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  • 1.
    Andersson, Anders
    et al.
    KTH, Superseded Departments, Biotechnology.
    Keskitalo, J.
    Sjödin, A.
    Bhalerao, Rupali
    KTH, Superseded Departments, Biotechnology.
    Sterky, Fredrik
    KTH, Superseded Departments, Biotechnology.
    Wissel, K.
    Tandre, K.
    Aspeborg, Henrik
    KTH, Superseded Departments, Biotechnology.
    Moyle, R.
    Ohmiya, Y.
    Brunner, A.
    Gustafsson, P.
    Karlsson, J.
    Lundeberg, Joakim
    KTH, Superseded Departments, Biotechnology.
    Nilsson, O.
    Sandberg, G.
    Strauss, S.
    Sundberg, B.
    Uhlén, Mathias
    KTH, Superseded Departments, Biotechnology.
    Jansson, S.
    Nilsson, Peter
    KTH, Superseded Departments, Biotechnology.
    A transcriptional timetable of autumn senescence2004In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 5, no 4, p. R24-Article in journal (Refereed)
    Abstract [en]

    Background: We have developed genomic tools to allow the genus Populus ( aspens and cottonwoods) to be exploited as a full-featured model for investigating fundamental aspects of tree biology. We have undertaken large-scale expressed sequence tag ( EST) sequencing programs and created Populus microarrays with significant gene coverage. One of the important aspects of plant biology that cannot be studied in annual plants is the gene activity involved in the induction of autumn leaf senescence. Results: On the basis of 36,354 Populus ESTs, obtained from seven cDNA libraries, we have created a DNA microarray consisting of 13,490 clones, spotted in duplicate. Of these clones, 12,376 (92%) were confirmed by resequencing and all sequences were annotated and functionally classified. Here we have used the microarray to study transcript abundance in leaves of a free-growing aspen tree ( Populus tremula) in northern Sweden during natural autumn senescence. Of the 13,490 spotted clones, 3,792 represented genes with significant expression in all leaf samples from the seven studied dates. Conclusions: We observed a major shift in gene expression, coinciding with massive chlorophyll degradation, that reflected a shift from photosynthetic competence to energy generation by mitochondrial respiration, oxidation of fatty acids and nutrient mobilization. Autumn senescence had much in common with senescence in annual plants; for example many proteases were induced. We also found evidence for increased transcriptional activity before the appearance of visible signs of senescence, presumably preparing the leaf for degradation of its components.

  • 2.
    Andersson, Anders
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology.
    Lundgren, Magnus
    Department of Molecular Evolution, Evolutionary Biology Center, Uppsala University.
    Eriksson, Stefan
    Department of Molecular Evolution, Evolutionary Biology Center, Uppsala University.
    Rosenlund, Magnus
    KTH, School of Engineering Sciences (SCI), Mathematics (Dept.).
    Bernander, Rolf
    Department of Molecular Evolution, Evolutionary Biology Center, Uppsala University.
    Nilsson, Peter
    KTH, School of Biotechnology (BIO), Gene Technology.
    Global analysis of mRNA stability in the archaeon Sulfolobus2006In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 7, no 10, p. R99-Article in journal (Refereed)
    Abstract [en]

    Background: Transcript half-lives differ between organisms, and between groups of genes within the same organism. The mechanisms underlying these differences are not clear, nor are the biochemical properties that determine the stability of a transcript. To address these issues, genome-wide mRNA decay studies have been conducted in eukaryotes and bacteria. In contrast, relatively little is known about RNA stability in the third domain of life, Archaea. Here, we present a microarray-based analysis of mRNA half-lives in the hyperthermophilic crenarchaea Sulfolobus solfataricus and Sulfolobus acidocaldarius, constituting the first genome-wide study of RNA decay in archaea. Results: The two transcriptomes displayed similar half-life distributions, with medians of about five minutes. Growth-related genes, such as those involved in transcription, translation and energy production, were over-represented among unstable transcripts, whereas uncharacterized genes were over-represented among the most stable. Half-life was negatively correlated with transcript abundance and, unlike the situation in other organisms, also negatively correlated with transcript length. Conclusion: The mRNA half-life distribution of Sulfolobus species is similar to those of much faster growing bacteria, contrasting with the earlier observation that median mRNA half-life is proportional to the minimal length of the cell cycle. Instead, short half-lives may be a general feature of prokaryotic transcriptomes, possibly related to the absence of a nucleus and/or more limited post-transcriptional regulatory mechanisms. The pattern of growth-related transcripts being among the least stable in Sulfolobus may also indicate that the short half-lives reflect a necessity to rapidly reprogram gene expression upon sudden changes in environmental conditions.

  • 3. Brownstein, Catherine A.
    et al.
    Beggs, Alan H.
    Homer, Nils
    Merriman, Barry
    Yu, Timothy W.
    Flannery, Katherine C.
    DeChene, Elizabeth T.
    Towne, Meghan C.
    Savage, Sarah K.
    Price, Emily N.
    Holm, Ingrid A.
    Luquette, Lovelace J.
    Lyon, Elaine
    Majzoub, Joseph
    Neupert, Peter
    McCallie, David, Jr.
    Szolovits, Peter
    Willard, Huntington F.
    Mendelsohn, Nancy J.
    Temme, Renee
    Finkel, Richard S.
    Yum, Sabrina W.
    Medne, Livija
    Sunyaev, Shamil R.
    Adzhubey, Ivan
    Cassa, Christopher A.
    de Bakker, Paul I. W.
    Duzkale, Hatice
    Dworzynski, Piotr
    Fairbrother, William
    Francioli, Laurent
    Funke, Birgit H.
    Giovanni, Monica A.
    Handsaker, Robert E.
    Lage, Kasper
    Lebo, Matthew S.
    Lek, Monkol
    Leshchiner, Ignaty
    MacArthur, Daniel G.
    McLaughlin, Heather M.
    Murray, Michael F.
    Pers, Tune H.
    Polak, Paz P.
    Raychaudhuri, Soumya
    Rehm, Heidi L.
    Soemedi, Rachel
    Stitziel, Nathan O.
    Vestecka, Sara
    Supper, Jochen
    Gugenmus, Claudia
    Klocke, Bernward
    Hahn, Alexander
    Schubach, Max
    Menzel, Mortiz
    Biskup, Saskia
    Freisinger, Peter
    Deng, Mario
    Braun, Martin
    Perner, Sven
    Smith, Richard J. H.
    Andorf, Janeen L.
    Huang, Jian
    Ryckman, Kelli
    Sheffield, Val C.
    Stone, Edwin M.
    Bair, Thomas
    Black-Ziegelbein, E. Ann
    Braun, Terry A.
    Darbro, Benjamin
    DeLuca, Adam P.
    Kolbe, Diana L.
    Scheetz, Todd E.
    Shearer, Aiden E.
    Sompallae, Rama
    Wang, Kai
    Bassuk, Alexander G.
    Edens, Erik
    Mathews, Katherine
    Moore, Steven A.
    Shchelochkov, Oleg A.
    Trapane, Pamela
    Bossler, Aaron
    Campbell, Colleen A.
    Heusel, Jonathan W.
    Kwitek, Anne
    Maga, Tara
    Panzer, Karin
    Wassink, Thomas
    Van Daele, Douglas
    Azaiez, Hela
    Booth, Kevin
    Meyer, Nic
    Segal, Michael M.
    Williams, Marc S.
    Tromp, Gerard
    White, Peter
    Corsmeier, Donald
    Fitzgerald-Butt, Sara
    Herman, Gail
    Lamb-Thrush, Devon
    McBride, Kim L.
    Newsom, David
    Pierson, Christopher R.
    Rakowsky, Alexander T.
    Maver, Ales
    Lovrecic, Luca
    Palandacic, Anja
    Peterlin, Borut
    Torkamani, Ali
    Wedell, Anna
    Huss, Mikael
    Alexeyenko, Andrey
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Stockholm Bioinformatics Centre, Science for Life Laboratory, Solna, Sweden .
    Lindvall, Jessica M.
    Magnusson, Mans
    Nilsson, Daniel
    Stranneheim, Henrik
    Taylan, Fulya
    Gilissen, Christian
    Hoischen, Alexander
    van Bon, Bregje
    Yntema, Helger
    Nelen, Marcel
    Zhang, Weidong
    Sager, Jason
    Zhang, Lu
    Blair, Kathryn
    Kural, Deniz
    Cariaso, Michael
    Lennon, Greg G.
    Javed, Asif
    Agrawal, Saloni
    Ng, Pauline C.
    Sandhu, Komal S.
    Krishna, Shuba
    Veeramachaneni, Vamsi
    Isakov, Ofer
    Halperin, Eran
    Friedman, Eitan
    Shomron, Noam
    Glusman, Gustavo
    Roach, Jared C.
    Caballero, Juan
    Cox, Hannah C.
    Mauldin, Denise
    Ament, Seth A.
    Rowen, Lee
    Richards, Daniel R.
    San Lucas, F. Anthony
    Gonzalez-Garay, Manuel L.
    Caskey, C. Thomas
    Bai, Yu
    Huang, Ying
    Fang, Fang
    Zhang, Yan
    Wang, Zhengyuan
    Barrera, Jorge
    Garcia-Lobo, Juan M.
    Gonzalez-Lamuno, Domingo
    Llorca, Javier
    Rodriguez, Maria C.
    Varela, Ignacio
    Reese, Martin G.
    De la Vega, Francisco M.
    Kiruluta, Edward
    Cargill, Michele
    Hart, Reece K.
    Sorenson, Jon M.
    Lyon, Gholson J.
    Stevenson, David A.
    Bray, Bruce E.
    Moore, Barry M.
    Eilbeck, Karen
    Yandell, Mark
    Zhao, Hongyu
    Hou, Lin
    Chen, Xiaowei
    Yan, Xiting
    Chen, Mengjie
    Li, Cong
    Yang, Can
    Gunel, Murat
    Li, Peining
    Kong, Yong
    Alexander, Austin C.
    Albertyn, Zayed I.
    Boycott, Kym M.
    Bulman, Dennis E.
    Gordon, Paul M. K.
    Innes, A. Micheil
    Knoppers, Bartha M.
    Majewski, Jacek
    Marshall, Christian R.
    Parboosingh, Jillian S.
    Sawyer, Sarah L.
    Samuels, Mark E.
    Schwartzentruber, Jeremy
    Kohane, Isaac S.
    Margulies, David M.
    An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge2014In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 15, no 3, p. R53-Article in journal (Refereed)
    Abstract [en]

    Background: There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. Results: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. Conclusions: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups.

  • 4. Dick, G J
    et al.
    Andersson, Anders
    KTH, School of Biotechnology (BIO), Gene Technology.
    Baker, B J
    Simmons, S L
    Thomas, B C
    Yelton, A P
    Banfield, J F
    Community-wide analysis of microbial genome sequence signatures2009In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 10, no 8, p. R85-Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Analyses of DNA sequences from cultivated microorganisms have revealed genome-wide, taxa-specific nucleotide compositional characteristics, referred to as genome signatures. These signatures have far-reaching implications for understanding genome evolution and potential application in classification of metagenomic sequence fragments. However, little is known regarding the distribution of genome signatures in natural microbial communities or the extent to which environmental factors shape them. RESULTS: We analyzed metagenomic sequence data from two acidophilic biofilm communities, including composite genomes reconstructed for nine archaea, three bacteria, and numerous associated viruses, as well as thousands of unassigned fragments from strain variants and low-abundance organisms. Genome signatures, in the form of tetranucleotide frequencies analyzed by emergent self-organizing maps, segregated sequences from all known populations sharing < 50 to 60% average amino acid identity and revealed previously unknown genomic clusters corresponding to low-abundance organisms and a putative plasmid. Signatures were pervasive genome-wide. Clusters were resolved because intra-genome differences resulting from translational selection or protein adaptation to the intracellular (pH approximately 5) versus extracellular (pH approximately 1) environment were small relative to inter-genome differences. We found that these genome signatures stem from multiple influences but are primarily manifested through codon composition, which we propose is the result of genome-specific mutational biases. CONCLUSIONS: An important conclusion is that shared environmental pressures and interactions among coevolving organisms do not obscure genome signatures in acid mine drainage communities. Thus, genome signatures can be used to assign sequence fragments to populations, an essential prerequisite if metagenomics is to provide ecological and biochemical insights into the functioning of microbial communities.

  • 5.
    Hard, Joanna
    et al.
    Karolinska Inst, Dept Cell & Mol Biol, Solna, Sweden..
    Al Hakim, Ezeddin
    Karolinska Inst, Dept Cell & Mol Biol, Solna, Sweden..
    Kindblom, Marie
    Karolinska Inst, Dept Cell & Mol Biol, Solna, Sweden..
    Bjorklund, Asa K.
    Uppsala Univ, Dept Cell & Mol Biol, Natl Bioinformat Infrastruct Sweden, Scilifelab, Uppsala, Sweden..
    Sennblad, Bengt
    Uppsala Univ, Dept Cell & Mol Biol, Natl Bioinformat Infrastruct Sweden, Scilifelab, Uppsala, Sweden..
    Demirci, Ilke
    Karolinska Inst, Dept Cell & Mol Biol, Solna, Sweden..
    Paterlini, Marta
    Karolinska Inst, Dept Cell & Mol Biol, Solna, Sweden..
    Reu, Pedro
    Karolinska Inst, Dept Cell & Mol Biol, Solna, Sweden..
    Borgström, Erik
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology.
    Stahl, Patrik L.
    Karolinska Inst, Dept Cell & Mol Biol, Solna, Sweden..
    Michaelsson, Jakob
    Karolinska Inst, Dept Med, Ctr Infect Med, Huddinge, Sweden..
    Mold, Jeff E.
    Karolinska Inst, Dept Cell & Mol Biol, Solna, Sweden..
    Frisen, Jonas
    Karolinska Inst, Dept Cell & Mol Biol, Solna, Sweden..
    Conbase: a software for unsupervised discovery of clonal somatic mutations in single cells through read phasing2019In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 20, article id 68Article in journal (Refereed)
    Abstract [en]

    Accurate variant calling and genotyping represent major limiting factors for downstream applications of single-cell genomics. Here, we report Conbase for the identification of somatic mutations in single-cell DNA sequencing data. Conbase leverages phased read data from multiple samples in a dataset to achieve increased confidence in somatic variant calls and genotype predictions. Comparing the performance of Conbase to three other methods, we find that Conbase performs best in terms of false discovery rate and specificity and provides superior robustness on simulated data, in vitro expanded fibroblasts and clonal lymphocyte populations isolated directly from a healthy human donor.

  • 6.
    Hugerth, Luisa W.
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology.
    Larsson, John
    Alneberg, Johannes
    KTH, School of Biotechnology (BIO), Gene Technology.
    Lindh, Markus V.
    Legrand, Catherine
    Pinhassi, Jarone
    Andersson, Anders F.
    KTH, School of Biotechnology (BIO), Gene Technology.
    Metagenome-assembled genomes uncover a global brackish microbiome2015In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 16, article id 279Article in journal (Refereed)
    Abstract [en]

    Background: Microbes are main drivers of biogeochemical cycles in oceans and lakes. Although the genome is a foundation for understanding the metabolism, ecology and evolution of an organism, few bacterioplankton genomes have been sequenced, partly due to difficulties in cultivating them. Results: We use automatic binning to reconstruct a large number of bacterioplankton genomes from a metagenomic time-series from the Baltic Sea, one of world's largest brackish water bodies. These genomes represent novel species within typical freshwater and marine clades, including clades not previously sequenced. The genomes' seasonal dynamics follow phylogenetic patterns, but with fine-grained lineage-specific variations, reflected in gene-content. Signs of streamlining are evident in most genomes, and estimated genome sizes correlate with abundance variation across filter size fractions. Comparing the genomes with globally distributed metagenomes reveals significant fragment recruitment at high sequence identity from brackish waters in North America, but little from lakes or oceans. This suggests the existence of a global brackish metacommunity whose populations diverged from freshwater and marine relatives over 100,000 years ago, long before the Baltic Sea was formed (8000 years ago). This markedly contrasts to most Baltic Sea multicellular organisms, which are locally adapted populations of freshwater or marine counterparts. Conclusions: We describe the gene content, temporal dynamics and biogeography of a large set of new bacterioplankton genomes assembled from metagenomes. We propose that brackish environments exert such strong selection that lineages adapted to them flourish globally with limited influence from surrounding aquatic communities.

  • 7. Moreau, C.
    et al.
    Aksenov, N.
    Lorenzo, M. G.
    Segerman, B.
    Funk, C.
    Nilsson, Peter
    KTH, School of Biotechnology (BIO), Proteomics.
    Jansson, S.
    Tuominen, H.
    A genomic approach to investigate developmental cell death in woody tissues of Populus trees2005In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 6, no 4Article in journal (Refereed)
    Abstract [en]

    Background: Poplar ( Populus sp.) has emerged as the main model system for molecular and genetic studies of forest trees. A Populus expressed sequence tag ( EST) database (POPULUSDB) was previously created from 19 cDNA libraries each originating from different Populus tree tissues, and opened to the public in September 2004. We used this dataset for in silico transcript profiling of a particular process in the woody tissues of the Populus stem: the programmed death of xylem fibers. Results: One EST library in POPULUSDB originates from woody tissues of the Populus stem where xylem fibers undergo cell death. Analysis of EST abundances and library distribution within the POPULUSDB revealed a large number of previously uncharacterized transcripts that were unique in this library and possibly related to the death of xylem fibers. The in silico analysis was complemented by a microarray analysis utilizing a novel Populus cDNA array with a unigene set of 25,000 sequences. Conclusions: In silico analysis, combined with the microarray analysis, revealed the usefulness of non-normalized EST libraries in elucidating transcriptional regulation of previously uncharacterized physiological processes. The data suggested the involvement of two novel extracellular serine proteases, nodulin-like proteins and an Arabidopsis thaliana OPEN STOMATA 1 (AtOST1) homolog in signaling fiber-cell death, as well as mechanisms responsible for hormonal control, nutrient remobilization, regulation of vacuolar integrity and autolysis of the dying fibers.

  • 8. Quince, Christopher
    et al.
    Delmont, Tom O.
    Raguideau, Sebastien
    Alneberg, Johannes
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Darling, Aaron E.
    Collins, Gavin
    Eren, A. Murat
    DESMAN: a new tool for de novo extraction of strains from metagenomes2017In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 18, article id 181Article in journal (Refereed)
    Abstract [en]

    We introduce DESMAN for De novo Extraction of Strains from Metagenomes. Large multi-sample metagenomes are being generated but strain variation results in fragmentary co-assemblies. Current algorithms can bin contigs into metagenome-assembled genomes but are unable to resolve strain-level variation. DESMAN identifies variants in core genes and uses co-occurrence across samples to link variants into haplotypes and abundance profiles. These are then searched for against non-core genes to determine the accessory genome of each strain. We validated DESMAN on a complex 50-species 210-genome 96-sample synthetic mock data set and then applied it to the Tara Oceans microbiome.

  • 9.
    Sahlén, Pelin
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Abdullayev, Ilgar
    Ramsköld, Daniel
    Matskova, Liudmila
    Rilakovic, Nemanja
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lötstedt, Britta
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Albert, Thomas J.
    Lundeberg, Joakim
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Sandberg, Rickard
    Genome-wide mapping of promoter-anchored interactions with close to single-enhancer resolution2015In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 16, article id 156Article in journal (Refereed)
    Abstract [en]

    Although the locations of promoters and enhancers have been identified in several cell types, we still have limited information on their connectivity. We developed HiCap, which combines a 4-cutter restriction enzyme Hi-C with sequence capture of promoter regions. Applying the method to mouse embryonic stem cells, we identified promoter-anchored interactions involving 15,905 promoters and 71,984 distal regions. The distal regions were enriched for enhancer marks and transcription, and had a mean fragment size of only 699 bp - close to single-enhancer resolution. High-resolution maps of promoter-anchored interactions with HiCap will be important for detailed characterizations of chromatin interaction landscapes.

  • 10.
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics (closed 20130101).
    A new era for proteomics research?2008In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 9, no 11Article in journal (Refereed)
    Abstract [en]

    A report of the 7th Annual Human Proteome Organization (HUPO) Conference, Amsterdam, the Netherlands, 16-20 August 2008.

  • 11. Yosef, Nir
    et al.
    Käll, Lukas
    KTH, School of Biotechnology (BIO), Gene Technology.
    From sequence to structure to networks2008In: Genome Biology, ISSN 1465-6906, E-ISSN 1474-760X, Vol. 9, no 11Article in journal (Refereed)
    Abstract [en]

    A report on the 7th European Conference on Computational Biology (ECCB), Cagliari, Italy, 22-26 September 2008.

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