| 1. |
- Formenti, Giulio, et al.
(författare)
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The era of reference genomes in conservation genomics
- 2022
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Ingår i: Trends in Ecology & Evolution. - : Elsevier. - 0169-5347 .- 1872-8383. ; 37:3, s. 197-202
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Progress in genome sequencing now enables the large-scale generation of reference genomes. Various international initiatives aim to generate reference genomes representing global biodiversity. These genomes provide unique insights into genomic diversity and architecture, thereby enabling comprehensive analyses of population and functional genomics, and are expected to revolutionize conservation genomics.
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| 2. |
- Theissinger, Kathrin, et al.
(författare)
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How genomics can help biodiversity conservation
- 2023
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Ingår i: Trends in Genetics. - : Elsevier. - 0168-9525 .- 1362-4555. ; 39:7, s. 545-559
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Forskningsöversikt (refereegranskat)abstract
- The availability of public genomic resources can greatly assist biodiversity assessment, conservation, and restoration efforts by providing evidence for scientifically informed management decisions. Here we survey the main approaches and applications in biodiversity and conservation genomics, considering practical factors, such as cost, time, prerequisite skills, and current shortcomings of applications. Most approaches perform best in combination with reference genomes from the target species or closely related species. We review case studies to illustrate how reference genomes can facilitate biodiversity research and conservation across the tree of life. We conclude that the time is ripe to view reference genomes as fundamental resources and to integrate their use as a best practice in conservation genomics.
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| 3. |
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| 4. |
- Palsboll, Per J., et al.
(författare)
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Detecting populations in the 'ambiguous' zone : kinship-based estimation of population structure at low genetic divergence
- 2010
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Ingår i: Molecular ecology notes. - : Wiley. - 1755-098X. ; 10:5, s. 797-805
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Tidskriftsartikel (refereegranskat)abstract
- Identifying population structure is one of the most common and important objectives of spatial analyses using population genetic data. Population structure is detected either by rejecting the null hypothesis of a homogenous distribution of genetic variation, or by estimating low migration rates. Issues arise with most current population genetic inference methods when the genetic divergence is low among putative populations. Low levels of genetic divergence may be as a result of either high ongoing migration or historic high migration but no current, ongoing migration. We direct attention to recent developments in the use of the tempo-spatial distribution of closely related individuals to detect population structure or estimate current migration rates. These 'kinship-based' approaches complement more traditional population-based genetic inference methods by providing a means to detect population structure and estimate current migration rates when genetic divergence is low. However, for kinship-based methods to become widely adopted, formal estimation procedures applicable to a range of species life histories are needed.
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| 5. |
- Palsboll, Per J., et al.
(författare)
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Inferring recent historic abundance from current genetic diversity
- 2013
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Ingår i: Molecular Ecology. - : Wiley. - 0962-1083 .- 1365-294X. ; 22:1, s. 22-40
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Forskningsöversikt (refereegranskat)abstract
- Recent historic abundance is an elusive parameter of great importance for conserving endangered species and understanding the pre-anthropogenic state of the biosphere. The number of studies that have used population genetic theory to estimate recent historic abundance from contemporary levels of genetic diversity has grown rapidly over the last two decades. Such assessments often yield unexpectedly large estimates of historic abundance. We review the underlying theory and common practices of estimating recent historic abundance from contemporary genetic diversity, and critically evaluate the potential issues at various estimation steps. A general issue of mismatched spatio-temporal scales between the estimation itself and the objective of the estimation emerged from our assessment; genetic diversitybased estimates of recent historic abundance represent long-term averages, whereas the objective typically is an estimate of recent abundance for a specific population. Currently, the most promising approach to estimate the difference between recent historic and contemporary abundance requires that genetic data be collected from samples of similar spatial and temporal duration. Novel genome-enabled inference methods may be able to utilize additional information of dense genome-wide distributions of markers, such as of identity-by-descent tracts, to infer recent historic abundance from contemporary samples only.
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