The ability to examine thousands of genetic markers
with relative ease will make it possible to answer many
important questions in conservation that have been
intractable until now. Simply increasing the number of
neutral loci that we can screen will increase the power
and accuracy of estimating a variety of important
parameters in conservation (for example, kin rela-
tionships and inbreeding coefficients (F)). However,
the most exciting contributions of genomics to con-
servation are those that will allow new questions to
be addressed in a wide variety of species (BOX 1). For
instance, it should be possible to estimate the effect
size and distribution of loci affecting fitness across the
genome or to ask whether the loci are coincident across
populations1,2 (FIG. 1).
Genomic approaches are currently being used pri-
marily with a few species for which genomic informa-
tion and tools are available3; for example, wolves, bison
and bighorn sheep have been studied using genomic
tools developed in related domestic species4. However,
the range of species is expanding as new approaches are
developed that are not dependent on genomic infor-
mation from closely related species5,6. For example,
van Bers et al.7 obtained over 16 million short sequence
reads and conducted de novo assembly of 550,000 contigs
covering 2.5% of the genome to discover 20,000 novel
SNPs in the great tit (Parus major). These markers will
be used for quantitative trait locus mapping and whole
genome association studies.
In addition, multiple taxa can be combined in a sin-
gle sequencing analysis using genomic techniques that
can assay large amounts of variable DNA sequence8.
The application of metagenomics to conservation is still
in its early stages, but shows promise. First, functional
metagenomics of microbial communities provides a
novel perspective on ecosystem processes, such as
nutrient and energy flux. Although some studies have
compared functions across a broad scale of biomes9,
similar comparative approaches may identify aspects
of ecosystem function across sites within a habitat.
The second potential application of metagenomics to
conservation is in assessment of physiological con-
dition of individual organisms. For instance, Vega
Thurber et al.10 have found numerous shifts in the
endosymbiont community of corals in response to
multiple stressors, such as reduced pH, increased
nutrients and increased temperature. Third, a metage-
nomic analysis of human faecal samples catalogued
3.3 million microbial genomes and found substantial
differences in the microbial metagenome between
healthy individuals and those with inflammatory
bowel disease11. It may be possible in the future to
apply metagenomic techniques to faecal samples from
wildlife species to assess physiological states, such as
Genomics already has provided some interesting
surprises, such as the discovery of adaptive loci that
show extremely high genetic divergence between popu-
lations of marine fish for which there is virtually no
allele frequency divergence at neutral loci12 (BOX 2). In
addition, a multi-faceted genomic approach has pro-
vided important insights into the treatment of a facial
tumour disease that threatens the persistence of the
Tasmanian devil (Sarcophilus laniarius)13.
*Division of Biological
Sciences, University of
Montana 59812, USA.
‡School of Biological Sciences,
Victoria University of
§Center for Ecology and
University of Oregon, Eugene,
Oregon 97403, USA.
||Department of Zoology,
Oregon State University,
Corvallis, Oregon 97331, USA.
¶Flathead Lake Biological
Station, Division of Biological
Sciences, University of
Montana, Polson, Montana
#Centro de Investigação em
Biodiversidade e Recursos
Genéticos, Universidade do
Porto, 4485-661 Vairão,
A locus that has no effect
on adaptation because
all genotypes have the
Genomics and the future of
Fred W. Allendorf*‡, Paul A. Hohenlohe§|| and Gordon Luikart¶#
Abstract | 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.
NATURE REVIEWS | GENETICS
VOLUME 11 | OCTOBER 2010 | 697
The probability that two alleles
in an individual are both
descended from a single allele
in an ancestor (that is, that
they are ‘identical-by-descent’).
An abbreviation for contiguous
sequence; used to indicate a
contiguous piece of DNA that
is assembled from shorter
overlapping sequence reads.
The study of the collective
genomic material contained in
an environmental sample of
microorganisms, facilitated by
technology that allows the
direct sequencing of
An organism that lives within
the cells of a host organism.
The loss of vigour and fitness
that is observed when
is increased by inbreeding.
There have been several excellent reviews on con-
servation genomics recently3,14–17. We have attempted to
build on these reviews and to distinguish ours by mak-
ing specific practical recommendations on how genomic
approaches can be applied to key problems in conserva-
tion (TABLE 1). For example, Ouborg et al.15 present a com-
prehensive view of how genomics will provide insights
into the mechanisms behind the interaction between
selectively important variation and environmental
conditions. Nevertheless, if we are to apply this under-
standing of fitness to conservation, we need to address
the population-level consequences of genetic variation,
which include population subdivision, demography and
population viability. We have incorporated population
structure and demographic effects into FIG. 1, and have
distinguished issues that only genomic approaches can
thoroughly address from issues that can be adequately
tackled with traditional techniques.
We have two primary objectives. The first is to iden-
tify those problems in conservation biology in which
genomics will be most valuable in providing new insights
and understanding. The second is to provide guidelines
as to which new genomics approaches will be most
appropriate for the different problems in conservation
that can benefit from genetic analysis.
We begin by focusing on issues in conservation
genomics that are immediately accessible (for example,
increasing the number of neutral markers) and then
proceed through issues that will become more feasible
in the future. We consider how genomic approaches will
allow us to understand the genetic basis of inbreeding
depression and adaptation. We then apply these insights
to important outstanding problems in conservation,
including understanding the effects of hybridization and
predicting outbreeding depression, as well as predicting
evolutionary responses to climate change.
The most straightforward contribution of genomics to
conservation will be to enormously increase the pre-
cision and accuracy of estimation of parameters that
require neutral loci (for example, effective population size
(Ne) and migration rate (m)) by genotyping hundreds
to thousands of neutral loci in numerous individuals.
The accuracy of parameter estimation will be improved
because examining several loci facilitates the identifica-
tion and exclusion of loci under selection (outlier loci)
that cause biased estimates of parameters. For example, a
small proportion (1–5%) of non-neutral loci can change
estimates of mean FST by 30–50%18–20, and change the
topology and branch lengths of evolutionary trees21,22.
Similarly, the assessment of demographic parameters,
such as population bottlenecks or growth rates, requires
many loci to identify outliers and reliably infer change
in population size. Selection can shrink (by bottlenecks)
or expand genealogies at a locus23. Therefore, inferences
about population growth should be more robust if out-
lier loci are removed, for example by using a hierarchical
Bayesian model to assess the parameters of each locus
Increasing the number of markers will also facilitate
estimation of directionality of migration (emigration
and immigration rates), especially if haplotypes can be
inferred from linked loci25. Certain questions require
linked loci or can be vastly improved by using haplotype
inference; for example, estimating relationships among
individuals26, population structure27, admixture28, dates of
historical bottlenecks and directionality of migration25.
Furthermore, it will become increasingly feasible to
jointly estimate multiple parameters, which generally
requires more loci than single parameter estimation. For
example, likelihood, Bayesian and approximate Bayesian
estimators combined with coalescent approaches will
allow the simultaneous estimation of multiple param-
eters, such as Ne and m25,29, or Ne and the selection
coefficient (s)30. This is important because it will improve
parameter estimation, allow parameter estimation in
metapopulations (not just in isolated populations with
no gene flow), and facilitate investigations of the relative
importance and interactions among drift, selection and
migration in populations of conservation concern.
By contrast, simulations suggest that as the number
of loci increases, the accuracy of parameter estima-
tion can decrease owing to non-independence or link-
age among loci31. Failure to account for linkage could
limit the utility of SNPs or multi-locus sequencing in
studies using genealogical information32. Markers are
usually assumed to be independent. Failure to account
for non-independence can lead to overestimation of
Box 1 | What is ‘conservation genomics’?
Conservation genomics can be broadly defined as the use of new genomic techniques
to solve problems in conservation biology. Frankham72 recently reviewed the current
status of conservation genetics and proposed 13 priorities for development in the field.
Many of these priorities have been intractable through traditional genetic techniques.
Although genomic techniques are not appropriate or necessary in all cases, we believe
that genomics will have an important role in addressing several research challenges
over the next few years.
Genomic techniques will be more immediately applicable to some questions than to
others (TABLE 1). For example, in estimating neutral population parameters, such as
effective population size, genomics simply provides a larger number of markers to an
analytical and conceptual framework that is already widely used in conservation
genetics. Genomic identification of functionally important genes is now common in
other fields; conservation genomics can incorporate these approaches to study the
genetic basis of local adaptation or inbreeding depression. By contrast, predicting a
population’s viability or capacity to adapt to climate change based on genomic
information will require not only the identification of relevant loci, but also a
quantitative estimate of their connection to fitness and demographic vital rates.
These challenges must be tackled by conservation genomics over the longer term.
Understanding genomic approaches is crucial to the success of applying genomics
to conservation (FIG. 1). A growing list of techniques is available for detecting DNA
sequence differences across individuals in natural populations, and these vary widely in
the density of markers across the genome, their ability to target candidate loci, the cost
per sample, and so on. Genomic techniques can be roughly grouped into three classes:
marker-based genotyping, including a diversity of array-based SNP genotyping
platforms; reduced-representation sequencing, which uses next-generation
sequencing technology to target a subset of orthologous regions across the genome of
many individuals; and whole-genome sequencing. A crucial component of all genomic
techniques is bioinformatics. The tools for handling genomic data are changing as fast
as (and in response to) techniques for gathering the data, and we do not review the
software and analytical issues here111. Nonetheless, researchers using genomic
techniques should plan on a substantial investment of time and resources devoted to
data storage and analysis.
698 | OCTOBER 2010 | VOLUME 11
Population structurePopulation size
Genetic driftInbreeding Hybridization
Loss of genetic diversity
Loss of adaptive variationInbreeding depression
Demographic vital rates
Population growth or viability
Heritable changes in genotype
or phenotype that result in
Interbreeding of individuals
from genetically distinct
of the taxonomic status of
Reduced fitness of F1 or F2
individuals after a cross
between two species or
populations. It can result from
genetic incompatibility or
reduced adaptation to local
Effective population size
The size of the ideal population
that would experience the
same amount of genetic drift
as the observed population.
A genome location (or marker
or base pair) that shows
behaviour or a pattern of
variation that is extremely
divergent from the rest of the
genome (locus-specific effects),
as revealed by simulations or
precision and overconfidence in subsequent inferences.
Fortunately, the problem is likely to be minor unless loci
are tightly linked33. Failure to consider linkage could also
have other effects; for example, human loci in regions
of lower recombination tend to have greater FST, appar-
ently because of the greater probability of being associ-
ated with selected loci in chromosomal regions with less
Description of kin relationships and pedigrees.
Examining hundreds of loci will vastly increase the
precision and accuracy of kinship estimates. For exam-
ple, Santure et al.35 showed that the average pair-wise
relatedness estimated from 771 SNPs closely brackets
known pedigree relationships for a pedigree population
of zebra finch. This suggests that assessments of correla-
tions between phenotypes and genetic relatedness and
thus estimation of heritability will be feasible in natural
populations. Nevertheless, the accuracy of estimating
individual levels of inbreeding is somewhat limited, and
the variances for relatedness between individuals remain
substantial even with 771 SNPs36.
Pedigree reconstruction will become feasible in some
wild populations with hundreds of loci33,37. This will
improve estimates of effects of inbreeding and outbreed-
ing on fitness and the detection of paternities or pol-
len flow between populations and over long distances,
if most individuals can be sampled over many years.
Santure et al.35 suggested that using marker information
to reconstruct the pedigree, and then calculating relat-
edness from the pedigree, is likely to give more accurate
relatedness estimates than using marker-based estimators
directly. Skare et al.26 conducted simulation power analy-
ses and showed that relatively distant relationships (for
example, cousins) can be inferred using 500,000 SNPs
and likelihood-based relationship estimators.
Nonetheless, pedigrees often will not have sufficient
depth or completeness because it is difficult to sample
most individuals in a population over many years. In
such cases, genotyping thousands of loci could poten-
tially give more reliable estimates of relationships and
individual heterozygosity (inbreeding) than pedigrees26,38
or at least greatly improve pedigree reconstruction37.
Future research is needed to quantify the trade-off point
between using pedigree inference versus thousands of
genetic markers to estimate individual inbreeding.
Individual-based population genetics. Individual-based
approaches can yield less biased delineation of popula-
tions than traditional population-based approaches that
require somewhat subjective grouping of individuals39
(for example, based on morphology or geographic
origin). For population delineation, an empirical study
of 377 microsatellites in humans has shown that using
greater numbers of loci can increase statistical power to
resolve between closely related ethnic groups (FST < 0.05)
and infer the proportion of admixture40,41.
Individual-based approaches can give less biased
estimation of contemporary migration rates without
assumptions such as mutation–migration–drift equilib-
rium42. However, the power to estimate contemporary
migration rates is low unless FST is relatively high (for
example, FST > 0.10) when using only 10–20 microsatel-
lite loci43. Little is known about power when genotyp-
ing hundreds of loci, although Rannala and Mountain44
reported that an assignment test method using 50–100
loci gave reasonable power to identify individuals with
grandparents from different countries, although the
differentiation of allele frequencies among populations
was low. Individual-based approaches are crucial for
fine-scale spatial genetic analyses to localize genetic dis-
continuities (for example, barriers or secondary contact
zones) on a landscape. Individual-based approaches in
landscape genetics45 also allow assessment of the influ-
ence of landscape features on dispersal and gene flow
across spatial scales.
Genomic approaches can potentially address basic ques-
tions about the molecular basis and genetic architecture
of inbreeding depression46. For instance, is inbreeding
depression caused by a few loci with major effects or by
many loci with small effects? How much of inbreeding
depression results from dominance (or partial domi-
nance) versus overdominace (heterozygous advan-
tage)? What is the contribution of epistasis to inbreeding
depression? Understanding the number of loci involved
in inbreeding depression and the mechanism of their
effects would allow prediction of the potential efficacy
Recent work indicates that the intensity of inbreed-
ing depression can differ greatly depending on which
specific individuals are founders47,48. This suggests that
Figure 1 | Schematic diagram of interacting factors in conservation of natural
populations. Traditional conservation genetics, using neutral markers, provides direct
estimates of some interacting factors (blue). Conservation genomics can address a wider
range of factors (red). It also promises more precise estimates of neutral processes (blue)
and understanding of the specific genetic basis of all of these factors. For example,
traditional conservation genetics can estimate overall migration rates or inbreeding
coefficients, whereas genomic tools can assess gene flow rates that are specific to
adaptive loci or founder-specific inbreeding coefficients.
NATURE REVIEWS | GENETICS
VOLUME 11 | OCTOBER 2010 | 699
A measure of population
subdivision that indicates the
proportion of genetic diversity
found between populations
relative to the amount
A marked reduction in
population size followed by the
survival and expansion of a
small random sample of the
original population. It often
results in the loss of genetic
variation and more frequent
matings among closely
Hierarchical Bayesian model
A Bayesian model in which
the prior depends on another
parameter that is not in
the likelihood function and
that can vary and have
A set of genetic markers
that are present on a single
chromosome and that show
complete or nearly complete
They are inherited through
generations without being
changed by crossing-over
or other recombination
The production of new
genetic combinations in
hybrid populations through
A means of investigating the
shared genealogical history
of genes. A genealogy is
constructed backwards in time
starting with the present-day
sample. Lineages coalesce
when they have a common
A term that describes the
difference in average fitness
between genotypes when
fitness is measured relative to
the average fitness of one of
the genotypes (known as the
A collection of populations
of a species found in differing
geographic locations and
with restricted gene flow
(exchange of genes) between
the genetic load is unevenly spread among founder
genomes and supports the notion that inbreeding
depression sometimes results from major effects at a few
loci49. The founder-specific partial F coefficient is the
identical-by-descent (IBD) probability (for an individual)
that is attributed to a particular founder. A study with
Ripollesa domestic sheep found that most of the inbreed-
ing depression resulted from individuals being IBD for
genes from just two of the nine founders49. Managing
founder-specific inbreeding depression using partial
inbreeding coefficients could be extremely effective in
cases in which inbreeding depression results primarily
from a few loci with major effects; such partial inbreed-
ing coefficients could be useful when selecting potential
matings in a captive population.
Identifying alleles responsible for inbreeding depression.
Genome scans of large numbers of markers can detect
the signature of inbreeding depression. Deleterious reces-
sive alleles related to inbreeding depression have been
identified in a few species46,50,51. In general, attempts to
identify loci responsible for inbreeding depression may
be less successful than those aimed at positive selection
for a few reasons. First, detecting the multiple genetic
mechanisms that may underlie inbreeding depression,
including epistasis and genotype-by-environment inter-
action, may prove more difficult52. Second, populations
of interest are likely to be small, necessitating small
sample sizes, which reduce power and accuracy. Third,
the longer regions of gametic disequilibrium expected
in small inbred populations (observed in wolves by
Hagenblad et al.46) mean that genotyped anonymous
markers are more likely to lie within a genomic region
affected by selection at a particular locus, but that fine-
mapping of a selected locus will be more difficult. Ideally,
researchers would study populations with both long and
short chromosomal regions of gametic disequilibrium
to allow for initial coarse-mapping and subsequent
fine-mapping of loci under selection.
In the future, it could be possible to identify loci that
contribute to inbreeding depression by sequencing the
whole genomes of parents and offspring. For example,
Roach et al.53 analysed the complete genome sequence
of two parents and their two children, who suffered
from two clinical recessive disorders. They narrowed
down the candidate genes for both of these Mendelian
disorders to four using family-based genome analysis.
One of the most promising aspects of applying genomic
tools to conservation is the simultaneous estimation
of neutral (that is, genome-wide average) processes
along with identification of specific genomic regions
responding to selection, such as adaptation to local
conditions that vary across a metapopulation. These
specific genomic regions appear as outliers from the
patterns observed at the neutral genomic background,
which is determined primarily by genetic drift and gene
flow. Researchers have developed multiple approaches
to detect these outliers54,55 (BOX 3). The utility of these
approaches depends on the timescale over which selec-
tion has operated and the study’s taxonomic scale (for
example, the study might be investigating divergence
among species, differentiation among populations
within a species or evolutionary history within a single
population), as well as on the techniques used55.
Box 2 | Detection of cryptic subdivision and local adaptation in marine species
There is little genetic drift in many marine fish and invertebrates because of their large population sizes121,122. As a
consequence, population genetic studies of many marine species have failed to detect genetic substructure even
between geographically disjunct subpopulations for which there is evidence of reproductive isolation122. The absence
of genetic differentiation at neutral markers, however, should not be taken to mean the absence of adaptive
differences. The amount of genetic divergence among subpopulations at selectively neutral markers is largely a
function of the number of migrants per generation (Nem) rather than the migration rate (m). With large population
sizes, even very low migration or dispersal rates can result in enough migrant individuals to eliminate genetic
evidence of population differentiation at neutral loci, but not at locally selected adaptive loci.
We expect this effect to be greatest in marine species because of the large local population sizes, which allow
selection to be more efficient because drift is weaker. The amount of divergence at selected loci is determined by the
relative values of migration and selection coefficient (s). Species with larger local populations (Ne) will have much
lower rates of migration than species with small population size with the same number of migrants and amount of
divergence at neutral loci. Therefore, even fairly weak selection may bring about genetic differentiation between
subpopulations in species with large local population sizes because s is much more likely to be greater than m.
This prediction is supported by a recent study123 of Atlantic cod (Gadus morhua) in which almost no genetic
differentiation (FST = 0.003) was found at nine microsatellite loci, but substantial differentiation (FST = 0.261) was found
at the PanI locus, which previous studies have shown to be under natural selection105. Similarly, Haemmer-Hansen et al.124
reported an FST of 0.45 at a heat shock protein locus in comparison to a mean FST value of only 0.02 at nine
microsatellite loci in the European flounder (Platichthys flesus). This approach of simultaneously comparing many
neutral and candidate gene markers has been highly successful in a range of species19.
In addition, the absence of genetic differentiation in marine species should not be interpreted to indicate that
the populations are demographically connected as a single management unit125. Demographic connectivity is
largely a function of the proportional amount of exchange. Therefore, low migration rates (m < 0.001) can result
in a substantial number of migrant individuals when local population sizes are in the thousands, resulting in FST
values near zero. Much greater exchange is necessary for demographic connectivity between populations.
For example, Waples and Gaggiotti126 have suggested that m must be greater than 10% for populations to be
700 | OCTOBER 2010 | VOLUME 11
Proportion of admixture
The proportion of alleles in a
hybrid swarm or individual
that comes from each of
the hybridizing taxa.
The dependency of the
effects of alleles at one locus
on the genotypes at other
loci in the genome.
The selective reduction in
frequency of deleterious
recessive alleles in small
populations because the
increase in homozygosity
increases the ability of selection
to act on recessive alleles.
An allele shared by two
related individuals is said to
be identical-by-descent if
the allele is inherited from the
same common ancestor.
A measure of whether alleles at
two loci in a population occur
in a non-random fashion.
Type I and type II errors
Statistical errors in which
a true null hypothesis is
rejected (type I) or a false
null hypothesis is not
rejected (type II).
Expressed sequence tag
A short DNA fragment (several
hundred base pairs) produced
by reverse transcription of
mRNA into DNA.
For most conservation purposes, only a subset of
these tools will be most appropriate, and application
of the wrong approach could result in type I and type II
errors. Specifically, detecting genomic regions that are
responsible for local adaptation in a species relies on
comparisons among related populations that may or
may not be linked by ongoing gene flow. In this case,
the most appropriate analyses often will focus on dif-
ferentiation in allele frequencies among populations
(that is, FST
quency spectrum can indicate regions under selection55.
By contrast, techniques for detecting historical selection
based on fixed sequence divergence between species or
the relationship between divergence and polymorphism
are likely to have only limited applications in conser-
vation because of the longer timescale of selection that
can be detected (but see Garrigan and Hedrick56). Here
we focus on the first case — local adaptation among
populations within a species.
20). Within a single population, the allele fre-
Methods for assessing local adaptation. There are two
general ways to assess local adaptation in the genome
(BOX 3): the first starts with a list of candidate loci or
genomic regions and asks whether these lie in the tails of
the genome-wide distribution of population differentia-
tion57–60. Genomics can augment these studies indirectly
by providing a list of candidates; for example, expressed
sequence tag (EST) databases allow for the bioinformatic
identification of microsatellites or other traditional
markers closely linked with target genes, and primers or
probes can be developed from these EST sequences61–65.
Genomic databases may even come from related species,
so that rare species of conservation concern are ‘genome-
enabled’ by the resources of better-studied, related taxa3.
A growing variety of genomic tools can also be used
directly to genotype individuals at up to thousands of
candidate loci (TABLE 2).
The second major approach to detecting local adap-
tation searches the genome for signatures of selection
using anonymous markers66,67. A limitation here is that
markers must be in gametic disequilibrium with selected
loci to exhibit a signature of selection, and the signa-
ture can be quite small depending on the nature of the
selection. In particular, local adaptation with ongoing
gene flow between populations subject to differential
selection is expected to produce a soft sweep; such a
signature of selection can have a very narrow footprint
along the genome and be difficult to detect, even given
strong selection68. Nonetheless, the density of markers
along the genome allowed by high-throughput genomic
techniques can be sufficient to identify these regions,
especially when replicate populations subject to simi-
lar selection pressures can be sampled66. The array of
genomic techniques covers the range of trade-offs
between density of markers and number of individuals
or populations sampled. Any information on the overall
amount of gametic disequilibrium can inform the exper-
imental design of genome scans (see Supplementary
information S1 (figure)).
There are trade-offs between the two general
approaches outlined above. The first allows targeting
of particular loci, which can be valuable if selection is
Table 1 | Primary genetic problems in conservation and how genomics can contribute to their solution*
Estimation of Ne, m and s
Possible genomic solution
Increasing the number of markers, reconstructing pedigrees and using
haplotype information will provide greater power to estimate and monitor Ne
and m, as well as to identify migrants, estimate the direction of migration and
estimate s for individual loci within a population
Reducing the amount of admixture
in hybrid populations
Genome scanning of many markers will help to identify individuals with greater
amounts of admixture so that they can be removed from the breeding pool
Identification of units of conservation:
species, evolutionarily significant
units and management units
The incorporation of adaptive genes and gene expression will augment our
understanding of conservation units based on neutral genes. The use of
individual-based landscape genetics will help to identify boundaries between
conservation units more precisely
Minimizing adaptation to captivity Numerous markers throughout the genome could be monitored to detect
whether populations are becoming adapted to captivity
Predicting harmful effects of
Understanding the genetic basis of inbreeding depression will facilitate the
prediction of the effectiveness of purging. Genotyping of individuals at loci
associated with inbreeding depression will allow the selection of individuals as
founders or mates in captive populations. Pedigree reconstruction will allow
more powerful tests of inbreeding depression
Predicting the intensity of
Understanding the divergence of populations at adaptive genes will help
to predict effects on fitness when these genes are combined. Detecting
chromosomal rearrangements will help to predict outbreeding depression
Predicting the viability of local
Incorporating genotypes that affect vital rates and the genetic architecture of
inbreeding depression will improve population viability models
Predicting the ability of populations
to adapt to climate change and other
Understanding adaptive genetic variation will help to predict the response
to a rapidly changing environment or to harvesting by humans and allow the
selection of individuals for assisted migration
*These problems are listed from top to bottom in sequence of those that can be immediately addressed to those that will become
more feasible to address in the future. m, migration rate; Ne, effective population size; s, selection coefficient.
NATURE REVIEWS | GENETICS
VOLUME 11 | OCTOBER 2010 | 701
suspected to act on particular phenotypic traits and func-
tional genetic information is available from related spe-
cies. This approach can also be applied to a larger number
of individuals or populations for the same overall effort.
By contrast, the second approach is most useful in the
absence of a priori hypotheses about specific loci or selec-
tive pressures and can provide quantitative information,
such as estimates of how many regions of the genome are
subject to selection, as well as test whether selection is
acting on similar genomic regions across populations.
These approaches can also be combined; for example,
genotyping arrays can be printed with a combination
of probes for candidate and anonymous loci.
Climate change and other anthropogenic challenges.
An important component of conservation genetics is
understanding how to maintain the ability to evolve in
anticipation of environmental change; for example, cli-
mate change will affect a wide range of species and habi-
tats. Genomic approaches may allow the identification
of adaptive genetic variation related to key traits, such as
phenology or drought tolerance, so that management may
focus on maintaining adaptive genetic potential. In this
context, a landscape genomics approach allows the map-
ping of associations between adaptive genome regions69
and environmental gradients in space and time. This
could allow forecasting of the effects of environmental
change on gene flow of adaptive alleles by predicting
spatial–temporal landscape change and modelling gene
flow across landscapes expected in the future.
The harvest of phenotypically desirable animals from
wild populations imposes selection that can reduce the
frequencies of those desirable phenotypes70. In addition,
genetic changes in response to the harvesting of animals
by humans threaten the persistence of many species71.
The use of genomics to monitor these genetic changes
could be extremely important because early detection of
potentially harmful changes will maximize our ability to
implement management to limit or reverse the effects
before substantial or irreversible changes occur71.
Units of conservation and hybridization
Describing units of conservation is one of the most
important contributions of genetics to conservation72.
The identification of appropriate taxonomic and popu-
lation units for protection and management is essential
for the conservation of biological diversity. For species
identification and classification, genetic principles and
methods are relatively well developed. Nevertheless,
species identification remains controversial, and agree-
ing upon a uniform definition of species is Frankham’s
number two priority for conservation genetics72.
A great deal of effort is currently involved in describ-
ing units within species that are distinct enough to
require separate management: these units include
evolutionarily significant units (ESUs), distinct population
segments and management units. The identification of
population units is necessary so that management and
monitoring programmes can be efficiently targeted
towards distinct or independent populations; such
methods could be used to effectively plan harvesting
Box 3 | Genome scans to detect local adaptation
Genome scans for selection can focus on either candidate loci or anonymous loci.
Namroud et al.62 sampled white spruce (Picea glauca) from 6 populations in Quebec and
genotyped 534 SNPs located on 345 candidate genes. Part a of the figure shows their FST
outlier analysis of these data, based on the relationship between FST and expected
heterozygosity59; the grey and red lines represent the 95% and 99% confidence levels,
respectively. Against a background of little population differentiation (FST = 0.006), this
analysis identified 20 SNPs (circled dots) in 19 genes above the 95% confidence level. New
genomic tools also allow anonymous markers to be assayed across the genome to identify
local adaptation; for example, Hohenlohe et al.66 sampled 100 threespine stickleback
individuals across 5 populations in Alaska. They used sequencing of restriction-site-
associated DNA (RAD) tags127 to simultaneously identify and genotype over 45,000 SNPs
across the genome. This density of markers allows population genetic statistics, such as FST,
to be visualized as continuous distributions along chromosomes. In part b of the figure,
the top panel shows FST between the two marine populations. The next three panels show
differentiation between each of the three freshwater populations and the two marine
populations. Coloured bars above each graph show regions of significantly elevated FST,
as indicated by bootstrap resampling (blue, p?????–5; red, p?????–7). Vertical grey shading
indicates the chromosomes, and yellow shading indicates the nine most significant and
consistent peaks of freshwater-versus-marine differentiation. Common patterns of
population differentiation (yellow shading shared among the three populations)
indicate genomic regions that have responded to divergent selection in parallel across
populations.The image in part a is reproduced, with permission, from REF. 62 © John
Wiley and Sons. The image in part b is reproduced from REF. 66.
702 | OCTOBER 2010 | VOLUME 11
The timing of periodic
that are usually correlated
with climatic conditions.
quotas (to avoid overharvesting, for example) or to
devise ways to translocate and reintroduce individuals
(to avoid, for example, the mixing of adaptively dif-
ferentiated populations). It is sometimes necessary to
prioritize population units for conservation owing to
limited financial resources.
Hybridization is one of the major threats to con-
servation of many plant and animal species73. Rates
of hybridization and introgression have increased dra-
matically worldwide because of widespread intentional
and incidental translocations of organisms and habitat
modifications by humans. Hybridization has contributed
to the extinction of many species73,74. Genomics could
have an important role in distinguishing between natural
and anthropogenic hybridization73. Also, genomics pro-
vides the potential to predict the effects of hybridization
on fitness (heterosis or outbreeding depression).
Units of conservation. The description of conserva-
tion units generally requires two steps: estimating the
amount of gene flow among populations and evaluat-
ing the amount of adaptive divergence. The ability to
Table 2 | Major techniques for detecting DNA sequence variation and considerations for conservation applications
for small to
individuals in a
Cost per sample VariableUS$10–50$200–500 $200–1,000$50–150$500–5,000
Number of markers101–102
ModerateLowLow Low–moderateHigh Low
Ability to target
YesYes YesYesNo Yes
LowLow High HighLow–moderateHigh
$100,000 platform $150,000 platform $5,000 for
LimitedLimited–moderate YesYesYes Data overkill in
Yes, but variance
due to few markers
Yes, but variance
due to moderate
number of markers
More data than
with candidate loci
loci and targeting
de novo mapping
of few known
of few known
key markers are
key markers are
key markers are
qPCR, quantitative PCR; RAD, restriction-site-associated DNA.
NATURE REVIEWS | GENETICS
VOLUME 11 | OCTOBER 2010 | 703
The study of many markers,
including markers in genes
under selection, in spatially
referenced samples collected
across a landscape and often
across selection gradients. It
uses comparisons of adaptive
and neutral variation to quantify
the effects of landscape
features and environmental
variables on gene flow and
spatial genetic variation.
Evolutionarily significant unit
A classification of populations
that have substantial
reproductive isolation which has
led to adaptive differences so
that the population represents
a significant evolutionary
component of the species.
Distinct population segment
A classification under the
Endangered Species Act
of the United States that
allows for legal protection of
populations that are distinct,
isolated and represent a
lineage to the species.
A local population that is
managed as a unit owing to its
Gene flow between
populations or species
whose individuals hybridize.
When hybrid individuals
have greater fitness than
either of the parental types.
genotype many neutral loci will provide much better
estimates of the patterns of reproductive isolation and
demographic history of populations to address the first
step. Genomic approaches for studying functional genes
will provide the opportunity to evaluate the amount of
adaptive divergence among populations required in the
second step, and its distribution across the genome.
Conservation units have been described on the
basis of divergence at loci that are assumed to be selec-
tively neutral. It has been suggested that this could be
improved by including genetic divergence at adaptive
markers along with the divergence at neutral loci75–77.
Adaptive markers could enhance and help set priori-
ties for the identification and management of units of
conservation. However, a complete understanding
of adaptive divergence is unattainable. Moreover, a
recent comparison of assumed neutral and putatively
selected alleles in over 640,000 autosomal SNPs in
humans concluded that average allele frequency diver-
gence is highly predictive of adaptive divergence and
that neutral processes (population history, migration
and effective population size) exert powerful influences
over the geographic distribution of selected alleles78.
This result supports the use of neutral loci to provide
useful descriptions of the patterns of divergence at
There are pitfalls in focusing on individual adap-
tive loci rather than neutral patterns or genome-wide
averages. Genes important for contemporary or past
adaptations might not be those that will be crucial
for adaptation in future environments. In addition, much
effort has been devoted recently to genome-wide asso-
ciation studies for detecting the genetic basis of com-
plex traits, particularly disease in humans, using large
samples of individuals and genetic markers. Although
many candidate genes have been identified, often a large
proportion of the heritability remains unexplained79. A
focus on detectable adaptive genomic regions could
result in loss of important genetic variation at other
regions. Moreover, even when the same genomic regions
are implicated in, for example, local adaptation across
populations, the particular alleles involved may be dif-
ferent and perhaps even result in outbreeding depression
Landscape genomics will help to identify manage-
ment units by providing sufficient power to localize
boundaries on the landscape that separate demograph-
ically independent groups. Examination of hundreds
to thousands of loci in hundreds of individuals across
landscapes will improve assessments of the interac-
tions of gene flow, genetic drift and natural selection
in influencing the evolution and persistence of popula-
tions. Landscape genomics will help to identify ESUs
(and spatial locations of boundaries between them) by
including both neutral and adaptive variation.
Recent papers have explored the potential of tran-
scriptomic analysis of gene expression to assess func-
tional genetic divergence among populations80; for
example, Tymchuk et al.81 hybridized a microarray
with 16,000 salmonid cDNAs (16K cDNA microarray)
to RNA extracted from whole fry raised in captivity in
12 Atlantic salmon (Salmo salar) populations to exam-
ine global patterns of gene expression and found they
were concordant with patterns of divergence at seven
microsatellite loci. These results support the notion that
patterns of divergence at neutral loci reflect patterns of
adaptive variation in gene expression.
Detection of hybridization. Molecular detection of
hybridization and estimation of the proportion of admix-
ture between genetically divergent populations can be
accomplished accurately with tens of loci73,82. However,
accurate description of the dynamics of hybridization
and introgression can require hundreds of loci83. In addi-
tion, estimation of the proportion of admixture within
individuals will require many more markers.
For example, Halbert and Derr84 found that 7 of 11
US federal bison (Bos bison) populations contained
introgression from domestic cattle (Bos taurus) based
on 14 nuclear loci. The conservation value of admixed
populations has been controversial73,85,86, and some
believe that these herds should not be considered as
bison for conservation purposes87. However, this posi-
tion has not been generally accepted87. Regardless, the
potential to estimate the proportion of cattle alleles in
individual bison will allow the selection of individuals
to reduce the magnitude of introgression from cattle in
managed bison herds.
Genomics provides exciting opportunities to assess
differential rates of introgression across different
genomic regions following hybridization88. For exam-
ple, Fitzpatrick et al.89 found that 3 of 68 markers
spread rapidly into native California tiger salamanders
(Ambystoma californiense), whereas the other 65 markers
show little evidence of spread beyond the region where
introductions of non-native barred tiger salamanders
(Ambystoma tigrinum mavortium) occurred. Differential
introgression rates of genomic regions raises some dif-
ficult issues with regards to treating hybridized popu-
lations in conservation89 and brings into question the
efficacy of using a few (that is, ten or so) neutral markers
to detect hybridization.
Outbreeding depression. Concerns about the possibility
of outbreeding depression have restricted, perhaps
unnecessarily, the use of managed gene flow to avoid
increased risks of extinction caused by loss of genetic
variation because of habitat fragmentation and isola-
tion. Frankham72 has identified the development of
methods for predicting outbreeding depression as the
top priority in conservation genetics. Outbreeding
depression can result from either chromosomal or genic
incompatibilities between hybridizing taxa (intrinsic
outbreeding depression) or reduced adaptation to
local environmental conditions (extrinsic outbreeding
depression)90. Genomic approaches can potentially
provide valuable empirical information for predicting
the probability of either of these sources of outbreeding
depression; for example, next-generation sequencing
using paired-end reads can be used to detect chromosomal
rearrangements91, such as large inversions or gene copy
704 | OCTOBER 2010 | VOLUME 11
Mean number of offspring per female
Proportion of rainbow trout admixture
0.6 1.00.40.2 0.8
Mean number of offspring per male
Proportion of rainbow trout admixture
The use of molecular genetic
markers to increase the
response to selection in a
population by the favouring of
reproduction by individuals
with a certain allele or
genotype. The marker is
closely linked to a quantitative
The recovery in the average
fitness of individuals through
increased gene flow into small
populations, typically following
a fitness reduction due to
A genetically based skeletal
disorder that affects the
development of cartilage.
Genomic approaches will also be increasingly
used to detect outbreeding depression by estimating
the number of progeny produced by individuals with
different proportions of admixture. For example,
Muhlfeld et al.93 estimated the individual propor-
tion of admixture between introduced rainbow trout
(Oncorhynchus mykiss) and native westslope cutthroat
trout (Oncorhynchus clarkii lewisi) (FIG. 2).
Captive breeding and assisted migration
Genomic tools may assist the management of ex situ
populations and reintroductions by providing increased
precision and accuracy of estimates of neutral popula-
tion genetic parameters and by identifying specific loci
of importance, which is essential for selecting founder
individuals. First, many neutral loci could be used to
construct a more precise pedigree of the captive popula-
tion and determine whether the founders from the wild
are kin. Second, screening of the founders for known
deleterious recessive alleles could substantially reduce
any subsequent inbreeding depression in the captive
population. In addition, screening of the founders for
known adaptive alleles could increase the evolutionary
potential of the captive population.
Managing inbreeding depression. The overarching goal
of maintaining genetic diversity in an ex situ population
pre-dates genomic techniques. Nonetheless, genome
scans may produce better estimates of genome-wide het-
erozygosity and genetic diversity than smaller numbers
of traditional markers, such as microsatellites94. Methods
are being developed to maximize the sampling of genetic
variation for founders of captive breeding colonies
based on genomic data95. A caveat here is that the rela-
tionship between genome-wide average heterozygosity
and inbreeding depression is not always strong. As a
result, a more powerful application of genomics may be
to estimate pedigrees and degrees of relatedness among
captive or founding individuals35,96, allowing captive
management plans to minimize inbreeding per se.
The ability to use genomics to identify specific loci
related to local adaptation or inbreeding depression and
the success of marker-assisted selection in livestock
and crops97 raise the possibility of managing specific
loci in some conservation situations. For example,
individuals with particular adaptive genetic variants
could be chosen for reintroduction or genetic rescue.
In captive breeding programmes, particular genetic
variants could be selected against. In one example, the
small population of the California condor (Gymnogyps
californianus) has a relatively high frequency of a recessive
lethal allele causing chondrodystrophy. A condor genom-
ics project is seeking a marker to identify carriers of the
chondrodystrophy allele, and members of this project
have therefore developed several genomic resources,
including a bacterial artificial chromosome library
and a fibroblast cell line for transcriptomic analysis17,
with the goal of designing breeding programmes to
select against heterozygotes for the chondrodystrophy
allele while minimizing loss of genetic diversity
elsewhere in the genome.
Minimizing adaptation to captivity. The emphasis of
captive breeding protocols has been to reduce genetic
drift by maximizing effective population size98, which
is appropriate for captive breeding programmes of
mammals and birds in zoos that have a relatively small
number of individuals that are managed using pedigrees.
Figure 2 | Effects of proportion of individual admixture
with introduced rainbow trout on the fitness of native
westslope cutthroat trout. Sixteen microsatellite loci
were used to estimate the individual proportion of
admixture between introduced rainbow trout and native
westslope cutthroat trout93. These same loci were used to
identify the parents of progeny produced in a stream over
a 5-year period. The bubble plots show the mean number
of offspring per individual identified plotted against the
proportion of rainbow trout admixture for females (a) and
males (b). In a bubble plot, the size of the bubble is
proportional to the number of observations with that
value. The mean values for first-generation hybrids are
shown as triangles; these points were not included in the
regression. These results are striking in two ways. First,
there was a strong reduction in the number of progeny
produced as the amount of admixture with introduced
rainbow trout increased in both females and males.
Second, first-generation hybrids had much greater
reproductive success than other individuals with 50%
admixture. This suggests a strong heterotic effect in the
first-generation hybrids caused by sheltering of
deleterious recessive alleles. Figure is reproduced, with
permission, from REF. 93 © (2009) The Royal Society.
NATURE REVIEWS | GENETICS
VOLUME 11 | OCTOBER 2010 | 705
The study of the effect of
individual alleles or genotypes
on the species composition,
diversity or functioning of a
community or ecosystem.
However, adaptation to captivity is a serious problem
associated with captive breeding programmes for many
species99,100. This will inevitably reduce the fitness of
individuals reintroduced to wild or natural conditions.
For example, tameness in response to humans is gener-
ally advantageous in captivity but can have serious con-
sequences in the wild. In addition, increasing effective
population size for some captive species (for example,
fish and plants) may increase the rate of adaptation to
captive conditions. Genetic monitoring101 of many loci
throughout the genome should become a standard tool
for detecting adaptation to captivity (that is, rapid, locus-
specific change in allele frequencies) in species for which
adaptation to captivity is a concern100.
Restoration. The condor example highlights the com-
plexity of identifying specific loci to allow targeted
genetic management of populations, even when a single
Mendelian locus is implicated. However, the success of
marker-assisted selection in livestock is due in part to
the fact that specific alleles and their functional roles
need not be determined; rather a correlation between
phenotype and genotype at multiple markers is estab-
lished, and selection on genotype produces a correlated
response in phenotype (for example, growth rate or dis-
ease resistance). Given the ability to identify genomic
regions correlated with local adaptation (BOX 3), con-
servation genomics could similarly use this informa-
tion in, for example, selecting source populations for
translocation or reintroduction. A general risk in such
efforts is outbreeding depression as a result of differ-
ent and incompatible genetic bases of adaptation in the
two populations. The choice of source population can
now be informed by four factors: ecological similar-
ity, phenotypic similarity, genome-wide similarity as
indicated by neutral markers, and genetic similarity at
Genetic rescue has been used as an effective res-
toration tool to avoid or reverse the consequences of
inbreeding depression102. However, the identification of
individual loci with major adaptive effects (for exam-
ple, major histocompatibility complex in animals103 and
self-incompatibility loci in plants104) raises the possibility
of allele-specific genetic rescue. Interestingly, other loci
with exceptionally strong fitness effects are being found
in a number of species, such as PanI105 in the cod family
(Gadidae) and Pgi in butterflies and other insects106. It
remains to be seen whether such loci are unusual or are
present in most species.
Research in community genomics suggests that indi-
vidual alleles can affect community diversity and com-
position107–109. For example, alleles at tannin loci in
cottonwood trees increase the palatability and decay
rate of leaves, which in turn influences the abundance
of soil microbes, fungi and arboreal insects and birds108.
Loss or restoration of such alleles to populations could
thus influence community diversity and ecosystem
function108. Nevertheless, the complexity of these inter-
actions presents real challenges before it will be pos-
sible to use this information in a practical conservation
Choosing genomic approaches
The diverse and growing list of genomic techniques
provides a range of options for experimental design
(TABLE 2). Currently, array-based techniques (SNP chips)
can efficiently genotype markers across many individuals
for a range of conservation applications. As the cost of
sequencing continues to fall, reduced-representation
sequencing may replace SNP chips as a preferred method
in many cases110. Sequence data can provide additional
information for functional assessment of candidate
genes or detection of haplotype structure or inversion
polymorphisms, and sequencing is easily applied to taxa
without any existing genomic resources. However, at
least in the near term, array techniques will retain their
advantage of having a highly standardized protocol for
genotyping a fixed set of markers. This makes them well-
suited to, for example, long-term genetic monitoring
It is becoming feasible to sequence complete genomes
in a reasonable research timeline and budget111. Whole-
genome resequencing of all individuals in a study will
become an option in conservation112. However, while
there are potential uses for whole-genome resequenc-
ing, such as detection of Mendelian inherited traits in
families53, in most situations it is likely to create more
challenges than it solves. First, because of linkage dis-
equilibrium, dense marker genotyping already provides
a nearly complete view of genomic variation113. Such
genomic structure is likely to be even more pronounced
in small populations of conservation concern than in
traditional model organisms46; whole-genome rese-
quencing is thus data overkill. Moreover, whole-genome
resequencing introduces many challenges for compu-
tational bioinformatics; the resources simply to store,
assemble and analyse such large data sets may outweigh
their benefits, at least for the near future.
We envision an emerging standard for conservation
genomics in which the starting point will be a reference
genome sequence. A rapidly growing number of species,
particularly vertebrates, have reference sequences avail-
able already114, or an initial investment can be made to
produce one. From this point, genotyping of multiple
individuals from population samples would be done
with array-based or reduced-representation sequenc-
ing techniques, with the reference sequence providing a
valuable resource for sequence alignment and candidate
gene identification and annotation.
This is an exciting and challenging time for conserva-
tion genetics. Genomic approaches have the potential
to transform the management of populations for con-
servation in various ways, from estimates of pedigrees
and inbreeding based on large numbers of markers to
identification of loci responsible for local adaptation
and outbreeding depression. Genomics also provides the
potential to understand the genetic basis of interactions
among species, which could greatly enhance our abil-
ity to manage communities rather than just individual
species. Perhaps the greatest contribution of genomics
to conservation will be the precise genomic monitoring
706 | OCTOBER 2010 | VOLUME 11
Changes in or gene expression
caused by mechanisms
other than changes in the
underlying DNA sequence,
such as DNA methylation
and histone modifications.
Demographic values that
affect population growth
(for example, age-specific
survival, fecundity and age
at first reproduction).
of changes in allelic frequency to quantify the effects of
genetic drift, natural selection and hybridization in wild
and captive populations.
Although we have focused on genomic techniques
that detect variation in DNA sequences, emerging tech-
niques also allow the study of epigenetics, which may
have an important role in conservation genetics in the
future115,116. There is increasing evidence that epigenetic
processes can be important following hybridization and
in outbreeding depression115,117. In addition, epigenetic
effects might be an important source of variation for
invasive species. Richards et al.118 have shown that the
invasive Japanese knotweed (Fallopia spp.), which has
little variation in DNA sequence, maintains substantial
phenotypic variation even under controlled environ-
mental conditions. Epigenetic effects associated with this
phenotypic variation might enhance knotweed’s ability to
invade novel environments. This could partially explain
the paradox of invasive species that have lost genetic
variation during a bottleneck associated with their
introduction but are nonetheless able to adapt to new
Recognizing the limitations of new techniques is
also essential. Improved basic scientific understanding
through genomics will not necessarily lead to improved
conservation. For example, genomics will make it pos-
sible to provide genome-wide estimates of functional
genetic variation and fitness1. Nevertheless, this will
not be sufficient to improve our estimates of popula-
tion viability unless we are able to make the connec-
tions between individual fitness and population growth
rates120 (FIG. 1). To make these connections will require
long-term studies of individual fitness and of the effects
of fitness differences among individuals on demographic
vital rates. This is perhaps the most important and
difficult future challenge facing conservation genetics.
Ellegren, H. & Sheldon, B. C. Genetic basis of fitness
differences in natural populations. Nature 452,
An important paper that reviews current
understanding of the molecular basis of fitness
differences between individuals in natural
Slate, J. et al. Gene mapping in the wild with SNPs:
guidelines and future directions. Genetica 136,
Kohn, M. H., Murphy, W. J., Ostrander, E. A. &
Wayne, R. K. Genomics and conservation genetics.
Trends Ecol. Evol. 21, 629–637 (2006).
Pertoldi, C. et al. Genome variability in European and
American bison detected using the BovineSNP50
BeadChip. Conserv. Genet. 11, 627–634 (2010).
Thomson, R. C., Wang, I. J. & Johnson, J. R.
Genome-enabled development of DNA markers for
ecology, evolution and conservation. Mol. Ecol. 19,
Kerstens, H. et al. Large scale single nucleotide
polymorphism discovery in unsequenced genomes
using second generation high throughput sequencing
technology: applied to turkey. BMC Genomics 10, 479
van Bers, N. E. M. et al. Genome-wide SNP detection
in the great tit Parus major using high throughput
sequencing. Mol. Ecol. 19, 89–99 (2010).
DeLong, E. F. The microbial ocean from genomes to
biomes. Nature 459, 200–206 (2009).
A review of metagenomics in marine systems,
including transcriptomic and functional approaches
linking microbial genomes to ecosystem processes.
Dinsdale, E. A. et al. Functional metagenomic profiling
of nine biomes. Nature 452, 629–634 (2008).
10. Vega Thurber, R. L. et al. Metagenomic analysis
indicates that stressors induce production of herpes-
like viruses in the coral Porites compressa. Proc. Natl
Acad. Sci. USA 47, 18413–18418 (2008).
11. Qin, J. et al. A human gut microbial gene catalogue
established by metagenomic sequencing. Nature 464,
12. Nielsen, E. E., Hemmer-Hansen, J., Larsen, P. F. &
Bekkevold, D. Population genomics of marine fishes:
identifying adaptive variation in space and time.
Mol. Ecol. 18, 3128–3150 (2009).
13. Murchison, E. P. et al. The Tasmanian devil
transcriptome reveals Schwann cell origins of a clonally
transmissible cancer. Science 327, 84–87 (2010).
14. Avise, J. Perspective: conservation genetics enters the
genomics era. Conserv. Genet. 11, 665–669 (2010).
15. Ouborg, N. J., Pertoldi, C., Loeschcke, V., Bijlsma, R. &
Hedrick, P. W. Conservation genetics in transition to
conservation genomics. Trends Genet. 26, 177–187
16. Primmer, C. R. From conservation genetics to
conservation genomics. Ann. N. Y. Acad. Sci. 1162,
17. Romanov, M. N. et al. The value of avian genomics to
the conservation of wildlife. BMC Genomics 10, S10
18. Allendorf, F. W. & Seeb, L. W. Concordance of
genetic divergence among sockeye salmon
populations at allozyme, nuclear DNA, and
mitochondrial DNA markers. Evolution 54,
19. Luikart, G. H., England, P., Tallmon, D. A., Jordan, S. &
Taberlet, P. The power and promise of population
genomics: from genotyping to genome-typing. Nature
Rev. Genet. 4, 981–994 (2003).
20. Storz, J. F. Using genome scans of DNA polymorphism
to infer adaptive population divergence. Mol. Ecol. 14,
21. Giger, T. et al. Life history shapes gene expression in
salmonids. Curr. Biol. 16, R281–R282 (2006).
22. Landry, P.-A., Koskinen, M. T. & Primmer, C. R.
Deriving evolutionary relationships among populations
using microsatellites and (δμ)2: all loci are equal, but
some are more equal than others. Genetics 161,
23. Nordborg, M. Structured coalescent processes on
different time scales. Genetics 146, 1501–1514
24. Beaumont, M. A. Detecting population expansion and
decline using microsatellites. Genetics 153,
25. Beerli, P. & Felsenstein, J. Maximum likelihood
estimation of a migration matrix and effective
population sizes in n subpopulations by using a
coalescent approach. Proc. Natl Acad. Sci. USA 98,
26. Skare, O., Sheehan, N. & Egeland, T. Identification of
distant family relationships. Bioinformatics 25,
27. Browning, S. R. & Weir, B. S. Population structure with
localized haplotype clusters. Genetics 10 May 2010
28. Lecis, R. et al. Bayesian analyses of admixture in wild
and domestic cats (Felis silvestris) using linked
microsatellite loci. Mol. Ecol. 15, 119–131 (2006).
29. Anderson, C. & Meikle, D. Genetic estimates of
immigration and emigration rates in relation to
population density and forest patch area in
Peromyscus leucopus. Conserv. Genet. 5 Feb 2010
30. Bollback, J. P., York, T. L. & Nielsen, R. Estimation of
2Nes from temporal allele frequency data. Genetics
179, 497–502 (2008).
31. Wang, J. & Santure, A. W. Parentage and sibship
inference from multilocus genotype data under
polygamy. Genetics 181, 1579–1594 (2009).
32. Glaubitz, J. C., Rhodes, O. E. & DeWoody, J. A.
Prospects for inferring pairwise relationships with
single nucleotide polymorphisms. Mol. Ecol. 12,
33. Jones, O. R. & Wang, J. Molecular marker-based
pedigrees for animal conservation biologists.
Anim. Conserv. 13, 26–34 (2010).
34. Keinan, A. & Reich, D. Human population
differentiation is strongly correlated with local
recombination rate. PLoS Genet. 6, e1000886
35. Santure, A. W. et al. On the use of large marker
panels to estimate inbreeding and relatedness:
empirical and simulation studies of a pedigreed
zebra finch population typed at 771 SNPs.
Mol. Ecol. 19, 1439–1451 (2010).
36. Smouse, P. How many SNPs are enough? Mol. Ecol.
19, 1265–1266 (2010).
37. Pemberton, J. M. Wild pedigrees: the way forward.
Proc. Biol. Sci. 275, 613–621 (2008).
A persuasive argument for the value of
constructing pedigrees in wild populations to
investigate major issues in evolutionary biology,
including the genetic architecture of traits,
inbreeding depression and inbreeding avoidance.
38. Sham, P., Cherny, S. & Purcell, S. Application of
genome-wide SNP data for uncovering pairwise
relationships and quantitative trait loci. Genetica 136,
39. Pritchard, J. K., Stephens, M. & Donnelly, P.
Inference of population structure using multilocus
genotype data. Genetics 155, 945–959 (2000).
40. Hubisz, M. J., Falush, D., Stephens, M. &
Pritchard, J. K. Inferring weak population structure
with the assistance of sample group information.
Mol. Ecol. Resour. 9, 1322–1332 (2009).
41. Rosenberg, N. A. et al. Genetic structure of human
populations. Science 298, 2381–2385 (2002).
42. Wilson, G. A. & Rannala, B. Bayesian inference of
recent migration rates using multilocus genotypes.
Genetics 163, 1177–1191 (2003).
43. Faubet, P., Waples, R. S. & Gaggiotti, O. E.
Evaluating the performance of a multilocus Bayesian
method for the estimation of migration rates.
Mol. Ecol. 16, 1149–1166 (2007).
44. Rannala, B. & Mountain, J. L. Detecting immigration
by using multilocus genotypes. Proc. Natl Acad. Sci.
USA 94, 9197–9201 (1997).
45. Holderegger, R. & Wagner, H. H. Landscape genetics.
BioScience 58, 199–207 (2008).
An integrated review of the emerging field of
46. Hagenblad, J., Olsson, M., Parker, H. G.,
Ostrander, E. A. & Ellegren, H. Population genomics
of the inbred Scandinavian wolf. Mol. Ecol. 18,
47. Casellas, J., Varona, L., Ibanez-Scriche, N.,
Quintanilla, R. & Noguera, J. L. Skew distribution
of founder-specific inbreeding depression effects
on the longevity of landrace sows. Genet. Res. 90,
48. Lacy, R. C., Alaks, G. & Walsh, A. Hierarchical analysis
of inbreeding depression in Peromyscus polionotus.
Evolution 50, 2187–2200 (1996).
49. Casellas, J., Piedrafita, J., Caja, G. & Varona, L.
Analysis of founder-specific inbreeding depression on
birth weight in Ripollesa lambs. J. Anim. Sci. 87,
50. Charlier, C. et al. Highly effective SNP-based
association mapping and management of recessive
defects in livestock. Nature Genet. 40, 449–454
NATURE REVIEWS | GENETICS
VOLUME 11 | OCTOBER 2010 | 707
51. Vermeulen, C. J., Bijlsma, R. & Loeschcke, V.
QTL mapping of inbreeding-related cold sensitivity
and conditional lethality in Drosophila melanogaster.
J. Evol. Biol. 21, 1236–1244 (2008).
52. Kristensen, T. N., Pedersen, K. S., Vermeulen, C. J. &
Loeschcke, V. Research on inbreeding in the ‘omic’ era.
Trends Ecol. Evol. 25, 44–52 (2010).
An important evaluation of the use of new
technologies to understand the genetic basis of
53. Roach, J. C. et al. Analysis of genetic inheritance in a
family quartet by whole-genome sequencing. Science
328, 636–639 (2010).
54. Nielsen, R. Molecular signatures of natural selection.
Annu. Rev. Genet. 39, 197–218 (2005).
55. Oleksyk, T. K., Smith, M. W. & O’Brien, S. J.
Genome-wide scans for footprints of natural
selection. Philos. Trans. R. Soc. Lond. B 365,
56. Garrigan, D. & Hedrick, P. W. Detecting adaptive
molecular polymorphism: lessons from the MHC.
Evolution 57, 1707–1722 (2003).
57. Antao, T., Lopes, A., Lopes, R., Beja-Pereira, A. &
Luikart, G. LOSITAN: a workbench to detect
molecular adaptation based on a Fst-outlier method.
BMC Bioinformatics 9, 323 (2008).
58. Beaumont, M. A. & Balding, D. J. Identifying adaptive
genetic divergence among populations from genome
scans. Mol. Ecol. 13, 969–980 (2004).
59. Beaumont, M. A. & Nichols, R. A. Evaluating loci
for use in the genetic analysis of population
structure. Proc. R. Soc. Lond. B 263, 1619–1626
60. Foll, M. & Gaggiotti, O. A genome-scan method to
identify selected loci appropriate for both dominant
and codominant markers: a Bayesian perspective.
Genetics 180, 977–993 (2008).
61. Makinen, H. S., Cano, J. M. & Merilä, J.
Identifying footprints of directional and balancing
selection in marine and freshwater three-spined
stickleback (Gasterosteus aculeatus) populations.
Mol. Ecol. 17, 3565–3582 (2008).
62. Namroud, M.-C., Beaulieu, J., Juge, N., Laroche, J. &
Bousquet, J. Scanning the genome for gene single
nucleotide polymorphisms involved in adaptive
population differentiation in white spruce. Mol. Ecol.
17, 3599–3613 (2008).
63. Nielsen, E. E. et al. Genomic signatures of local
directional selection in a high gene flow marine
organism; the Atlantic cod (Gadus morhua).
BMC Evol. Biol. 9, 276 (2009).
64. Oetjen, K. & Reusch, T. B. H. Genome scans detect
consistent divergent selection among subtidal vs.
intertidal populations of the marine angiosperm
Zostera marina. Mol. Ecol. 16, 5156–5167
65. Vasemägi, A., Nilsson, J. & Primmer, C. R.
Expressed sequence tag-linked microsatellites
as a source of gene-associated polymorphisms for
detecting signatures of divergence selection in
Atlantic salmon (Salmo salar L.). Mol. Biol. Evol. 22,
66. Hohenlohe, P. A. et al. Population genomic analysis of
parallel adaptation in threespine stickleback using
sequenced RAD tags. PLoS Genet. 6, e1000862
One of the first papers to use genomic scans of
thousands of markers to understand the genetic
basis of adaptation in natural populations.
67. Wilding, C. S., Butlin, R. K. & Grahame, J.
Differential gene exchange between parapatric
morphs of Littorina saxatilis detected using AFLP
markers. J. Evol. Biol. 14, 611–619 (2001).
68. Pennings, P. S. & Hermisson, J. Soft sweeps II —
molecular population genetics of adaptation from
recurrent mutation or migration. Mol. Biol. Evol. 23,
69. Voight, B. F., Kudaravalli, S., Wen, X. & Pritchard, J. K.
A map of recent positive selection in the human
genome. PLoS Biol. 4, e72 (2006).
70. Allendorf, F. W. & Hard, J. J. Human-induced evolution
caused by unnatural selection through harvest of wild
animals. Proc. Natl Acad. Sci. USA 106, 9987–9994
71. Allendorf, F. W., England, P. R., Luikart, G.,
Ritchie, P. A. & Ryman, N. Genetic effects of harvest
on wild animal populations. Trends Ecol. Evol. 23,
72. Frankham, R. Where are we in conservation genetics
and where do we need to go? Conserv. Genet. 11,
73. Allendorf, F. W., Leary, R. F., Spruell, P. &
Wenburg, J. K. The problems with hybrids:
setting conservation guidelines. Trends Ecol. Evol.
16, 613–622 (2001).
74. Levin, D. A., Franciscoortega, J. & Jansen, R. K.
Hybridization and the extinction of rare plant species.
Conserv. Biol. 10, 10–16 (1996).
75. Crandall, K. A., Binindaemonds, O. R. P., Mace, G. M.
& Wayne, R. K. Considering evolutionary processes in
conservation biology. Trends Ecol. Evol. 15, 290–295
76. Hedrick, P. W., Parker, K. M. & Lee, R. N.
Using microsatellite and MHC variation to
identify species, ESUs, and MUs in the endangered
Sonoran topminnow. Mol. Ecol. 10, 1399–1412
77. Bonin, A., Nicole, F., Pompanon, F., Miaud, C. &
Taberlet, P. Population adaptive index: a new method
to help measure intraspecific genetic diversity and
prioritize populations for conservation. Conserv. Biol.
21, 697–708 (2007).
78. Coop, G. et al. The role of geography in human
adaptation. PLoS Genet. 5, e1000500 (2009).
79. Frazer, K. A., Murray, S. S., Schork, N. J. & Topol, E. J.
Human genetic variation and its contribution to
complex traits. Nature Rev. Genet. 10, 241–252
80. Hansen, M. M. Expression of interest: transcriptomics
and the designation of conservation units. Mol. Ecol.
19, 1757–1759 (2010).
81. Tymchuk, W. V., O’Reilly, P., Bittman, J., MacDonald, D.
& Schulte, P. Conservation genomics of Atlantic
salmon: variation in gene expression between and
within regions of the Bay of Fundy. Mol. Ecol. 19,
82. Cornuet, J.-M., Piry, S., Luikart, G., Estoup, A. &
Solignac, M. New methods employing multilocus
genotypes for selecting or excluding populations as
origins of individuals. Genetics 153, 1989–2000
83. Witherspoon, D. J. et al. Genetic similarities within
and between human populations. Genetics 176,
84. Halbert, N. D. & Derr, J. N. A comprehensive
evaluation of cattle introgression into US federal
bison herds. J. Hered. 98, 1–12 (2007).
85. Allendorf, F. W. et al. Cutthroat trouth
hybridization and the U. S. Endangered Species
Act: one species, two policies. Conserv. Biol. 19,
86. Campton, D. E. & Kaeding, L. R. Westslope cutthroat
trout, hybridization, and the U. S. Endangered
Species Act. Conserv. Biol. 19, 1323–1325
87. Marris, E. The genome of the American west. Nature
457, 950–952 (2009).
88. Payseur, B. A. Using differential introgression in
hybrid zones to identify genomic regions involved
in speciation. Mol. Ecol. Resour. 10, 806–820
89. Fitzpatrick, B. M. et al. Rapid spread of invasive genes
into a threatened native species. Proc. Natl Acad. Sci.
USA 107, 3606–3610 (2010).
A fascinating study showing that natural selection
can rapidly accelerate the rate of introgression for
certain regions of the genome from introduced into
90. Edmands, S. Between a rock and a hard place:
evaluating the relative risks of inbreeding and
outbreeding for conservation and management.
Mol. Ecol. 16, 463–475 (2007).
91. Shendure, J. & Ji, H. Next-generation DNA
sequencing. Nature Biotech. 26, 1135–1145
92. Hoffmann, A. A. & Rieseberg, L. H. Revisiting the
impact of inversions in evolution: from population
genetic markers to drivers of adaptive shifts and
speciation? Annu. Rev. Ecol. Evol. Syst. 39, 21–42
An important synthesis that evaluates the
importance of chromosomal inversions in
population genetics and evolution using modern
93. Muhlfeld, C. C. et al. Hybridization rapidly reduces
fitness of a native trout in the wild. Biol. Lett. 5,
94. Ljungqvist, M., Åkesson, M. & Hansson, B.
Do microsatellites reflect genome-wide genetic
diversity in natural populations? A comment
on Väli. et al. (2008). Mol. Ecol. 19, 851–855
95. Miller, W., Wright, S. J., Zhang, Y., Schuster, S. C. &
Hayes, V. M. Optimization methods for selecting
founder individuals for captive breeding or
reintroduction of endangered species. Pac. Symp.
Biocomput. 2010, 43–53 (2010).
96. Blouin, M. S. DNA-based methods for pedigree
reconstruction and kinship analysis in natural
populations. Trends Ecol. Evol. 18, 503–511(2003).
97. Goddard, M. E. & Hayes, B. J. Mapping genes for
complex traits in domestic animals and their use in
breeding programmes. Nature Rev. Genet. 10,
98. Lacy, R. C. in Conservation Genetics in the Age of
Genomics (eds Amato, G., Ryder, O., Rosenbaum, H. &
DeSalle, R.) 58–81 (Columbia Univ. Press, New York,
99. Araki, H., Cooper, B. & Blouin, M. S. Genetic effects of
captive breeding cause a rapid, cumulative fitness
decline in the wild. Science 318, 100–103 (2007).
One of the first papers to demonstrate a reduction
in fitness in wild populations caused by gene flow
from captive populations.
100. Frankham, R. Genetic adaptation to captivity in
species conservation programs. Mol. Ecol. 17,
101. Schwartz, M. K., Luikart, G. & Waples, R. S.
Genetic monitoring as a promising tool for
conservation and management. Trends Ecol. Evol.
22, 25–33 (2007).
A foundation paper that defined and organized the
emerging field of genetic monitoring.
102. Tallmon, D. A., Luikart, G. & Waples, R. S.
The alluring simplicity and complex reality of genetic
rescue. Trends Ecol. Evol. 19, 489–496 (2004).
103. Piertney, S. B. & Oliver, M. K. The evolutionary
ecology of the major histocompatibility complex.
Heredity 96, 7–21 (2006).
104. Holmes, G. D., James, E. A. & Hoffmann, A. A.
Limitations to reproductive output and genetic rescue
in populations of the rare shrub Grevillea repens
(Proteaceae). Ann. Bot. 102, 1031–1041 (2008).
105. Pogson, G. H. & Fevolden, S. E. Natural selection and
the genetic differentiation of coastal and Arctic
populations of the Atlantic cod in northern Norway: a
test involving nucleotide sequence variation at the
pantophysin (PanI) locus. Mol. Ecol. 12, 63–74
106. Wheat, C. Phosphoglucose isomerase (Pgi)
performance and fitness effects among Arthropods
and its potential role as an adaptive marker in
conservation genetics. Conserv. Genet. 11, 387–397
107. Barbour, R. C., Forster, L. G., Baker, S. C., Steane, D. A.
& Potts, B. M. Biodiversity consequences of genetic
variation in bark characteristics within a foundation
tree species. Conserv. Biol. 23, 1146–1155 (2009).
108. Whitham, T. G. et al. Extending genomics to natural
communities and ecosystems. Science 320, 492–495
109. Crutsinger, G. M. et al. Plant genotypic diversity
predicts community structure and governs an
ecosystem process. Science 313, 966–968 (2006).
110. Hodges, E. et al. Genome-wide in situ exon capture for
selective resequencing. Nature Genet. 39,
111. Nowrousian, M. Next-generation sequencing
techniques for eukaryotic microorganisms: sequencing-
based solutions to biological problems. Eukaryot. Cell
2 Jul 2010 (doi:10.1128/EC.00123-10).
112. Li, R. et al. SNP detection for massively parallel whole-
genome resequencing. Genome Res. 19, 1124–1132
113. International HapMap Consortium. A second
generation human haplotype map of over 3.1 million
SNPs. Nature 449, 851–861 (2007).
114. Haussler, D. et al. Genome 10K: a proposal to obtain
whole-genome sequence for 10000 vertebrate
species. J. Hered. 100, 659–674 (2009).
115. Bossdorf, O., Richards, C. L. & Pigliucci, M.
Epigenetics for ecologists. Ecol. Lett. 11, 106–115
A valuable consideration of the future application
of epigenetics to understanding the ecology of
116. Richards, C. L., Bossdorf, O. & Pigliucci, M. What role
does heritable epigenetic variation play in phenotypic
evolution? BioScience 60, 232–237 (2010).
117. Salmon, A., Ainouche, M. L. & Wendel, J. F.
Genetic and epigenetic consequences of recent
hybridization and polyploidy in Spartina (Poaceae).
Mol. Ecol. 14, 1163–1175 (2005).
708 | OCTOBER 2010 | VOLUME 11
118. Richards, C. L. et al. Plasticity in salt tolerance traits
allows for invasion of novel habitat by Japanese
knotweed s. l. (Fallopia japonica and F. bohemica,
Polygonaceae). Am. J. Bot. 95, 931–942 (2008).
119. Allendorf, F. W. & Lundquist, L. L. Introduction:
population biology, evolution, and control of invasive
species. Conserv. Biol. 17, 24–30 (2003).
120. Coulson, T. et al. Estimating individual contributions
to population growth: evolutionary fitness in ecological
time. Proc. Biol. Sci. 273, 547–555 (2006).
121. Palsbøll, P. J., Berube, M. & Allendorf, F. W.
Identification of management units using population
genetic data. Trends Ecol. Evol. 22, 11–16 (2007).
122. Waples, R. S. Separating the wheat from the chaff:
patterns of genetic differentiation in high gene flow
species. J. Hered. 89, 438–450 (1998).
An important paper that considers how to interpret
the low genetic differentiation observed between
marine populations that are apparently
123. Pampoulie, C. et al. The genetic structure of Atlantic
cod (Gadus morhua) around Iceland: insight from
microsatellites, the PanI locus, and tagging
experiments. Can. J. Fish. Aquat. Sci. 63, 2660–2674
124. Hemmer-Hansen, J., Nielsen, E. E., Frydenberg, J. &
Loeschcke, V. Adaptive divergence in a high gene flow
environment: Hsc70 variation in the European
flounder (Platichthys flesus L.). Heredity 99,
125. Lowe, W. H. & Allendorf, F. W. What can genetics tell
us about population connectivity? Mol. Ecol. 19,
126. Waples, R. S. & Gaggiotti, O. What is a population?
An empirical evaluation of some genetic methods
for identifying the number of gene pools and their
degree of connectivity. Mol. Ecol. 15, 1419–1439
An extremely valuable paper that considers the
fundamental problem of defining ‘population’ in
127. Baird, N. A. et al. Rapid SNP discovery and genetic
mapping using sequenced RAD markers. PLoS ONE 3,
128. Perkel, J. SNP genotyping: six technologies that keyed
a revolution. Nature Methods 5, 447–453 (2008).
129. Decker, J. E. et al. Resolving the evolution of extant
and extinct ruminants with high-throughput
phylogenomics. Proc. Natl Acad. Sci. USA 106,
This article is based partially on work supported by the US
National Science Foundation grants DEB 074218 to F.W.A. and
G.L., and IOS 0843392 to P.A.H. G.L. also received support
from the Walton Family Foundation and research grants PTDC/
BIA-BDE/65625/2006 and PTDC/CVT/69438/2006 from the
Portuguese Science Foundation. We thank D. E. Campton,
R. Frankham, O. Gaggiotti, P. Hedrick, L. S. Mills, B. A. Payseur,
K. M. Ramstad, M. K. Schwartz, P. Sunnucks and D. A. Tallmon
for useful comments, and W. H. Lowe for endless EndNote
tutoring to F.W.A.
Competing interests statement
The authors declare no competing financial interests.
Fred W. Allendorf’s homepage: http://www.cas.umt.edu/
See online article: S1 (figure)
ALL LINKS ARE ACTIVE IN THE ONLINE PDF
NATURE REVIEWS | GENETICS
VOLUME 11 | OCTOBER 2010 | 709
000 Genomics and the future of conservation
Fred W. Allendorf, Paul A. Hohenlohe and Gordon
This article discusses how genomic techniques are
expected to provide new insights into important
problems in conservation and to allow questions to
be addressed that have previously not been tractable.
The authors also offer advice on choosing the most
appropriate genomic approaches for studying
different aspects of conservation.
??We will soon have complete genome sequences from thousands of
species. This coming explosion of information will transform our
understanding of the amount, distribution and functional signifi-
cance of genetic variation in natural populations.
??We identify those problems in conservation biology in which
genomics will be most valuable in providing new insights and
understanding. We also provide guidelines as to which new genom-
ics approaches will be most appropriate for the different problems
in conservation that can benefit from genetic analysis.
??The most straightforward contribution of genomics to conserva-
tion will be to enormously increase the precision and accuracy
of estimation of crucial parameters that require neutral loci (for
example, effective population size and migration rate).
??Genomic approaches can address important questions about the
molecular basis and genetic architecture of inbreeding depression.
Recent work indicates that the intensity of inbreeding depression
can differ greatly depending on which specific individuals are
founders. This suggests that the genetic load is unevenly spread
among founder genomes and supports the notion that inbreeding
depression sometimes results from major effects at a few loci.
??Anthropogenic challenges affect a wide range of species and habi-
tats. Genomic approaches will allow the identification of adaptive
genetic variation related to key traits for the response to climate
change, such as phenology or drought tolerance, so that manage-
ment may focus on maintaining adaptive genetic potential. The use
of genomics to monitor genetic change caused by the harvesting
of animals by humans could be extremely important because early
detection of potentially harmful genetic change will maximize our
ability to implement management to limit or reverse the effects
before substantial or irreversible changes occur.
??Genomics provides exciting opportunities to assess differential
rates of introgression across different genomic regions following
hybridization between native and introduced species. The differ-
ential introgression rates of genomic regions raise some difficult
issues with regards to treating hybridized populations in conserva-
tion and bring into question the efficacy of using a few (that is, ten
or so) neutral markers to detect hybridization.
??Genomic tools will assist the management of ex situ populations
and reintroductions by providing increased precision and accuracy
of estimates of neutral population genetic parameters and by iden-
tifying specific loci of importance, which are essential for selecting
select founder individuals.
??There is increasing evidence that epigenetic processes can be impor-
tant following hybridization. Therefore, an epigenetics perspective
might be important for understanding the effects of hybridization
and predicting outbreeding depression.
??Improved basic scientific understanding through genomics will not
necessarily lead to improved conservation. For example, under-
standing the relationship between genetic variation and fitness
itself will not be sufficient to improve our estimates of population
viability. Understanding the connections between individual fit-
ness and population growth rates is perhaps the most important
and difficult future challenge facing conservation genetics.
Fred W. Allendorf received his Ph.D. from the University of
Washington, Seattle, USA, and was a postdoctoral fellow at Aarhus
University, Denmark, and the University of Nottingham, UK. He has
been at the University of Montana, Missoula, USA, since 1976 and cur-
rently has a partial appointment at Victoria University of Wellington,
New Zealand. He recently has held fellowships at the University of
Western Australia in Perth and Australia’s Commonwealth Scientific
and Industrial Research Organisation (CSIRO) in Hobart. His pri-
mary research focus is the application of population genetics to
Paul A. Hohenlohe received his Ph.D. from the University of
Washington and worked as a conservation biologist for the US Bureau
of Land Management and Forest Service under the Northwest Forest
Plan. He is currently a research associate at the University of Oregon,
Eugene, USA, and Oregon State University, Corvallis, USA. His
research is focused on population genomics approaches to questions
in conservation and evolution.
Gordon Luikart received his Ph.D. at the University of Montana,
was a Fulbright fellow at LaTrobe University, Victoria, Australia, a
research scientist at the Centre National de la Recherche Scientifique
(CNRS), Grenoble, France, and a research scientist at the Centro
de Investigação em Biodiversidade e Recursos Genéticos (CIBIO),
Vairão, Portugal. He is a research associate professor at the Flathead
Lake Biological Station, University of Montana. His research is aimed
at developing molecular and computational approaches to bridge the
gaps between theory, basic science and practical applications in con-
servation biology and evolutionary ecology.