lesson 2: local adaptation 2

Question 1

summary and key points of this lecture

Answer 1

1. example experiments which use reciprocal transplant experiment and genomic methods to identify local adaptations
2. reciprocal experiments: large scale arabidopsis, small scale bacteria + bacteriophage in port meadows and horse chestnut trees
3. meta analysis example done in 74 studies (1000+ measurement) to define local adaptation using equations. identified fitness: composite, fecundity, viability. and correlations with environment and phenotype
4. use of genetic methods to infer local adaptation process and pattern.
5. types of genetic methods: 5
6. local adaptation in humans: EGLN1
7. stickleback EDA locus analysis + whole genome analysis
8. crypsis genetics as a model in rodents: agouti locus and color coats
9. issues and potential criticisms: unable to identify genetic driver and direct association (gene and phenotype) un;ess you knock gene out

Question 2

what is the example of local adaptation in arabidopsis? what does it show?

Answer 2

1. large scale local adaptation
2. . carried out reciprocal transplants between 2 locations where arabidopsis is found. one in italy one in sweden (2000km apart) large spatial and environmental difference
   2.seeds were reciprocally transplanted at each site for 5 years
3. measured whether local adaptation occured, and whether the extent of local adaptation changed year on year
4. Findings: 8/10 comparisons showed significant difference - 8/10 had higher local fitness than non local; the magnitude of local adaptation also varied among years.
5. overall italian population had 670% and sweden had 60% difference in compared fitness. Fitness differences due to LA are large
6. explanation for difference is the minimum soil temperature in winter. This also causes why we see a change in magnitude year by year difference in local adaptation.

Ågren & Schemske (2012):

Question 3

what are examples of small scale local adaptation

Answer 3

1. port meadows: bacteria vs bactriophage (vos et al 2009)
2. horse chestnut tree: b acteria and bacteriophage (koskella et al., 2011)

Question 4

what is the example of port meadows: bacteria and bacteriophage local adaptation?

Answer 4

1. placed two 25 * 25cm grid in soil of port meadows
2. each big grid is divided into 5 * 5 small squares
3. stenotrophomonas and pooled bacteriophage are isolated from each square, and on average 35% of the local cloned bacteria are lysed by local bacteriophage
4. performed reciprocal testing within the grid
5. Finding: phages were 9% more effective on local bacteria than foreign bacteria (from the bigger grid)
6. interesting finding: there was no correlation found between the magnitude of local adaptation and distance between the grids
7. conclusion: scale of adaptation is in the order of 1cm or less, very locally adapted (local to the extent of 1cm, and distance passed 1cm is foreign -> very small scale adapted)

(vos et al 2009)

Question 5

what is the other small scale local adaptation experiment?

Answer 5

1. sampled 8 horse chestnut tree
2. Samples collected from tree surfaces and interior leaf tissues. Tested bacteria-phage interactions at different hierarchical scales:
   - Within leaves (leaflets).
   - Between leaves on the same tree.
   - Across different trees
3. findings: Surface bacteria-phage pairs: Showed stronger LA compared to interior pairs.
   * No evidence of LA within individual leaves or between leaves of the same tree.
   * Significant LA detected between trees (sympatric phages outperformed allopatric phages).
4. Key Insights:
   * Habitat structure and scale influence the strength of LA, with stronger effects across larger spatial scales.

koskella et al 2011

Question 6

what is the meta analysis experiment

Answer 6

• meta analysis on reciprocal transplant experiment
• compiled data from 1000+ fitness measures across 74 studies including plants, animal, fungi…etc
• local adaptation defined as: [Fitness (native)– Fitness (non-native)] / Mean Fitness
• index > 0 is local adaptation
• used
• Findings: average 45% for local populations; slight correlation between greater environmental divergence and stronger LA; no correlation between phenotypic difference and strength of LA;
• split fitness in to composite measures and individual measures of fecundity and viability
• Findings: strong trade of between magnitude and strength of LA in non local vs local environment. If individual has very high fitness in local, can often mean it has low fitness in non local as it is very specialized/adapted to one environment.
• majority showed trade offs, 20% showed non-trade-off (no cross over inthe plot), and only 9% was maladapted

hereford 2009

Question 7

what are some genomic methods to measure and identify LA?

Answer 7

1. Allele Frequency Spectrum: Detects deviations in allele frequencies that suggest selection (e.g., rare alleles being disproportionately common). - pairwise comparison
2. Phylogenetic Approaches: Longer branches in phylogenies at specific loci indicate rapid evolution and possible local adaptation. - multiple comparison within population
3. Genome-Wide Association Studies (GWAS): Identifies genetic variants linked to traits across populations and environmental conditions. - within population then between population comparisons
4. extended haplotype homozygosity (EHH): Long stretches of homozygosity indicate selective sweeps at a locus. - pairwise
5. FST Analysis: Measures genetic differentiation at specific loci; high FST suggests local adaptation. - pairwise

Question 8

what is the purpose or what can we infer using genetic methods to identify LA?

Answer 8

1. Either seeking pattern – an association between genetic basis traits thought to be linked to fitness & spatially divergent environments/selection
2. Or process – inference of divergent selection obtained from genome comparisons

Question 9

what is the experiment for local adaptation in humans, how is it criticized?

Answer 9

1. very difficult to track because fo so much migration in humans (high migration dispersal)
2. difficult to identify and conduct studies on, and data collection is difficult too - cant really place humans somewhere and track their fitness
3. All inferred from genomic analysis
4. In some cases, multiple independent evolution of same local adaptation (e.g. MCM6 associated lactase gene;
5. EGLN1: Found in Andean and Himalayan populations, linked to oxygen regulation at high altitudes.
6. EPAS1 believed to have derived from introgressive hybridization with Denisovans

Fan et al 2016

Question 10

what is the case study on stickleback fish?

Answer 10

1. stickleback fish are found in various geographies, in atlantic and pacific oceans they are also found in various habitats within pacific and atlantic oceans- marine vs freshwater
2. variation in phenotype of stickleback fish: (marine populations = more plates; freshwater populations = fewer plates)
3. findings: LA at the EDA locus and created a phylogenetic tree -> genomic data showed: phylogeny clustered in habitat and phenotype (freshwater vs marine) and not based on geography (atlantic vs pacific)
4. Evidence of parallel evolution: Same genetic adaptation occurring independently across populations.
5. potential driver for this: marine has higher calcium and salt conc -> more calcium for bones, or higher predation in marine -> bones evolve as anti-predation

colosimo et al., 2005

Question 11

what were further experiments done on sticklebacks?

Answer 11

1. samples multiple sticklebacks globally, and samples neighbouring freshwater and marine sticklebacks
2. did genome sequencing of whole genome to identify regions, using Fst: looking at genetic differences in freshwater vs marine
3. they identified loci (high peaks) which were locally adapted and driven by selection pressures in different environments -> divergent (genetic differentiation) -> big peaks on Fst
4. this result confirms EDA locus, but also other loci such as chromosomal inversions playing a big part in local adaptation
5. unsure what exactly causes the selection, dont know what drives the differences as marine and freshwater are so different in habitats: so many factors come to play, difficult to identify which factor drives the genetic differentiation (can make assumptions but unsure)

jones te al, 2012

Question 12

what is the example using crypsis genetics as a model?

Answer 12

1. crypsis genetics as a model: looks at crypsis (camouflage) as an example of local adaptation to specific environments
2. simple spatial contrast: Studies often deal with species adapting to clear environmental contrasts (e.g., light vs. dark substrates, sand vs. rock).
3. Closely related species in similar environments often show parallel adaptations, making these systems ideal for comparative studies.
4. experiments done on many rodent species show that local populations have adapted their coat color/color to their substrate or environments (like sand color)
5. can either be divergence of dark and light, or directional selection to form a lighter color to adapt to lighter substrate
6. takeaway: similar adaptation arise repeatedly in different species under same selective pressure (crypsis)
7. key genes: mc1r and agouti
8. Studies reveal how rapid and localized evolutionary pressures shape the genetic architecture of traits critical for survival.
9. combines field observation, genomic data, experiments to link phgenotype, fitness and genotype together

review from harris et al 2020

Question 13

dive into detail of a few crypsis genetic model experiments

Answer 13

1. example Peromyscus polionotus (Beach Mouse)
   i. Demographic Model:
   Gulf Coast populations adapted to light-colored sandy beaches.
   Divergence time estimated at >3k years ago.
   ii. Brightness Differences:
   Shows fitness costs when coat brightness mismatches local substrate.
   iii. Likelihood Ratio of Selection:
   High likelihood of directional selection driving light pigmentation in this population.
   Data derived from genomic analyses (e.g., SweepFinder).
2. Sceloporus cowlesi (White Sands Lizard)
   i. Population Divergence:
   Populations from “White Sands” and “off-sand” habitats diverge in spine brightness.
   Demographic models estimate divergence times of 11k years.
   ii. Survival and Mc1r Genotype:
   Genotypes at the Mc1r locus influence brightness and survival probability:
   AA (wild type): Associated with darker color and higher survival in non-sandy environments.
   aa (homozygous recessive): Produces lighter coloration and higher survival in sandy environments.
   iii. Likelihood of Selection:
   Shows a strong likelihood of selection acting on Mc1r for crypsis adaptation.

review from harris et al 2020

Question 14

give me the details for the experiment done on nebraska deer mouse

Answer 14

1. linnen et al 2009: Previous research examined genomic differences in Nebraskan Deer Mice across an environmental gradient in the Nebraska Sandhills.
   The Agouti gene was identified as a key factor in the evolution of a light coat phenotype over approximately 8000 years, aligning with the formation of the Nebraska Sandhills.
   Lighter coats are thought to provide crypsis (camouflage) against the pale sandy environment, reducing predation risk.
2. Barratt et al 2019: To measure natural selection at the genomic level by conducting a field experiment using reciprocal transplant
3. experiment method: dark and light substrates, introduced 75-100 mice (equal mix from original sites), tracked survival over time
4. results: Non-local mice (those with mismatched coat color for the substrate) showed lower survival than local, well-matched mice. Individual survival strongly correlated with fur color:
   * Light-coated mice: Higher survival on light sand.
   * Dark-coated mice: Higher survival on dark soil.
   * Demonstrated antagonistic effects: Coat colors adapted to one environment were maladaptive in the other.
5. genome analysisL fst analysis of agouti locus: Identified a single SNP (∆Ser) within the Agouti locus as having the strongest effect on coat brightness. mice w ser allele had light coats
6. In dark experimental enclosures, the frequency of the ∆Ser allele decreased over time, consistent with selection against lighter coats in dark environments.
7. conclusions: shows evolutionary tradeoffs, SNP controls color, The experiment connects ecological and genomic insights, providing a model system for studying local adaptation.
8. criticism:dont know what causes the low fitness rate: stress or predation. also unsure about precise association between causality and color, can use crispr to really identify the association

linnen et al 2009, barratt et al 2019