Genomics and the future of conservation genetics. Nat Rev Genet

University of Montana, Missoula, 59812, USA.
Nature Reviews Genetics (Impact Factor: 36.98). 10/2010; 11(10):697-709. DOI: 10.1038/nrg2844
Source: PubMed


We will soon have complete genome sequences from thousands of species, as well as from many individuals within species. This coming explosion of information will transform our understanding of the amount, distribution and functional significance of genetic variation in natural populations. Now is a crucial time to explore the potential implications of this information revolution for conservation genetics and to recognize limitations in applying genomic tools to conservation issues. We identify and discuss those problems for which genomics will be most valuable for curbing the accelerating worldwide loss of biodiversity. We also provide guidance on which genomics tools and approaches will be most appropriate to use for different aspects of conservation.

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    • "For example, Dixon et al. (2015) have identified genomic regions potentially involved in the response to selection for thermal tolerance in the coral Acropora millepora . This gives some clues on the possibility of adaptive evolution in future environments, which is essential for conservation (Allendorf et al. 2010). Then, detecting climatic variables and polymorphisms potentially involved in local adaptation can improve models of future species dynamics under climate change (Manel et al. 2012). "
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    ABSTRACT: Genome scans represent powerful approaches to investigate the action of natural selection on the genetic variation of natural populations and to better understand local adaptation. This is very useful for example in the field of conservation biology and evolutionary biology. Thanks to Next Generation Sequencing, genomic resources are growing exponentially, improving genome scan analyses in non-model species. Thousands of SNPs called using Reduced Representation Sequencing are increasingly used in genome scans. Besides, genomes are also becoming more available, allowing better processing of short-read data, offering physical localisation of variants, and improving haplotype reconstruction and data imputation. Ultimately, genomes are also becoming the raw material for selection inferences. Here, we discuss how the increasing availability of such genomic resources, notably genomes, influences the detection of signals of selection. Mainly, increasing data density and having the information of physical linkage data expand genome scans by i) improving the overall quality of the data; ii) helping the reconstruction of demographic history for the population studied to decrease false positive rates; iii) improving the statistical power of methods to detect the signal of selection. Of particular importance, the availability of a high quality reference genome can improve the detection of the signal of selection by i) allowing matching the potential candidate loci to linked coding regions under selection, ii) rapidly moving the investigation to the gene and function, and iii) ensuring that the highly variable regions in coding regions of the genomes are also investigated. For all those reasons, using reference genomes in analyses of genome scans is highly recommended. This article is protected by copyright. All rights reserved.
    Full-text · Article · Mar 2016 · Molecular Ecology
    • "Moreover, the probabilistic approach of pedigree analysis does not take into account the stochastic nature of recombination (McQuillan et al., 2008). Recently, with the availability of highdensity single nucleotide polymorphism (SNP) arrays, F can be estimated accurately in absence of pedigree information (Allendorf et al., 2010). There are two categories of genomic inbreeding measures based on genome-wide SNPs. "
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    ABSTRACT: In the local breeds with small population size, one of the most important problems is the increase of inbreeding coefficient (F). High levels of inbreeding lead to reduced genetic diversity and inbreeding depression. The availability of high-density single nucleotide polymorphism (SNP) arrays has facilitated the quantification of F by genomic markers in farm animals. Runs of homozygosity (ROH) are contiguous lengths of homozygous genotypes and represent an estimate of the degree of autozygosity at genome-wide level. The current study aims to quantify the genomic F derived from ROH (FROH) in three local dairy cattle breeds. FROH values were compared with F estimated from the genomic relationship matrix (FGRM), based on the difference between observed v. expected number of homozygous genotypes (FHOM) and the genomic homozygosity of individual i (FMOL i ). The molecular coancestry coefficient (fMOL ij ) between individuals i and j was also estimated. Individuals of Cinisara (71), Modicana (72) and Reggiana (168) were genotyped with the 50K v2 Illumina BeadChip. Genotypes from 96 animals of Italian Holstein cattle breed were also included in the analysis. We used a definition of ROH as tracts of homozygous genotypes that were >4 Mb. Among breeds, 3661 ROH were identified. Modicana showed the highest mean number of ROH per individual and the highest value of FROH, whereas Reggiana showed the lowest ones. Differences among breeds existed for the ROH lengths. The individuals of Italian Holstein showed high number of short ROH segments, related to ancient consanguinity. Similar results showed the Reggiana with some extreme animals with segments covering 400 Mb and more of genome. Modicana and Cinisara showed similar results between them with the total length of ROH characterized by the presence of large segments. High correlation was found between FHOM and FROH ranged from 0.83 in Reggiana to 0.95 in Cinisara and Modicana. The correlations among FROH and other estimated F coefficients were generally lower ranged from 0.45 (FMOL i −FROH) in Cinisara to 0.17 (FGRM−FROH) in Modicana. On the basis of our results, recent inbreeding was observed in local breeds, considering that 16 Mb segments are expected to present inbreeding up to three generations ago. Our results showed the necessity of implementing conservation programs to control the rise of inbreeding and coancestry in the three Italian local dairy cattle breeds.
    No preview · Article · Jan 2016 · animal
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    • "However, QTL analysis has historically been difficult to conduct in nonmodel organisms due the absence of genomic resources and the large number of genetic markers required (Slate 2005). The proliferation of genomic data provides a potential solution to this limitation (reviewed in Allendorf et al. 2010). Genotypingby-sequencing (GBS) techniques now make it possible to screen thousands of markers in hundreds of individuals (Tonsor 2012). "
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    ABSTRACT: Understanding the genetic architecture of phenotypic traits can provide important information about the mechanisms and genomic regions involved in local adaptation and speciation. Here, we used genotyping-by-sequencing and a combination of previously published and newly generated data to construct sex-specific linkage maps for sockeye salmon (Oncorhynchus nerka). We then used the denser female linkage map to conduct quantitative trait locus (QTL) analysis for 4 phenotypic traits in 3 families. The female linkage map consisted of 6322 loci distributed across 29 linkage groups and was 4082 cM long, and the male map contained 2179 loci found on 28 linkage groups and was 2291 cM long. We found 26 QTL: 6 for thermotolerance, 5 for length, 9 for weight, and 6 for condition factor. QTL were distributed nonrandomly across the genome and were often found in hotspots containing multiple QTL for a variety of phenotypic traits. These hotspots may represent adaptively important regions and are excellent candidates for future research. Comparing our results with studies in other salmonids revealed several regions with overlapping QTL for the same phenotypic trait, indicating these regions may be adaptively important across multiple species. Altogether, our study demonstrates the utility of genomic data for investigating the genetic basis of important phenotypic traits. Additionally, the linkage map created here will enable future research on the genetic basis of phenotypic traits in salmon.
    Full-text · Article · Dec 2015 · The Journal of heredity
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