Dataset Information

Discovery of SNPs for individual identification by reduced representation sequencing of moose (Alces alces).

ABSTRACT: Monitoring of wild animal populations is challenging, yet reliable information about population processes is important for both management and conservation efforts. Access to molecular markers, such as SNPs, enables population monitoring through genotyping of various DNA sources. We have developed 96 high quality SNP markers for individual identification of moose (Alces alces), an economically and ecologically important top-herbivore in boreal regions. Reduced representation libraries constructed from 34 moose were high-throughput de novo sequenced, generating nearly 50 million read pairs. About 50 000 stacks of aligned reads containing one or more SNPs were discovered with the Stacks pipeline. Several quality criteria were applied on the candidate SNPs to find markers informative on the individual level and well representative for the population. An empirical validation by genotyping of sequenced individuals and additional moose, resulted in the selection of a final panel of 86 high quality autosomal SNPs. Additionally, five sex-specific SNPs and five SNPs for sympatric species diagnostics are included in the panel. The genotyping error rate was 0.002 for the total panel and probability of identities were low enough to separate individuals with high confidence. Moreover, the autosomal SNPs were highly informative also for population level analyses. The potential applications of this SNP panel are thus many including investigations of population size, sex ratios, relatedness, reproductive success and population structure. Ideally, SNP-based studies could improve today's population monitoring and increase our knowledge about moose population dynamics.

SUBMITTER: Blahed IM

PROVIDER: S-EPMC5976195 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Discovery of SNPs for individual identification by reduced representation sequencing of moose (Alces alces).

Blåhed Ida-Maria IM Königsson Helena H Ericsson Göran G Spong Göran G

PloS one 20180530 5

Monitoring of wild animal populations is challenging, yet reliable information about population processes is important for both management and conservation efforts. Access to molecular markers, such as SNPs, enables population monitoring through genotyping of various DNA sources. We have developed 96 high quality SNP markers for individual identification of moose (Alces alces), an economically and ecologically important top-herbivore in boreal regions. Reduced representation libraries constructe ...[more]

PMID: 29847564

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Project description:Given recent and abrupt declines in the abundance of moose (Alces alces) throughout parts of Minnesota and elsewhere in North America, accurately estimating statewide population trends and demographic parameters is a high priority for their continued management and conservation. Statistical population reconstruction using integrated population models provides a flexible framework for combining information from multiple studies to produce robust estimates of population abundance, recruitment, and survival. We used this framework to combine aerial survey data and survival data from telemetry studies to recreate trends and demographics of moose in northeastern Minnesota, USA, from 2005 to 2020. Statistical population reconstruction confirmed the sharp decline in abundance from an estimated 7,841 (90% CI = 6,702-8,933) in 2009 to 3,386 (90% CI = 2,681-4,243) animals in 2013, but also indicated that abundance has remained relatively stable since then, except for a slight decline to 3,163 (90% CI = 2,403-3,718) in 2020. Subsequent stochastic projection of the population from 2021 to 2030 suggests that this modest decline will continue for the next 10 years. Both annual adult survival and per-capita recruitment (number of calves that survived to 1 year per adult female alive during the previous year) decreased substantially in years 2005 and 2019, from 0.902 (SE = 0.043) to 0.689 (SE = 0.061) and from 0.386 (SE = 0.030) to 0.303 (SE = 0.051), respectively. Sensitivity analysis revealed that moose abundance was more sensitive to fluctuations in adult survival than recruitment; thus, we conclude that the steep decline in 2013 was driven primarily by decreasing adult survival. Our analysis demonstrates the potential utility of using statistical population reconstruction to monitor moose population trends and to identify population declines more quickly. Future studies should focus on providing better estimates of per-capita recruitment, using pregnancy rates and calf survival, which can then be incorporated into reconstruction models to help improve estimates of population change through time.

Project description:BACKGROUND:This study demonstrates the use of reduced-representation genotyping to provide preliminary identifications for thermophilic bacterial isolates. The approach combines restriction enzyme digestion and PCR with next-generation sequencing to provide thousands of short-read sequences from across the bacterial genomes. Isolates were obtained from compost, hot water systems, and artesian bores of the Great Artesian Basin. Genomic DNA was double-digested with two combinations of restriction enzymes followed by PCR amplification, using a commercial provider of DArTseq™, Diversity Arrays Technology Pty Ltd. (Canberra, Australia). The resulting fragments which formed a reduced-representation of approximately 2.3% of the genome were sequenced. The sequence tags obtained were aligned against all available RefSeq bacterial genome assemblies by BLASTn to identify the nearest reference genome. RESULTS:Based on the preliminary identifications, a total of 99 bacterial isolates were identified to species level, from which 8 isolates were selected for whole-genome sequencing to assess the identification results. Novel species and strains were discovered within this set of isolates. The preliminary identifications obtained by reduced-representation genotyping, as well as identifications obtained by BLASTn alignment of the 16S rRNA gene sequence, were compared with those derived from the whole-genome sequence data, using the same RefSeq sequence database for the three methods. Identifications obtained with reduced-representation sequencing agreed with the identifications provided by whole-genome sequencing in 100% of cases. The identifications produced by BLASTn alignment of 16S rRNA gene sequence to the same database differed from those provided by whole-genome sequencing in 37.5% of cases, and produced ambiguous identifications in 50% of cases. CONCLUSIONS:Previously, this method has been successfully demonstrated for use in bacterial identification for medical microbiology. This study demonstrates the first successful use of DArTseq™ for preliminary identification of thermophilic bacterial isolates, providing results in complete agreement with those obtained from whole-genome sequencing of the same isolates. The growing database of bacterial genome sequences provides an excellent resource for alignment of reduced-representation sequence data for identification purposes, and as the available sequenced genomes continue to grow, the technique will become more effective.

Dataset Information

Discovery of SNPs for individual identification by reduced representation sequencing of moose (Alces alces).

Publications

Discovery of SNPs for individual identification by reduced representation sequencing of moose (Alces alces).

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