e.g. stitch contigs together that have been separated for one reason or another in an assembly
• Another tool – pemap – has been added that can be used to determine whether an assembled contig is from a circular DNA element
• The default offset value for FASTQ files has been set to 33 (as in Sanger and Illumina 1.8+ PHRED format)
• The documentation has been vastly improved (but is still rather inferior)

If you’re looking for a PhD position in bioinformatics, working with antibiotic resistance, there’s an opening in Erik Krisiansson’s (best bioinformatician in Gothenburg? I think so) group. To apply you need to have a master’s level degree in bioinformatics, mathematical statistics, mathematics, computer science, physics, molecular biology or any equivalent topic, obtained latest June 2014. If you’re a master student and want to join us, this is your chance! You can read more and apply for the position here.

A new year has begun, and it brings with it a few updates on the website. I have added a summary of the year 2013 from my perspective, and (as you may recognize) updated my picture on the front page. Briefly, this year will bring lots of exciting stuff. Personally, I am quite excited to finally be able to share the new version of Metaxa – Metaxa2 – which will be released to the public late this Winter (or early Spring). Additionally, I look forward to wrap up some manuscript on metagenomics and antibiotic resistance, which I have been working with for more than 2.5 years now. Also, we look forward to some super-intersting technology developments in DNA sequencing, with PacBio finally finding proper usage scenarios, Nano-pore sequencing around the corner, and super-multiplexing on the Illumina instruments. We’re in for a treat with DNA sequencing in 2014!

Those of you attending the Swedish Bioinformatics Workshop, this year given in Skövde, will have a chance seeing me talk about how sequencing depth influences the picture we get of the environmental resistance gene diversity. I think the topic is very urgent and interesting, and will likely come back to it in a more thorough blog post later. There are also a few other very interesting talks, for example about metagenomic gene quantification, and en masse sequencing of E. coli and H. pylori isolates. I think all attendants are in for a treat! See you there!

I am happy to inform you that our paper on ITSx now is out online in Methods in Ecology and Evolution issue 4.10. Meanwhile, I am slowly getting my stuff together on an update that will bring some minor requested features. The publication brings the proper citation of the ITSx paper to be:

Bengtsson-Palme, J., Ryberg, M., Hartmann, M., Branco, S., Wang, Z., Godhe, A., De Wit, P., Sánchez-García, M., Ebersberger, I., de Sousa, F., Amend, A. S., Jumpponen, A., Unterseher, M., Kristiansson, E., Abarenkov, K., Bertrand, Y. J. K., Sanli, K., Eriksson, K. M., Vik, U., Veldre, V., Nilsson, R. H. (2013), Improved software detection and extraction of ITS1 and ITS2 from ribosomal ITS sequences of fungi and other eukaryotes for analysis of environmental sequencing data. Methods in Ecology and Evolution, 4: 914–919. doi: 10.1111/2041-210X.12073

Our paper on the most recent developments of the UNITE database for fungal rDNA ITS sequences has just been published as an Early view article in Molecular Ecology. In this paper, we aim to ease two of the major problems facing the identification of newly generated fungal ITS sequences: the lack of a sufficiently goof reference dataset, and the lack of a way to refer to fungal species without a Latin name. As part of a solution, we have introduced the term species hypothesis for all fungal species represented by at least two ITS sequences. The UNITE database has an easy-to-use web-based sequence management system, and we encourage everybody that can improve on the annotations or metadata of a fungal lineage to do so.

My main contribution on this paper has been to tailor ITSx functionality for the UNITE database, so that ITS data could be more easily processed for the Species Hypotheses.

Paper reference:
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. Accepted in Molecular Ecology. doi: 10.1111/mec.12481 [Paper link]

The paper describing our software tool ITSx has now gone online as an Early View paper on the Methods in Ecology and Evolution website. The software just recently left its beta-status behind, and with the paper out as well, we hope that as many people as possible will find use for the software in barcoding efforts of the ITS region. If you’re not familiar with the software – or its predecessor; the fungal ITS Extractor – here is a brief description of what it does:

ITSx is a Perl-based software tool that extracts the ITS1, 5.8S and ITS2 sequences – as well as full-length ITS sequences – from high-throughput sequencing data sets. To achieve this, we use carefully crafted hidden Markov models (HMMs), computed from large alignments of a total of 20 groups of eukaryotes. Testing has shown that ITSx has close to 100% detection accuracy, and virtually zero false-positive extractions. Additionally, it supports multiple processor cores, and is therefore suitable for running also on very large datasets. It is also able to eliminate non-ITS sequences from a given input dataset.

While ITSx supports extractions of ITS sequences from at least 20 different eukaryotic lineages, we ourselves have considerably less experience with many of the eukaryote groups outside of the fungi. We therefore release ITSx with the intent that the research community will evaluate its performance also in other parts of the eukaryote tree, and if necessary contribute data required to address also those lineages in a thorough way.

The ITSx paper can at the moment be cited as:
Bengtsson-Palme, J., Ryberg, M., Hartmann, M., Branco, S., Wang, Z., Godhe, A., De Wit, P., Sánchez-García, M., Ebersberger, I., de Sousa, F., Amend, A. S., Jumpponen, A., Unterseher, M., Kristiansson, E., Abarenkov, K., Bertrand, Y. J. K., Sanli, K., Eriksson, K. M., Vik, U., Veldre, V., Nilsson, R. H. (2013), Improved software detection and extraction of ITS1 and ITS2 from ribosomal ITS sequences of fungi and other eukaryotes for analysis of environmental sequencing data. Methods in Ecology and Evolution. doi: 10.1111/2041-210X.12073