TY - JOUR
AU - Wachowiak, Witold
AB - Scots pine (Pinus sylvestris L.) is one of the most ecologically and economically important forest-forming tree species in the Northern Hemisphere. Because of value, numerous genetic studies have been conducted since the 19th century to develop or improve the breeding and conservation programs of the species. Current studies are motivated by growing concerns about the survival and productivity of Scots pine populations, especially in the face of long-term environmental change predictions. In this article, we review major questions in the population genetics of Scots pine and show how previous studies advance current research approaches. We refer to major outcomes of the research describing the genetic variation and postglacial history of Scots pine compared with those of other cold-tolerant tree species such as Norway spruce (Picea abies) and silver birch (Betula pendula). We present results from studies of quantitative trait variation and local adaptation across the Scots pine distribution. We focus on the main research directions in dissection of the genetic basis of adaptive traits and the search for signatures of selection using quantitative trait locus mapping, candidate genes, association genetics, and genome scanning approaches. Finally, we highlight novel approaches in molecular breeding and point out new research prospects in genomic studies of Scots pine and other forest tree species in the face of rapid developments in next-generation sequencing and genotyping methods. association mapping, local adaptation, population structure, genomic selection, single nucleotide polymorphism arrays Forest trees cover roughly 30% of the world’s land area and constitute about 90% of the continental biomass. They are one of the key elements of forest ecosystems that harbor the vast majority of the world’s terrestrial biodiversity and fulfill significant economic, environmental, and social functions. Moreover, trees are valuable research objects as they form large, open-pollinated populations and have high levels of genetic diversity and phenotypic variation. The fact that trees possess great genetic variation and low genetic differentiation in comparison to other plant species is not surprising, given their longevity, extensive gene flow, mating system, and complex postglacial history (Petit and Hampe 2006). To understand this genetic diversity, much effort is now being focused on constructing and interpreting the genomes of forest trees. Genetic studies of forest species have primarily involved one gymnosperm (Pinaceae) and three angiosperm (Salicaceae, Myrtaceae, and Fagaceae) families. In particular, several genera within these families have been intensively studied including Pinus, Picea, Pseudotsuga, Populus, Abies, Fagus, Eucalyptus, and Quercus (Neale and Kremer 2011). In this group, Scots pine (Pinus sylvestris L.) has proved to be an important example for advancing the understanding of the impact of demographic (population history) and evolutionary (natural selection) forces on patterns of genetic variation in widespread tree species. Understanding the genetic basis of adaptation by linking genetic and phenotypic variation is a key goal in evolutionary biology, and this knowledge will advance forest tree breeding and management. Therefore, disentangling patterns of demographic and adaptive differentiation in the species using complementary approaches (Figure 1) is an important research objective. Figure 1. View largeDownload slide Connections between different processes and approaches in demographic and evolutionary assessments of neutral and adaptive genetic variation. Figure 1. View largeDownload slide Connections between different processes and approaches in demographic and evolutionary assessments of neutral and adaptive genetic variation. Scots pine has the widest natural distribution range of all conifers. Currently, it extends from the Arctic Circle in northern Scandinavia (70° N) to central Spain and Turkey (40° N) and from western Scotland (6° W) to eastern Siberia (150° E). It grows at elevations from sea level in western Scotland to 2,500 m in the Caucasus Mountains in Turkey and grows in mixed forests with other conifers or broadleaved trees or in pure stands. In cultivation, it is used as an admixed and a pioneer crop or nurse species, especially in fir forests (Boratyński 1993), and has great breeding significance in Europe and Asia. For instance, commercial Scots pine plantations cover >70% of forest tree production in Poland and about 50% of the whole productive forest area in Sweden and Finland. Pine timber is used as firewood, as sawn wood, and as pulp for the paper industry. Because of the high ecological and economic value of Scots pine, it has been the subject of many genetic studies since the 19 th century. Initial studies were motivated by the need to understand the species biology for conservation and breeding programs. Later, development of biochemical and molecular methods moved research into assessment of genetic variation. Recent progress in sequencing and genotyping methods together with data on phenotypic trait variation and fine-scale ecological data provided the opportunity to address fundamental questions about the genetic architecture of adaptive traits. These traits have allowed Scots pine to succeed in a wide range of environments and become one of the keystone forest-forming species in the northern hemisphere. In this article, we focus on major questions and approaches in the population genetics and genomics of Scots pine (Table 1). Our aim was to look at how the outcomes of the previous and ongoing studies can advance future research directions in the species. We review the results of quantitative and population genetic studies and focus on research in genomics and natural selection to discuss developments in analysis at the whole-genome level. Finally, we discuss prospects for molecular breeding programs and perspectives for future directions in genomic research. Table 1. Outstanding questions and approaches in genetic research of Scots pine.   Areas for further investigation  Possible approaches  Demographic processes  Number and location of refugial areas and identification of natural populations  Comparative sequencing of large proportion of mitochondrial genome using next generation sequencing approaches    Level of admixture of populations of different origin during recolonization process  Development of high resolution mtDNA markers for fine-scale phylogeographic assessments    Major demographic drivers of current genetic variation of the species  Use of new phylogeographic data for testing the role of standing and novel mutations in development of clines of adaptive variation    Assessment of anthropogenic influence on genetic structure of the species and identification of truly native populations  Denser sampling across Europe and east part of distribution range  Evolutionary processes  Genetic architecture of adaptive traits  Application of genome-wide polymorphisms study    Identification of genes under selection involved in variation at quantitative traits and biotic and abiotic environmental adaptations of populations  Development of new methods for detecting signal of selection at polygenic traits    Linking genotypic data and phenotypic variation  Application of genomic selection methods for improvement of breeding strategies    Use of genetic data for management of long-term response of populations to environmental changes  Development of phenotyping and physiological assessments methods for association genetic studies    Areas for further investigation  Possible approaches  Demographic processes  Number and location of refugial areas and identification of natural populations  Comparative sequencing of large proportion of mitochondrial genome using next generation sequencing approaches    Level of admixture of populations of different origin during recolonization process  Development of high resolution mtDNA markers for fine-scale phylogeographic assessments    Major demographic drivers of current genetic variation of the species  Use of new phylogeographic data for testing the role of standing and novel mutations in development of clines of adaptive variation    Assessment of anthropogenic influence on genetic structure of the species and identification of truly native populations  Denser sampling across Europe and east part of distribution range  Evolutionary processes  Genetic architecture of adaptive traits  Application of genome-wide polymorphisms study    Identification of genes under selection involved in variation at quantitative traits and biotic and abiotic environmental adaptations of populations  Development of new methods for detecting signal of selection at polygenic traits    Linking genotypic data and phenotypic variation  Application of genomic selection methods for improvement of breeding strategies    Use of genetic data for management of long-term response of populations to environmental changes  Development of phenotyping and physiological assessments methods for association genetic studies  View Large Table 1. Outstanding questions and approaches in genetic research of Scots pine.   Areas for further investigation  Possible approaches  Demographic processes  Number and location of refugial areas and identification of natural populations  Comparative sequencing of large proportion of mitochondrial genome using next generation sequencing approaches    Level of admixture of populations of different origin during recolonization process  Development of high resolution mtDNA markers for fine-scale phylogeographic assessments    Major demographic drivers of current genetic variation of the species  Use of new phylogeographic data for testing the role of standing and novel mutations in development of clines of adaptive variation    Assessment of anthropogenic influence on genetic structure of the species and identification of truly native populations  Denser sampling across Europe and east part of distribution range  Evolutionary processes  Genetic architecture of adaptive traits  Application of genome-wide polymorphisms study    Identification of genes under selection involved in variation at quantitative traits and biotic and abiotic environmental adaptations of populations  Development of new methods for detecting signal of selection at polygenic traits    Linking genotypic data and phenotypic variation  Application of genomic selection methods for improvement of breeding strategies    Use of genetic data for management of long-term response of populations to environmental changes  Development of phenotyping and physiological assessments methods for association genetic studies    Areas for further investigation  Possible approaches  Demographic processes  Number and location of refugial areas and identification of natural populations  Comparative sequencing of large proportion of mitochondrial genome using next generation sequencing approaches    Level of admixture of populations of different origin during recolonization process  Development of high resolution mtDNA markers for fine-scale phylogeographic assessments    Major demographic drivers of current genetic variation of the species  Use of new phylogeographic data for testing the role of standing and novel mutations in development of clines of adaptive variation    Assessment of anthropogenic influence on genetic structure of the species and identification of truly native populations  Denser sampling across Europe and east part of distribution range  Evolutionary processes  Genetic architecture of adaptive traits  Application of genome-wide polymorphisms study    Identification of genes under selection involved in variation at quantitative traits and biotic and abiotic environmental adaptations of populations  Development of new methods for detecting signal of selection at polygenic traits    Linking genotypic data and phenotypic variation  Application of genomic selection methods for improvement of breeding strategies    Use of genetic data for management of long-term response of populations to environmental changes  Development of phenotyping and physiological assessments methods for association genetic studies  View Large Phylogeography and Genetic Structure of Scots Pine Genetic Variation and Population Differentiation Studies of historical processes such as population size fluctuations and geographical range shifts (Figure 1) are needed to help separate the effects of demographic factors on background genetic variation from those due to selection. Historical range shifts or population size reductions will affect all genes in a similar way, producing genomewide patterns of genetic variation in contrast to polymorphisms of individual loci under selection. Overall, high levels of genetic variation have been found across the Scots pine distribution in biochemical and molecular studies. Typically, this diversity is widely distributed as shown by low levels of among-population genetic differentiation across the range (Gullberg et al. 1984, Karhu et al. 1996, Puglisi and Attolico 2000, Prus-Głowacki et al. 2003, Robledo-Arnuncio et al. 2005, Bilgen and Kaya 2007, Wachowiak et al. 2011, 2013, 2014, Belletti et al. 2012). Low genetic differentiation was also observed between the Scandinavian and eastern parts of the range (Wang et al. 1991) and among populations along a large latitudinal cline in continental Europe (Goncharenko et al. 1994, Dvornyk et al. 2002, García-Gil et al. 2003, Pyhäjärvi et al. 2007) and between the northern and central European parts of the species distribution (Wachowiak et al. 2014). Such low genetic structure is expected for highly outcrossing, wind-pollinated trees, in which efficient gene flow has a homogenizing effect on the distribution of genetic variation across large geographical ranges. The highest levels of differentiation were found between populations from the Iberian Peninsula and Asia Minor based on biometric characteristics of needles and molecular analysis (Naydenov et al. 2007, Pyhäjhärvi et al. 2008, Jasińska et al. 2014). Moreover, analysis of morphological and molecular data has shown genetic subdivision of marginal Scots pine populations in Spain (Prus-Głowacki et al. 2003, 2012, Robledo-Arnuncio et al. 2005, Jasińska et al. 2010, 2014) and Scotland (Kinloch et al. 1986, Birks 1989), which had high levels of genetic variation compared with populations in the parts of the range where the species is continuously distributed. However, many aspects of the history of Scots pine, including the location of glacial refugia, postglacial recolonization routes, and associated demographic events, remain unclear. Knowledge about population history, which affects genomewide genetic variation, is needed to understand how genomes reflect evolutionary history and to effectively search for genomic regions subjected to natural selection. Glacial and Postglacial History The uniparentally inherited, haploid, and nonrecombinant nature of organelle genomes makes them useful tools for studies of plant phylogeography (Petit et al. 2005). In pines, mitochondrial DNA (mtDNA) is maternally inherited and dispersed by seeds over short distances, which makes mtDNA markers especially useful for tracking migration routes. So far, however, only a few low-resolution mtDNA markers have been found for Scots pine (Table 3). Spatial analysis of mtDNA haplotypes and other genetic markers including isozymes in combination with palynological data (Sinclair et al. 1999, Soranzo et al. 2000, Cheddadi et al. 2006, Naydenov et al. 2007, Pyhäjarvi et al. 2008, Prus-Głowacki et al. 2012) indicate that Scots pine survived the last glacial maximum (25,000–18,000 years ago) in Southern peninsulas (Iberian, Apennine, and Balkan) and possibly some parts of Eastern and Central Europe (Taberlet et al. 1998, Petit et al. 2003, Willis and van Andel 2004, Buchovska et al. 2013). Unique mtDNA mitotypes in Anatolia (Asia Minor) also pinpoint this region as an area of endemism for Scots pine (Naydenov et al. 2007, Pyhäjarvi et al. 2008). However, disentangling postglacial population dynamics beyond the recognized refugia has been complex. Because newly colonized areas are expected to contain only a subset of genetic variation present in source populations, the central and northernmost populations of Scots pine might be expected to show reduced mtDNA diversity. It now seems clear that gene flow by seeds from the southern populations of the Iberian Peninsula, the Apennine Peninsula, and Anatolia was limited (Cheddadi et al. 2006, Pyhäjärvi et al. 2008) (Figure 2). Therefore, it is possible that several distinct lineages of Scots pine from cryptic refugial areas located at higher latitudes in Eurasia have mixed in Central and Northern Europe. Genetic data indicate colonization of Central and North Europe from refugial areas localized in the Balkans (Prus-Głowacki et al. 2012, Sannikov and Petrova 2012), Alps (Cheddadi et al. 2006) and the region of Moscow (Naydenov et al. 2007, Pyhäjärvi et al. 2008, Buchovska et al. 2013) (Figure 2). Moreover, some alternative routes of Scots pine postglacial migration from Southern Siberia to Central Europe and Asia Minor have been suggested on the basis of analysis of allozyme markers (Sannikov and Egorov 2015) (Table 2). Figure 2. View largeDownload slide Map showing the locations of the major southern refugia during the last glacial maximum including Iberian Peninsula (Ib), Italy (It), Balkans (Ba), and Anatolia (An) and other putative refugial areas (BI, British Isles; Al, Alps; Ca, Carpathians, WA, Western Asia; N, Northern Europe). Possible recolonization routes are marked with arrows as suggested in previous Scots pine studies (Table 2). Figure 2. View largeDownload slide Map showing the locations of the major southern refugia during the last glacial maximum including Iberian Peninsula (Ib), Italy (It), Balkans (Ba), and Anatolia (An) and other putative refugial areas (BI, British Isles; Al, Alps; Ca, Carpathians, WA, Western Asia; N, Northern Europe). Possible recolonization routes are marked with arrows as suggested in previous Scots pine studies (Table 2). Table 2. Indication of Scots pine phylogeography based on biometric, biochemical, and molecular data. Area (marker type)  Major conclusions and hypotheses  Iberian Peninsula (Ib) (mtDNA, cpDNA, isoenzymes, biometry)  Subdivision of populations into two genetically heterogeneous groups including West-Central and Northeastern Spain. Unique haplotypes at mtDNA suggest limited seed flow from Iberian populations during recolonization of Europe; genetic similarity between populations from Massif Central in France and northern parts of the Iberian Peninsula (Sinclair et al. 1999, Soranzo et al. 2000, Prus-Głowacki et al. 2003, 2012, Robledo-Arnuncio et al. 2005, Cheddadi et al. 2006, Naydenov et al. 2007, Pyhäjärvi et al. 2008, Jasińska et al. 2014)  British Isles (BI) (terpens, mtDNA, cpDNA, SNPs of nDNA)  Genetic subdivision of populations to western and eastern stands explained by two hypotheses: western refugial populations versus eastern stands of continental origin; and result of two distinct colonization routes from continental Europe. High level of genetic polymorphism as compared to mainland populations not compatible with simple recolonization model (Kinloch et al. 1986, Provan et al. 1998, Sinclair et al. 1998, Naydenov et al. 2007, Wachowiak et al. 2011)  Apennine Peninsula (It) (mtDNA, SSR cpDNA, SSR and SNPs of nDNA)  At least three different refugia in the Western Alps, Eastern Alps, and Apennines. Isolation of Italian populations due to the presence of Alpine barrier and its exclusion from colonization of Central and Northern Europe; high nucleotide divergence between Italy versus Central Europe (Cheddadi et al. 2006, Belletti et al. 2012, Kujala and Savolainen 2012)  Alps (Al) and Carpathians (Ca) (mtDNA, SSR cpDNA)  Existence of patchy refugia located around the Alps and Carpathians involved in postglacial colonization of Europe (Cheddadi et al. 2006)  Balkan Peninsula (Ba) (isozymes, mtDNA)  Similar genetic variation and low genetic differentiation indicating contribution of Balkan refugium in postglacial recolonization of Europe (Naydenov et al. 2007, Prus-Głowacki et al. 2012)  Anatolia (An) (isozymes, mtDNA, SNPs of nDNA, biometry)  Asia Minor as the area of endemism comparable to Iberian and Apennine Peninsulas. Unique mtDNA mitotype suggesting limited gene flow by seeds during recolonization. Low variation at nuclear gene loci, isozymes, and morphological traits suggest ongoing gene flow between some populations from Turkey, the Balkans, and Central and Northern Europe; genetic subdivision within Turkish populations (Bilgen and Kaya 2007, Naydenov et al. 2007, Pyhäjärvi et al. 2008, Jasińska et al. 2014, Sannikov and Egorov 2015)  Northern Europe (N) (mtDNA, SNPs of nDNA)  Possible existence of cryptic refugia in Fennoscandia or Eastern Europe based on frequency of mtDNA haplotypes compared with other distribution range in Euro-Asia; high genetic similarity between Polish and Northern European populations at nDNA (Naydenov et al. 2007, Pyhäjärvi et al. 2008, Wachowiak et al. 2011)  Western Asia (WA) (isozymes, mtDNA)  Nonrandom distribution of mitotypes suggests the existence of the southeastern refugium at about 300 km southeast of Moscow, rather than the Central European origin of the Scandinavian populations; three distinct gene pools including the Balkans, Southern Urals, and Northern Mongolia; free gene flow from the Southern Baikal region to the Balkans, Central Europe, and Asia Minor along the northern coast of the Eastern Paratethys (Sannikov and Petrova 2012, Buchovska et al. 2013, Sannikov and Egorov 2015)  Area (marker type)  Major conclusions and hypotheses  Iberian Peninsula (Ib) (mtDNA, cpDNA, isoenzymes, biometry)  Subdivision of populations into two genetically heterogeneous groups including West-Central and Northeastern Spain. Unique haplotypes at mtDNA suggest limited seed flow from Iberian populations during recolonization of Europe; genetic similarity between populations from Massif Central in France and northern parts of the Iberian Peninsula (Sinclair et al. 1999, Soranzo et al. 2000, Prus-Głowacki et al. 2003, 2012, Robledo-Arnuncio et al. 2005, Cheddadi et al. 2006, Naydenov et al. 2007, Pyhäjärvi et al. 2008, Jasińska et al. 2014)  British Isles (BI) (terpens, mtDNA, cpDNA, SNPs of nDNA)  Genetic subdivision of populations to western and eastern stands explained by two hypotheses: western refugial populations versus eastern stands of continental origin; and result of two distinct colonization routes from continental Europe. High level of genetic polymorphism as compared to mainland populations not compatible with simple recolonization model (Kinloch et al. 1986, Provan et al. 1998, Sinclair et al. 1998, Naydenov et al. 2007, Wachowiak et al. 2011)  Apennine Peninsula (It) (mtDNA, SSR cpDNA, SSR and SNPs of nDNA)  At least three different refugia in the Western Alps, Eastern Alps, and Apennines. Isolation of Italian populations due to the presence of Alpine barrier and its exclusion from colonization of Central and Northern Europe; high nucleotide divergence between Italy versus Central Europe (Cheddadi et al. 2006, Belletti et al. 2012, Kujala and Savolainen 2012)  Alps (Al) and Carpathians (Ca) (mtDNA, SSR cpDNA)  Existence of patchy refugia located around the Alps and Carpathians involved in postglacial colonization of Europe (Cheddadi et al. 2006)  Balkan Peninsula (Ba) (isozymes, mtDNA)  Similar genetic variation and low genetic differentiation indicating contribution of Balkan refugium in postglacial recolonization of Europe (Naydenov et al. 2007, Prus-Głowacki et al. 2012)  Anatolia (An) (isozymes, mtDNA, SNPs of nDNA, biometry)  Asia Minor as the area of endemism comparable to Iberian and Apennine Peninsulas. Unique mtDNA mitotype suggesting limited gene flow by seeds during recolonization. Low variation at nuclear gene loci, isozymes, and morphological traits suggest ongoing gene flow between some populations from Turkey, the Balkans, and Central and Northern Europe; genetic subdivision within Turkish populations (Bilgen and Kaya 2007, Naydenov et al. 2007, Pyhäjärvi et al. 2008, Jasińska et al. 2014, Sannikov and Egorov 2015)  Northern Europe (N) (mtDNA, SNPs of nDNA)  Possible existence of cryptic refugia in Fennoscandia or Eastern Europe based on frequency of mtDNA haplotypes compared with other distribution range in Euro-Asia; high genetic similarity between Polish and Northern European populations at nDNA (Naydenov et al. 2007, Pyhäjärvi et al. 2008, Wachowiak et al. 2011)  Western Asia (WA) (isozymes, mtDNA)  Nonrandom distribution of mitotypes suggests the existence of the southeastern refugium at about 300 km southeast of Moscow, rather than the Central European origin of the Scandinavian populations; three distinct gene pools including the Balkans, Southern Urals, and Northern Mongolia; free gene flow from the Southern Baikal region to the Balkans, Central Europe, and Asia Minor along the northern coast of the Eastern Paratethys (Sannikov and Petrova 2012, Buchovska et al. 2013, Sannikov and Egorov 2015)  mtDNA, mitochondrial DNA; cp DNA, chloroplast DNA; SNP, single nucleotide polymorphism; SSR, simple sequence repeat; nDNA, nuclear DNA. View Large Table 2. Indication of Scots pine phylogeography based on biometric, biochemical, and molecular data. Area (marker type)  Major conclusions and hypotheses  Iberian Peninsula (Ib) (mtDNA, cpDNA, isoenzymes, biometry)  Subdivision of populations into two genetically heterogeneous groups including West-Central and Northeastern Spain. Unique haplotypes at mtDNA suggest limited seed flow from Iberian populations during recolonization of Europe; genetic similarity between populations from Massif Central in France and northern parts of the Iberian Peninsula (Sinclair et al. 1999, Soranzo et al. 2000, Prus-Głowacki et al. 2003, 2012, Robledo-Arnuncio et al. 2005, Cheddadi et al. 2006, Naydenov et al. 2007, Pyhäjärvi et al. 2008, Jasińska et al. 2014)  British Isles (BI) (terpens, mtDNA, cpDNA, SNPs of nDNA)  Genetic subdivision of populations to western and eastern stands explained by two hypotheses: western refugial populations versus eastern stands of continental origin; and result of two distinct colonization routes from continental Europe. High level of genetic polymorphism as compared to mainland populations not compatible with simple recolonization model (Kinloch et al. 1986, Provan et al. 1998, Sinclair et al. 1998, Naydenov et al. 2007, Wachowiak et al. 2011)  Apennine Peninsula (It) (mtDNA, SSR cpDNA, SSR and SNPs of nDNA)  At least three different refugia in the Western Alps, Eastern Alps, and Apennines. Isolation of Italian populations due to the presence of Alpine barrier and its exclusion from colonization of Central and Northern Europe; high nucleotide divergence between Italy versus Central Europe (Cheddadi et al. 2006, Belletti et al. 2012, Kujala and Savolainen 2012)  Alps (Al) and Carpathians (Ca) (mtDNA, SSR cpDNA)  Existence of patchy refugia located around the Alps and Carpathians involved in postglacial colonization of Europe (Cheddadi et al. 2006)  Balkan Peninsula (Ba) (isozymes, mtDNA)  Similar genetic variation and low genetic differentiation indicating contribution of Balkan refugium in postglacial recolonization of Europe (Naydenov et al. 2007, Prus-Głowacki et al. 2012)  Anatolia (An) (isozymes, mtDNA, SNPs of nDNA, biometry)  Asia Minor as the area of endemism comparable to Iberian and Apennine Peninsulas. Unique mtDNA mitotype suggesting limited gene flow by seeds during recolonization. Low variation at nuclear gene loci, isozymes, and morphological traits suggest ongoing gene flow between some populations from Turkey, the Balkans, and Central and Northern Europe; genetic subdivision within Turkish populations (Bilgen and Kaya 2007, Naydenov et al. 2007, Pyhäjärvi et al. 2008, Jasińska et al. 2014, Sannikov and Egorov 2015)  Northern Europe (N) (mtDNA, SNPs of nDNA)  Possible existence of cryptic refugia in Fennoscandia or Eastern Europe based on frequency of mtDNA haplotypes compared with other distribution range in Euro-Asia; high genetic similarity between Polish and Northern European populations at nDNA (Naydenov et al. 2007, Pyhäjärvi et al. 2008, Wachowiak et al. 2011)  Western Asia (WA) (isozymes, mtDNA)  Nonrandom distribution of mitotypes suggests the existence of the southeastern refugium at about 300 km southeast of Moscow, rather than the Central European origin of the Scandinavian populations; three distinct gene pools including the Balkans, Southern Urals, and Northern Mongolia; free gene flow from the Southern Baikal region to the Balkans, Central Europe, and Asia Minor along the northern coast of the Eastern Paratethys (Sannikov and Petrova 2012, Buchovska et al. 2013, Sannikov and Egorov 2015)  Area (marker type)  Major conclusions and hypotheses  Iberian Peninsula (Ib) (mtDNA, cpDNA, isoenzymes, biometry)  Subdivision of populations into two genetically heterogeneous groups including West-Central and Northeastern Spain. Unique haplotypes at mtDNA suggest limited seed flow from Iberian populations during recolonization of Europe; genetic similarity between populations from Massif Central in France and northern parts of the Iberian Peninsula (Sinclair et al. 1999, Soranzo et al. 2000, Prus-Głowacki et al. 2003, 2012, Robledo-Arnuncio et al. 2005, Cheddadi et al. 2006, Naydenov et al. 2007, Pyhäjärvi et al. 2008, Jasińska et al. 2014)  British Isles (BI) (terpens, mtDNA, cpDNA, SNPs of nDNA)  Genetic subdivision of populations to western and eastern stands explained by two hypotheses: western refugial populations versus eastern stands of continental origin; and result of two distinct colonization routes from continental Europe. High level of genetic polymorphism as compared to mainland populations not compatible with simple recolonization model (Kinloch et al. 1986, Provan et al. 1998, Sinclair et al. 1998, Naydenov et al. 2007, Wachowiak et al. 2011)  Apennine Peninsula (It) (mtDNA, SSR cpDNA, SSR and SNPs of nDNA)  At least three different refugia in the Western Alps, Eastern Alps, and Apennines. Isolation of Italian populations due to the presence of Alpine barrier and its exclusion from colonization of Central and Northern Europe; high nucleotide divergence between Italy versus Central Europe (Cheddadi et al. 2006, Belletti et al. 2012, Kujala and Savolainen 2012)  Alps (Al) and Carpathians (Ca) (mtDNA, SSR cpDNA)  Existence of patchy refugia located around the Alps and Carpathians involved in postglacial colonization of Europe (Cheddadi et al. 2006)  Balkan Peninsula (Ba) (isozymes, mtDNA)  Similar genetic variation and low genetic differentiation indicating contribution of Balkan refugium in postglacial recolonization of Europe (Naydenov et al. 2007, Prus-Głowacki et al. 2012)  Anatolia (An) (isozymes, mtDNA, SNPs of nDNA, biometry)  Asia Minor as the area of endemism comparable to Iberian and Apennine Peninsulas. Unique mtDNA mitotype suggesting limited gene flow by seeds during recolonization. Low variation at nuclear gene loci, isozymes, and morphological traits suggest ongoing gene flow between some populations from Turkey, the Balkans, and Central and Northern Europe; genetic subdivision within Turkish populations (Bilgen and Kaya 2007, Naydenov et al. 2007, Pyhäjärvi et al. 2008, Jasińska et al. 2014, Sannikov and Egorov 2015)  Northern Europe (N) (mtDNA, SNPs of nDNA)  Possible existence of cryptic refugia in Fennoscandia or Eastern Europe based on frequency of mtDNA haplotypes compared with other distribution range in Euro-Asia; high genetic similarity between Polish and Northern European populations at nDNA (Naydenov et al. 2007, Pyhäjärvi et al. 2008, Wachowiak et al. 2011)  Western Asia (WA) (isozymes, mtDNA)  Nonrandom distribution of mitotypes suggests the existence of the southeastern refugium at about 300 km southeast of Moscow, rather than the Central European origin of the Scandinavian populations; three distinct gene pools including the Balkans, Southern Urals, and Northern Mongolia; free gene flow from the Southern Baikal region to the Balkans, Central Europe, and Asia Minor along the northern coast of the Eastern Paratethys (Sannikov and Petrova 2012, Buchovska et al. 2013, Sannikov and Egorov 2015)  mtDNA, mitochondrial DNA; cp DNA, chloroplast DNA; SNP, single nucleotide polymorphism; SSR, simple sequence repeat; nDNA, nuclear DNA. View Large Less clear at the moment is the possible existence of refugial populations at mid-northern latitudes that potentially contributed to recolonization of Fennoscandia and the British Isles, as indicated by the spatial distribution of different mtDNA haplotypes in Scots pine (Sinclair et al. 1998, Naydenov et al. 2007, Pyhäjärvi et al. 2008) and also other boreal forest tree species (Parducci et al. 2012). Phylogeographic studies of silver birch (Betula pendula) and Norway spruce (Picea abies) show the role of higher-latitude refugia, including those near Moscow, in the colonization of Central and Northern Europe (Palme et al. 2003, Willis and van Andel 2004, Maliouchenko et al. 2007, Tollefsrud et al. 2008, Parducci et al. 2012). Glacial survival of Norway spruce in Northwest Scandinavia was postulated on the basis of microfossil and molecular data (Kullman 2006, Parducci et al. 2012).The present day co-occurrence of Scots pine with birch and spruce across large parts of their geographical distribution indicates that some parts of the range of those cold-tolerant forest tree species could also have been shared during the last glacial maximum. Studies in continental European populations of Scots pine and Norway spruce have so far found little evidence for the effects of recent (postglacial) population size changes during migration, and they indicate bottlenecks in the mid-to-late Pleistocene based on the patterns of sequence polymorphisms at nuclear genes (Heuertz et al. 2006, Pyhäjärvi et al. 2007). At the northwestern limit of the Scots pine distribution, different origins of the populations contributing to the postglacial colonization of the Scottish Highlands were indicated by pollen data, allozymes, monoterpenes, and unique polymorphisms found at mtDNA and chloroplast DNA markers (Kinloch et al. 1986, Birks 1989, Provan et al. 1998, Sinclair et al. 1998). Authors of these studies suggested a West/East population subdivision within Scotland originating from distinct sources that were also different from those that repopulated the mainland. Scottish populations also show high levels of genetic polymorphism at nuclear gene loci and patterns of allelic frequency incompatible with a simple model of expansion from mainland populations (Wachowiak et al. 2011). Neither the existence of refugial populations on the British Isles nor the colonization of this area from independent routes from northern parts of the Iberian Peninsula and Central Europe can be excluded (Kinloch et al. 1986, Sinclair et al. 1999, Soranzo et al. 2000, Pyhäjärvi et al. 2008). Understanding Demographic Processes Affecting Neutral Genetic Variation The genetic markers analyzed to date have provided low phylogeographic resolution (Naydenov et al. 2007, Pyhäjärvi et al. 2008). More mtDNA markers are needed to resolve the origin of North European populations and to evaluate the impact of the East and Southeast (Balkan Peninsula) gene pools on the current genetic structure of Scots pine. Screening of a large proportion of the mitochondrial genome using next-generation sequencing (NGS) approaches would be a useful advance. Comparative studies of mitochondrial sequences from individuals from across-species distribution range will advance the discovery of polymorphic regions for development of high-resolution mtDNA markers. Denser sampling of populations and spatial analysis of the new markers over a large proportion of the range of Scots pine could shed light on the population structure, locations of refugia, and postglacial recolonization routes of this species. Table 3. Molecular markers and genomic resources developed for Scots pine. Genome  Marker type  Regions/number  References  Nuclear  RAPD  Random genomic regions  Hurme and Savolainen (1999), Lučić et al. (2011)  Nuclear  AFLP  Random genomic regions  Lerceteau and Szmidt (1999)  Nuclear  SSR  PMS/8 loci  Kostia et al. (1995)      SPAC/5 loci  Soranzo et al. (1998)      SPAG/2 loci        PtTX/40 loci  Liewlaksaneeyanawin et al. (2004)      LOP/14 loci        psyl/10 loci  Sebastiani et al. (2012)  Nuclear  EST  Genes associated with cold acclimation  Joosen et al. (2006)  Nuclear  Gene loci  12 loci  Dvornyk et al. (2002)      2 loci  García-Gil et al. (2003)      16 loci  Pyhäjärvi et al. (2007)      14 loci  Wachowiak et al. (2009)      12 loci  Wachowiak et al. (2011)      11 loci  Kujala and Savolainen (2012)      29 loci  Wachowiak et al. (2014)      8 loci  Wachowiak et al. (2015a)  Nuclear  Transcriptome  40,798 unigenes  Wachowiak et al. (2015)  Nuclear  Genome sequence  Whole genome  Ongoing; HYPERLINK "http://www.procogen.eu"  cpDNA  PCR-RFLP/STS  trnL-trnF  Wachowiak et al. (2000)      iVal    cpDNA  SSR  Pt/20 loci  Vendramin et al. (1996)      PCP/17 loci  Provan et al. (1999)  mtDNA  PCR-RFLP/STS  cox1 gene  Sinclair et al. (1999)      nad 1, exon B/C  Soranzo et al. (2000)      nad 1  Cheddadi et al. (2006)      nad7 intron 1  Naydenov et al. (2007)      nad 1 intron B/C        nad7 intron 2  Pyhäjärvi et al. (2008)      nad 1 intron B/C    Genome  Marker type  Regions/number  References  Nuclear  RAPD  Random genomic regions  Hurme and Savolainen (1999), Lučić et al. (2011)  Nuclear  AFLP  Random genomic regions  Lerceteau and Szmidt (1999)  Nuclear  SSR  PMS/8 loci  Kostia et al. (1995)      SPAC/5 loci  Soranzo et al. (1998)      SPAG/2 loci        PtTX/40 loci  Liewlaksaneeyanawin et al. (2004)      LOP/14 loci        psyl/10 loci  Sebastiani et al. (2012)  Nuclear  EST  Genes associated with cold acclimation  Joosen et al. (2006)  Nuclear  Gene loci  12 loci  Dvornyk et al. (2002)      2 loci  García-Gil et al. (2003)      16 loci  Pyhäjärvi et al. (2007)      14 loci  Wachowiak et al. (2009)      12 loci  Wachowiak et al. (2011)      11 loci  Kujala and Savolainen (2012)      29 loci  Wachowiak et al. (2014)      8 loci  Wachowiak et al. (2015a)  Nuclear  Transcriptome  40,798 unigenes  Wachowiak et al. (2015)  Nuclear  Genome sequence  Whole genome  Ongoing; HYPERLINK "http://www.procogen.eu"  cpDNA  PCR-RFLP/STS  trnL-trnF  Wachowiak et al. (2000)      iVal    cpDNA  SSR  Pt/20 loci  Vendramin et al. (1996)      PCP/17 loci  Provan et al. (1999)  mtDNA  PCR-RFLP/STS  cox1 gene  Sinclair et al. (1999)      nad 1, exon B/C  Soranzo et al. (2000)      nad 1  Cheddadi et al. (2006)      nad7 intron 1  Naydenov et al. (2007)      nad 1 intron B/C        nad7 intron 2  Pyhäjärvi et al. (2008)      nad 1 intron B/C    mtDNA, mitochondrial DNA; cpDNA, chloroplast DNA; RAPD, random amplified polymorphic DNA; AFLP, amplified fragment length polymorphism; SSR, simple sequence repeat; EST, expressed sequence tag; PCR, polymerase chain reaction; RFLP, restriction fragment length polymorphism; STS, sequence-tagged sites. View Large Table 3. Molecular markers and genomic resources developed for Scots pine. Genome  Marker type  Regions/number  References  Nuclear  RAPD  Random genomic regions  Hurme and Savolainen (1999), Lučić et al. (2011)  Nuclear  AFLP  Random genomic regions  Lerceteau and Szmidt (1999)  Nuclear  SSR  PMS/8 loci  Kostia et al. (1995)      SPAC/5 loci  Soranzo et al. (1998)      SPAG/2 loci        PtTX/40 loci  Liewlaksaneeyanawin et al. (2004)      LOP/14 loci        psyl/10 loci  Sebastiani et al. (2012)  Nuclear  EST  Genes associated with cold acclimation  Joosen et al. (2006)  Nuclear  Gene loci  12 loci  Dvornyk et al. (2002)      2 loci  García-Gil et al. (2003)      16 loci  Pyhäjärvi et al. (2007)      14 loci  Wachowiak et al. (2009)      12 loci  Wachowiak et al. (2011)      11 loci  Kujala and Savolainen (2012)      29 loci  Wachowiak et al. (2014)      8 loci  Wachowiak et al. (2015a)  Nuclear  Transcriptome  40,798 unigenes  Wachowiak et al. (2015)  Nuclear  Genome sequence  Whole genome  Ongoing; HYPERLINK "http://www.procogen.eu"  cpDNA  PCR-RFLP/STS  trnL-trnF  Wachowiak et al. (2000)      iVal    cpDNA  SSR  Pt/20 loci  Vendramin et al. (1996)      PCP/17 loci  Provan et al. (1999)  mtDNA  PCR-RFLP/STS  cox1 gene  Sinclair et al. (1999)      nad 1, exon B/C  Soranzo et al. (2000)      nad 1  Cheddadi et al. (2006)      nad7 intron 1  Naydenov et al. (2007)      nad 1 intron B/C        nad7 intron 2  Pyhäjärvi et al. (2008)      nad 1 intron B/C    Genome  Marker type  Regions/number  References  Nuclear  RAPD  Random genomic regions  Hurme and Savolainen (1999), Lučić et al. (2011)  Nuclear  AFLP  Random genomic regions  Lerceteau and Szmidt (1999)  Nuclear  SSR  PMS/8 loci  Kostia et al. (1995)      SPAC/5 loci  Soranzo et al. (1998)      SPAG/2 loci        PtTX/40 loci  Liewlaksaneeyanawin et al. (2004)      LOP/14 loci        psyl/10 loci  Sebastiani et al. (2012)  Nuclear  EST  Genes associated with cold acclimation  Joosen et al. (2006)  Nuclear  Gene loci  12 loci  Dvornyk et al. (2002)      2 loci  García-Gil et al. (2003)      16 loci  Pyhäjärvi et al. (2007)      14 loci  Wachowiak et al. (2009)      12 loci  Wachowiak et al. (2011)      11 loci  Kujala and Savolainen (2012)      29 loci  Wachowiak et al. (2014)      8 loci  Wachowiak et al. (2015a)  Nuclear  Transcriptome  40,798 unigenes  Wachowiak et al. (2015)  Nuclear  Genome sequence  Whole genome  Ongoing; HYPERLINK "http://www.procogen.eu"  cpDNA  PCR-RFLP/STS  trnL-trnF  Wachowiak et al. (2000)      iVal    cpDNA  SSR  Pt/20 loci  Vendramin et al. (1996)      PCP/17 loci  Provan et al. (1999)  mtDNA  PCR-RFLP/STS  cox1 gene  Sinclair et al. (1999)      nad 1, exon B/C  Soranzo et al. (2000)      nad 1  Cheddadi et al. (2006)      nad7 intron 1  Naydenov et al. (2007)      nad 1 intron B/C        nad7 intron 2  Pyhäjärvi et al. (2008)      nad 1 intron B/C    mtDNA, mitochondrial DNA; cpDNA, chloroplast DNA; RAPD, random amplified polymorphic DNA; AFLP, amplified fragment length polymorphism; SSR, simple sequence repeat; EST, expressed sequence tag; PCR, polymerase chain reaction; RFLP, restriction fragment length polymorphism; STS, sequence-tagged sites. View Large The role of hybridization in shaping nucleotide polymorphism in the species is also unclear. It is known that Scots pine hybridizes in contact zones with its close relatives from the Pinus mugo complex (Lewandowski et al. 2000, Wachowiak and Prus-Głowacki 2008, Jasińska et al. 2010, Wachowiak et al. 2015a). Itneeds to beverified, however, whether levels of genetic diversity of closely related pine species were influenced by interspecific admixture during range shifts and recolonization processes when the ranges of the species overlapped. The influence of forest management and the associated trade of seed on the population structure of present day woodlands also needs substantial revision (Bradshaw 2004, Wagner et al. 2015). There is growing evidence that seeds from distinct regions were mixed in seed extraction houses and redistributed on a massive scale to customers across Europe since the mid-19th century, in conjunction with the rapid development of the railways (Lewandowski et al. 2012). A map of verifiably natural populations of the species is urgently needed to advance the search for genomic regions involved in local adaptation. Better understanding of Scots pine population history is important for three reasons: development of conservation programs for genetic resources in the species; evaluation of the role of natural selection during expansion in development of local adaptation across the species distribution range; and assessment of anthropogenic influences on the species’ population structure. Search for Genes under Selection in Scots Pine Phenotypic Differentiation and Adaptive Variation in Scots Pine The present distribution of Scots pine covers extreme gradients of environmental variation. It is a well-recognized phenomenon in plants that spatially variable natural selection, driven by factors such as environmental conditions or disease, can lead to local adaptation and differentiation between populations (Savolainen et al. 2007). Most empirical studies focus, at least initially, on detecting local adaptation in the pattern of mean fitness shown by a set of populations across a set of habitats in reciprocal transplant or common garden experiments. According to these classic methods, local adaptation occurs when a local population performs better at the local site than elsewhere or has an advantage over a nonlocal population in terms of traits associated with its relative fitness (Kawecki and Ebert 2004). For Scots pine populations, such dependence was described by Beuker et al. (1996). Other studies showed that the growth potential of Scots pine populations matched different climatic optima (Rehfeldt et al. 2002). Nearly 200 years of common garden experiments have provided insight into the phenotypic variation of Scots pine populations. They were also used to evaluate the performance of progeny from native populations as potential sources of material for reforestation and breeding programs (Sabor 2006). Moreover, these experiments were useful for studying adaptive differentiation of plants from different parts of the natural range grown together under homogeneous common-garden conditions (Oleksyn et al. 1998). Several geographic trends have been found in phenotypic variation of different Scots pine populations. Most were found across latitudinal gradients, but a few appear to be related to altitudinal gradients. The clearest latitudinal clines observed in the natural range of Scots pine are related to growth rhythm traits such as total height (Wright and Bull 1962, Oleksyn et al. 1998, Alia et al. 2001), maximum growth rate (Notivol et al. 2007), growth cessation and phenology (Wright and Bull 1962, Beuker 1993, Hurme et al. 1997, Oleksyn et al. 1998, Savolainen et al. 2004, Notivol et al. 2007, Salmela et al. 2011), and frost hardiness (Hurme et al. 1997, Andersson and Fedorkov 2004, Savolainen et al. 2004). Studies of growth rhythm traits indicated that the northernmost pine populations had earlier bud set, grew faster, and were more frost resistant than southern populations because of a shorter growing period and exposure to lower temperatures. For instance, the timing of bud set was on average 45 days earlier for the most northern pine populations than for the most southern populations from Turkey and Spain (Figure 3). Certain needle traits, including morphology (Oleksyn et al. 2002, 2003, Pensa and Jalkanen 2005) and terpenoid composition and amount (Nerg et al. 1994, Manninen et al. 1998, Semiz et al. 2007), demonstrated geographical variation, both for altitudinal and latitudinal gradients. Interestingly, some differences, for instance in the lifespan of needles, show patterns of phenotypic plasticity that can be observed only in natural populations of Scots pine. In controlled environmental conditions, the phenotypic plasticity for some traits (e.g., frost hardiness) is considerably restricted as shown by Beuker et al. (1996). High heritability was observed for traits under strong natural selection, which ultimately leads to local adaptation, especially for the populations from the extremes of the natural range, where the selection pressure is the most powerful. Collectively, various reciprocal transplant and common garden experiments have provided evidence that phenotypic variation in Scots pine populations has a strong genetic component. Figure 3. View largeDownload slide Latitudinal variation in timing of bud set in populations of Scots pine in response to environmental gradient. Figure 3. View largeDownload slide Latitudinal variation in timing of bud set in populations of Scots pine in response to environmental gradient. Quantitative Trait Locus (QTL) Mapping High phenotypic differentiation and low among-population genetic variation of Scots pine at neutral markers provide the potential to identify genomic regions that influence local adaptation. Therefore, there has been much interest in discovery of genes involved in adaptation and phenotypic differences between populations. Development of molecular markers has offered great opportunities for studying complex traits using QTL mapping. Generally, this approach uses inbred line crosses or outbred populations to find a statistically meaningful correlation between genetic markers and phenotypic traits and to place the resulting QTLs on a genetic map (Mauricio 2001). Results from QTL mapping give information about the number and genomic location of major genes affecting a quantitative trait that could potentially be used to advance breeding programs based on the application of genetic markers (marker-assisted breeding) (Guevara et al. 2005). QTL mapping has been widely used in plants for genetic dissection of biomass, yield, or disease resistance traits (Veeresha et al. 2015). For Scots pine, studies utilizing QTL mapping generally focused on economically important traits such as height or trunk diameter (Lerceteau et al. 2000, 2001). Lerceteau et al. (2000) detected three QTLs that explained 25.8% of the phenotypic variance for the tree height, based on 94 full-sib progenies of the cross between two plus-trees from northern Sweden. The remaining QTLs, which were detected for the other traits, explained phenotypic variance in the range from 9.3 to 22.7%, with the latter value corresponding to frost hardiness. Collections of QTLs strictly associated with adaptive traits of Scots pine were described in the studies of Hurme et al. (2000) and Yazdani et al. (2003). These studies dealt with mapping of QTLs involved in the genetic control by growth rhythm and acclimated to autumn cold in Scots pine. They explained 15.4% of the total phenotypic variation for timing of bud set. In addition, they accounted for 16 to 47% of the additive variation for annual shoot elongation and for 42 to 79% of growth termination. Despite some indication from QTL studies about the architecture of adaptive traits, identification of chromosomal regions and genes controlling phenotypes is seriously limited by characteristics of the pine genome. Pines are diploid organisms that have large genomes of about 20–30 Gbp (Nystedt et al. 2013, Neale et al. 2014), which is roughly 200 times bigger than the Arabidopsis genome (Goodstein et al. 2012). In Pinus taeda, 82% of the genome is repetitive, with retrotransposons representing 62% of its content. There is a high number of complex gene families, probably resulting from duplication events. For instance, 1,554 of the identified complex gene families in P. taeda were specific to conifers, of which 159 were specific to the species (Neale et al. 2014).Although some QTL studies indicated the existence of genes of a major phenotypic effect, in fact many quantitative traits are probably under multigenic control (Plomion et al. 2003). Therefore, in the case of highly outcrossing forest tree species with a large genome, QTL mapping strategies have a limited application in breeding compared with that in highly inbred crop species, such as corn and tomato (Edwards et al. 1987, Paterson et al. 1991). Furthermore, because forest trees are characterized by long juvenile periods, establishing and maintaining biparental crosses and progenies (preferably in multiple locations) are often impractical and costly. Moreover, QTL intervals are usually quite long, about 5–10 cM, which in pines can cover hundreds of genes. Therefore, potential applications of mapped QTLs in marker-assisted breeding must contend with linkage drag caused by the presence of physically linked undesirable genes and alleles within the QTL. For this reason, only a few gene markers have so far been used in plant breeding programs (Bernardo 2008), and in fact these were major genes rather than QTLs. Because mapped QTLs are imprecise, direct search for genomic regions underlying quantitative adaptive traits in pines has been considered a more promising approach. Nucleotide Polymorphism and Association Genetic Studies More recently, the search for loci involved in local adaptation has focused on genomewide nucleotide polymorphism from large numbers of individuals due to the development of efficient DNA sequencing, genotyping, and analytical methods. Such approaches generally involve the analysis of variation of single nucleotide polymorphisms (SNPs) and detection of loci that exhibit outlier patterns of genetic variation in comparison to the genome wide neutral variation (Oleksyk et al. 2010). The signature of selection may be marked by a reduction in the amount of variation, an increase in linkage disequilibrium, or a skew in the distribution of allele frequencies in the genomic region around the selected mutation. Because of the different strength of selection across the species distribution range, polymorphism at genomic regions involved in local adaptation will show an increased level of differentiation between populations compared with neutrally evolving loci. This selection-driven and locus-specific pattern of differentiation can be distinguished from demographic events (Luikart et al. 2003, Li et al. 2012). In contrast to traditional QTL mapping techniques, association mapping (AM) or linkage disequilibrium (LD) mapping takes advantage of recombination events to find marker-trait associations in unrelated individuals. After many generations of random mating and recombination during meiosis, polymorphisms at tightly linked loci will show statistical association with the trait of interest. This method has been widely used since 2000 to study biomass traits, yield, and disease resistance or to search for genomic regions under selection in plants (Gupta et al. 2005, Zhu et al. 2008, Neale and Kremer 2011, Khan and Korban 2012). For geographically distinct populations, the method was also used for association of genetic polymorphisms with selection pressures caused by the environment using landscape genomic approaches. However a whole-genome AM strategy has so far been limited in conifers because of their large and complex genomes and the rapid decay of LD in natural populations (Neale and Savolainen 2004). Therefore, most studies to date have focused on preselected target regions or putative candidate gene loci for the particular adaptive traits derived from eastern standard time studies, biochemical and/or physiological pathways identified in model species, or genes linked to QTLs (García-Gil et al. 2003, González-Martínez et al. 2006, Wachowiak et al. 2009, Eckert et al. 2010). Nucleotide polymorphism studies in Scots pine have identified a few genes, including some members of the dehydrin gene family, whose patterns of polymorphism across the species distribution range contrast with other genes and the genetic background (Wachowiak et al. 2009, Kujala and Savolainen 2012). Although progress has been made in discovering regions under selection in forest tree species, the links between polymorphism and phenotypes are not conclusive. So far, association analyses have indicated that the polymorphism can explain only a small percentage of the observed variability. It seems clear that many markers at the whole-genome level will be needed to capture genetic variation at quantitative traits, especially those influenced by many genes of small individual effect. Linking Genetic and Phenotypic Variation High-Density SNP Genotyping Arrays Because of the large genome size and rapid decay of LD in conifers, the success of genomewide genetic analysis depends primarily on the type and number of genetic markers. Access to many markers is no longer a limiting factor due to continuous improvement of access to NGS. High-throughput SNP discovery and genotyping methods include, among others, restriction site-associated DNA tags (Baird et al. 2008), genotyping by sequencing (Elshire et al. 2011), and multiplexed-shotgun genotyping (Andolfatto et al. 2011). Comparative studies of the whole transcriptome sequence is another efficient method for SNP discovery in species that lack a reference genome sequence. Recent whole transcriptome sequencing studies in Scots pine show the efficiency of the method: a set of 40,798 high-quality transcripts were identified with nearly 20,000 unique genes covering a broad range of gene function categories. Comparative analyses of the transcriptome sequence derived from several samples from across the species distribution range provided a set of >200,000 SNPs that will advance population and association genetic studies in pines (Wachowiak et al. 2015b). Those resources form a powerful source of data for population genetic and genomic studies in pines. In the case of Scots pine and its close relatives, those resources are being used for development of a high-density SNP genotyping platform (W. Wachowiak, Polish Academy of Sciences, and S. Cavers, Centre for Ecology and Hydrology Edinburgh, pers. comm. March 20, 2015). Such a platform, also known as a SNP genotyping array, is a small silicon glass with a large number of synthetic, single-stranded DNA to which DNA of individuals is hybridized to identify the presence of specific DNA sequences that differ by a single nucleotide (Isik 2014). High-density SNP genotyping arrays are already available for the major animal breeding programs (Schefers and Weigel 2012, Kranis et al. 2013) and also for white spruce (Pavy et al. 2013) and Western white pine (Liu et al. 2014). In conifers, the development of SNP resources should help to advance population genetics and association studies. The so far small-scale SNP genotyping studies in conifers including spruce, loblolly pine, and maritime pine (e.g., Namroud et al. 2008, Holliday et al. 2010, Chancerel et al. 2011, Chen et al. 2012, Resende et al. 2012c) show the implementation of SNP genotyping approaches in forest tree species. Demand for Phenotypic and Analytical Methods The application of NGS approaches has resulted in significant progress in development of new genomic resources for population structure and gene-trait association studies in forest tree species such as pines, oaks, poplars, and eucalypts (González-Martínez et al. 2006, Grattapaglia and Kirst 2008, Grattapaglia et al. 2009, Neale and Kremer 2011). Although some polymorphisms associated with variation at quantitative traits or selection gradient have been identified in these studies, less is known about the impact of the genes and alleles on phenotype. Most often genes are called “adaptive” if patterns of nucleotide variation at the locus are consistent with positive selection or, less often, if an allele has been shown to affect a phenotype with known or suspected functional importance (Barrett and Hoekstra 2011). Direct relationships between gene function and fitness are usually unknown, however, and the adaptive role of the polymorphism is rarely experimentally verified. Therefore, in addition to methods for generating large numbers of molecular markers, there is an equally strong need for development of methods for assessment of the adaptive phenotypic traits of trees under uniform environmental conditions. Detailed assessment of physiological traits in biological experiments and elucidation of the hereditary background of physiological variation is needed to fully understand adaptive responses of plants most often measured only at target phenotypic traits like growth performance, cold hardiness, or draft tolerance. Therefore, more complementary information is needed about the details of the physiology of growth and other traits (downscaled to the molecular level) and the physiological variation among genotypes and populations. Plants derived from provenance trial experiments and common garden studies, commonly well characterized for phenology and growth performance, could be used for complementary physiological assessments of target adaptive traits. Such complementary studies are needed to effectively link genotypic and phenotypic variation. There is also demand for novel approaches to test for the signature of natural selection at the whole-genome scale. Most of the existing methods focus on models of selection at a small number of loci, assuming new advantageous mutations spreading rapidly to fixation and decreasing variation at linked sites in a process that has been named “hard sweep” (Oleksyk et al. 2010). However, such models are appropriate only with additive gene effects and overlook dominance effects and epistatic interactions among genes, which usually hamper evolutionary response and can even lead to an evolutionary stasis. Recent results of genomewide association studies show that quantitative traits in many organisms including trees are highly polygenic and can be influenced by variations in the frequency of alleles at many loci but not necessarily fixation of particular alleles. Moderate changes in allelic frequency at many loci could allow rapid adaptation without generating any large differences in allele frequencies between populations. Therefore, the effect of selection may be more difficult to detect using current population genetic methods that are focused on hard sweeps (Pritchard et al. 2010). To search for the signal of polygenic adaptation in a genome, new approaches that combine knowledge from genomewide association studies and population genetic modeling have been proposed (Berg and Coop 2014). In the human genome, this approach allowed detection of polygenic adaptation for height, skin pigmentation, and inflammatory bowel disease (Berg and Coop 2014). Such methods applied to detection of selection in forest trees could advance development of predictive models of the adaptive response of forest trees to changing environmental conditions and successfully link phenotypic and genetic differentiation. Perspectives for New Breeding Applications The development of novel molecular markers in parallel with the availability of phenotypic data on adaptive trait variation has the potential to improve breeding methods for Scots pine. Breeding populations, including seed orchards, have been used since the 1950s to improve seed production and to increase genetic quality through the use of selected clones or progeny of elite trees, which have been isolated to avoid or reduce pollination from outside plantations (Ertekin 2012). In an orchard design the goal is to select trees with the best phenotype, capture as much diversity as technically a possible, minimize self-ing, and maximize out-crossing and mating of all genotypes. Moreover, seed orchards should reflect the genetic diversity of the original population and be sufficiently large to maintain genetic diversity for future generations. It is challenging to maintain the high effective number of clones in a plantation and achieve flowering synchronization where clones were derived from distinct locations (Muona and Harju 1989, Gömöry et al. 2000, Nikkanen and Ruotsalainen 2000, Kang et al. 2001, Gömöry et al. 2003). Effective isolation of seed orchards is also difficult in the case of a highly outcrossing and wind-pollinated species such as Scots pine. Research has shown that contamination by foreign pollen in such stands reaches 48% (Harju and Nikkanen 1996). As a result, the genetic gain after a typical breeding cycle, which may last decades, may be relatively small. The development of novel genomic resources and analytical methods provides the opportunity to use traditional breeding populations as “training” stands for marker-assisted selection. One promising approach is a method of genomic selection (GS) that aims to assess the breeding value of individual trees by estimating all genetic marker effects simultaneously and retaining all of them as predictors of performance. Selection for all traits of interest in all plants of a progeny trial has the potential to significantly accelerate breeding cycles and improve selection precision and intensity, especially for late-expressed traits (Desta and Ortiz 2014, Grattapaglia 2014). The reported efficiency of GS ranged from 0.3 to 0.8 for all traits obtained for loblolly pine, eucalyptus, and apple trees, and they are in the same range as that reported for crop plants or trees obtained by conventional phenotypic selection (Kumar et al. 2012, Resende et al. 2012a, 2012b, 2012c, Zapata-Valenzuela et al. 2012). Therefore, the prospects of GS for forest tree breeding are promising despite initial challenges such as the evaluation of the accuracy of predictions for long-term gain, reduction in genetic diversity with faster successive cycles of breeding, and cost-efficiency. It seems, however, that the necessary resources for application of this method for Scots pine are already available, at least at the test scale. Conclusions Provenance trials have provided strong evidence that Scots pine populations are locally adapted to environmental conditions and are characterized by high phenotypic variation. On the other hand, the genetic background of Scots pine populations seems highly homo-geneous at large geographical scales. There is little evidence of increased or reduced diversity due to demographic events like admixture between eastern and western colonization lineages or recent bottlenecks that might have taken place in the postglacial recolonization period. This leads to the conclusion that processes of local adaptation and range expansion depend strongly on an interplay between selection and gene flow. Genetic clines were already observed at some candidate genes showing outlier patterns of variation compared with background polymorphisms. Most likely, adaptation to new environmental conditions was due to selection acting on standing genetic variation rather than on new mutations. Selected beneficial alleles available in the migratory populations could increase their frequency and promote rapid adaptation (Savolainen et al. 2011). More studies are needed to evaluate range shifts and adaptive potential of pines and their likely response to different scenarios of long-term environmental change. Predicted changes will certainly affect forest survival and productivity and will force redistribution of genotypes across the landscape (Rehfeldt et al. 2002). Better understanding of the role of natural selection in the evolution of pines and its effects on current adaptive variation of the species requires revision of the history and postglacial recolonization routes of pines with the use of mtDNA markers. Development of new mtDNA markers of high phylogeographic resolution would also allow identification of numerous nonnative populations of Scots pine, which were established through transfer in the last two centuries of seeds of unknown origin. Development of a good predictive model for phenotypes of forest tree species is needed but so far has been inhibited by the fact that known loci under selection explain only a small percentage of the observed phenotypic variation. NGS and genotyping methods will soon provide new data on nucleotide variation at a genomewide scale. Molecular analysis needs to be complemented by detailed evaluation of phenotypic and physiological traits of the populations studied to successfully link genetic and phenotypic information. These data should advance the evolutionary studies of Scots pine and improve our understanding of the role of mutation, genetic drift, gene flow, and selection in natural populations of Scots pine and other keystone forest tree species. Considering the homogeneous patterns of polymorphism across the Scots pine distribution and the high selective pressure on photoperiod, temperature sensitivity, and water availability, this species seems an appropriate model for searching for the genetic signatures of selection and adaptation. Development of large-scale genotyping methods will advance novel breeding approaches such as genomic selection to accelerate and improve breeding strategies. Newly developed genomic resources for Scots pine that include the whole transcriptome sequence and a large SNP database provide a useful tool for such analysis (Wachowiak et al. 2015). Large-scale studies of nucleotide polymorphism, association genetics, and landscape genomic approaches are needed to better understand the genetic architecture of quantitative traits and the impact of natural selection on genomic patterns of variation in forest tree species. The availability of data also will require development of new statistical methods for detection of the signatures of selection. New analytical approaches will be needed to understand adaptation through information from large numbers of markers and reference samples phenotypically differentiated and collected at landscape scales (Li et al. 2012). 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TI - Current Approaches and Perspectives in Population Genetics of Scots Pine (Pinus sylvestris L.)
JO - Forest Science
DO - 10.5849/forsci.15-040
DA - 2016-06-01
UR - https://www.deepdyve.com/lp/springer-journals/current-approaches-and-perspectives-in-population-genetics-of-scots-lr0OP0mbby
SP - 343
EP - 354
VL - 62
IS - 3
DP - DeepDyve
ER -