Genetic variation in nature
|Eviatar Nevo and Avigdor Beiles (2011), Scholarpedia, 6(7):8821.||doi:10.4249/scholarpedia.8821||revision #91310 [link to/cite this article]|
Genetic diversity in nature, i.e., molecular genetic hereditary differences within and between populations and species, is the basis of evolutionary change (Darwin, 1859). Extensive molecular genetic diversity has been revealed in natural populations since its early discovery in enzymes (Markert and Moller, 1959), proteins (Zuckerkandl and Pauling, 1965), isozymes/allozymes (Lewontin, 1974), and DNA (Kimura, 1983). Many reviews described natural genetic diversity in nature (e.g., Avise, 1994; Dieckmann et al., 2004; Gillespie, 1991; Hamrick et al., 1979; Hoffmann and Parsons, 1991; Johns and Avise, 1998; Kimura, 1983; Lewontin, 1974; Mitton, 1997; Mousseau et al., 2000; Nevo, 1978, 1988, 1998, 2001; Nevo et al., 1984a; Schluter, 2000).
Nevertheless, despite its cardinal role in evolution and domestication, the origin, nature, dynamics, function, significance, and maintenance of genetic diversity in nature remains controversial. Likewise, questions concerning which evolutionary processes influence natural genetic variation for phenotypic, quantitative-trait (QTL) variation (Mitchell-Olds et al., 2007) or what the genetic basis of ecologically important morphological variation such as diverse color patterns of mammals (Steiner et al., 2007) emerged. Controversies included allozyme and DNA markers (RAPDs, AFLPs, SSRs, see glossary), and currently include the basic units of genetic diversity, i.e., single nucleotide polymorphisms (SNPs) and copy number variation (CNV), which are both abundant in nature and largely enigmatic as to their functional significance. The basic pending problems are how much of molecular diversity in nature, at both the coding and noncoding genomic regions, is adaptive and how much of the mutations occurring in natural populations are nonrandom (adaptive, directed) rather than random, neutral, nearly neutral, non-adaptive or deleterious (see Galhardo et al., 2007). The following review will briefly summarize past conclusions on the nature of molecular markers including SSR, but then focuses on SNP polymorphisms at global, regional, and local scales, and other sources of variation in nature in an attempt to summarize the current understanding of genetic diversity in diverse taxa across phylogeny, and outlines future prospects.
Significance of genetic diversity in nature
Evolution results from natural selection acting on diversity in populations, which ultimately stems from mutations. Extensive comparative analyses across genomes of model organisms elucidate diversity in nature (Avise 1994; Gillespie, 1991; Hamrick et al., 1979; Lewontin, 1974; Mitton 1997; Nevo 1978, 1998; Nevo et al., 1984a). These new horizons partly unraveled the molecular structure, function, and evolution of life. Bioinformatics analyzed allozyme and DNA diversity at both coding and noncoding genomic regions permitting precise gene homologous alignment across taxa, the unraveling of gene and genome structure, expression, function, regulation, evolution, and the potential determination of the genetic basis of speciation and adaptation. In the early stages of allozyme studies of genetic diversity, it was shown that genetic diversity and heterozygosity varied nonrandomly between loci, populations, species, habitats, and life zones and were correlated with, and partly predicted by, ecological heterogeneity (Nevo, 1978; Nevo et al., 1984a).
The idea of the neutrality theory of molecular evolution (Kimura, 1983) in which nature is sharply dichotomized into phenotypes subjected to positive Darwinian selection and genotypes that are largely invisible to natural selection and governed primarily by random genetic drift (Kimura 1983) is unrealistic. Protein and DNA variation in nature do not primarily reflect evolutionary noise entering into populations through mutational input and random fixation, as maintained by the neutrality theory of molecular evolution (Kimura, 1983). Protein and DNA variations are largely subjected to natural selection. Genetic polymorphism and heterozygosity in nature are structured nonrandomly on a massive scale. Various forms of natural selection, primarily through the mechanisms of spatiotemporally varying environments and epistasis as well as balancing, directional, diversifying, frequency - dependent and purifying selection regimes are massively involved in genetic structure and divergence of populations (Nevo, 1998), including small populations (Nevo et al., 1997).
Ecological heterogeneity at epigenetic levels (and even at microscales) may cause dramatic genetic divergence (reviewed in Nevo, 2009). Different levels of polymorphism, heterozygosity, and gene diversity cut across taxonomic and biotic borders, highlighting that ecology prevails in genetic diversity and divergence of populations. The amounts of genetic diversity are largely nonrandom among populations, species, life-zones, habitats, climates, and other biological characteristics (Nevo et al., 1984a). Environmental heterogeneity is a major factor in maintaining and structuring genetic diversity in natural populations at all geographical scales - global, regional, and local (Nevo, 1998). This is particularly highlighted at microscales, such as in the "Evolution Canyon" model, or at microscales subjected to sharp ecological inter-climates or inter-soils divergence (Nevo, 1998, 2009), complemented by studies of biochemical networks, kinetics, and physiological function of protein variation (Gillespie, 1991). Reassuringly, DNA variation, mitochondrial and nuclear, like protein variation, is largely subjected to natural selection.
Genetic allozyme diversity across life
The roles and relative importance of the major evolutionary forces causing evolutionary change in protein and DNA levels, i.e., mutation, natural selection, gene flow, and genetic drift, are still controversial but become increasingly elucidated, especially in microscale studies (e.g., Nevo, 2009) and whole genome analyses in bacteria (Foster et al., 2009; Galhardo et al., 2007), Drosophila (Gonzales et al., 2010), dogs (von Holdt et al., 2010), cattle (Bovine HapMap Consortium, 2009) and humans (Coop et al., 2009; Haygood et al., 2010; Schuster et al., 2010).
Early analyses of protein variation in nature for 815 species out of 1100 species examined (Nevo et al., 1984a) for 21 variables (7 ecological, 5 demographic, and 9 life history and other biological characteristics) indicated the following results:
- The levels of genetic diversity vary nonrandomly among populations, species, higher taxa; ecological parameters (life zone, geographic range, habitat type and range, climatic region); demographic parameters (species size and population structure, gene flow, and sociality); life history characteristics (longevity, generation length, fecundity, origin, and mating/reproductive parameters).
- Genetic diversity is largely higher (i) in species living in broader environmental spectra, (ii) in large species with patchy population structure and limited migration, as well as in solitary or social species, and (iii) species with small body size, annuals or long-lived perennials that are older in time with diploid chromosome numbers, primarily out-crossed, and plant species reproducing sexually and pollinated by wind. Species with the above characteristics harbor, generally, more genetic diversity than their opposite counterparts.
- Genetic diversity is partly correlated and predictable by 3-4 variable combinations of ecological, demographic, and life-history variables, largely in this order.
Ecological factors account for the highest proportion of the 20% explained protein genetic variation of all species as compared with demographic and life-history factors (90%, 39%, and 3.5%, respectively). Within individual higher taxa, the explained portion of genetic diversity increases considerably (mean 44% and maximum of 74% in mollusks). However, significantly small inter-correlations (\(r = 0.1-0.3\)) occur both within and between subdivided biotic variables. Therefore, Nevo et al. (1984a) concluded that additional critical tests at the population microgeographical levels complemented by genomic, proteomic, biochemical, physiological, and biological tests may verify the earlier inferences of causal relationships between abiotic and biotic factors and genetic diversities as was later substantiated at the "Evolution Canyon" model (Nevo, 2009) and other microsites (Nevo lists at www.evolution.haifa.ac.il).
Natural selection predominance in adaptive evolution
The patterns and correlates of genetic diversity revealed in early allozyme studies, and later in DNA studies, including SNPs, and involving many unrelated species subdivided into different biotic regimes, strongly implicate natural selection in the genetic divergence of species. Natural selection in several forms, but most likely through the mechanisms of spatiotemporally varying and changing stressful environments and epistasis at the various life cycle stages of the organism, prevails in directing evolutionary dynamics of adaptation and speciation in nature. Other evolutionary forces including mutation, migration, and genetic drift certainly interact with natural selection, either directly or indirectly, and thereby contribute differentially according to circumstances to population divergence at the molecular level (e.g., Cronin et al., 2007; Yang et al., 2009; Wang et al., 2010).
Natural selection perception from Darwin to the 21st century was reviewed by Templeton (2009). Quantitative tests for natural selection on individual genes (Hoekstra et al., 2006) or complete genomes (Larkin et al., 2009) reinforce selection analyses. The role and relative importance of each evolutionary force and its interactive patterns with other forces as well as the establishment of direct cause-effect relationships between abiotic, biotic, and genetic factors may need subtle in-depth future experimentation at both the protein and DNA levels and their networks. However, the first generalized approximation becomes available based on many field and laboratory experiments on many populations and species, contributing to a new science of whole genome structure, expression, and the contribution of immense noncoding genomic regions in adaptation and speciation (Brodsky et al., 2008a,b; Kashi and King, 2006; Kashi et al., 1997: Li et al., 2002, 2004; Haygood et al., 2010).
Evolutionary roles of microsatellites (SSRs)
Simple sequence repeats (SSRs, microsatellites, and minisatellites) provide particularly interesting sources of high mutability, prolific and adaptively meaningful variation in natural populations (Goldstein and Schlötterer, 1999). Frequent mutations at SSR sites alter the number of tandem repeats generating extensive polymorphisms (Kashi and King, 2006). Commonly presumed to be largely neutral, SSR diversity influences many biological characters: biochemical, morphological, physiological, and behavioral . SSRs are abundant across genomes displaying high levels of polymorphisms. Reviews of microsatellite genomic distribution between genes, putative functions, and mutational mechanisms (Li et al., 2002) and within genes (Li et al., 2004) highlight their nonrandom distribution. Random expansions or contractions of SSRs appear to be selected against, for at least part of SSR loci, presumably because of their effect on chromatin organization, regulation of gene activity, recombination, DNA replication, cell cycle, and mismatch repair system, among many other functions. Specific kinds of repetitive elements and segmental duplications appear to directly promote the chromosome rearrangements associated with speciation in multiple mammalian lineages (Lewin, 2009). Many SSRs have been found and characterized within protein coding genes and their untranslated regions (UTRs).
The review of SSR distributions in both prokaryotes and eukaryotes within expressed sequence tags (ESTs) and genes, including protein coding 3'-UTRs and 5'-UTRs, and introns (Li et al., 2004), displays nonrandomiality on a large scale. SSR variations in 5'-UTRs could regulate gene expression by affecting transcription and translation. The SSR expansion in the 3'-UTRs cause transcription slippage and produce expanded mRNA, which can accumulate as nuclear foci that can disrupt splicing and other cellular functions. Intronic SSRs can affect gene transcription, mRNA splicing, and export to the cytoplasm. Triplet SSRs located in the UTRs or introns can induce heterochromatin mediated-like gene silencing. These functions can be expressed phenotypically, hence, SSRs within genes should be subjected to stronger selective pressure than those in other genomic regions. These SSRs may provide a molecular basis for fast adaptation to environmental stresses and changes in both prokaryotes and eukaryotes (Kashi and King, 2006; Li et al., 2002, 2004).
Microscale critical tests of molecular evolution
Microsite ecological contrasts are excellent critical tests for evaluating the dynamics of genome and phenome evolution and in assessing the relative importance (of adaptation and speciation) of the evolutionary forces causing adaptive convergence and speciational divergence (Nevo, 2009). The evolutionary driving forces involve mutation (in the broadest sense, including recombination), gene flow, chance (stochasticity), and natural selection. At a microsite, mutation, which is usually considered a clockwise neutral process, is expected to be similar across the microsite. Gene flow, involving all organisms at the microsite, including sessile organisms, is expected to homogenize allele frequencies. Stochasticity is not expected to result in repetitive ecologically-correlated patterns. Selection seems to be the only evolutionary force expected to result in repeated ecologically correlated patterns (Nevo et al., 1984a).
Early genetic diversity and divergence microsite studies conducted at the Institute of Evolution, University of Haifa, compared and contrasted temperatures (cold versus hot in sessile balanid crustaceans; Nevo et al., 1977), aridity index (high versus low in wild cereals; e.g., Li et al., 2000a,b; Nevo, 1998, Nevo and Chen, 2010; Nevo et al., 1988, Yang et al., 2009), rock diversity (igneous, volcanic, and sedimentary rocks (e.g., Li et al., 2000a,b), soil types (terra rossa, rendzina, and basalt in wild cereals; Li et al., 2000 a,b), topography (Nevo et al., 1991), and chemical (non-polluted versus polluted environments with inorganic heavy metals (Hg, Cd, Zn, Pb, and Fe), and organic (detergents and oil) pollutants in marine organisms (e.g., Nevo, 1986; Nevo et al., 1984b). The aforementioned studies demonstrated differential viability of allozyme genotypes where allozyme diversity and divergence were selected at a microscale or under critical empirically contrasting conditions and ecologies. The "Evolution Canyon" model has been a major testing ground during the years 1991-2010 (Nevo lists at www.evolution.haifa.ac.il).
The "Evolution Canyon" model: evolution in action across life
The "Evolution Canyon" model reveals evolution in action across life at a microscale involving biodiversity divergence, adaptive evolution, and incipient sympatric ecological speciation across life (Nevo, 2009). The model highlights species richness, genetic diversity and divergence, genomics, proteomics, phenomics, and metabolomics phenomena in diverse taxa by exploring genetic polymorphisms at protein and DNA levels and, recently, genome-wide gene expression and regulation (Brodsky et al., 2008a,b, 2009; Kossover et al., 2009). Genetic diversity and divergence reveal evolutionary dynamics of natural populations from bacteria to mammals exposed to sharp-interslope, ecologically divergent, tropical versus temperate microclimates on a xeric, tropical, "African" south-facing slope (AS) abutting with a mesic, temperate, "European" north-facing slope (ES) separated by 200 meters on average, e.g., as in Figure 1. Four "Evolution Canyons" (EC) are currently being investigated in Israel in the Carmel, Galilee, Negev, and Golan Mountains (EC I-IV, respectively, see (Nevo lists at www.evoution.haifa.ac.il).
We identified 2,500 species in EC I in Mount Carmel from bacteria to mammals in an area of 7,000 square meters. Local biodiversity patterns parallel global patterns. Higher terrestrial species richness was found on the AS. Aquatic species richness prevails on the ES. In 9 out of 14 (64%) model organisms across life, we identified a significantly higher genetic polymorphism (in both allozymes and DNA markers and gene sequences) on the climatically more stressful AS (which is tropical and more heterogeneous ecologically). Likewise, in some model taxa we found largely higher levels of mutation rates (see the review of Galhardo et al., 2007 on mutation as a stress response and regulation of evolvability): gene conversion, recombination, DNA repair, genome size, simple sequence repeats (SSRs), single nucleotide polymorphisms (SNP), retrotransposons, transposons, candidate gene diversity, and genome-wide gene expression and regulation on the more stressful AS than the milder ES (references in Nevo, 2009 and in (Nevo lists at www.evolution.haifa.ac.il).
Remarkably, incipient sympatric ecological speciation was found across life from bacteria (Sikorski and Nevo, 2005) to mammals (Nevo, 2006, 2009). The "Evolution Canyon" model represents the Israeli ecological analogue of the Galapagos Islands. Microclimatic selection overrides gene flow and drift (Nevo, 2010) and drives both interslope adaptive divergence and incipient sympatric ecological speciation at a microscale. Analyzing whole genomes with the next generation rapid high throughput techniques could unravel ecological-genomics dynamics at its best (e.g., Brodsky et al., 2008a,b, 2009; Kossover et al., 2009).
Single nucleotide polymorphisms (SNP)
Single nucleotide polymorphism (SNP) is the most common sequence variation in coding and noncoding genomes in diverse taxa across life from viruses and bacteria to humans (Kwok and Chen, 2003). Its extensive and intensive studies began with the massive sequence of genes and genomes. The sequencing of more than 3,800 genomes (Venter, 2010) and many new genes provide new horizons for deciphering SNP variation. SNPs are best fit to answer the question about the nature and meaning of genetic diversity in natural populations in diverse ecological contests of variable stresses and changing environments. Do they represent neutral variation, or, by contrast, appear to be correlated with environment and partly predicting it? How does gene function change with SNP mutations? The following evidence, first reported from research at the Institute of Evolution and then from worldwide studies, clearly indicates that SNPs, as with all other protein and DNA markers examined earlier, are nonrandomly distributed, correlated with diverse ecological stresses, and appear to be, to a large extent, adaptive, subjected primarily to the major evolutionary driving force of natural selection.
Studies at the Institute of Evolution
Wild cereals in the Near East Fertile Crescent: macro- and microscales
The Near East Fertile Crescent is the cradle of Old World agriculture including wild barley, Hordeum spontaneum, the progenitor of cultivated barley, and wild emmer wheat, Triticum dicoccoides, the progenitor of most cultivated wheats worldwide. Both these economically important progenitors proved to be rich in adaptive genetic diversity of both proteins and coding and noncoding DNAs, associated primarily with abiotic (climatic, soil, and mineral stresses) and biotic (parasites and pathogen stresses) (Nevo, 1992; Nevo et al., 2002) factors. Recent studies indicate that SNP diversity of cereal progenitors are also determined by climatic and soil stresses, certainly also indirectly reflecting pathogen and parasite distribution, as indicated in some examples below. Some examples will be reviewed below in wild cereals based on SNP studies conducted on wild cereals at the Institute of Evolution, University of Haifa, Israel. Additional citations from world literature appear later in different sections.
Wild barley, Hordeum spontaneum
Hina grain hardness genes: adaptive SNP polymorphism
Hina genes in wild barley are one of two known genes related to grain hardness, hordoindolines (hin), located at the short arm of chromosome 5H (Li et al., 2010b and references therein). Soft texture grain has better malting characteristics, and low milling energy is best for malting barleys. Remarkably, the genetic divergence between Near Eastern populations was independent of geographical distances. Eight SNP positions, both in coding and noncoding genomic regions, were significantly correlated with ecological factors, primarily temperature reflected by altitude (Li et al., 2010b).
Isa gene: Bifunctional alpha amylase/subtilisin inhibitor (BASI): SNP polymorphism
The Isa gene from barley has a putative role in plant defense inhibiting the bacterial serine protease subtilisin, fungal xylanase, and the plant's own alpha amylase. Sixteen SNPs in the coding region of the Isa locus of wild barley, Hordeum spontaneum, from eight climatically divergent sites across Israel, indicate high recombination within this gene regardless of the plant's high inbreeding (Cronin et al., 2007). Seven amino acid substitutions were present in the coding region. Genetic diversity at the Isa locus was highly and significantly correlated with key water variables, evaporation, rainfall, humidity, and latitude. This association suggests selective sweeps in the wetter climates with resulting low diversity, and weaker selection or diversifying selection in the dryer climates resulting in much higher diversity. Remarkably, high diversity was also found in the Isa locus in populations from the xeric-tropical "African" south-facing slope at "Evolution Canyon" and at Tabgha, another microsite, subdivided into two soil types: wetter basalt and drier terra rossa (Cronin et al., 2007). The parallelism between the higher genetic diversity at dry environments, both at the macro- and microscales, suggest that the evolution of Isa is subjected to natural selection, which is probably caused by fungal and bacterial pathogens associated with climatic variation, demonstrating remarkable host (wild barley) and pathogen (fungus) co-evolution.
Adaptive dehydrin-1 SNP evolution in "Evolution Canyon"
Dehydrins (DHNs; Lea D-11) are water soluble, lipid, vesicle-associating proteins involved in the adaptive response of plants to drought, low temperature, and salinity. Dehydrin 1 (Dhn 1) SNP polymorphism and expression was examined in 47 plants of wild barley from the opposite slopes of "Evolution Canyon" in 7,000 square meters for a total of 708 bp sites located in the 5' upstream flanking region of the gene (Yang et al., 2009). Significant interslope diversity of 29 haplotypes was found, mostly 25 (86.2%) represented by one genotype unique to one population. Only a single haplotype was common to both slopes. Interslope divergence was significantly higher than intraslope divergence. SNP diversity proved non-neutral. Dhn 1 RNA expression under dehydration displayed interslope divergence between the opposite slopes, AS ("African" Slope) and ES ("European" Slope), reinforcing its drought-resistance potential. A similar interslope variation was found by 28 allozyme loci and 51 RAPD loci at the level of the whole species. These results are inexplicable only by mutation, gene flow, or chance effects, and support adaptive natural microclimatic diversifying selection as the major evolutionary divergence force (Yang et al., 2009). Similar adaptive microclimatic evolution of the dehydrin-6 also occurred in wild barley at "EC" (Li et al., 2010a).
Amy2 SNPs involved in germination and malting
Alpha-amylases hydrolyze internal a-1,4-glucosidic bonds in starch and related dextrins and oligosaccharides. Two isozymes, AMY1 and AMY2, play an essential role in germination and malting processes in Hordeum spontaneum by hydrolyzing the storage starch granules of the endosperm. Both isozymes degrade starch, providing energy for plant embryo development and its cardinal role in germination and brewing. SNP and haplotype diversity of AMY2 sequence were studied in 11 Israeli populations of Hordeum spontaneum. Six populations were from "Evolution Canyon", three populations from the xeric, tropical, south-facing "African" slope (AS), and three populations from the mesic, temperate, north-facing "European" slope (ES), separated by 200 meters, on average, from the AS (Wang et al., 2010). One population was from the Tabgha microsite in the Upper Galilee Mountains, subdivided into 50 meters of wetter basalt and 50 meters of drier terra rossa soils. One population was from Newe Yaar, a mosaically structured microsite in the Lower Galilee Mountains involving microclimatic, lithological, and edaphic divergent ecological stresses. Two Upper Galilee populations, Maalot and Meron, are mesic, and Sede Boqer in the northern Negev Desert is xeric.
The fully analyzed sequences of 109 Amy2 genes consist of four conserved exons and three variable introns. One out of 7.5 bases displayed a SNP variation, much more variable than cultivated barley. A total of 36 SNPs were detected in the mature protein coding sequence of Amy2. Population-specific SNPs were missing from the desert Sede Boqer population and another SNP (825 A) was found in mesic Maalot and Meron. In wild barley from "Evolution Canyon" 14 SNPs were detected in 6 close populations in the canyon. Seven SNPs were fixed in slopes and population-specific, 4 SNPs from the lower AS slope, and only one SNP was shared between slopes. Most of the slope-specific SNPs were correlated with water and temperature factors, representing amino acid changes, displaying slope-specific adaptive patterns driven by diversifying natural selection and affecting functionally important protein domains of Amy2.
Wild emmer wheat, Triticum dicoccoides
Adaptive alpha amylase inhibitor SNPs diversity
Molecular evolution of dimeric α-amylase inhibitor genes in wild emmer wheat, Triticum dicoccoides, the progenitor of most cultivated wheats, showed widespread diversity in dimeric α-amylase inhibitors, both within and between populations (Wang et al., 2008). SNP markers are useful for estimating genetic diversity of functional genes in wild emmer. They are also significantly correlated with ecological factors and can predict ecogeographic, primarily climatic, regimes. SNPs in the α-amylase inhibitor genes have been adaptively selected by natural selection (Wang et al., 2008) and likewise in sequence-related amplified polymorphism (SRAP) (Dong et al., 2010). A NAC gene Gpc-B1, a wheat QTL regulating senescence that improves grain proteins, zn, and iron content in wheat (Uauy et al., 2006), which could improve human nutrition and health based on wild emmer wheat.
Similar ecological-genetic associations to those found in wild barley were also found between EST-SSR diversity and resistance of gene analog polymorphisms (RGAPs), and sequence-related amplified polymorphism (SRAP) in wild emmer wheat with ecogeographical (primarily climatic) factors (Dong et al., 2009a,b, 2010, respectively).
Worldwide studies in diverse taxa
Genome-wide analyses in 52 human populations identified 139 immune response genes. They comprised 441 variant alleles involved in anti-viral immune response identified in 660,000 SNPs, which were significantly associated with virus-driven selection pressure (Fumagalli et al., 2010). A second-generation human haplotype map of over 3.1 million SNPs (The International HapMap Consortium, 2007) showed novel aspects of structure and linkage disequilibrium. Likewise, recombination rates vary systematically around and between genes of different function. Finally, increased differentiation at nonsynonymous, compared to synonymous SNPs, result from systematic differences in the strength or efficacy of natural selection between populations. Adaptive disease-associated SNPs in humans (lipid levels and coronary heart diseases) were described by Hao et al. (2010). Genome-wide analysis involving 160,000 non-redundant SNP variations revealed relationships among landraces and modern varieties of rice useful for future rice improvement (McNally et al., 2009). SNP variation and rapid postglacial range expansion in the balsam poplar, Populus balsamifera, strongly increased genomic diversity during colonization northward into previous ice-sheet regions (Keller et al., 2010). In Populus nigra an analysis of 9 genes and 312 SNPs indicated non-neutrality in some genes (Chu et al., 2009). Worldwide SNP analysis at 48 loci of castor beans, Ricinus communis, revealed low levels of genetic diversity but high non-geographical population divergence of local ecological demes (Foster et al., 2010). Adaptive altitudinal evolution of the dehydrogenase mitochondrial ND6 gene was described in the domestic horse in China (Ning et al., 2010). SNP association in Pacific white shrimp was described for economic traits and viral resistance (Ciobanu et al., 2010). The human melatonin signaling pathway, particularly the melatonin receptor, appears to be subjected to a selective pressure in response to global variation in sunshine duration (Xu et al., 2010). In cassava, Manihot esculenta, 26 SNPs were found in 9 genes, 1 SNP every 121 nucleotides, and correlated with SSR variation (Kawuki et al., 2009). Evidence of selection was found in domesticated cattle populations and outgroup species (Bison, Yak, and Banteg) analyzed for SNP diversity, unfolding ancient polymorphisms (MacEachern et al., 2009). A coding SNP of Limhomeobox transcription factor 4 (LHX 4) is associated with body weight and length in bovine (Ren et al., 2010). Cotton 270 -SNP and indel diversity showed that A and D genomes remain distinct and paralogous, and are identifiable (Van Deynze et al., 2009).
Adaptive selected SNPs widespread across life
Adaptive selected SNP polymorphism was found in maize domestication (Sigmon and Vollbrecht, 2010); in the bacterium Thiomonas, genomic evolution appears by gain or loss of genomic islands in adaptation to arsenic-rich acid mine drainage (Arsene-Ploetze et al., 2010) and likewise in naturally occurring Arabidopsis thaliana (Koornneef et al., 2004; Atwell et al., 2010). Adaptive chromosomes and SNP evolution of regulatory elements were identified in nine mammals (human, chimp, macaque, rat, mouse, pig, cattle, dog, and opossum) and chicken (Larkin et al., 2009); in an altitudinal gradient in horses' mtDNA ND6 (Ning et al., 2010); in humans by disease-associated SNPs (lipid levels and coronary heart disease) (Hao et al., 2010), and in high-altitude adaptation to hypoxia (Beall et al., 2010; Simonson et al., 2010; Yi et al., 2010). By contrast, only scant evidence for positive selection, but abundant evidence for deleterious SNPs (12% of coding and 7% of noncoding SNPs) were described in a genomic analysis of the yeast Saccharomyces cerevisiae (Doniger et al., 2008).
In Anopheles mosquitoes' sequenced immune genes displayed positive selection in both SNPs and amino acid sites (Parmakelis et al., 2010). Local selection of SSRs was identified in olive cultivars (Belaj et al., 2010). In maize, evidence of selection at the ramosa1 locus occurred during domestication (Sigmon and Vollbrecht, 2010). In chichlid fish SNP polymorphism enables assessing levels of gene flow (Mims et al., 2010). High polymorphism of SNPs in 109 olfactory receptor genes (out of 800 such genes) distribute nonuniformly in 48 dogs of six breeds, clearly affecting odorant potential. In the human genome SSRs can predict SNP diversity and divergence (Varela and Amos, 2010). A computation integrating genetic variation within regulatory elements and their possible effects appear in Wu et al. (2009). Hyten et al. (2010) demonstrated how next-generation sequencing was combined with high-throughput SNP detection assays to quickly discover large numbers of SNPs, enabling a high-resolution genetic map of the soybean whole genome sequence into pseudo-molecules corresponding to the chromosomes of the organism. SSRs and SNPs could effectively identify parentage, such as in the bison with low-genetic diversity due to severe bottleneck (Torskarska et al., 2010). Whole genome-based phylogeny and divergence of the genus Brucella, a worldwide bacterial pathogen of livestock and wildlife, unfolded evolutionary history with promising prospects for molecular epidemiological and clinical studies (Foster et al., 2009). The following are overviews of additional mechanisms causing genetic diversity in nature.
Copy number variation (CNV)
Copy number variation (CNV) of DNA sequences is abundant in natural populations and is functionally significant but still needs to be fully ascertained. CNV is generated by both recombination and replication mechanisms and de novo locus-specific mutation rate, which is higher than in SNP. CNVs can cause Mendelian, sporadic, or diseased effects and affect gene duplication, exon shuffling, and genome diversity and evolution, subjected to both purifying and positive selection (Zhang et al., 2009). Mechanisms of change causing CNV evolution in humans, through deletions and duplications of chromosomal segments, were described by Hastings et al. (2009).
CNV in humans was examined by SNP genotyping arrays and clone-based comparative genomic hybridization (Redon et al., 2006). A total of 1,447 CNVRs in regions covering 360 megabases (12% of the genome) were identified in 270 individuals from four populations that originated in Europe, Africa, and Asia (the HapMap collection). These CNVRs contained hundreds of genes, disease loci, functional elements, and segmental duplications. Remarkably, the CNVRs in humans displayed more nucleotide content per genome than SNPs, highlighting the importance, ubiquity, complexity, and functional diversity of CNV in genetic and phenotypic diversity and evolution. Population analysis of \(\approx\)2,500 individuals, added to published records of 12,000 individuals, unfolded large copy number variants and hotspots of human genetic disease (Itsara et al., 2009). Conrad (2010) identified 30 loci in humans with CNVs that are candidates for influencing disease susceptibility. Craddock et al. (2010) confirmed in \(\approx\)19,000 individuals three loci where CNVs were associated with diseases but concluded that common CNVs are well tagged by SNPs and are unlikely to contribute greatly to the genetic basis of common human diseases. Our own, yet unpublished, CNV work in the blind mole rat Spalax confirms this richness both at micro- and macroscales. The human data unfold linkage disequilibria patterns for many CNVs and reveal marked variation in CNV among populations. Their utility for genetic disease studies are highlighted in Redon et al. (2006). CNV is extensive in the genomes of 12 natural isolates of Caenorhabditis elegans, affecting 5% of genes in the genome.
CNVs in the human genome caused by both recombination and replication-based mechanisms can produce many complex traits, including autism and schizophrenia (Stankiewicz and Lupski, 2010). Integrated detection and population-genetic analysis of SNPs and CNVs by a hybrid genotyping array (Affymetrix SNP 6.0) to simultaneously measure 906,600 SNPs and copy number at 1.8 million genomic locations appear in McCarrol et al. (2008).
Large (>100 kb) CNVs affect much less of the genome than initially reported. Approximately 80% of observed copy number differences between pairs of individuals were due to common copy number polymorphisms (CNPs) with an allele frequency >5% and more than 99% were derived from inheritance rather than new mutations. Most common were the diallelic CNPs in strong linkage disequilibrium with SNPs, and most low-frequency CNVs segregated onto specific SNP haplotypes.
Significant temporal fluctuations in the copy number of TEs provide new insights into adaptation and speciation genome evolution of the wild diploid wheat Aegilops speltoides in its marginal population in Israel (Belyayev et al., 2010). The revealed temporal dynamics of TEs could promote and intensify morphological and karyotypic changes affecting microevolution and the evolution of new species under stressful and rapid climatic change (Belyayev et al., 2010).
Transposable elements (TEs) mediate large-scale rearrangements of the bacterial genome revealing a striking connection between ecophysiological stress and activation of DNA rearrangement functions. TEs, similar to controlling elements in maize, confirm Barbara McClintock's view that cells frequently respond to stimuli by restructuring their genomes. This view provides a novel dynamic instead of the earlier dogmatic insights into the natural genetic engineering evolutionary processes (Shapiro, 2009, 2011). Detection of new genomic control elements is critical in understanding transcriptional regulatory networks in their entirety. Transposable elements contributed up to 25% of the bound sites in humans and mice and have wired new genes into the core regulatory network of embryonic stem cells. Species-specific transposable elements have substantially altered the transcriptional circuitry of pluripotent stem cells (Kunarso et al., 2010). TEs provide insight not only to spatial variation but, remarkably, to temporal fluctuations in plant population and genome dynamics (Belyayev et al., 2010).
Sequence conservation of noncoding DNA across species can indicate functional conservation. Nevertheless, Kunarso et al. (2010) demonstrated notable differences between human and mouse stem cell regulatory networks, suggesting caution in generalizing from sequence to functional conservation. Mobile DNA and evolution in the 21st century has been reviewed by Shapiro (2011). He emphasized that dynamic molecular cell biology has revealed a dense structure of information processing networks that use the genome as an interactive read-write (RW) memory system rather than as an organism blueprint (see additional non-dogmatic modern evolutionary perspectives in Shapiro, 2011). Mobile DNA rearrangements and major genome restructuring events at key junctures in evolution (exon shuffling, changes in cis-regulatory sites, horizontal transfer, cell fusions and whole genome doublings) highlight interactive evolutionary process, emphasized by McClintock (1984). This view elucidates the molecular basis of genetic change, major genomic events in evolution, ecological changes, cellular response and control networks, and stimuli restructuring DNA. Likewise, the rapid emergence of adaptive novel complexes, coupled with a classical cytogenetic role of hybridization (allotetraploidization) in the origin of species. As Shapiro (2010) emphasizes, the study of mobile elements "has most significantly transformed evolution from natural history into a vibrant empirical science".
Horizontal gene transfer (HGT)
HGT is a major source of natural genetic diversity between taxa, resulting in genome innovation and evolution, particularly in prokaryotes (Gogarten and Townsend, 2005). It may play a major role in shaping bacterial genomes and in the rapid dissemination and acquisition of new adaptive traits across bacterial populations. Raz and Tannenbaum (2010) found that HGT has a non-trivial affect on the mean fitness of the population. They concluded that the main advantage of HGT is by promoting faster adaptation in dynamic, stressful environments.
By contrast, Koonin (2009) suggested that major contributions of HGT show that the tree of life changes into a "forest of life", and natural selection is only one of the forces that shapes genome evolution. Presumably, concludes Koonin, the prevalence of non-adaptive evolution at the genomic level suggests the need for a revised synthesis of evolutionary biology models (Koonin, 2009). A critical review of HGT (Kurkland et al., 2003) suggested that rampant global HGT is likely to have been relevant only to primitive genomes, whereas selection constraints limited the range and frequencies of HGT in modern organisms, and likewise the claim that HGT is the "essence of phylogeny" is exaggerated. HGT of a eudicot parasitic plant and its monocot host was described by Yoshida et al. (2010), demonstrating that HGT is not restricted to exchanges between plants and microbes, mitochondrial transfer, or the translocation of mobile elements among related species. Evidence that host-parasite interactions have promoted the HGT of four transposon families between invertebrates and vertebrates (phyla) was described by Gilbert et al. (2010).
Alternative splicing complexity
Alternative splicing (AS) allows individual genes to produce multiple protein isoforms, in contrast to the "one-gene-one-polypeptide rule", generating highly diverse and complex proteomes. Early estimates stated that about 100,000 genes would be required to make up a mammal; however, the actual number is around 20,000, less than four times the number of genes in budding yeast. It is now clear that the missing information is to a large part due to the AS, the process by which different multiple functional messenger RNAs and, therefore, proteins can be synthesized from a single gene (Nilsen and Graveley, 2010). The AS is considered to be a key factor in generating increased genetic diversity and cellular and functional complexity in higher eukaryotes (Pan et al., 2008). It has been estimated that two-thirds of human genes contain one or more alternatively spliced exons. Recent studies using high-throughput sequencing indicate that 95-100% of human pre-mRNAs that contain sequences corresponding to more than one exon are processed to yield multiple mRNAs (references in Nilsen and Graveley, 2010).
Likewise, there are \(\approx\)100,000 intermediate to high-abundance alternative splicing events in major human tissues. This estimate suggests that, on average, there are at least seven alternative splicing events per multi-exon human gene (Pan et al., 2008) generating huge genetic variation in nature. Another study of global gene activity and alternative splicing by deep sequencing of the human transcriptome (Sultan et al., 2008) identified 94,241 splice junctions and showed that exon skipping is the most prevalent form of alternative splicing. Genome-wide analysis of alternative pre-mRNA splicing indicates the high potential of the AS to greatly influence the regulatory evolution of complex genomes and decipher human pathologies (Ben-Dov et al., 2007). Barash et al. (2010) deciphered the splicing code, which uses various combinations of hundreds of RNA features to predict tissue-dependent changes in alternative splicing for thousands of exons. Thus, the AS has a crucial role in generating genetic diversity and complexity, and its misregulation is often involved in human disease. The code determines new classes of splicing patterns, identifies distinct regulatory programs in different tissues, and identifies mutation-verified regulatory sequences. The code facilitates the discovery and detailed characterization of regulated alternative splicing events on a genome-wide scale (Barash et al., 2010).
RNA multiverse diversity and adaptive evolution
RNA multiverse world
The genomic era provides complete genome sequences, indicating that gene number is not the sole determinant of genome and proteome diversity, and complexity. Remarkably, the genomes of all studied eukaryotes are almost entirely transcribed, generating an enormous number of nonprotein-coding RNAs (ncRNAs), and many of these RNAs have regulatory functions. Via the mechanism of retroposition, RNAs massively change genomic landscapes providing potentially functional elements selected to alter gene structure and expression (Brosius, 2005). Retroposition is a major mediator of genomic plasticity and a contributor to gene novelty (Brosius, 2003; Volff and Brosius, 2007). The diversity of ncRNA controls genome dynamics, cell biology, and developmental programming (Amaral et al., 2008). Remarkably, microRNAs (miRNAs are \(\approx\)22 nucleotides long), exert multilevel regulation of gene expression by suppressing translation and destabilizing messenger RNAs bearing complementary target sequences (Makeyev and Maniatis, 2008). Additional diversity and complexity is provided by the noncoding genome and its immense diversity whose regulatory functional potential is currently under extensive investigation, including the "nonprotein-coding RNAs" (Brosius, 2009).
Retroelement genes participate massively in generating new proteins - provide raw material for the evolution of genes in a wide variety of ways, duplicate and mend the protein coding region of existing genes, as well as generate the potential for new protein coding spaces or noncoding RNAs, by unexpected contributions out of the frame, in reverse orientation or from previously non-protein coding sequence (Baertsch et al., 2008). Coding genes can also be generated by reverse transcription of mRNA from classical genes by the enzymatic machinery of autonomous retroelements. New nonprotein-coding RNA genes have been repeatedly generated through retroposition during evolution. Likewise, genes for small molecular RNAs (snmRNAs) and microRNAs (miRNAs) can also be duplicated via retroposition (Volff and Brosius, 2007). Gene silencing induced by RNA interference (RNAi) became a highlight in molecular regulation. It offers new quick ways of easily creating loss of function phenotypes (Sohail, 2005).
The many roles of an RNA Editor involving many transcripts that can derive from each locus are of paramount importance in expanding diversity, including exonization (Möller-Krull et al., 2008). RNA editing is less well recognized than alternative splicing as a method of generating diversity. RNA editing has been defined as RNA modification that changes its coding capacity and is distinct from RNA splicing (Keegan et al., 2001). The conversion of an adenosine (A) to inosine (I) in primary RNA transcripts can result in amino acid change in the encoded protein, a change in secondary structure of the RNA, creation or elimination of a splice consensus site, or otherwise altering RNA fate (Gommans et al., 2009).
A-to-I editing in humans primarily occurs in noncoding regions of the RNA, typically in Alu repeats by members of the ADAR (adenosine deaminases acting on RNA) family leading to the site- specific A-to-I in precursor messenger RNAs (Levanon et al., 2004). Substantial transcriptome and proteome variability is generated by A-to-I RNA editing through site-selective post-transcriptional recording of single nucleotides. Gommans et al. (2009) hypothesized that this epigenetic source of phenotypic variation is an unrecognized mechanism of adaptive evolution. The genetic variation introduced through editing occurs at low evolutionary cost since predominant production of the wild type protein is retained. This property, as these authors posit, allows exploration of sequence space that is inaccessible through mutation, leading to increased phenotypic plasticity, providing evolutionary advantage for acclimatization as well as long-term adaptation. Novel RNA-editing sites can enrich the transcriptome and is an intrinsic property of the editing machinery representing the molecular basis of increased evolvability and adaptability. Hence, higher organisms might have evolved systems with increasing RNA-editing activity and thus increase complexity. This explanatory model could be one of the important mechanisms shaping transcriptome diversity in primates.
The question why, despite 99% genomic similarity between humans and chimpanzees, the former have higher brain function calls for an explanation. The RNA-editing level in humans is significantly higher, compared with nonprimates, due to exceptional editing within the primate-specific Alu sequences. Paz-Yaacov et al. (2010) first reported that, on average, the editing level in the analyzed Alu transcripts is higher in the human brain compared with nonhuman primates, chimpanzee, and rhesus. Moreover, new editable species-specific Alu insertions, subsequent to the human-chimpanzee split, are significantly enriched in genes related to neuronal functions and neurological diseases. The enhanced editing level in the human brain and the association with neuronal functions suggest the possible contribution of A-to-I editing to the development of higher human brain function (Paz-Yaacov et al., 2010). This enhanced editing of genes of higher brain function may have been generated adaptively by natural selection to cope with the climatically stressful savanna environment humans occupied after descending from trees. Interestingly, A-to-I pre-mRNA editing in Drosophila is primarily involved in the adult nervous system function and in integrity and behavior (Palladino et al., 2000).
Protein intrinsic disorder, genetic diversity, and cell signaling
Current biology still largely adheres to the standard view that a protein's amino acid sequence provides the folding information into a specific 3D-structure resulting in a specific function. This is the sequence-to-structure-to-function paradigm. This paradigm is correct for enzymes but not for biological processes, such as cell division and development, which require regulation and organization of chemical reactions and complex pathways. Recent computational and bioinformatics methods (e.g., intrinsic disorder predictor PONDR VLXT) show that the regulatory signaling interactions in cells depend not just on protein 3D structure but also on the lack of 3D-structure or intrinsic disorder (Dunker et al., 2008; Xue et al., 2010). For signaling proteins, a new paradigm was proposed, namely, the sequence-to-flexible-ensemble-to function. Recent studies have shown that intrinsically disordered proteins (IDPs), i.e., biologically active proteins that do not possess stable secondary and/or tertiary structures and intrinsically disordered regions (IDR), are highly abundant in different proteomes and function primarily in regulation related to molecular recognition and signal transduction, for example, in viral pathogens (Goh et al., 2009).
An accurate prediction of the protein's predisposition to be intrinsically disordered is a necessary prerequisite for the further understanding of principles and mechanisms of protein folding and function, and is a key for the elaboration of a new structural and functional hierarchy of proteins (He et al., 2009). Long disordered regions should be recognized as a distinct class of biologically functional protein domains (Topa et al., 2009) functioning in regulation, recognition, signaling, and control. They are much more common in eukaryotes than in prokaryotes and archea, reflecting the greater need for disorder-associated signaling and regulated in nucleated cells (Uversky and Dunker, 2010), which are more developed evolutionarily. The abundance of IDPs and IDRs in 53 archea species was analyzed (Xue et al., 2010) showing rich intrinsic disorder, 14% disordered residues in the Thermoproteales and 34% in Halobacteria. There is a weak correlation between environmental factors (e.g., salinity, ph, and temperature) and the abundance of intrinsic disorder in archea. However, a combination of harsh environmental conditions clearly favors increased disorder content in archea. Some of the IDPs and IDRs likely evolved to adapt archea to their hostile habitats; some of them are similar to those in bacteria and eukaryotes (Xue et al., 2010).
Comparisons of the Neanderthal genome to the genomes of extant humans identified a number of genomic regions that may have been affected by positive selection in ancestral modern humans, including genes involved in metabolism and in cognitive and skeletal development (Green et al., 2010). A genome-wide survey of SNPs variation in 497 cattle from 19 breeds uncovered the genetic structure of cattle breeds (Bovine HapMap Consortium 2009). Domestication and artificial selection left detectable selection signatures within the cattle genome with high diversity within breeds.
Genome-wide patterns of adaptation to temperate environments associated with transposable element (TEs) in Drosophila identified environmental selective signals (Gonzalez et al., 2010). Strong evidence was shown for the phenotypic adaptive elements of TEs, of an original African species, specifically to temperate climates. Genome-wide SNP haplotype analyses based on 48,000 SNPs reveal a rich history underlying dog domestication primarily from the Middle Eastern wolf progenitor, demonstrating a surprising correspondence between genetic and rapid phenotypic/functional adaptive divergence by positively selected breed diversification unique to the domestic dog (von Holdt et al., 2010). Pattern of polymorphism after strong positive artificial selection in dog domestication was described by Innan and Kim (2004). The dog is a striking example of adaptive-selective genetic and phenotypic variation under domestication. The genome of the zebra finch shows that neural function genes implicated in cognitive processing of song have been rapidly evolving. Song behavior engages gene regulatory networks, altering the expression of long noncoding RNAs, microRNAs, transcription factors, and targets (Warren et al., 2010). Paired-end mapping reveals extensive structural variation in the human genome affecting gene function (Korbel et al., 2007). A high resolution genetic map of the human genome identified more than 25,000 recombination hotspots (Myers et al., 2005).
Hotspots of biased nucleotide substitutions in human genes can lead to accelerated evolution in coding sequences and excess amino acid replacement substitutions, with a significant tendency to contain clusters of AT-to-GC (weak-to-strong biased substitutions), thereby generating significant results for tests of adaptive complexes by positive selection. This pattern is also observed in noncoding sequences flanking rapidly evolving exons (Berglund et al., 2009; see also Haygood et al., 2010). A biased gene conversion might drive fixation of GC alleles in the human genome. Remarkably, the interslope divergence of AT and GC in the ecologically milder and harsher slopes, respectively, was also found in Bacillus subtilis in "Evolution Canyon" III, Nahal Shaharut, in the southern Negev Desert, Israel (Barash et al., 2006). Finally, population genomics of parallel adaptations in threespine stickleback, based on 45,000 SNPs, exhibit signatures of both balancing and divergent selection consistent across many populations, indicating genomic parallel genetic-phenetic evolution, unfolding repetitive shifts from ocean to divergent freshwater populations (Hohenlohe et al., 2010).
Whole genome sequencing
Genomic diversity of humans
The decade from 2000 to 2010 involved breakthrough acceleration in genome science; numerous genomes have been sequenced and others are planned for complete sequences: 10,000 vertebrate genomes (Genome 10K community of scientists, 2009) and 1,000 Drosophila genomes. Comparative genomics became a powerful tool for understanding evolution and genome function. Genetic diversity will be linked to function. Regulatory diversity in the noncoding genome will prove essential in functional processes. This will certainly revolutionize agriculture, medicine, and personalized medicine. Researchers hypothesized that small hotspots (kilobases) are stochastic but large-scale hotspots (megabase) are constrained, correlated between humans and chimpanzees. The genetic structure and history of Africans and African-Americans based on 1,327 nuclear microsatellites and insertion/deletion markers revealed high levels of mixed ancestry in most 121 African populations, reflecting historical migration across the continent (Tishkoff et al., 2009).
Accurate whole human genome sequencing using reversible terminator chemistry revealed 4 million single nucleotide polymorphisms and 400,000 structural variants many of which were previously unknown. This approach is effective for accurate, rapid, and economical whole-genome re-sequencing and many biomedical applications (Bentley et al., 2008). In the analysis of the diploid genome sequence of an individual human, J. Craig Venter (Levy et al., 2007) revealed 4.1 million variants (1,288,319 novel), including 3,213,401 SNPs (the majority of genomic alterations), 53,823 block substitutions (2-206 bp), 292,102 heterozygous insertion/deletion events (indels), (1-571 bp), 559,473 homozygous indels (1-82,711), 90 inversion as well as numerous segmental duplications and copy number variation (CNV) regions. Non-SNP DNA variation accounts for 22% of all events identified, involving 74% of all variant bases. This suggests an important role for non-SNP genetic variation in defining the diploid genome structure. Moreover, 44% of genes were heterozygous for one or more variants. These whole genome analyses permit inter-individual population and ethnic comparisons of human variation. The data also indicate that genetic variation between two individuals is as much as five times higher than previously estimated, initiating the emerging era of individualized genomic information. The complete genome of James D. Watson (Wheeler et al., 2008) revealed 3.3 million SNPs, of which 10,654 cause amino acid substitutions within the coding sequence. Also, Watson's genome included small-scale (2-40,000 bp) indel polymorphisms as well as copy number variation, resulting in large-scale gain and loss of chromosomal segments ranging from 26,000 to 1.5 million bp. This was the first genome sequenced by next-generation technologies initiating personalized genome sequencing and permitting personalized medicine.
The first human Korean genome sequence for a socio-ethnic group (Ahn et al., 2009) revealed 420,083 novel SNPs. Despite a close similarity, when the Chinese (YH) and Korean (SJK) individual genomes were compared, 39.87% of SJK SNPs were specific (49.51% against Venter's, 46.94 against Watson's, and 44.17 against the Yoruba genomes). On the same loci, 99.5% of short indels (<4bp) had the same size and type as YH; 11.3% deletion structural variants were SHK-specific, and 5.77% SJK reads could not be mapped. These findings indicate significant ethnic group differences. Complete genome sequences of five indigenous Africans, a hunter-gatherer from Kalahari-Bushmen, a bantu from southern Africa (Archbishop Desmond Tutu), and three additional hunter-gatherers from disparate Kalahari Desert regions (Schuster et al., 2010) displayed 1.3 million novel DNA genome-wide differences, including 13,146 novel amino acid variants.
Remarkably, in terms of nucleotide substitutions, the Bushmen seem to be, on average, more different from each other, than to a European and an Asian. Adaptations evolved to arid climates in the Kalhari Bushmen, such as the ability to store water and lipid metabolites in body tissue. Adaptive (selected) evolution was inferred from human-chimp-mouse orthologous gene trios. Partitions of genes into inferred biological classes identified accelerated evolution in several functional classes, including olfaction and nuclear transport (Clark et al., 2003). Analyzing the role of geography in human adaptation across genomes in numerous populations, Coop et al. (2009) suggested that selection is often weak enough (strongly constrained) that neutral processes, especially population history, migration, and drift, exert powerful influences over the fate and geographic distribution of selected alleles. The small number of human genes (26,000) compared to earlier estimates (of up to 300,000) and the small amount of variation between individuals (0.1%) suggest that the major future challenge in human genomics is to link genetic (and phenotypic) diversity with physiology and diseases. Remarkably, subsequent discoveries indicated that inter-individual genomes differ by 1% to 3%, displaying significantly higher variation between individuals (Venter, 2010).
Pelak et al. (2010) reported on the nearly complete genomic sequence of twenty different human individuals, the largest set of unrelated human genomic sequences that have been reported till September 2010, by using next generation sequencing technologies. They found a surprising number of variants predicted to reduce or remove the proteins encoded by many different genes. They identified rare and highly penetrant functional variants by confirming that the cause of hemophilia A is easily recognizable in this data set. They also show that the number of novel single nucleotide variants (SNVs) discovered per genome seems to stabilize at about 144,000 new variants per genome, after the first 15 individuals have been sequenced. Likewise, they found that, on average, each genome carries 165 homozygous protein-truncating or stop-loss variants in genes representing a diverse set of pathways. This work elucidates the scope of human genetic variation, and suggests ways to further explore the relationships between these genetic variants and human disease.
Genomic functional divergence
Comparative genomics becomes a powerful approach for understanding evolution and genome function. The target of sequencing 1,000 individual human genomes and the genome 10K: A proposal to obtain whole genome sequence for 10,000 vertebrate species (Journal of Heredity, DOI:10.1093/jhered/esp086) and 1,000 Drosophila genomes highlight that the genome and post-genome revolution is proliferating. The sequencing of 50 Tibetan human exomes revealed significant allele frequency changes in candidate genes for altitude adaptations (Yi et al., 2010). Likewise, they identified a functionally important locus, endothelial Per-Arnt-Sim (PAS) domain protein 1 (EPAS1), also known as hypoxia inducible factor 2a (HIF2a), a transcription factor involved in adaptive responses to hypoxia, including regulation of blood cell production. The focal SNP at EPAS1 evolved extremely fast since the Tibetan diverged 2,750 years ago from the Hans, displaying the fastest change of frequencies in humans driven by natural selection (Yi et al., 2010). The natural selection pressure on EPAS1 (HIF2a) was associated with low hemoglobin concentration in the Tibetan highlands (Beall et al., 2010).
A genome-wide association study of 139 SNPs in several T-cell subsets genes significantly associated with Alopecia areata, which is among the most highly prevalent human autoimmune diseases, implicates both innate and adaptive immunity (Petukhova et al., 2010). Fine-scaled human genetic structure, involving 240,000 transcription loci \(\approx\)250,000 SNPs, revealed by SNP microarray analyses in 554 individuals from 27 populations in Africa, Asia, and Europe, classified individuals to their populations, including Indian caste and tribal populations, and established a correlation of genetic and geographic distances. The highest genetic diversity was in African populations, followed by European and Asian populations. The Chinese populations proved more diverse than the Japanese populations (Lonita-Laza et al., 2009).
An extensive mtDNA analysis provides evidence that the first European farmers were not the descendants of local hunter-gatherers but immigrated into central Europe at the onset of the Neolithic Age (Bramanti et al., 2009). The HapMap Consortium published a haplotype map of the human genome (International HapMap Consortium, 2005). It included more than one million SNPs from 269 DNA samples of four populations. These data document the generality of hotspots, a block-like structure of linkage disequilibrium and low-haplotype diversity, leading to substantial correlations of SNPs with their neighbors, which are adequate for association studies, structural variation, and recombination. Likewise, they enable the identification of loci that may have been subject to natural selection during human evolution. Mapping and sequencing of structural variation from eight human genomes examined up to a few million base pairs. Many new CNVs between individuals and gene complexities provide the first high-resolution sequence map of human structural variation (Kidd et al., 2008). Genetic structure of a uniquely admixed population in South Africa, arising \(\approx\)350 years ago from the European settlement in South Africa, examined 900,000 SNPs showing genetic contributions of Europeans, South Asians, Indonesians, and sub-Saharan Bantu, with future medical promise (Patterson et al., 2010).
In a complete genome analysis of the baker yeast Saccharomyces cerevisiae (including gene content, SNPs, CNV and transposons), Liti et al. (2009) found that phenotypic variation broadly correlates with global genome-wide phylogenetic relationships, and extensive differences exist in genomic and phenotypic variation despite the ecological variation between S. cerevisiae and S. paradoxus. S. cerevisiae consists of geographically defined lineages with many mosaics and cross-breedings associated with human activities. A remarkable ancient, balanced, unlinked gene polymorphism of the galactose (GAL) utilization gene network of Saccharomyces kudriavzevii, a relative of S. cerevisiae, suggests the prevalence in yeasts of multi-locus polymorphisms in nature (Hittinger et al., 2010). Transcription factor polymorphism appears to be a major source of natural phenotypic diversity within yeast species (Gerke et al., 2009). MicroRNAs (miRNAS) posttranscriptional regulators are abundant across life. The designed miRNA SNP panel could identify still hidden links between miRNA and human disease (Muinos-Gimena et al., 2010). Population structure and eigen analysis methodology presents solid statistics for population analysis (Patterson et al., 2006).
Epigenetics, heritable changes causing differential gene expression in cells, tissues, and organisms, unfolds internal and external cues regulating the genetic code beyond DNA nucleotide changes, conferring phenotypic plasticity and complexity. Epigenetic signals affect both soma and germlines in normal and diseased conditions. Epigenomics unifies epigenetics and genomics, i.e., modification at the whole genome level, channeled by a set of chemical modifications not encoded by DNA that determine how and when genes are expressed, hence, are key elements of development and disease. Epigenetic mechanisms, switching genes on or off, or silencing repetitive elements in tissues include the following: chromatin modification, transcription factors, DNA and protein methylation, histone protein modification, nucleosome regulation, polycomb group proteins, noncoding RNA (ncRNA, e.g., small interfering RNAs, siRNA, and microRNAs, miRNA), transcription modulation, translation repression, RNA splicing, RNA stability and translation, all of which contribute to regulation and heritability of epimutations (Tost, 2008; Petronis, 2010). Nonpromoter DNA methylation by Dnmt3a facilitates transcription of neurogenic genes critical for development (Wu et al., 2010).
DNA methylation differs significantly across individual sperm and oocytes, and each sperm cell has a unique methylation profile. The variation in epigenetic marks (epialleles) exceeds that in a DNA sequence (Flanagan et al., 2006), thus contributing substantially to higher genetic diversity in nature. Much in the mystery of epigenomics in gene and protein regulatory networks awaits future elucidation, not least, its heritability patterns. Epigenomics might elucidate the mystery that higher organisms have extraordinary phenotypic complexity despite the limited number of protein coding genes. Interestingly, sessile plants exposed to changing environments and differing from other eukaryotes, particularly in development and metabolism, share their epigenetic machinery of DNA methylation with mammals, though more elaborated, as is also true for small RNAs, and chromatin modifying proteins, which is possibly related to their being exposed to extreme environmental fluctuation and intricate multicellular developmental program (Grant-Downton, 2008).
Environmental factors can have long-term and life-lasting consequences for genome function and adaptation through dynamics epigenome. Transgenerational epigenetic inheritance is transferred through meiosis, and the epigenetic component can collaborate with DNA in phenotypic inheritance. The inheritance of epigenetic markers is under in-depth investigation. Clearly the phenotype is the interaction of genetic, environmental, and epigenetic variables all contributing to phenotypic variation, yet their complex interaction and long-term repercussions await further elucidation and are currently under intensive research, which will expand our horizons on genetic and phenotypic diversity in nature tremendously. Genome-wide evolutionary analysis of eukaryotic DNA methylation was discussed by Zemach et al. (2010). A special issue of Heredity, August 2010, "From genotype to phenotype: what do epigenomics and epigenetics tell us?" (Biemont, 2010) features a selection of review articles that cover epigenetic processes occurring at several different levels and in various organisms.
Theory: natural selection and evolution
Natural selection edits both adaptation and speciation. Darwin (1859) suggested natural selection as the major mechanism of adaptive evolution. The synthesis of Darwinian natural selection with Mendelian inheritance in the 20th century elevated the importance of natural selection as the primary force of adaptive evolution (Templeton, 2009). Advances in genetics enabled the analysis of ecological or developmental traits in testing for natural selection on the trait of interest (e.g., Hoekstra et al., 2006). Moreover, genomic tests of natural selection (e.g., Emerson et al., 2008; Mitchell-Olds et al., 2007) unravel adaptations in whole genomes (Harris, 2008). Ecological functional genomics emerges as a very promising science, linking ecology and genomics, and it certainly will include epigenomics to unveil selective epigenetic regulatory networks.
The Darwinian vision of adaptive evolution may include adaptive nonrandom mutations as Darwin himself emphasized when discussing directed variation in addition to natural selection (chapter IV of the 6th edition of The Origin of Species): "there can also be little doubt that the tendency to vary in the same manner has often been so strong that all the individuals of the same species have been similarly modified without the aid of any form of selection". As Templeton (2009) emphasized, "we are just beginning to embrace again Darwin's broad vision that adaptive evolution involves more than natural selection or random variation... the 21st century will undoubtedly witness a more comprehensive synthesis based on Darwin's enduring legacy".
Types of selection
Theoretically, spatial and temporal variation of selection ("diversifying selection") could maintain genetic polymorphisms. Spatial variation appeared more effective than temporal variation, although combined, they can reinforce the maintenance of polymorphism. Most results related to selection variation in time analyzed the one locus case. However, polymorphism maintenance may be reinforced in the case of two loci or multilocus structures (Nevo, 1999 and references therein) as well as entire genomes (Brodsky et al., 2008a,b; 2009). The selective mechanism is much more efficient if carriers of the alternative alleles are able to select the niche in which their fitness is greatest, e.g., xeric versus mesic in "Evolution Canyon", displayed by Drosophila. Quantification of the selective pressures is now available for genes and genomes (Templeton, 2009), and across Israel where ecological stress drives not only genetic diversity (Nevo and Beiles, 1988) but also sex evolution (Grishkan et al., 2003). Remarkably, genetic polymorphism, recombination frequencies, and mutation rates tend to increase under stressful conditions (Nevo, 2001), as was clearly shown in "Evolution Canyon" (Nevo, 2009). Rates of evolutionary change are enhanced in adverse environments: locally, regionally, and globally (Korol et al., 1994; Nevo et al., 1984a, Parsons, 1996; Weinberg et al., 2001). Evidence for adaptive mutations was reviewed by Metzgar and Wills (2000) and by Galhardo et al. (2007) in describing mutation as a stress response and the regulation of evolvability.
Genomes are plastic and responsive to environmental changes. Environmental stresses induce genomic instability in bacteria, yeast, and human cancer cells generating occasionally fitter mutants and potentially accelerating adaptive evolution. Matic (2010) emphasized that new mutations can range from deleterious through neutral to beneficial. However, when adaptation is limited by the mutation supply rates under stressful conditions, natural selection favors increased mutation rates by acting on allelic variation of the genetic systems that control fidelity of DNA replication and repair. Mutator alleles are carried to high frequency through hitchhiking with the adaptive mutations they generate.
Significant interslope differences for a complex of adaptive fitness stress response traits (genetic, genomic, morphological, physiological, and behavioral) in diverse organisms from bacteria to soil fungi, plants, and animals were reviewed at "Evolution Canyon" (Nevo, 2009). These fitness traits respond to local opposite interslope microclimatic stresses on the tropical "African" (high UV, temperature, and increased drought) and temperate "European" (low UV, cool temperature, lower drought stress, and light restriction for photosynthesis in plants) slopes for tropical or Mediterranean plants and animals.
Dramatic genome-wide divergent interslope adaptive complexes in the annual crucifer Ricotia lunaria transcriptome and methylation regulation on the opposite slopes of EC I to xeric and mesic adaptations were revealed by full genome tiling array hybridizations (Brodsky et al., 2008a,b, 2009; see the binary search approach to whole genome data analysis in Brodsky et al., 2010; Kossover et al., 2009). Several gene categories are specifically upregulated in Ricotia in the stressful EC I "African" slope in contrast to the "European" slope and Arabidopsis: blue light signaling pathway, circadian rhythm, ethylene mediated genes, leaf development, protein amino acid phosphorylation, RNA splicing, and flower development. The shadier "European" slope demonstrates upregulation of chlorophyll-related processes, photosynthesis, and carbon utilization GO processes. The revealed interslope divergence appears to reflect genome-wide xeric and mesic adaptations to the interslope microclimatic stresses mediated by natural selection. Adaptive patterns occur also regionally across Israel and the planet, associated primarily with climatic selection (Nevo, 1998). Adaptive divergence leads to sympatric and allopatric speciation, both locally at "Evolution Canyon" and regionally across Israel, respectively (Nevo, 2009).
The relative importance of evolutionary forces
Evolutionary change in organisms is affected by the interaction of several major forces including mutation (broadly conceived), recombination, inbreeding, migration, natural selection, and genetic drift presently operating on past evolutionary constraints of individuals and higher levels of organization. Natural selection seems to be the predominant evolutionary editor force underlying (directly and indirectly) the twin evolutionary processes of adaptation and speciation (details in Nevo, 1978, 1988, 1998, 2009). Genetic diversity of proteins (allozymes) and DNA (RAPDs, AFLP, SSR, SNP), single genes, multilocus structures, candidate genes, and the entire genome organization and sequencing in natural populations at micro- and macroscales are nonrandom, structured across life on a massive and parallel scale. Genetic diversity of coding and noncoding genomes, including transposons and retrotransposons, is partly correlated and predictable by a combination of a few variables primarily involving climatic ecological factors, solar radiation, temperature, and drought. These patterns strongly implicate natural selection not only at the phenotypic level but also at the genotypic level.
Various forms of selection, primarily through the mechanisms of diversifying, balancing, and directional as well as purifying selection regimes are massively involved, singly or in combination, affecting genetic diversity and divergence of populations at various life-cycle stages of organisms. Other evolutionary forces including mutation, migration, and genetic drift interact with natural selection, either directly or indirectly, but appear secondary in importance in the final processes of adaptation and speciation. Natural selection appears to overrule migration and stochasticity in the dynamic evolution of population genetic structure in diverse taxa across life from bacteria to vertebrates, challenging Wright's (1970) promotion of genetic drift as a major evolutionary factor even in very small populations (Nevo et al., 1997). This conclusion appears also relevant to the neutrality theory of molecular evolution (Kimura, 1983) and the nearly neutral model (Ohta, 1996; Ohta and Gillespie, 1996) and seems relevant to local, regional, and global scales (Nevo, 1998).
Stable equilibria for multiple alleles are best explained by multiple niche selection (Levene 1953; Lewontin et al., 1978). Ecological heterogeneity and stress appear to cultivate genetic polymorphism (Nevo, 1978, 1988, 1998), particularly in contrasting and dynamically cycling environments that can generate complex supercycles (Kirzhner et al., 1996). This supercycle mode of multilocus dynamics far exceeds the potential for maintaining genetic polymorphism attainable under ordinary selection models. It may represent a novel evolutionary mechanism increasing genetic polymorphism over long-term time periods. Models of sexual reproduction (Hamilton et al., 1990), such as an adaptation to resist parasites, may also contribute to sex evolution, recombination, and polymorphisms. Our model (Kirzhner et al., 1999) of genetic interaction between multiple species governed by abiotic and biotic selection for multilocus quantitative traits opens wide horizons for evolution of genetic diversity due to species dynamic interactions in nature.
Genetic diversity: from structural to functional genomics
Explanatory models shift now from structural to functional genomics. Genetic diversity in nature is nonrandom, heavily structured, and correlated with abiotic and biotic ecological diversity and stress. Explorations at the interface of ecology and genomics, combined with critical tests and strong inferences of abiotic and biotic stresses, will highlight the understanding of the maintenance of genetic diversity in nature. Experimentation could include transplant experiments, particularly at microscales, to unravel genome organization, function, and fitness in contrasting stressful and changing environments. Molecular ecology now has modern tools with increasingly diverse genetic markers and sequence potentials using next-generation sequence technologies at the population level (Schuster, 2008; Brodsky et al., 2008a,b, 2009). Reassuringly, DNA polymorphisms mirror protein (isozyme) polymorphisms and can highlight genome structure and evolution caused by environmental stress as indicated by wide-genome gene expression (Miyazaki et al., 2003) and tiling arrays of both coding and noncoding parts of genomes of the crucifers Ricotia and Arabidopsis (Brodsky et al., 2008a,b, 2009; Kossover et al., 2009).
Selection overrules gene flow
Strong selection overrules gene flow at "Evolution Canyon" (EC) across life (bacteria, soil fungi, flowering plants, Drosophila, and Acomys rodents), operating against the ongoing homogenizing effect of migration, which proceeds in parallel in diverse taxa across life (Nevo, 2009, 2010). This pattern at "Evolution Canyon" demonstrates how natural selection is the major evolutionary driving force of adaptation and speciation across life locally, as well as possibly regionally and globally (Nevo, 2010). The fact that selection overrules gene flow at "Evolution Canyon" is the main reason for the incipient sympatric speciation across life from bacteria to mammals at this unique microsite.
What's next? The major focus in studying genetic diversity in nature should be on population functional ecological genomics across life coupled with proteomics, metabolomics, and phenomics. A major future perspective should try to analyze the effects of stresses not only through individual genes but through genomic-biochemical networks related to individual and collective environmental stresses (solar radiation, temperature, global warming, drought, mineral and photosynthetic deprivations, biotic stresses, etc). Epigenomics should be coupled with genomics, including DNA methylation, histone modification, and the regulatory effects of small RNA, and noncoding repeat elements, including transposon and retrotransposon dynamics in both adaptation and speciation to evaluate genome-wide adaptive divergence (Andolfatto, 2005; Biemont and Vieria, 2006; Eyre-Walker, 2006; Parsons, 2005). Comparisons should be made between local, regional, and global "genetic laboratories" and the study of genomic diversity and divergence across life. The next-generation technologies will open dramatic new horizons for the study of genetic diversity in nature, unraveling its nature and dynamics at micro- and macroscales. These future studies will highlight theoretical mysteries of evolutionary biology as to the genetic diversity in nature and the evolutionary driving forces shaping its fate in adaptation and speciation.
Glossary of genetic molecular markers
- AFLP: Amplified Fragment Length Polymorphism. A sensitive method for detecting DNA polymorphism. Because one can screen many loci simultaneously, AFLP can be useful for detecting phylogenetic signals in poorly differentiated taxa. Because it is a dominant marker (vs. codominant), analysis requires some assumptions about heterozygote frequencies.
- Isozymes: Enzyme variants with the same functional role, but differing in 1°, 2°, 3° or 4° structure. In some cases, isozymes may be multimers produced by multiple genes. They may, therefore, not qualify as codominant allozymes for use as genetic markers.
- RAPD: Randomly Amplified Polymorphic DNA. A genetic marker technique using PCR amplification from short (= 10 bp) segments of arbitrary sequences to look for polymorphisms. Quick (no development time for primers!), but can be problematic in terms of interpretability within the framework of population genetics theory.
- RFLP: Restriction Fragment Length Polymorphism. A genetic marker technique using variants in the DNA exposed by cutting with restriction enzymes. Variants are visualized by running through electrophoretic gels.
- RGAP: Resistance gene analog polymorphisms. This technique is advantageous because of the numerous fragments amplified by RGAP primers, as there were numerous genes for resistance to a large number of pathogens in plant species
- SNP: Single nucleotide polymorphism. In genome sequencing projects, attention is now often focusing on detection of single base-pair changes in the DNA sequence.
- SSR: Microsatellites: Short tandem repeats of nucleotide. The apparent mutation process is by slippage replication errors, where the repeats allow matching via excision or addition of repeats. Because this sort of slippage replication is more likely than point mutations, microsatellite loci tend to be hypervariable.
- STR: Short tandem repeat.
- VNTR: Variable number tandem repeat. Segments of repeated DNA. Short base unit repeats (2-6 base pairs) are microsatellites, longer repeats (100s of bp) are minisatellites. The short length of the microsatellites (\(\leq\)300 bp) allows one to amplify the DNA with the PCR and is a key factor making microsatellites preferable to minisatellites (which require radioactively labeled probes).
See details of molecular markers, and references therein, in Wikipedia: Molecular Marker Glossary, David McDonald, Fall 2008.
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- Molecular Marker Glossary