population structuring Flashcards

1
Q

known population structuring example

A
  • European hake (Merluccius merluccius) = commercially important - Widely distributed in northeast Atlantic + Mediterranean Sea
  • International Council for the Exploration of the Seas (ICES) considers 2 stocks in the Atlantic:
    (1)Northern stock (northern Bay of Biscay, Celtic Sea and all waters west of the British Isles round to western Norway)
    (2)Southern stock (southern waters of the Bay of Biscay and around the Iberian peninsula)
    (3)Mediterranean?
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2
Q

what areas were sampled and what were the outcome FST values - what can we draw from this

A

(1)Mediterranean vs Atlantic:
FST = 0.029 (P < 0.001)
(2) Within the Mediterranean Sea:
FST = 0.003 (P > 0.05)
(3) Bay of Biscay vs Portugal (currently managed as one stock)
FST = 0.013 (P < 0.001)
(4) Southern Bay of Biscay vs Celtic Sea samples (managed as separate stocks)
FST = 0.003 (P = 0.2)
- Point = not all parts of the genome are neutral – some are actively selected for in this case

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3
Q

what needs to be considered when looking at Fst values to get an actual differentiation

A

type of marker

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4
Q

what are the 2 types of markers

A

Neutral & Non-neutral (often adaptive)
- Neutral markers = important - great at studying demographic processes - FST values often relatively small - subject to genetic drift and mutation but are not directly influenced by natural selection
- Adaptive markers often have very high FST values (0.25 = highest) and can tell us about specific processes underlying and often driving genetic population structuring - directly influenced by natural selection

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5
Q

what is a Genetic Outlier

A

loci that shows significantly higher or lower genetic differentiation than expected under neutrality

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6
Q

what biotic and abiotic factors make populations exhibit genetic structuring

A

Abiotic:
- Physical separation - mountains and rivers, followed by genetic drift
- Environmental factors (temperature, weather, salinity etc.)
- Environmental change
- Habitat fragmentation
Biotic:
- Life history traits- e.g. migratory behaviour, fecundity
- Dispersal potential (e.g. Flight)
- Evolutionary pressures: population bottlenecks and expansions, founder effects etc

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7
Q

what is genetic drift

A

allele frequencies of a population change over generations due to chance (sampling error)
- Primary mechanism for ‘neutral’ evolution
- Can result in extinction of some alleles (could be beneficial) and fixation of others (i.e. 100% freq)
- Effects small populations more
- Fst value represents the change in aleles in two separate populations due to genetic drift

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8
Q

what is the founder effect

A

Small group of individuals breaks off from a larger population to establish a new colony (extreme example of genetic drift)
- New colony isolated from original
- the ‘new’ gene pool is reflective of the founding individuals
- allele frequencies can be very different from the source populations’ - can lead to a reduction in genetic diversity + increase in the frequency of certain alleles (including rare or recessive ones)
- Prevalence of Huntington’s disease in Afrikaners in humans

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9
Q

explain Genetic bottleneck

A
  • when an event severely reduces the size of a population (another extreme example of genetic drift) e.g natural disasters (earthquakes, floods, fires)
  • small, random assortment of survivors
  • Allele freq’s in the new pop can be drastically different from prior pop
  • Many alleles can go extinct, with alleles continuing to be lost post event
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10
Q

example of a Genetic bottleneck

A

northern elephant seals
- Huge hunting pressure from humans
- Greatly reduced genetic diversity- approx 20 individuals surviving by 1890s
- Have rebounded to over 30,000 individuals
- BUT their genes still reflect this drastic bottleneck
- More susceptible to Environmental change?

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11
Q

what needs to be considered when sampling population genetics

A
  • Sampling strategy?
  • Only breeding individuals?
  • Sample size 30 considered ‘standard’ - BUT more is often better
  • Conservation concerns and ethics?
  • Non-lethal / harmful methodologies?
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12
Q

what is the Wahlund effect

A
  • Wahlund Effect = He (expected heterozygosity) ALWAYS exceeds Ho (observed heterozygosity) when randomly-mating, differentiated subpopulations are merged
  • ONLY if merged population is not randomly mating as a whole
  • More important: failure to detect the underlying population structure!
  • Populations may mix in feeding grounds, but return to their own mating ground - NO random mating
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13
Q

what must be considered when choosing a genetic marker

A

depends on question asked + cost
- Neutral or non-neutral?
- Mitochondrial vs neutral?
- Variability of the marker - do you need to identify individuals?
- Sequencing technology to be used? Sanger Sequencing, NGS?
- £££ cost is often a deciding factor here

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14
Q

what factors are important regarding bioinformatics

A

Must be considered and costed into project planning - most population genetic analyses can be considered bioinformatics
- Sanger sequencing results relatively easy to do - BUT complex for thousands of samples
- NGS analysis ‘pipeline’ quality checks, de - barcoding etc
- access to appropriate computing power
- Ensure you have the expertise – workshops - colleagues

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15
Q

different methods used for Population genetic analyses

A

HWE dependent:
- Traditional population genetics - FST etc - HWE important
- Clustering analyses- STRUCTURE
- Detection of markers out of HWE - outliers
HWE independent:
- Essential methods which do not have the model assumptions of Hardy- Weinberg
- PCA, DAPC.
- Adaptation- gene under study here are not going to be in HWE

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16
Q

what is Linkage Disequilibrium and why is it important to test for it

A
  • Crossing over during meiosis cause recombination - means genes can be inherited independently
  • If genes don’t assort independently, they show linkage disequilibrium e.g. If they are close together on the same chromosome, sex linked0 little recombination
  • Must be tested for - if markers are linked they are not independent
  • Not in HWE & essentially replicated markers - inflate observed differences
17
Q

how to resolve population structure

A
  • what we really want to know is how many genetic groups or clusters (K) are in our data?
  • Do these groups correspond to geography, known biology of the organism?
  • Correspond to physical (i.e. phenotypic) traits?
    >With priors- i.e. analysis is run using presumed structure, often using the original sample ID - number of K = obvious
    >Without priors- i.e. analysis is run without known sample ID – K = less obvious
18
Q

what are the HWE based- F statistics

A
  • Calculated overall (all markers) and per marker
    >FST original Wright’s FST value
    >ΦST adapted version - useful for DNA sequence data (e.g. COI, CR, ITS etc)
    >RST modified for stepwise mutation model - microsatellites
    >P-values often calculated as either being statistically significant from 0 (95% CI) or using permutation model
    >Permutations essentially calculate (from your genotype data set) the expected scenario of panmixia - then compare your actual FST values to those observed
    >Global FST- overall FST value of all your samples
    **FST values can be presented graphically (PCoA - FST)
19
Q

most common Clustering based methods

A

structure
- Uses Bayesian modelling cluster method to infer population structuring
- Can be run with and without priors
- Still assumes HWE
- Help inform conservation management
- identifies discrete demographic units

20
Q

Non- HWE based approaches

A
  • Most pop gen methods assume HWE and non-linked markers
  • PCA = statistical method for exploring and making sense of datasets with a large number of measurements (which can be thought of as dimensions) by reducing the dimensions to the few principal components (PCs) that explain the main patterns
  • these make the data more manageable + remove some of the assumptions of other underlying methods
  • However, you get no ‘p-values’ from inferred clusters
21
Q

what are the demographics for analysis

A
  • Population expansion and contraction
  • Migration / gene flow
  • Sex ratios
22
Q

what are the assignment methods for analysis

A
  • Need to resolve pop structure first!
  • HWE- based methods- Maximum likelihood, Bayesian
  • Machine learning
    **Several pieces of analysis both HWE dependent and non- HWE dependent are useful (even better if these correlate with life history traits, geography and
    know biology)