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Association genetics of growth and adaptive traits in loblolly pine (Pinus taeda L.) using whole-exome-discovered polymorphisms

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Abstract

In the USA, forest genetics research began over 100 years ago and loblolly pine breeding programs were established in the 1950s. However, the genetics underlying complex traits of loblolly pine remains to be discovered. To address this, adaptive and growth traits were measured and analyzed in a clonally tested loblolly pine (Pinus taeda L.) population. Over 2.8 million single nucleotide polymorphism (SNP) markers detected from exome sequencing were used to test for single-locus associations, SNP-SNP interactions, and correlation of individual heterozygosity with phenotypic traits. A total of 36 SNP-trait associations were found for specific leaf area (5 SNPs), branch angle (2), crown width (3), stem diameter (4), total height (9), carbon isotope discrimination (4), nitrogen concentration (2), and pitch canker resistance traits (7). Eleven SNP-SNP interactions were found to be associated with branch angle (1 SNP-SNP interaction), crown width (2), total height (2), carbon isotope discrimination (2), nitrogen concentration (1), and pitch canker resistance (3). Non-additive effects imposed by dominance and epistasis account for a large fraction of the genetic variance for the quantitative traits. Genes that contain the identified SNPs have a wide spectrum of functions. Individual heterozygosity positively correlated with water use efficiency and nitrogen concentration. In conclusion, multiple effects identified in this study influence the performance of loblolly pines, provide resources for understanding the genetic control of complex traits, and have potential value for assisting breeding through marker-assisted selection and genomic selection.

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Acknowledgements

We thank the Allele Discovery for Economic Pine Traits 2 (ADEPT 2) project (National Science Foundation Grant DBI-0501763) for developing the population; Dr. John Davis and Dr. Tania Quesada for providing the pitch canker disease resistance data and comments on the manuscript; Dr. Jill Wegrzyn and the PineRefSeq Project (USDA National Institute of Food and Agriculture, Award #2011-67009-30030) for providing the draft loblolly pine reference sequences, exon annotation, and bioinformatics assistance; Dr. Tomasz Koralewski for the exome capture probe design; Dr. Claudio Casola for the discussion on the analysis methods; and Texas A&M Institute for Genome Sciences and Society (TIGSS) for providing the computational resources and system administration support for the TIGSS HPC Cluster. Special gratitude goes to Jeffrey Puryear for the assistance on sample grinding and Dr. Tom Byram, Dr. Fred Raley, and technicians of the Harrison Experimental Forest at Southern Institute of Forest Genetics (Gay Flurry, Chance Parker, Chuck Burdine) for the help on sample collections. This study was funded by the Pine Integrated Network: Education, Mitigation, and Adaptation Project (PINEMAP), a Coordinated Agricultural Project funded by the USDA National Institute of Food and Agriculture, award no. 2011-68002-30185.

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Authors and Affiliations

  1. Department of Ecosystem Science and Management, Texas A&M University, 2138 TAMU, College Station, TX, 77843-2138, USA

    Mengmeng Lu, Konstantin V. Krutovsky, Jason B. West & Carol A. Loopstra

  2. Molecular and Environmental Plant Sciences Program, Texas A&M University, 2474 TAMU, College Station, TX, 77843-2474, USA

    Mengmeng Lu, Konstantin V. Krutovsky, Jason B. West & Carol A. Loopstra

  3. Department of Forest Genetics and Forest Tree Breeding, Georg-August-University of Göttingen, Büsgenweg 2, 37077, Göttingen, Germany

    Konstantin V. Krutovsky

  4. N. I. Vavilov Institute of General Genetics, Russian Academy of Sciences, 3 Gubkina Str., Moscow, 119333, Russia

    Konstantin V. Krutovsky

  5. Genome Research and Education Center, Siberian Federal University, 50a/2 Akademgorodok, Krasnoyarsk, 660036, Russia

    Konstantin V. Krutovsky

  6. USDA Forest Service, Southern Research Station, Southern Institute of Forest Genetics, 23332 Success Road, Saucier, MS, 39574, USA

    C. Dana Nelson

  7. Forest Health Research and Education Center, University of Kentucky, 730 Rose Street, Lexington, KY, 40546, USA

    C. Dana Nelson

  8. Department of Biology and Marine Biology, University of North Carolina Wilmington, 601 S. College Road, Dobo Hall 102, Wilmington, NC, 28403-5915, USA

    Nathalie A. Reilly

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Contributions

ML performed the sample collection and measurement, data analysis, and wrote the manuscript. KVK and CAL conceived and designed the study, coordinated the research, and participated in the drafting of the manuscript. CDN helped with the sampling, interpretation, and manuscript editing. JBW helped with the measurement of the carbon isotope discrimination and nitrogen concentration and interpretation. NAR performed the sample collection and measurement. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Carol A. Loopstra.

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The authors declare that they have no conflicts of interest.

Data archiving statement

The Illumina HiSeq short read sequences that were used to detect the SNPs are deposited in the Sequence Read Archive (SRA) (accession number SRP075363; https://www.ncbi.nlm.nih.gov/sra).

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Communicated by P. Ingvarsson

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Lu, M., Krutovsky, K.V., Nelson, C.D. et al. Association genetics of growth and adaptive traits in loblolly pine (Pinus taeda L.) using whole-exome-discovered polymorphisms. Tree Genetics & Genomes 13, 57 (2017). https://doi.org/10.1007/s11295-017-1140-1

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  • DOI: https://doi.org/10.1007/s11295-017-1140-1

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