| 1. |
- Armstrong, Joel, et al.
(författare)
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Progressive Cactus is a multiple-genome aligner for the thousand-genome era
- 2020
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Ingår i: Nature. - : Springer Nature. - 0028-0836 .- 1476-4687. ; 587:7833, s. 246-251
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Tidskriftsartikel (refereegranskat)abstract
- New genome assemblies have been arriving at a rapidly increasing pace, thanks to decreases in sequencing costs and improvements in third-generation sequencing technologies(1-3). For example, the number of vertebrate genome assemblies currently in the NCBI (National Center for Biotechnology Information) database(4) increased by more than 50% to 1,485 assemblies in the year from July 2018 to July 2019. In addition to this influx of assemblies from different species, new human de novo assemblies(5) are being produced, which enable the analysis of not only small polymorphisms, but also complex, large-scale structural differences between human individuals and haplotypes. This coming era and its unprecedented amount of data offer the opportunity to uncover many insights into genome evolution but also present challenges in how to adapt current analysis methods to meet the increased scale. Cactus(6), a reference-free multiple genome alignment program, has been shown to be highly accurate, but the existing implementation scales poorly with increasing numbers of genomes, and struggles in regions of highly duplicated sequences. Here we describe progressive extensions to Cactus to create Progressive Cactus, which enables the reference-free alignment of tens to thousands of large vertebrate genomes while maintaining high alignment quality. We describe results from an alignment of more than 600 amniote genomes, which is to our knowledge the largest multiple vertebrate genome alignment created so far. The Progressive Cactus program can create reference-free alignments of hundreds of large vertebrate genomes efficiently, and is used for the alignment of more than 600 amniote genomes.
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| 2. |
- Casewell, Nicholas R, et al.
(författare)
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Solenodon genome reveals convergent evolution of venom in eulipotyphlan mammals.
- 2019
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 116:51, s. 25745-25755
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Tidskriftsartikel (refereegranskat)abstract
- Venom systems are key adaptations that have evolved throughout the tree of life and typically facilitate predation or defense. Despite venoms being model systems for studying a variety of evolutionary and physiological processes, many taxonomic groups remain understudied, including venomous mammals. Within the order Eulipotyphla, multiple shrew species and solenodons have oral venom systems. Despite morphological variation of their delivery systems, it remains unclear whether venom represents the ancestral state in this group or is the result of multiple independent origins. We investigated the origin and evolution of venom in eulipotyphlans by characterizing the venom system of the endangered Hispaniolan solenodon (Solenodon paradoxus). We constructed a genome to underpin proteomic identifications of solenodon venom toxins, before undertaking evolutionary analyses of those constituents, and functional assessments of the secreted venom. Our findings show that solenodon venom consists of multiple paralogous kallikrein 1 (KLK1) serine proteases, which cause hypotensive effects in vivo, and seem likely to have evolved to facilitate vertebrate prey capture. Comparative analyses provide convincing evidence that the oral venom systems of solenodons and shrews have evolved convergently, with the 4 independent origins of venom in eulipotyphlans outnumbering all other venom origins in mammals. We find that KLK1s have been independently coopted into the venom of shrews and solenodons following their divergence during the late Cretaceous, suggesting that evolutionary constraints may be acting on these genes. Consequently, our findings represent a striking example of convergent molecular evolution and demonstrate that distinct structural backgrounds can yield equivalent functions.
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| 3. |
- Grabherr, Manfred G, et al.
(författare)
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Genome-wide synteny through highly sensitive sequence alignment : Satsuma
- 2010
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 26:9, s. 1145-1151
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Tidskriftsartikel (refereegranskat)abstract
- MOTIVATION: Comparative genomics heavily relies on alignments of large and often complex DNA sequences. From an engineering perspective, the problem here is to provide maximum sensitivity (to find all there is to find), specificity (to only find real homology) and speed (to accommodate the billions of base pairs of vertebrate genomes). RESULTS: Satsuma addresses all three issues through novel strategies: (i) cross-correlation, implemented via fast Fourier transform; (ii) a match scoring scheme that eliminates almost all false hits; and (iii) an asynchronous 'battleship'-like search that allows for aligning two entire fish genomes (470 and 217 Mb) in 120 CPU hours using 15 processors on a single machine. AVAILABILITY: Satsuma is part of the Spines software package, implemented in C++ on Linux. The latest version of Spines can be freely downloaded under the LGPL license from http://www.broadinstitute.org/science/programs/genome-biology/spines/.
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| 4. |
- Wucher, Valentin, et al.
(författare)
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FEELnc : a tool for long non-coding RNA annotation and its application to the dog transcriptome
- 2017
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Ingår i: Nucleic Acids Research. - : Oxford University Press (OUP). - 0305-1048 .- 1362-4962. ; 45:8
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Tidskriftsartikel (refereegranskat)abstract
- Whole transcriptome sequencing (RNA-seq) has become a standard for cataloguing and monitoring RNA populations. One of the main bottlenecks, however, is to correctly identify the different classes of RNAs among the plethora of reconstructed transcripts, particularly those that will be translated (mRNAs) from the class of long non-coding RNAs (lncRNAs). Here, we present FEELnc (FlExible Extraction of LncRNAs), an alignment-free program that accurately annotates lncRNAs based on a Random Forest model trained with general features such as multi k-mer frequencies and relaxed open reading frames. Benchmarking versus five state-of-the-art tools shows that FEELnc achieves similar or better classification performance on GENCODE and NONCODE data sets. The program also provides specific modules that enable the user to fine-tune classification accuracy, to formalize the annotation of lncRNA classes and to identify lncRNAs even in the absence of a training set of non-coding RNAs. We used FEELnc on a real data set comprising 20 canine RNA-seq samples produced by the European LUPA consortium to substantially expand the canine genome annotation to include 10 374 novel lncRNAs and 58 640 mRNA transcripts. FEELnc moves beyond conventional coding potential classifiers by providing a standardized and complete solution for annotating lncRNAs and is freely available at https://github.com/tderrien/FEELnc.
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