| 1. |
- Larson, Greger, et al.
(författare)
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Rethinking dog domestication by integrating genetics, archeology, and biogeography
- 2012
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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. ; 109, s. 8878-8883
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Tidskriftsartikel (refereegranskat)abstract
- The dog was the first domesticated animal but it remains uncertain when the domestication process began and whether it occurred just once or multiple times across the Northern Hemisphere. To ascertain the value of modern genetic data to elucidate the origins of dog domestication, we analyzed 49,024 autosomal SNPs in 1,375 dogs (representing 35 breeds) and 19 wolves. After combining our data with previously published data, we contrasted the genetic signatures of 121 breeds with a worldwide archeological assessment of the earliest dog remains. Correlating the earliest archeological dogs with the geographic locations of 14 so-called "ancient" breeds (defined by their genetic differentiation) resulted in a counterintuitive pattern. First, none of the ancient breeds derive from regions where the oldest archeological remains have been found. Second, three of the ancient breeds (Basenjis, Dingoes, and New Guinea Singing Dogs) come from regions outside the natural range of Canis lupus (the dog's wild ancestor) and where dogs were introduced more than 10,000 y after domestication. These results demonstrate that the unifying characteristic among all genetically distinct so-called ancient breeds is a lack of recent admixture with other breeds likely facilitated by geographic and cultural isolation. Furthermore, these genetically distinct ancient breeds only appear so because of their relative isolation, suggesting that studies of modern breeds have yet to shed light on dog origins. We conclude by assessing the limitations of past studies and how next-generation sequencing of modern and ancient individuals may unravel the history of dog domestication.
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| 2. |
- 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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