Genetics of Climate Change Adaptation
- 1. Doctoral Seminar II (FGR-692) Speaker: Shikha Thakur F-13-16-D
- 3. • Climate change: changes in global climatic conditions, e.g., temperature, precipitation, and frequency of extreme events such as storms and droughts • Adaptive evolution: evolution via natural selection in which individuals with phenotypes of higher fitness pass on more genes to the next generation
- 5. Global temperatures and patterns of precipitation - rapidly changing Ecological effects Genetic effects Climate change
- 6. Ecological effects of climate change Climate change Physiology Behavior Abundance Distribution
- 7. Genetic effects of climate change (genetically based adaptive evolution in traits) Climate change Body size Thermal responses Dispersal Diapause or Reproductive timing
- 9. Many - independently acting genes of small effect alternative and rapid mode Fewer - key regulatory genes within genetic and metabolic networks Epigenetic changes Selection Evolution Evolution Climate change alternative and rapid mode (Turner BM. 2009)
- 10. Evolution rescue populations from the effects of climate change no evidence commonly occur avoid a mass extinction and loss of genetic biodiversity. • In fact, a recent meta-analysis predicted major losses in genetic diversity for northern plants owing to climate change (Alsos IG, et al. 2012).
- 13. SELECTION TO EXPLOIT CONDITIONS OR TOLERATE STRESSES • A general framework on depicting how organisms may evolve in response to various changes in climate (Figure 1) • In this framework, changes in climatic conditions, such as temperature, are separated from cues that indicate conditions such as photoperiod. • Organisms perceive the changes in conditions by 2 ways: through matching cues to new conditions directly
- 15. Climatic changes as agents of selection Organisms evolve in response to climatic changes in one of two general ways: • evolving to take advantage of the new conditions- by exploiting novel or increased resources (Figure 1a) • or evolving to tolerate new conditions - to which the population is not currently optimally adapted (Figure 1b).
- 16. Evolving to exploit expanding their range expanding the period across which they are active at higher latitudes into high elevation areas Changes in season length migration and breeding patterns of speciesselection for increased dispersal Evolving to tolerate temperature extremes ocean acidification extreme events influence species distributions
- 17. • Extreme conditions can select for increased resistance to stressful conditions and/or ways of avoiding extremes, such as earlier flowering. (Franks SJ, Sim S and Weis AE. 2007) • increased resistance to drought or heat stress • An increase in the frequency of extreme climatic events such as droughts could select for either escape or tolerance strategies (Franks SJ. 2011). • These responses reflect the direct effects of climate change. These include • Altered selection pressures when climate change affects biotic interactions, • triggering adaptive changes in competitive ability or parasite/predator resistance, • adaptive changes in host shifts, allowing organisms to evade biotic stresses (Pelini SL, et al. 2010). Direct
- 18. Indirect • by altering patterns of hybridization as a consequence of shifts in species distributions, with important genetic consequences. • when a reduction in food supply is countered by switching to another food source, as in Darwin’s finches.
- 19. Evolutionary changes to exploit or tolerate a resource behavioral traits (migration) life-history traits (diapause) physiological traits (water-use efficiency) (Franks SJ. 2011)
- 20. • Responding to altered seasonality, populations may also respond to increases in CO2 and regional increases in precipitation when adapting to favorable effects of climate change. • For example, (Ward JK, et al. 2000). Arabidopsis thaliana plants raised for five generations under CO2 concentrations of 700 ppm evolved to take advantage of this increased resource showed higher seed production than control lines
- 21. Perhaps the simplest way that climate change can influence the genetic constitution of populations is shown in Figure 2a. Figure 2a
- 22. (Figure 2b) Response to Climate Change Plasticity Phenotypic plasticity no genetic change in the population same genotypes expressing different phenotypes in different environments Genotypic plasticity alleles leading to increased plasticity favored Organisms better match in more variable environment. Evolution Changes in allele frequencies allelic changes do not act in isolation but need to be considered within a gene network and within the context of environmental effects and the complex way that genotypes map onto phenotypes
- 24. (Reusch TBH and Wood TE. 2007) More and more genomes sequencing and annotation various studies indicating numerous connections between genes and traits a large gap in identifying the genetic basis of adaptive evolutionary shifts to different climatic conditions Experimental approaches and Genetic techniques those applicable to natural populations those applicable to experimental populations
- 27. Source material Description Advantage Limitation Reference Clinal comparison Comparisons of populations from along clines Possible to collect data immediately, takes advantage of past evolution and local adaptation Not always possible to determine if patterns reflect climate change or other factors Stinchcombe JR, et al. 2004. Natural evolution Comparisons based on changes in natural populations across time The only source material in which populations have actually adapted in contemporary time to changes in climate Often difficult to find natural examples of rapid evolution Franks SJ and Weis AE. 2008. Genome scan of Populations Population comparisons involving a large number of markers to determine which markers are more differentiated than expected from neutrality Relatively easy to apply, can use a number of different types of markers, allows a direct comparison between effects of selection and population processes Differentiated marker may be distant from marker under selection depending on linkage disequilibrium Prunier J, Laroche J, Beaulieu J and Bosquet J. 2011. DNA sequence comparison of Natural populations DNA hybridization on microarrays or other techniques to identify highly diverged areas of the genome, often involving cline ends Provides an unbiased assessment of parts of the genome involved in adaptive divergence (within the technical limits of the approach used) Can be difficult to link to adaptive phenotypic variation; differences may also be related to historical processes Turner TL, Levine MT, Eckert ML and Begun DJ. 2008. Known genetic polymorphisms Follow polymorphisms connected to climate adaptation across time Can indicate changes in polymorphisms with known adaptive functions Polymorphisms considered may only have minor effects on traits; ignores most of genome Umina PA, et al. 2005. Known morphological polymorphisms Follow changes in phenotypic morphs with a known genetic basis across time Morphs are often easily related to adaptive functions, as in the case of changes in pigmentation Only applicable to a specific class of polymorphisms Karell P, et al.. 2011.
- 29. Source material Description Advantage Limitation Reference Artificial selection and Experimental evolution Traits related to climate change adaptation selected directly (artificial selections), or populations are placed in environments simulating climate change effects (experimental evolution) Traits can be accurately defined, selection pressures set, and crosses and Sequence comparisons used to assess the genetic basis of selection reflecting natural environments; can assess potential rates of adaptation Limited by base population for selection, may not reflect intermittent selection and tradeoffs, depends on species with short generation time Bell G and Gonzalez A. 2009. Candidate gene comparisons Sets of genes that are candidates for adaptive divergence considered along gradients based on known polymorphisms or DNA sequencing Provides a direct link to particular genes and polymorphisms; effects on traits can be confirmed through functional analysis Can be difficult to isolate the critical polymorphisms, particularly if they are in promoter regions or if regulatory elements are involved; approach will miss many important genes not characterized Lee SF, et al. 2011. Transcriptome comparisons Gene expression microarrays (can also be used for some targeted genes) Identifies genes and gene networks that are differentiated between populations and cline ends for further adaptive studies Ignores adaptive responses that have no effect on gene expression Healy TM, Tymchuk WE, Osborne and EJ, Schulte PM. 2010.
- 30. Source material Description Advantage Limitation Reference Quantitative trait locus mapping Strains are made genetically homozygous and compared for quantitative traits The same set of strains can be scored for multiple traits, including correlated responses, sequenced strains can be used for a variety of purposes, covers whole Genome Strains are typically inbred to make them homozygous before sequencing, which means that mapping may partly relate to effects of inbreeding depression; adaptive changes may have a different genetic basis, particularly if evolution acts as a filtering mechanism; difficult for species with long generation times Morgan TJ, and Mackay TFC. 2006. Association mapping Genetic markers are compared with quantitative trait associated with climate change adaptation Undertaken in outbredpopulations, does not depend on short generation times, covers whole genome Most signals obtained when multiple markers available; can be biased towards detecting genes of large effect; proximity to genetic polymorphisms affecting trait depend on marker density Brachi B, et al. 2010.
- 31. Clinal comparison • Comparing populations naturally occurring under different conditions, including clines, is a classic technique of ecological genetics (Conner JK and Hartl DL. 2004). • If gene flow among populations is limited populations may become locally adapted to the climatic conditions experienced. • Experiments, such as reciprocal transplants, used to determine the extent of local adaptation can also be applied to help predict evolutionary responses to climate change. For example, Etterson & Shaw (Etterson JR and Shaw RG. 2001) found local adaptation but evolutionary constraints caused by genetic correlations in an annual plant occurring in different climatic regions of the midwestern United States.
- 32. Natural evolution There is now however, an ongoing effort to build a collection of seeds that will make it possible to apply the resurrection approach to detect evolution in a variety of plant species (Pennisi E. 2011). With this approach, ancestors and descendants can be compared to help elucidate the genetic basis of evolutionary change in natural populations. Before After propagules compare ancestors and descendants reared under common conditions
- 33. sets of source material genomic and transcriptomic techniques genetic basis of evolutionary change from artificial selection or evolution experiments from natural populations over space or time
- 35. QTL mapping and Association mapping • Standard approaches to determine the genetic basis of variation in a trait 1. Quantitative trait locus (QTL) mapping 2. Association mapping QTL mapping • requires the use of recombinant inbred lines • can only map traits to a coarse scale • requires fewer individuals than association mapping. Association mapping • does not depend on the development of inbred lines • can locate genes more precisely • requires more individuals Both find a gene’s underlying trait variation but neither is designed to examine evolution directly. (Zhu C, Gore M, Buckler ES and Yu J. 2008)
- 36. Identifying the genetic basis of evolution following climate change • Sets of source material from populations – compared at 3 levels : whole genome, the transcriptome, individual candidate genes Genome scans • By using genome scans (genotyping with many single nucleotide polymorphisms (SNPs) or other markers), many genes throughout the genome can be assessed for variation and compared among populations
- 37. Scanning the genome for gene SNPs related to climate adaptation and estimating selection at the molecular level in boreal black spruce. For example, • Prunier et al. (Prunier J, Laroche J, Beaulieu J and Bosquet J. 2011) used genome scans of black spruce (Picea mariana) from populations varying in temperature and precipitation to identify SNPs. Genes that had outlier FST values were located in exons, had nonsynonymous polymorphisms, showed significant regression with climatic variables, had functional annotation consistent with climatic responses, were considered prime candidates for adaptation to climatic variation, and could potentially show responses to climate change.
- 38. Transcriptome level • Study of transcribed genes or on the full transcriptome- possible to narrow the set of genes of interest to those actually expressed – also help to evaluate differences in levels of expression under different conditions. extracting mRNA and measuring expression level. Techniques followed are: Quantitative real-time PCR = small number of genes, microarrays = large number of genes, massively parallel sequencing of expressed genes (RNA-seq) = whole genome. Analysis of transcribed genes involves:
- 39. Advantages of examining gene expression in a climate change adaptation Different source material originating under different conditions can be compared The climatic factor can be experimentally manipulated and expression measured under the different treatments. For example, • Individuals could be collected from a warmer and a cooler area along a thermal cline • Gene expression measured at both warm and cool temperatures. • Genes that differed in expression between the source populations and between warm and cool temperature treatments might be particularly likely to play a role in thermal adaptation and evolution following changes in temperature.
- 40. Candidate genes • Approaches to isolate candidate genes: Genome scans Transcriptome scans • Genome screens are starting to be employed to identify areas of the genome connected to climate adaptation. Several screens of plant populations from different climates are starting to produce sets of candidate genes for climatic adaptation. Example of Boreal Black Spruce • In boreal black spruce (Picea mariana), a survey of more than 500 SNPs in genes potentially related to precipitation and thermal variability across 26 populations led to the eventual isolation of 26 SNPs in 25 genes that showed a strong association with the climate variables. • These genes have a variety of putative functions, including phenology, growth, reproduction, wood formation, and stress response, many of which make sense in a climate change adaptation context. (Prunier J, Laroche J, Beaulieu J and Bosquet J. 2011) Genome scans
- 41. Case study on A. thaliana • A broad genome screen of SNPs and a geographically diverse set of almost 1,000 accessions of A. thaliana across environmental variables produced numerous candidate genes potentially involved in climatic adaptation (43). • Signals of adaptive shifts were tested further by an enrichment of functional nonsynonymous changes and by growing plants in a common environment and then testing whether counts of putative adaptive alleles could predict fitness in this environment. • This analysis showed a strong correlation between fitness in the common environment and the number of favored alleles, confirming the validity of the initial screen. • In a different set of experiments with Arabidopsis, plants from multiple inbred lines were grown in four sites differing in climate, and SNPs at each location were associated with survival and reproductive output (32); • SNPs with substantial effects were identified, and these proved to be locally abundant at two of the sites.
- 42. • The absence of strong selective sweeps suggested that local alleles were favored via selection on standing variation rather than through sweeps. • Alleles affecting reproductive output were locally common (locally selected), and those affecting survival were more common across the species range, suggesting survival alleles were widely favored at multiple sites. • Several candidate loci involved in adaptation to different temperature and precipitation regimes were identified for future study. Use of single or multiple populations • Transcriptomic comparisons - usually involved a single population exposed to different climatic conditions - to identify genes and gene ontogeny classes - tend to be differentially expressed - may point to candidates. • Gene discovery from these efforts - challenging given the sheer number of genes that typically show altered expression patterns that may be indirectly related to the traits of interest (129). Transcriptome scans
- 43. • Recently, moved to consider multiple natural/ selected populations or lines - when reared under the same conditions and challenged by - the same sets of stressful conditions. • By linking changes in expression across multiple populations to environmentally induced changes in expression - it is more likely that candidate loci for adaptive responses can be identified - particularly when multiple stresses are considered. • Nevertheless, linking gene expression patterns across populations or lines with adaptive changes is not straightforward.
- 44. Challenge in transcriptomic studies of candidate genes • To move beyond simply describing patterns of up- and downregulation of genes - which can depend on background levels (113). • This can be achieved by linking patterns to those evident from other ‘omics technologies, particularly metabolomics (129), and interpreting changes within a network context. • Once networks are known on the basis of studies of environmental responses, gene knockouts, and other approaches - researchers can begin considering the effects of genetic variants at different phenotypic levels.
- 45. Genome-wide mapping efforts • Apart from genome and transcriptome scans - some very large genome-wide mapping efforts are starting. • These efforts provide a detailed picture of the genes - associated with changes in traits - responding to environmental cues. • In A. thaliana, an assessment of genome-wide diversity across more than 400 accessions planted in different climates and seasons led to the identification of 12 QTLs that affect flowering time in a season-location specific manner (73).
- 46. • To summarize, a number of approaches are now available to isolate candidate genes involved in climate adaptation across model and nonmodel species. Genome scans and transcriptomic studies are starting to produce long candidate lists. However, moving from lists to validated candidates remains challenging and requires studies of model organisms in which genetic manipulations are possible.
- 47. • Changes in genetic networks may play a large role in contemporary evolution and climate change responses. • Traits important in climate change responses, such as the timing of flowering (133) or stress responses (129)- controlled by genetic regulatory networks. • These networks involve: multiple genes and gene products, transcription factors, and proteins that interact with each other and with signals from the internal and external environment to produce a phenotype suited to given conditions (136). • Changes in specific genes within genetic networks influence the expression of genes, and changes within biochemical pathways ultimately dictate how genetic changes influence phenotypes.
- 48. Moreover, alternative splicing, in which RNA transcripts are arranged in multiple ways so that a single gene can code for multiple proteins (Brett D, et al. 2002), can influence the tissue expression of heat shock genes such as Hsr omega from D. melanogaster, which influences the repression of protein synthesis (Johnson TK, Cockerell FE and McKechnie SW. 2011). changes in genes phenotypic effects Simple connection Hsp70 genes Increased amount of Hsp70 protection from denaturation during heat stress and influence survival in a range of organisms genetic regulatory network interacting transcriptional factors Influence the expression Bind to promoter region (Ostling P, et al. 2007)
- 49. Key mechanisms of evolutionary responses to climate change • Most adaptive changes in response to climate change occur within a regulatory network of genetic effects • Processes such as: alternative splicing and the binding of transcription factors posttranscriptional regulatory mechanisms the expression and interaction of other elements. • There is now a much greater appreciation of the different levels of gene and metabolite regulation that mediate stress responses (116). • It is no longer considered particularly useful to split genetic variation into simple structural and regulatory categories.
- 50. Genetic variation - structural and regulatory categories • Changes in structural components of genes can affect expression • Regulatory elements now encompass a range of processes, including: cisacting control elements, transcription factors, and metabolites, posttranscriptional modification control of DNA through methylation (61, 129). • Some of these networks and interactions are quite well understood and can be linked to specific genetic variants. • For instance, the pathway controlling flowering time and vernalization in plants involves the integration of a number of pathways associated with different environmental cues. (Wilczek AM, et al. 2010).
- 52. EPIGENETICS: AN ALTERNATIVE MODE OF CLIMATE CHANGE ADAPTATION • It is now well established that the environment can influence gene expression, and thus phenotype, through epigenetic mechanisms. • In the contemporary sense, epigenetics refers to any inherited changes in the phenotype of an organism that are not directly due to variation in gene sequence. • Epigenetic mechanisms: the methylation of cytosine, modification of chromatin structure, the alterations in gene regulation due to small RNAs. (Bossdorf O, Richards CL and Pigliucci M. 2008)
- 54. An overview of interacting networks through which environmentally induced changes in gene expression influence cell behaviour and potential
- 56. Metabolic and environmental influences on histone- modifying enzymes
- 57. Environmental agent triggering a change in DNA sequence
- 58. Environmental agent triggering a change in DNA sequence
- 59. • To uncover the genetic basis of an adaptive evolutionary change in a quantitative trait to a change in climate, I would ideally like to be able to show that a particular trait: (a) is genetically based and heritable; (b) is under differential selection and has different fitness under different climatic conditions (changes in climate alter the pattern of selection); (c) varies geographically along latitudinal, altitudinal, or other gradients in a way consistent with climatic variation; and (d ) has changed in mean value in a population following natural or experimental changes in climate. • We should : (e) identify genes and networks underlying variation in the trait and ( f ) show that allele frequencies of one or more of these genes have changed within a population following a change in climate.
- 60. • All six of these criteria have not yet been met within a single study or system, although some studies mentioned above have shown one or more of these components. • Researchers provide two examples of traits— flowering time and body size— that have often been linked to climate change adaptation. • In the case of flowering time, researchers are close to meeting many of the criteria, • whereas with body size they are only just starting to reach a very preliminary level of understanding.
- 61. Flowering Time • Flowering time - important trait in plants and highly relevant for genetic adaptation to climate change. • Climatic conditions have a strong effect on reproductive phenology and the relationship between flowering time and fitness (101). • Previous studies have shown that flowering time meets several of the criteria to demonstrate the genetic basis of an evolutionary response to climate change. • One study (35) found that in the annual plant Brassica rapa, flowering time was heritable, early flowering plants had greater fitness under drought conditions than late flowering plants, and average flowering time was earlier in plants following a natural drought than in plants from before the drought when ancestors and descendants were grown together under common conditions. • In many other species flowering time is heritable (47), is under selection (52), and has shifted following changes in climate (85).
- 62. Case study 1: Rapid evolution of flowering time by an annual plant in response to a climate fluctuation (Franks et al., 2007) • Examined the evolutionary response of FT in field mustard, Brassica rapa L. (Brassicaceae), during a regional climate anomaly. We define FT as the number of days for a plant to go from germination to production of its first flower. • Experimental approach followed: This approach compares phenotypic and fitness values of ancestral, descendant and ancestral x descendant hybrid genotypes grown simultaneously under conditions that mimic the pre- and post-change environments. • Advantages: Ancestors and descendants are reared together under the same controlled conditions so that phenotypic differences between ancestors and descendants can be partitioned into components due to genetic change and due to phenotypic plasticity. By simulating pre- and post-change conditions and measuring fitness in both environments, it is possible to determine whether the descendant genotypes are better adapted to novel conditions, or, conversely, that they have lost adaptation to past conditions. The construction of hybrid lines provides information on the genetic basis and architecture of trait changes, allowing phenotypic shifts to be partitioned into additive versus dominant gene effects.
- 63. • In southern California the growing season for B. rapa is normally terminated in late spring by the end of the rainy season. Winter rainfall data for an 11-year period at our study site indicate a switch from above average to below average precipitation (Fig. 1), leading to abbreviated growing seasons from 2000 to 2004. • The series of dry years from 2000 to 2004 represents an extreme drought event. • Life history theory predicts that the optimal FT in annual plants will be shorter with shorter growing seasons (20, 21). This led to the prediction that the abbreviated growing seasons imposed by the extended drought would lead to the evolution of earlier FT in B. rapa.
- 64. 1997 Before drought 2004 After drought Dry Site Wet Site San Joaquin Freshwater Marsh Reserve Newport Harbor sandy, fast drying soils Soils retaining moisture Materials and Methods Study System
- 65. Phase I: Amelioration of Environmental Effect • Produced F1 plants by planting field-collected seeds in the greenhouse at the University of California, Irvine. • The resulting plants were assigned to 1997 X 1997, 1997 X 2004, and 2004 X 2004 crossing groups within each population. • Germination rates of the F1 plants were 94% for all groups and did not differ by generation for either the Dry Site or the Wet Site. • The creation of the F1 lines thus appears to have reduced differences in seed quality between the collection years. Phase II, Experiment I: FT Evolution • F1 seeds were stratified at 4°C on moist filter paper for 5 days and planted into 25- cm pots containing equal volumes of sand and potting medium in the greenhouse at the University of California, Irvine. • Six plants were grown in each pot: one each from the ancestor, descendant, and hybrid generations from both populations. Pots were watered daily to saturation for 33 days. Water was withheld starting on day 33 for the short season, day 51 for the medium season, and day 81 for the long season treatments. • Germination and flowering dates were recorded daily, and seed pods were collected when ripe. All flowers of all plants were pollinated by hand every 3 days.
- 66. Phase II, Experiment II: Heritability • Heritability for the ancestral generation was estimated by regressing family mean FT of the offspring in Phase II over the mid-parent FT in Phase I. Statistical Analysis • Used failure-time analysis, also known as survival analysis, to test for genetic differences in FT among the ancestral, descendant, and hybrid generations.
- 67. Results ( Descendant genotypes had earlier FT than ancestral genotypes, showing a shift to earlier flowering onset after the drought)
- 68. • Failure-time analysis showed significantly earlier FT for descendants than ancestors across all treatments in both populations. • Under long season treatments (where near-zero mortality allows expression of the full range of FT genes present) mean FT advanced by 1.9 days in the Dry Site population and by 8.5 days in the Wet Site population. • The mean FT of the hybrids did not differ significantly from the mid-point between ancestors and descendants which indicates an additive genetic basis for the observed change. • In addition, FT was earlier for Dry Site than for Wet Site genotypes.
- 69. To determine whether descendants were better adapted than ancestors to abbreviated growing seasons, examined survival and fecundity • Survival was nearly 100% in the long season treatment for all lines. • Under the drought-mimicking short season treatment, survival was 90% for the Dry Site population but only 62% for the Wet Site population. • Trends for fecundity were similar but were not statistically significant. Thus, the post-drought genotypes appear better adapted to short seasons than the pre- drought genotypes.
- 70. Conclusion of case study • Our results provide evidence for a rapid, adaptive evolutionary shift in flowering phenology after a climatic fluctuation. • The shift to earlier FT in B. rapa after only a few generations adds to growing evidence that evolution is not always a slow, gradual process but can occur on contemporary time scales in natural populations. • Results indicate that B. rapa adapted to this climate anomaly by an escape strategy of earlier FT. • Dry Site genotypes are better adapted to faster-drying soils than Wet Site genotypes, which supports the hypothesis of local adaptation.
- 71. Case study 2 & 3: Flowering time In Arabidopsis • One feature of flowering time that makes it ideal for a study of the genetic basis of evolution under climate change is that a substantial amount of information already is known about genes, pathways, and processes involved in determining flowering time. • In Arabidopsis, flowering time is controlled by a genetic regulator network involving four main pathways: photoperiod, temperature, gibberellin, and autonomous. • Internal (hormones such as gibberellins) and • External (photoperiod, temperature) • Both signals influence these pathways in a way that prevents a plant from flowering too early or too late.
- 73. • Although this regulatory network is quite complex; includes hundreds of genes, transcription factors, and receptor proteins; and involves variation in gene expression as well as epigenetic regulation; only a relatively small number of genes appear to vary in the wild and to influence the flowering time phenotype in natural populations. • These are thus prime candidate genes for examining the genetic basis of flowering time variation and evolution across taxa in natural conditions.
- 74. Diversity of Flowering Responses in Wild Arabidopsis thaliana Strains (Lempe J, et al., 2005) Materials and Methods • Stocks- Accessions were obtained from the Nottingham Arabidopsis Stock Centre (http://www.arabidopsis.info) • Growth conditions- Plants were grown in controlled growth rooms with a temperature variability of about plus or minus 0.10C. Long days had 16 h of light, short days had 8 h. • Maximal humidity was 65%. Light, temperature, and humidity were continuously monitored online. • Plant culture- Seeds were stratified at 4 0C for 7 d (to minimize variation due to differences in stratification requirements) in 0.1% agarose, then planted on soil. Before vernalization, seed germination was induced at 160C for 24 h. Plants were cultivated for 5 wk at 4 0C in a vernalization room with 8 h light of about 50 lmol m2 s1, before transfer to normal growth rooms. • Experimental design- Twelve seeds per genotype were sown in a completely randomized design
- 75. • Scoring of traits- The following traits were scored: DTF, TLN, juvenile leaf number (JLN), adult leaf number (ALN), cauline leaf number (CLN), and rosette leaf number (RLN). Flowering was scored on a daily basis for first macroscopic appearance of the inflorescence. DTF was calculated from the date of sowing. For vernalized plants, the vernalization period was subtracted. • Statistical analyses- Broad-sense heritability (H2) The coefficient of genetic variation (CVG) Genetic correlations (rGE) Genotype-by-environment interactions Hierarchical cluster analysis was performed with Cluster 3.0 Noncentric, average linkage (UPGMA) clustering was then performed using Pearson correlation. • DNA analyses- using the CTAB method. • Expression studies- RNA was extracted using Trizol, and 1 lg of total RNA was reverse transcribed using a Reverse Transcription kit. Microarray data were generated. RNA isolated from the aerial parts of 4-d-old seedlings was hybridized to Affymetrix ATH1 arrays.
- 76. Results/Discussion • Extensive Variation in Flowering Responses of A. thaliana Accessions • We measured several traits, including days to flowering (DTF) and total leaf number (TLN), which were highly correlated under different conditions (r2 ¼ 0.6 to 0.9), with environment-dependent variation in growth rate found in only a few accessions.Heritability of TLN was higher than that of DTF. • We studied the effects of vernalization, ambient growth temperature, and photoperiod, using four different environments: 23 8C long days (23LD), 16 8C long days (16LD), 16 8C long days after 5 wk vernalization (16LDV), and 23 8C short days (23SD).
- 78. The Contribution of FLC Activity to Flowering-Time Variation • To evaluate more precisely the relationship between absolute FLC levels and quantitative variation in flowering time, we analyzed FLC expression by qRT-PCR in 149 accessions grown at 23LD (Figure 4A). • We found that, among a set of 68 floral regulators, FLC was the one most highly associated with either TLN or DTF (Figure 4B). • When we considered all genes represented on the ATH1 array, we found FLC to be among the ten most highly correlated genes at 23LD (both positively and negatively correlated) (Figure 4C).
- 79. • The prominence of FLC, whose levels are highly correlated with vernalization response, may reflect the fact that this response is the most important variable affecting flowering time in A. thaliana accessions. A first step toward identifying the genetic mechanisms underlying the newly identified flowering behaviors • They examined F2 populations from crosses of Ei-6 and Fr-2, two strains that flower relatively early in 23SD, to the reference strain Col-0. In both cases, the earliness appeared to be recessive compared to Col-0 (Figure 7A). • When they crossed Ei-6 and Fr-2 to each other, the F1 hybrids were later than either parent, indicating that earliness in short days has a different genetic basis in these strains (Figure 7A). • The F2 progeny from a cross of Fr-2 to Col-0 included a distinct early class, suggesting that early flowering is due to variation at a major locus (Figure 7B). • In contrast, in the Ei-6 3 Col-0 cross, continuous variation can be seen, indicating the involvement of multiple loci (Figure 7C).
- 81. Conclusion • Much of the difference in vernalization response is apparently due to variation at two epistatically acting loci, FRI and FLC. • We present the response of over 150 wild accessions to three different environmental variables. • In long days, FLC is among those genes whose expression is most highly correlated with flowering. • In short days, FRI and FLC are less important, although their contribution is still significant. • In addition, there is considerable variation not only in vernalization response, but also in the response to differences in day length or ambient growth temperature. • The identification of accessions that flower relatively early or late in specific environments suggests that many of the flowering-time pathways identified by mutagenesis, such as those that respond to day length, contribute to flowering- time variation in the wild. • In contrast to differences in vernalization requirement, which are mainly mediated by FRI and FLC, it seems that variation in these other pathways is due to allelic effects at several different loci.
- 82. Flowering time regulation produces much fruit (Scott D Michaels, 2008) • A mobile flower-promoting signal, termed florigen, is produced in the leaves in response to inductive photoperiods and travels to the shoot apical meristem to induce flowering. • With regard to vernalization, one of the most interesting properties is that cold-treated plants retain a relatively permanent memory of vernalization. • Arabidopsis flowers more rapidly under long days than under short days. The ability to distinguish long days from short days is largely the result of the complex regulation of the B-box containing gene CONSTANS (CO). CO acts as a floral promoter and is regulated at both the mRNA and protein levels (Figure 1). CONSTANS is a critical component in the regulation of flowering by daylength
- 83. FLOWERING LOCUS C is the primary target of vernalization • The vernalization responsive block to flowering is created by the interaction of two genes: FLOWERING LOCUS C (FLC), a MADS-domain-containing transcription factor that acts as a floral repressor and FRIGIDA (FRI), a gene of unknown biochemical function that is required for high levels of FLC expression. • the upregulation of FLC by FRI requires the activity of chromatin remodeling complexes similar to the RNA Polymerase II Associated Factor 1 (PAF1) and SWR1 complexes from yeast
- 84. Negative regulation of FLC by the autonomous floral- promotion pathway • Naturally occurring loss-of-function mutations in FRI and therefore have low levels of FLC expression and are early flowering. • Genetic screens in rapid cycling backgrounds have identified a group of genes that act to constitutively repress FLC. These genes are collectively referred to as the ‘autonomous’ floral-promotion pathway. • Autonomous-pathway mutants contain elevated levels of FLC and are late- flowering; like winter annuals however, FLC can be epigenetically silenced by vernalization.
- 85. Integration of flowering signals from the photoperiod and vernalization pathways • In rapid-cycling Arabidopsis, or winter annuals following vernalization, FLC levels are low. It should be noted, however, that full expression of the floral integrators requires not only elimination of the repression by FLC, but also activation by long days through CO. Unlike FLC, CO has not been demonstrated to bind the floral integrators directly. • A current model for the biochemical activity of CO is that it acts as part of a Heme Activator Protein (HAP)-like complex. • In yeast, the HAP complex binds DNA and is composed of HAP2, HAP3, and HAP5 subunits. CO contains domains that exhibit similarity to HAP2, suggesting that CO might replace HAP2 in a HAP complex. • This model is supported by the findings that CO interacts with HAP3 and HAP5 in yeast and in plants, and that alteration of HAP expression levels affects flowering time.
- 86. Spatial considerations • Photoperiodic induction leads to the production of a mobile signal, CO and FT expression occurs in the phloem of leaves. • FT produced in leaves is translocated to the meristem. • At the meristem, FT physically interacts with bZIP transcription factor FD and the FT/FD complex activates the expression of SOC1 and the floral meristem identity gene APETALA1 (AP1).
- 88. Conclusion of all case studies on flowering time • It is therefore known that at least in some cases flowering time is heritable, is under selection by climatic factors, varies across climatic clines, and can evolve following changes in climatic conditions. • Additionally, candidate genes have been identified that are linked to variation in flowering time as well as to climatic conditions, and the function of many of these genes is known. • Further work on flowering time is likely to provide more information on the genetic basis of adaptive evolutionary responses to climate change.
- 89. 1. Climate change is occurring, affecting many organisms, and, at least in some cases, leading to evolutionary change that results in changed gene and allele frequencies in populations. 2. Studying evolutionary responses to climate change can help us to uncover the genetic basis of adaptive evolution. 3. Methods of studying the genetic basis of climate change adaptation involve a choice of source material (e.g., sampling along latitudinal or altitudinal gradients and before and after a natural or artificial environmental change) as well as a variety of possible genetic techniques (e.g., genome scans, transcriptome comparisons, candidate gene comparisons, and genetic mapping). 4. Substantial progress has been made recently in uncovering genes linked to traits of adaptive significance and genes associated with climatic variation. However, much less is known about genetic changes occurring as a result of climate change. 5. Body size in animals and flowering time in plants are two examples of areas in which further research into the genetic basis of climate change adaptation seems particularly promising.
- 90. CONCLUSIONS • Since the modern evolutionary synthesis, it has been a major goal of evolutionary biology to uncover the genetic basis of adaptive evolution. The rapid evolutionary responses of at least some organisms to current climate change indicates that studying contemporary evolutionary changes that result from climate change may provide opportunities to advance this goal. To do so, it is important to combine ecological approaches to studying responses to climate change with a variety of techniques in molecular and quantitative genetics and genomics. Recent advances, including genome sequencing and transcription profiling, help to uncover the genetic basis of climate change adaptation. However, future studies need to be grounded in a thorough understanding of the ecological context of the environmental changes, need to use well-designed experiments, and need to draw on current knowledge of genetic regulation and interactions to avoid fishing expeditions involving enormous amounts of genetic information without clear questions.
Editor's Notes
- #10: Now - to uncover the genetic basis of some of these traits
- #11: Although evolution could potentially rescue populations from the effects of climate change, there is not yet evidence that this will commonly occur and thereby circumvent a mass extinction and loss of genetic biodiversity.
- #14: For example, when the cue is photoperiod, it remains the same with changing climatic conditions, but the way organisms respond to the cue is different (Bradshaw WE, Holzapfel CM. 2008).
- #17: Geographic expansions may lead to selection for increased dispersal to take advantage of favorable conditions . Shorter and milder winters in temperate climates can select for earlier flowering in plants and earlier arrival of bird and insect migrants, particularly at temperate and boreal latitudes
- #22: Suppose that there is a particular allele (α) at a locus influencing a trait such as thermal tolerance. Suppose also that individuals carrying this allele have an increased tolerance, improving their fitness (ability to survive and reproduce) at high temperatures.
- #25: This issue can be explored with a variety of experimental approaches and genetic techniques
- #33: to examine evolutionary changes in natural populations is to collect propagules of individuals before and after a change in conditions and compare ancestors and descendants reared under common conditions
- #34: to determine the genetic basis of evolutionary change
- #36: both of which connect phenotypic variation in one or more traits to genetic variation at a number of loci. although variation at a particular locus might explain variation in a trait, this does not prove that the locus is necessarily involved in evolutionary responses in natural populations.
- #39: Genomic comparisons and genome scans - provide useful information on differences among populations (particularly for species with a reference genome), but much of the genome is not expressed.
- #49: a genetic regulatory network influences the expression of heat shock proteins through various interacting transcriptional factors that bind to the promoter region of Hsp70 genes to influence expression
- #54: Transcriptome- gene silencing