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10.1111/1755-0998.70014 http://scihub22266oqcxt.onion/10.1111/1755-0998.70014 40642868!ä!40642868 Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=40642868&cmd=llinks): Failed to open stream: HTTP request failed! 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Conserved Sequence Identification Within Large Genomic Datasets Using Unikseq2 : Application in Environmental DNA Assay Development |pdf=|usr=}}{{40642868}} gab.com Text Conserved Sequence Identification Within Large Genomic Datasets Using Unikseq2 : Application in Environmental DNA Assay Development JO: Mol Ecol Resour http://www.kidney.de/pget.php?&tw=1&pmid=40642868 #FOAvip Identification of conserved genomic sequences and their utilisation as anchor points for clade detection and/or characterisation is a mainstay in ecological studies. For environmental DNA (eDNA) assays, effective processing of large genomic datasets is crucial for reliable species detection in biodiversity monitoring. While considerable focus has been on developing robust species-targeted assays, eDNA assays with broader taxonomic coverage (e.g., detecting any species within a taxonomic group such as fish), can significantly streamline environmental monitoring, especially when detecting individual species' DNA proves challenging. Designing such assays requires identifying conserved regions representing the target taxonomic group, a chiefly manual task that is often labor-intensive and error-prone, particularly when working with large sequence datasets. To address these challenges, we present unikseq2, an enhanced, alignment-free, k-mer-based tool for identifying unique and conserved sequences. It introduces a new functionality to identify sequence conservation among target species, enabling more informed marker selection for applications such as universal primer design. This automates sequence selection in large-scale mitochondrial genome datasets eliminating the need for manual inspection of computationally costly multiple sequence alignments. Herein, we demonstrate unikseq2's capabilities by developing and validating eDNA assays for various taxa, including Osteichthyes (bony fishes), the Salmonidae family (salmon and trout), Myotis bats and Cervus deer. Unikseq2-based eDNA assays allow for accurate detection across multiple taxonomic levels, from genus to class, enhancing the flexibility, scalability and reliability of eDNA tools in environmental monitoring. By leveraging genomic data from public repositories, unikseq2 supports efficient, reproducible assay design, making it an invaluable tool for a wide range of ecological and biodiversity research applications. Twit Text FOAVip Conserved Sequence Identification Within Large Genomic Datasets Using Unikseq2 : Application in Environmental DNA Assay Development ????Mol Ecol Resour http://www.kidney.de/pget.php?&tw=1&pmid=40642868 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=40642868 #FOAvip English Wikipedia <ref>{{Cite pmid|40642868}}</ref> Conserved Sequence Identification Within Large Genomic Datasets Using Unikseq2 : Application in Environmental DNA Assay Development #MMPMID40642868 Lopez MLD; Warren RL; Allison MJ; Coombe L; Imbery JJ; Birol I; Helbing CC Mol Ecol Resour 2025[Jul]; ä (ä): e70014 PMID40642868show ga Identification of conserved genomic sequences and their utilisation as anchor points for clade detection and/or characterisation is a mainstay in ecological studies. For environmental DNA (eDNA) assays, effective processing of large genomic datasets is crucial for reliable species detection in biodiversity monitoring. While considerable focus has been on developing robust species-targeted assays, eDNA assays with broader taxonomic coverage (e.g., detecting any species within a taxonomic group such as fish), can significantly streamline environmental monitoring, especially when detecting individual species' DNA proves challenging. Designing such assays requires identifying conserved regions representing the target taxonomic group, a chiefly manual task that is often labor-intensive and error-prone, particularly when working with large sequence datasets. To address these challenges, we present unikseq2, an enhanced, alignment-free, k-mer-based tool for identifying unique and conserved sequences. It introduces a new functionality to identify sequence conservation among target species, enabling more informed marker selection for applications such as universal primer design. This automates sequence selection in large-scale mitochondrial genome datasets eliminating the need for manual inspection of computationally costly multiple sequence alignments. Herein, we demonstrate unikseq2's capabilities by developing and validating eDNA assays for various taxa, including Osteichthyes (bony fishes), the Salmonidae family (salmon and trout), Myotis bats and Cervus deer. Unikseq2-based eDNA assays allow for accurate detection across multiple taxonomic levels, from genus to class, enhancing the flexibility, scalability and reliability of eDNA tools in environmental monitoring. By leveraging genomic data from public repositories, unikseq2 supports efficient, reproducible assay design, making it an invaluable tool for a wide range of ecological and biodiversity research applications. äConserved Sequence Identification Within Large Genomic Datasets Using (epmc).pdf DeepDyve Pubget Overpricing