Adaptive genetic variation within and among populations. Kathleen O Malley Associate Professor, OSU 2017 Annual Meeting Genetics Workshop

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1 Adaptive genetic variation within and among populations Kathleen O Malley Associate Professor, OSU 2017 Annual Meeting Genetics Workshop

2 Structure i. Concept Genetic diversity - neutral and adaptive ii. Methods Candidate gene vs. Genome-wide scan iii. Applications Delineate units of conservation (Candidate-gene) Identify genetic basis of life history variation (Genome-wide)

3 Genetic diversity Neutral genetic variation does not have any affect on fitness Neutral markers (i.e. microsatellites) used to study phylogenetic relationships, population structure, mating systems, gene flow, and parental assignment Adaptive genetic variation that is correlated with fitness Adaptive markers (selection-driven) used to study evolutionary processes such as local adaptation or speciation

4 Candidate gene approach vs. Genome-wide scan

5 Candidate gene approach Use existing gene sequence information - National Center for Biotechnology Gene selected a prior based on a hypothesis

6 Genome-wide scan GBS Genotyping-By-Sequencing Andrews et al. (2016) Nat. Rev. Genet. GBS 2bRAD RAD ddrad EzRAD NextSeq500 MiSeq HiSeq

7 Genotyping-by-sequencing (Elshire et al. 2011) 1. Extract DNA 2. Add two restriction enzymes Frequent Rare 3. Double digest DNA Cut site 5 - A AGCTT - 3

8 AACT 4. Add unique and common adapters Unique Common 5. Pool samples and size select bp

9 6. Amplify via PCR and sequence the library 7. Demultiplex samples AACT 8. Align reads and call genotypes T C T/C

10 6. Amplify via PCR and sequence the library 7. Demultiplex samples AACT 8. Align reads and call genotypes T T T/C T/T

11 STACKS Pipeline Catchen et al. (2013) i. Reads are demultiplexed ii. Data from each individual grouped into loci and SNPs identified iii. Loci grouped together across individuals and a catalogue is written iv. Loci from each individual are matched against catalogue to determine genotype at each locus for each individual

12 Identify candidate outlier loci under natural selection (e.g. BayeScan) Fst Log10[PO] 3,480 3,490 3,500 3,510 3,520 3,530 3,540 3,550 Sequence 5 T T G A T T A T T T A G T T G C G A G G A A A T T G C A T G A C T G G A G T T A G G G C A C A G G T G G C G T T C C A T C A A A G T A T C A C T C T A G A A T T C A T T G A G C T C C A A C T A A T A A A T C A A C G C T C C T T T A A C G T A C T G A C C T C A A T C C C G T G T C C A C C G C A A G G T A G T T T C A T A G T G A G A T C T T A A G T A A C T C G A G G 5 Genes LOC BLAST Results for: Nucleotide Sequence (96 letters) Black et al Molecular Ecology Query_10661 T A T T T A G G G G T G A G G G A A T T T C A A A A C T G G A G G T A T T G C A C A G G T G G C A T C C T C T C A A A G T A T C A C A C T A G A A T T k PREDICTED: Xiphophorus maculatus sodium-driven chloride bicarbonate exchanger-like (LOC ), transcript variant X1, mrna Black et al. (2017) Mol. Ecol.

13 i. Concept What is adaptive genetic variation and what can it tell us? ii. Methods Candidate gene vs. Genome-wide scan iii. Applications Delineate units of conservation (Candidate gene) Identify genetic basis of life history variation (Genome-wide)

14 Candidate gene approach Evolutionary Significant Unit (ESU) Is a population (or group of populations) that is substantially reproductively isolated from other conspecific population units and that represents an important component in the evolutionary legacy of a species Waples (1991) Microsatellite markers have generally provided an effective means for delineating ESUs - Neutral, highly variable, and distributed throughout the genome

15 Candidate gene approach Human activities can inadvertently increase the rate of gene flow among populations Formerly diagnostic microsatellite markers provide limited power to discriminate populations May affect our ability to identify populations that represent an important evolutionary legacy of a species Habitat alteration (i.e. dams) Adaptive genetic markers might help resolve management dilemmas regarding the status of admixed populations Artificial propagation (i.e. hatchery)

16 Candidate gene approach Human activities increased gene flow between spring and fall runs of Chinook salmon Feather River, California 1) Dam blocked access to spawning habitat 2) Hatchery inadvertent mixing of broodstock Feather River spring run Chinook part of the Central Valley Spring Run ESU - Listed as threatened in 1999 (U.S. Endangered Species Act) Microsatellites fail to differentiate between spring and fall runs 1,2 Does the Feather River spring run still represent an important evolutionary legacy? 1 Banks et al. (2000), 2 Hedgecock et al. (2001)

17 Candidate gene approach Develop a novel gene marker to test for adaptive differences Day length is a critical environmental cue used to regulate seasonal behaviors (i.e. migration and breeding) Internal circadian clock is entrained by changes in day length Molecular mechanism underlying circadian clock well characterized Clock gene CRITFC Living Earth

18 Candidate gene approach Clock Gene Polyglutamine Domain 4 length variants identified in Feather River Chinook Clock gene differentiates fall and spring runs F st P-value Clock gene Nine microsatellite markers O Malley et al. (2007), O Malley et al. (2013)

19 Candidate gene approach O Malley et al. (2007), reported genetic differentiation at candidate loci linked to migration timing (so-called Clock gene) Hence, there is evidence that the Feather River runs are able to maintain some differentiation despite pressures against it. This fact is important for conservation purposes; therefore the Department of Water Resources plans to install a separation weir in the upper part of the low flow channel to help ensure genetic separation. The spring run would be allowed upstream of the weir while the fall run would not, based presumably on some characteristics of run timing. California Hatchery Review Project

20 Genome-wide scan Year No. of individuals 2007 N = N = N = 144

21 Genome-wide scan Identified 15,239 SNPs using the STACKS pipeline Sequence for each RAD tag aligned to the O. mykiss and S. salar reference genomes Examined coding regions within 5 kb of each SNP locus Coding regions were queried against NCBI database using BLAST2GO GBS GBS 2bRAD RAD ddrad EzRAD Restriction site-associated DNA sequencing Univariate analysis using a GLM and a MLM Multivariate Random Forest (RF) analysis

22 Genome-wide scan Univariate MLM 3 SNPs significantly associated with migration timing Explain 46% of trait variation Localize within a 46 kb region overlapping GREB1-like gene Multivariate RF Identified same 3 SNPs plus 15 additional SNPs that explain 60% of trait variation

23 Genome-wide scan Candidate gene markers may help predict the adult migration timing of individual steelhead throughout the entire course of their life cycle - Juvenile migration and size-at-age - Adults on spawning grounds

24 Useful Resources NCBI STACKS