New molecular markers to study genetic structure in longleaf pine (Pinus palustris)

Additional Poster Information, 13th Biennial Longleaf Conference

Background

• Understanding genetic differentiation between regions is important for restoration and conservation. Genetic differentation results when evolutionary histories are distinct, and may indicate that populations are locally adapted to unique environmental conditions.
• Studies of inherited traits in longleaf pine have shown marked genetic differentiation between populations (e.g., Boyer & Evans 1967; Kraus & Sluder 1990; Johnsen et al. 2015; Sameulson et al. 2018). However, previous molecular genetic studies using allozyme or microsatelline markers have found high levels of genetic diversity in the species but little genetic divergence between populations (Duba 1985; Schmidtling & Hipkins 1998; Echt et al. 2012).
• Genetic techniques like RADseq can yield thousands of single nucleotide polymorphism (SNP) markers, many more markers than used in prevous studies.
• I used RADseq to develop SNP markers for longleaf pine and examined evidence for genetic differentiation between sampling locations in the preliminary data resulting from this effort. These markers will be used in upcoming efforts to further characterize molecular genetic diversity across the species range.

Methods

Tissue Collection

• Collected leaf tissue from 8 locations across the longleaf pine range (n=55). Needles were collected from adults in natural stands in S. Georgia and N. Carolina, from adults in seed orchards in N. Georgia and Louisiana, and from seedlings in natural stands in the remaining locations.

Genomic Data

• Extracted DNA from homogenized dried or frozen tissues using DNeasy Plant Pro Kit and protocol (Qiagen, Hilden, Germany).
• Prepared genomic libraries using 3RAD, a version of RADseq which employs three restriction enzymes (Bayona-Vasquez 2019; restriction enzymes used were BamHI, MspI, and ClaI).
• Size-selected libraries for fragments 470-630 base pairs in length using the Pippin Prep automated system (Sage Science, Beverly, MA, U.S.A.).
• Sequenced pooled samples on an Illumina Hiseq platform for 150-bp paired-end reads.

Data Analysis

• Sequence reads demultiplexed, filtered, and clustered into putative loci using the Stacks v2.3e software pipeline (Catchen et al. 2013; user-specified parameters M=2 and n=3).
• Discriminant analysis of principal components (DAPC; Jombart et al. 2010) used to investigate genetic clustering of indivuals and populations. Conducted analysis in program R (R Core Team, 2020) using the ‘adegenet’ package (Jomabart 2008; Jombart & Ahmed 2011).

Results

• Found >190K frequently-occurring loci with SNPs. These were loci present in at least 60% of the individuals from 2 or more sampling sites.
• More than 24K those loci were identified in 80% of individuals in the datset. Sequencing coverage was somewhat unequal across individuals and populations, with missing loci most prevalent in individuals from N. Carolina, S. Georgia, and Mississippi.
• DAPC shows genetic clustering of most source populations, with the exceptions of Lousiana and Florida samples.

Conclusion

With SNPs developed, a thorough investigation of genetic structure in longleaf pine requires more data!

Next steps:

1. Collect needles from many more trees at at least 30 sites across the range.
2. Use sequence capture (Gnirke et al. 2009) to recover the same loci with thousands of SNPs repeatably and cheaply.
3. Conduct more comprehensive analyses of population genetic structure.

References

Bayona-Vásquez, N.J., Glenn, T.C., Kieran, T.J., Pierson, T.W., Hoffberg, S.L., Scott, P.A., Bentley, K.E., Finger, J.W., Louha, S., Troendle, N. and Díaz-Jaimes, P. 2019. Adapterama III: Quadruple-indexed, double/triple-enzyme RADseq libraries (2RAD/3RAD). PeerJ, 7:e7724. doi:10.7717/peerj.7755

Boyer, W. D., and Evans, S. R. 1967. Early flowering in longleaf pine related to seed source. Journal of Forestry, 65(11):806.

Catchen, J., Hohenlohe, P.A., Bassham, S., Amores, A. and Cresko, W.A. 2013. Stacks: an analysis tool set for population genomics. Molecular ecology, 22(11):3124-3140. doi:10.1111/mec.12354

Duba, S. E. 1985. Polymorphic isoenzymes from megagametophytes and pollen of longleaf pine: characterization, inheritance and use in analyses of genetic variation and genotype verification. Proceedings of the 18th Southern Forest Tree Improvement Conference.

Echt, C., Josserand, S., Hipkins, V., and Crane, B. 2012. Patterns of Longleaf Pine Genetic Diversity. 9th Regional Longleaf Conference, 23 Oct. 2012, Nacogdoches, TX.

Gnirke, A., Melnikov, A., Maguire, J., Rogov, P., LeProust, E.M., Brockman, W., Fennell, T., Giannoukos, G., Fisher, S., Russ, C. and Gabriel, S. 2009. Solution hybrid selection with ultra-long oligonucleotides for massively parallel targeted sequencing. Nature biotechnology, 27(2):182-189. doi:10.1038/nbt.1523

Johnsen, K. H., Creighton, J. L., and Maier, C. A. 2015. Longleaf pine grown in Virginia: a provenance test (e-Gen. Tech. Rep. SRS-203). Proceedings of the 17th Biennial Southern Silvicultural Research Conference.

Jombart, T. 2008. adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics, 24:1403-1405. doi:10.1093/bioinformatics/btn129

Jombart, T. and Ahmed, I. 2011. adegenet 1.3-1: new tools for the analysis of genome-wide SNP data. Bioinformatics. doi:10.1093/bioinformatics/btr521

Jombart, T., Devillard, S., and Balloux, F. 2010. Discriminant analysis of principal components: a new method for the analysis of genetically structured populations. BMC Genetics, 11:94. doi:10.1186/1471-2156-11-94

Kraus, J., and Sluder, E. 1990. Genecology of Longleaf Pine in Georgia and Florida (Res. Paper SE-278). Asheville, North Carolina.

R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/

Samuelson, L., Johnsen, K., Stokes, T., Anderson, P., and Nelson, C. D. 2018. Provenance variation in Pinus palustris foliar δ13C. Forests, 9(8):466. doi:10.3390/f9080466

Schmidtling, R. C., and Hipkins, V. 1998. Genetic diversity in longleaf pine (Pinus palustris): influence of historical and prehistorical events. Canadian Journal of Forest Research, 28(8):1135–1145.