| 1. |
- Ahola, Virpi, et al.
(författare)
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The Glanville fritillary genome retains an ancient karyotype and reveals selective chromosomal fusions in Lepidoptera
- 2014
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 5, s. 4737-
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Tidskriftsartikel (refereegranskat)abstract
- Previous studies have reported that chromosome synteny in Lepidoptera has been well conserved, yet the number of haploid chromosomes varies widely from 5 to 223. Here we report the genome (393 Mb) of the Glanville fritillary butterfly (Melitaea cinxia; Nymphalidae), a widely recognized model species in metapopulation biology and eco-evolutionary research, which has the putative ancestral karyotype of n = 31. Using a phylogenetic analyses of Nymphalidae and of other Lepidoptera, combined with orthologue-level comparisons of chromosomes, we conclude that the ancestral lepidopteran karyotype has been n = 31 for at least 140 My. We show that fusion chromosomes have retained the ancestral chromosome segments and very few rearrangements have occurred across the fusion sites. The same, shortest ancestral chromosomes have independently participated in fusion events in species with smaller karyotypes. The short chromosomes have higher rearrangement rate than long ones. These characteristics highlight distinctive features of the evolutionary dynamics of butterflies and moths.
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| 2. |
- Roslin, Tomas, et al.
(författare)
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A molecular-based identification resource for the arthropods of Finland
- 2022
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Ingår i: Molecular Ecology Resources. - : Wiley. - 1755-098X .- 1755-0998. ; 22:2, s. 803-822
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Tidskriftsartikel (refereegranskat)abstract
- To associate specimens identified by molecular characters to other biological knowledge, we need reference sequences annotated by Linnaean taxonomy. In this study, we (1) report the creation of a comprehensive reference library of DNA barcodes for the arthropods of an entire country (Finland), (2) publish this library, and (3) deliver a new identification tool for insects and spiders, as based on this resource. The reference library contains mtDNA COI barcodes for 11,275 (43%) of 26,437 arthropod species known from Finland, including 10,811 (45%) of 23,956 insect species. To quantify the improvement in identification accuracy enabled by the current reference library, we ran 1000 Finnish insect and spider species through the Barcode of Life Data system (BOLD) identification engine. Of these, 91% were correctly assigned to a unique species when compared to the new reference library alone, 85% were correctly identified when compared to BOLD with the new material included, and 75% with the new material excluded. To capitalize on this resource, we used the new reference material to train a probabilistic taxonomic assignment tool, FinPROTAX, scoring high success. For the full-length barcode region, the accuracy of taxonomic assignments at the level of classes, orders, families, subfamilies, tribes, genera, and species reached 99.9%, 99.9%, 99.8%, 99.7%, 99.4%, 96.8%, and 88.5%, respectively. The FinBOL arthropod reference library and FinPROTAX are available through the Finnish Biodiversity Information Facility (www.laji.fi) at https://laji.fi/en/theme/protax. Overall, the FinBOL investment represents a massive capacity-transfer from the taxonomic community of Finland to all sectors of society.
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| 3. |
- Salmela, Leena, et al.
(författare)
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Gap Filling as Exact Path Length Problem
- 2016
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Ingår i: Journal of Computational Biology. - : Mary Ann Liebert Inc. - 1066-5277 .- 1557-8666. ; 23:5, s. 347-361
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Tidskriftsartikel (refereegranskat)abstract
- One of the last steps in a genome assembly project is filling the gaps between consecutive contigs in the scaffolds. This problem can be naturally stated as finding an s-t path in a directed graph whose sum of arc costs belongs to a given range (the estimate on the gap length). Here s and t are any two contigs flanking a gap. This problem is known to be NP-hard in general. Here we derive a simpler dynamic programming solution than already known, pseudo-polynomial in the maximum value of the input range. We implemented various practical optimizations to it, and compared our exact gap-filling solution experimentally to popular gap-filling tools. Summing over all the bacterial assemblies considered in our experiments, we can in total fill 76% more gaps than the best previous tool, and the gaps filled by our method span 136% more sequence. Furthermore, the error level of the newly introduced sequence is comparable to that of the previous tools. The experiments also show that our exact approach does not easily scale to larger genomes, where the problem is in general difficult for all tools.
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