Kyle M. Gardner

Identifying loci under selection across contrasting environments in Avena barbata using quantitative trait locus mapping.

We constructed recombinant inbred lines of a cross between naturally occurring ecotypes of Avena barbata (Pott ex Link), Poaceae, associated with contrasting moisture environments. These lines were assessed for fitness in common garden reciprocal transplant experiments in two contrasting field sites in each of two years, as well as a novel, benign greenhouse environment. An AFLP (amplified fragment length polymorphism) linkage map of 129 markers spanned 644 cM in 19 linkage groups, which is smaller, with more linkage groups, than expected. Therefore parts of the A. barbata genome remain unmapped, possibly because they lack variation between the ecotypes. Nevertheless, we identified QTL (quantitative trait loci) under selection in both native environments and in the greenhouse. Across years at the same site, the same loci remain under selection, for the same alleles. Across sites, an overlapping set of loci are under selection with either (i) the same alleles favoured at both sites or (ii) loci under selection at one site and neutral at the other. QTL under selection in the greenhouse were generally unlinked to those under selection in the field because selection acted on a different trait. We found little evidence that selection favours alternate alleles in alternate environments, which would be necessary if genotype by environment interaction were to maintain genetic variation in A. barbata. Additive effect QTL were best able to explain the genetic variation among recombinant inbred lines for the greenhouse environment where heritability was highest, and past selection had not eliminated variation.

LinkImpute: Fast and Accurate Genotype Imputation for Nonmodel Organisms

Obtaining genome-wide genotype data from a set of individuals is the first step in many genomic studies, including genome-wide association and genomic selection. All genotyping methods suffer from some level of missing data, and genotype imputation can be used to fill in the missing data and improve the power of downstream analyses. Model organisms like human and cattle benefit from high-quality reference genomes and panels of reference genotypes that aid in imputation accuracy. In nonmodel organisms, however, genetic and physical maps often are either of poor quality or are completely absent, and there are no panels of reference genotypes available. There is therefore a need for imputation methods designed specifically for nonmodel organisms in which genomic resources are poorly developed and marker order is unreliable or unknown. Here we introduce LinkImpute, a software package based on a k-nearest neighbor genotype imputation method, LD-kNNi, which is designed for unordered markers. No physical or genetic maps are required, and it is designed to work on unphased genotype data from heterozygous species. It exploits the fact that markers useful for imputation often are not physically close to the missing genotype but rather distributed throughout the genome. Using genotyping-by-sequencing data from diverse and heterozygous accessions of apples, grapes, and maize, we compare LD-kNNi with several genotype imputation methods and show that LD-kNNi is fast, comparable in accuracy to the best-existing methods, and exhibits the least bias in allele frequency estimates.

Fast and cost-effective genetic mapping in apple using next-generation sequencing

Next-generation DNA sequencing (NGS) produces vast amounts of DNA sequence data, but it is not specifically designed to generate data suitable for genetic mapping. Recently developed DNA library preparation methods for NGS have helped solve this problem, however, by combining the use of reduced representation libraries with DNA sample barcoding to generate genome-wide genotype data from a common set of genetic markers across a large number of samples. Here we use such a method, called genotyping-by-sequencing (GBS), to produce a data set for genetic mapping in an F1 population of apples (Malus × domestica) segregating for skin color. We show that GBS produces a relatively large, but extremely sparse, genotype matrix: over 270,000 SNPs were discovered but most SNPs have too much missing data across samples to be useful for genetic mapping. After filtering for genotype quality and missing data, only 6% of the 85 million DNA sequence reads contributed to useful genotype calls. Despite this limitation, using existing software and a set of simple heuristics, we generated a final genotype matrix containing 3967 SNPs from 89 DNA samples from a single lane of Illumina HiSeq and used it to create a saturated genetic linkage map and to identify a known QTL underlying apple skin color. We therefore demonstrate that GBS is a cost-effective method for generating genome-wide SNP data suitable for genetic mapping in a highly diverse and heterozygous agricultural species. We anticipate future improvements to the GBS analysis pipeline presented here that will enhance the utility of next-generation DNA sequence data for the purposes of genetic mapping across diverse species.

Shared quantitative trait loci underlying the genetic correlation between continuous traits

We review genetic correlations among quantitative traits in light of their underlying quantitative trait loci (QTL). We derive an expectation of genetic correlation from the effects of underlying loci and test whether published genetic correlations can be explained by the QTL underlying the traits. While genetically correlated traits shared more QTL (33%) on average than uncorrelated traits (11%), the actual number of shared QTL shared was small. QTL usually predicted the sign of the correlation with good accuracy, but the quantitative prediction was poor. Approximately 25% of trait pairs in the data set had at least one QTL with antagonistic effects. Yet a significant minority (20%) of such trait pairs have net positive genetic correlations due to such antagonistic QTL ‘hidden’ within positive genetic correlations. We review the evidence on whether shared QTL represent single pleiotropic loci or closely linked monotropic genes, and argue that strict pleiotropy can be viewed as one end of a continuum of recombination rates where r = 0. QTL studies of genetic correlation will likely be insufficient to predict evolutionary trajectories over long time spans in large panmictic populations, but will provide important insights into the trade‐offs involved in population and species divergence.

The Genetic Structure of Marijuana and Hemp

Despite its cultivation as a source of food, fibre and medicine, and its global status as the most used illicit drug, the genus Cannabis has an inconclusive taxonomic organization and evolutionary history. Drug types of Cannabis (marijuana), which contain high amounts of the psychoactive cannabinoid Δ 9-tetrahydrocannabinol (THC), are used for medical purposes and as a recreational drug. Hemp types are grown for the production of seed and fibre, and contain low amounts of THC. Two species or gene pools (C. sativa and C. indica) are widely used in describing the pedigree or appearance of cultivated Cannabis plants. Using 14,031 single-nucleotide polymorphisms (SNPs) genotyped in 81 marijuana and 43 hemp samples, we show that marijuana and hemp are significantly differentiated at a genome-wide level, demonstrating that the distinction between these populations is not limited to genes underlying THC production. We find a moderate correlation between the genetic structure of marijuana strains and their reported C. sativa and C. indica ancestry and show that marijuana strain names often do not reflect a meaningful genetic identity. We also provide evidence that hemp is genetically more similar to C. indica type marijuana than to C. sativa strains.

Hybridization, recombination, and the genetic basis of fitness variation across environments in Avena barbata

We created Recombinant Inbred Lines (RILs) derived from a cross between ecotypes of Avena barbata associated with moist (mesic) and dry (xeric) habitats in California. Traits which were correlated with fitness across RILs mapped to the same Quantitative Trait Loci (QTLs) as fitness. However, different QTL affected fitness in different environments so that fitness was weakly correlated across environments. Recombination released considerable heritable variation both in fitness, and in ecologically relevant traits. Many traits showed transgressive segregation caused by recombination of QTL associated in repulsion phase in the parents. In addition, some traits were uncorrelated, allowing novel combinations of those traits to be created. Recombination also created heritable variation in reaction norms for at least one trait (root allocation). Altogether these results suggest that recombination can combine the most selectively advantageous genes and traits of the parents to produce broadly adapted genotypes that are capable of outperforming the parents. Indeed, two of the RILs showed higher fitness than the parental ecotypes across a range of environmental treatments in the greenhouse, but their superiority was less pronounced in the field. Although late-generation recombinants exhibited hybrid breakdown, being less fit, on average, than the mid-parent, early generation hybrids appear to exhibit hybrid vigour through the expression of dominance effects in the heterozyotes. This vigour may offset the effects of hybrid breakdown in the early generations following a cross, enhancing the opportunity for recombination to create broadly adapted genotypes. We discuss the implications of these findings to the evolution of colonizing species.

Heritable variation and genetic correlation of quantitative traits within and between ecotypes of Avena barbata.

We examined heritable variation for quantitative traits within and between naturally occurring mesic and xeric ecotypes of the slender wild oat (Avena barbata), and in 188 recombinant inbred lines derived from a cross between the ecotypes. We measured a suite of seedling and adult traits in the greenhouse, as well as performance‐related traits in field sites native to the two ecotypes. Although the ecotypes were genetically diverged for most traits, few traits showed significant heritable variation within either ecotype. In contrast, considerable heritable variation was released in the recombinant progeny of the cross, and transgressive segregation was apparent in all traits. Heritabilities were substantially greater in the greenhouse than in the field, and this was associated with an increase in environmental variance in the field, rather than a decrease in genetic variance. Strong genetic correlations were evident among the recombinants, such that 22 measured traits could be well represented by only seven underlying factors, which accounted for 80% of the total variation. The primary axis of variation in the greenhouse described a trade‐off between vegetative and reproductive allocation, mediated by the date of first flowering, and fitness was strongly correlated with this trade‐off. Other factors in the greenhouse described variation in size and in seedling traits. Lack of correlation among these factors represents the release of multivariate trait variation through recombination. In the field, a separate axis of variation in overall performance was found for each year/site combination. Performance was significantly correlated across field environments, but not significantly correlated between greenhouse and field.

Genome to Phenome Mapping in Apple Using Historical Data

Apple (Malus X. domestica Borkh.) is one of the worlds most valuable fruit crops. Its large size and long juvenile phase make it a particularly promising candidate for marker‐assisted selection (MAS). However, advances in MAS in apple have been limited by a lack of phenotype and genotype data from sufficiently large samples. To establish genotype‐phenotype relationships and advance MAS in apple, we extracted over 24,000 phenotype scores from the USDA‐Germplasm Resources Information Network (GRIN) database and linked them with over 8000 single nucleotide polymorphisms (SNPs) from 689 apple accessions from the USDA apple germplasm collection clonally preserved in Geneva, NY. We find significant genetic differentiation between Old World and New World cultivars and demonstrate that the genetic structure of the domesticated apple also reflects the time required for ripening. A genome‐wide association study (GWAS) of 36 phenotypes confirms the association between fruit color and the MYB1 locus, and we also report a novel association between the transcription factor, NAC18.1, and harvest date and fruit firmness. We demonstrate that harvest time and fruit size can be predicted with relatively high accuracies (r > 0.46) using genomic prediction. Rapid decay of linkage disequilibrium (LD) in apples means millions of SNPs may be required for well‐powered GWAS. However, rapid LD decay also promises to enable extremely high resolution mapping of causal variants, which holds great potential for advancing MAS.

NATURAL SELECTION ON PLEIOTROPIC QUANTITATIVE TRAIT LOCI AFFECTING A LIFE‐HISTORY TRADE‐OFF IN AVENA BARBATA

We applied QTL mapping to fitness variation of Avena barbata under well-watered greenhouse conditions. One hundred eighty recombinant inbred lines were assayed for flowering time, total size, mass allocation, and fitness. Composite Interval Mapping identified two to five loci affecting these traits. These were well supported in more powerful Multiple and Bayesian interval mapping analyses that indicated that additional QTL, as well as epistatic interactions also affect the traits. The posterior distribution of the number of QTL peaked at five to eight additive loci and one to two interactions, but the specific locations of the additional loci could not be determined with certainty. In most cases in which loci for separate traits mapped to similar locations, explicit tests supported pleiotropy over close linkage of separate loci. Alleles that hastened first flowering generally reduced vegetative mass, increased reproductive mass, and were associated with high fitness. Because effects on mass allocation generally cancelled one another, few loci affected total plant size. Only one QTL affected vegetative mass independent of reproductive mass and this locus had little effect on fitness. Thus selection acts to shift the mass allocation toward greater reproductive allocation, because the correlated decrease in vegetative mass poses only a minor fitness cost.

Quantitative Trait Locus Mapping of Genes Under Selection Across Multiple Years and Sites in Avena barbata: Epistasis, Pleiotropy, and Genotype-by-Environment Interactions

The genetic architecture of variation in evolutionary fitness determines the trajectory of adaptive change. We identified quantitative trait loci (QTL) affecting fitness in a mapping population of recombinant inbred lines (RILs) derived from a cross between moist- and dry- associated ecotypes of Avena barbata. We estimated fitness in 179 RILs in each of two natural environments in each of 4 years. Two loci account for over half of the variation in geometric mean fitness across environments. These loci are associated in repulsion phase in the wild ecotypes, suggesting the potential for strong transgressive segregation, but also show significant epistasis giving hybrid breakdown. This epistasis is the result of sharply lower fitness in only one of the recombinant genotypes, suggesting that the loci may contain synergistically acting mutations. Within each trial (year/site combination), we can explain less of the variation than for geometric mean fitness, but the two major loci are associated with variation in fitness in most environments. Tests for pleiotropic effects of QTL on fitness in different environments reveal that the same loci are under selection in all trials. Genotype-by-environment interactions are significant for some loci, but this reflects variation in the strength, not the direction of selection.