Abstract
Evolutionary analyses aimed at detecting the molecular signature of selection during crop domestication and/or improvement can be used to identify genes or genomic regions of likely agronomic importance. Here, we describe the DNA sequence-based characterization of a pool of candidate genes for crop-related traits in sunflower. These genes, which were identified based on homology to genes of known effect in other study systems, were initially sequenced from a panel of improved lines. All genes that exhibited a paucity of sequence diversity, consistent with the possible effects of selection during the evolution of cultivated sunflower, were then sequenced from a panel of wild sunflower accessions an outgroup. These data enabled formal tests for the effects of selection in shaping sequence diversity at these loci. When selection was detected, we further sequenced these genes from a panel of primitive landraces, thereby allowing us to investigate the likely timing of selection (i.e., domestication vs. improvement). We ultimately identified seven genes that exhibited the signature of positive selection during either domestication or improvement. Genetic mapping of a subset of these genes revealed co-localization between candidates for genes involved in the determination of flowering time, seed germination, plant growth/development, and branching and QTL that were previously identified for these traits in cultivated × wild sunflower mapping populations.
Introduction
Strong directional selection is thought to be responsible for the dramatic phenotypic differences between domesticated lineages and their wild progenitors [1], [2]. Genetic map-based approaches, including both QTL and association analyses, have been used to identify numerous genomic regions and, in some cases, genes underlying these phenotypic transitions (e.g., fw2.2, [3]; fw3.2 [4], [5] tb1, [6]; sh4, [7]). An alternative to mapping studies is the use of molecular population genetic methods to identify genes or genomic regions that may have experienced past selection. These efforts typically involve statistical tests to determine if the observed pattern of genetic diversity in a particular gene or genomic region can be explained by the standard neutral model (e.g., [8]–[13]). Rejection of the null hypothesis of neutrality provides evidence of past selection.
Overall, crop lineages are expected to exhibit a genome-wide loss of genetic diversity relative to their wild progenitors due to the occurrence of population bottlenecks during domestication and/or improvement [2], [14]. But because selection influences genetic diversity in a locus-specific manner, genes targeted by positive selection will exhibit a greater than expected loss of diversity as compared to the genome-wide, neutral expectation [12], [13], [15]. Importantly, this provides a means for identifying genes, or at least genomic regions, that are likely to be of agronomic importance even though they may be recalcitrant to map-based analyses due to a lack of segregating variation within the crop lineage. Here, we describe molecular evolutionary analyses aimed at identifying genes that were targeted by selection during the evolution of cultivated sunflower (Helianthus annuus L.) from amongst a pool of candidates identified based on homology to genes of known effect from other study systems.
Cultivated sunflower was domesticated from wild sunflower (both H. annuus) approximately 4,000 years ago by Native Americans as a source of edible seeds and as well as for non-food purposes (e.g., as a source of dyes for textiles; [16]). More recently, sunflower has been the subject of intensive breeding as it has been transformed into a globally-important oilseed crop [17]. Wild sunflower exhibits seed dormancy, variable flowering time, extensive and variable branching, and it also produces relatively small seeds that are dispersed upon maturity (i.e., the mature heads “shatter”). In contrast, cultivated sunflower typically exhibits a loss of seed dormancy, more rapid/consistent flowering, strong apical dominance (i.e., a loss of branching), and considerably larger seeds that are retained in the head until harvest. Previous studies have primarily employed map-based approaches to identify genomic regions involved in the evolution of cultivated sunflower (e.g., [18]–[21]), though evolutionary analyses have also shown great promise [22]–[24].
In the present study, we mined the literature for genes from other species that are known to influence traits related to the evolution of cultivated sunflower. These included genes with known effects on floral development and flowering time, seed/fruit development, germination, plant growth/development, and branching. We then identified homologs of these genes in sunflower and sequenced them from panels of wild, primitive, and improved sunflowers. These data allowed us to test for evidence of positive selection during the domestication and/or improvement of sunflower. When possible, we also genetically mapped genes showing evidence of selection and compared their positions to those of QTL that had previously been mapped in cultivated x wild sunflower mapping populations. We found strong evidence for positive selection in a number of these genes as well as evidence of QTL co-localization in several cases. As such, these genes are excellent candidates for future functional studies aimed at understanding the molecular mechanisms underlying the evolution of cultivated sunflower.
Materials And Methods
Gene identification and primer design
To identify candidates for genes underlying traits related to sunflower domestication and improvement, we searched the literature for genes influencing relevant aspects of floral development and flowering time, seed/fruit development, seed germination, plant growth/development, and branching. We then performed BLAST searches of these genes against sunflower expressed sequence tags (ESTs) from the Compositae Genome Project EST Database (http://compgenomics.ucdavis.edu/) as well as the reference transcriptome assembly from Bachlava et al. [25]. Reciprocal best BLAST hits with an E-value of less than 10E-10 were identified as putative sunflower homologs and retained for further analysis (Table S1). Primers specific to a portion of each sunflower unigene identified via BLAST were then designed using either PrimerPlus 3.0 (http://www.bioinformatics.nl/) or PrimerQuest (http://www.idtdna.com/). To help avoid designing primers across splice sites, we used a tblastx-based intron finding Perl script (http://www.citrusgenome.ucr.edu/usa/ucr/Files.php) with Arabidopsis genome sequence information (v. 10) available from TAIR (http://www.arabidopsis.org/) to identify putative intron positions in sunflower unigenes. The resulting primer sequences can be found in Table S2. We also included a set of 11 presumptively neutral control genes that were previously identified by Chapman et al. [22] (Table S2).
Plant materials and DNA sequencing
The focus of this study was a collection of 28 H. annuus individuals including 8 wild sunflowers, 6 primitive domesticates (i.e., Native American landraces which represent an intermediate stage between wild sunflower and modern cultivars), and 14 improved lines (Table 1). Achenes for these individuals were obtained, with permissions, from the USDA North Central Regional Plant Introduction Station (NCRPIS) and French National Institute for Agricultural Research (INRA). The improved lines included the parents of a well-characterized sunflower recombinant inbred line (RIL) mapping population (RHA 280 and RHA 801) as well as the “Core 12” from Mandel et al. [26], which includes 12 inbred lines that capture ca. 50% of the allelic diversity present within the cultivated sunflower gene pool. We also included two outgroups: H. argophyllus, which is sister to H. annuus, and H. petiolaris, another closely related species that is sister to the H. annuus/H. argophyllus clade. A single individual from each of the 28 genotypes was grown to the seedling stage, and total DNA was extracted from each using a CTAB extraction protocol [27] and quantified using Picogreen (Applied Biosystems). The quantity/quality of DNA was also evaluated using a Nanodrop 1000 spectrophotometer. For candidate gene sequencing, we employed a tiered approach, as follows: (1) we first sequenced all candidate genes in the improved panel; (2) following the recommendations of Yamasaki et al. [28] and Chapman et al. [29], those candidates that had no or very low nucleotide diversity (π<0.01) in the improved panel were retained for sequencing in the wild panel and the outgroups, thereby enabling tests for selection; and (3) when a gene showed evidence for selection in the improved panel, it was also sequenced in the panel of primitive accessions. This last piece of data allowed us to further infer the likely timing of selection (i.e., domestication vs. improvement by investigating these genes in a panel containing primitive sunflower varieties vs. recently improved sunflower varieties).
Table 1. List of sunflower accessions analyzed in this study.
| Panel | Name | USDA Accession Number |
| Wild | Ames 14400 | PI 649851 |
| Ann-1114 | PI 613727 | |
| Ames 1473 | PI 413027 | |
| Ames 1455 | PI 413011 | |
| Ames 1516 | PI 413067 | |
| Ames 23238 | PI 649853 | |
| Ames 23940 | PI 649854 | |
| Ann-646 | PI 435552 | |
| Primitive | Havasupai | PI 369358 |
| Hidatsa | PI 600721 | |
| Hopi | PI 432504 | |
| Mandan | PI 600717 | |
| Maiz Negro | PI 650761 | |
| Seneca | PI 369360 | |
| Improved | Mammoth | PI 476853 |
| HA 234 | PI 599778 | |
| HA 316 | NSL 208764 | |
| HA 404 | PI 597368 | |
| HA 821 | PI 599984 | |
| RHA 280 | PI 552943 | |
| RHA 328 | NSL 202284 | |
| RHA 358 | PI 531071 | |
| VIR 847 | PI 386230 | |
| RHA 408 | PI 603989 | |
| RHA 426 | PI 617099 | |
| RHA 801 | PI 599768 | |
| SF 33* | --- | |
| SF 230* | --- |
*Accessions from the French National Institute for Agricultural Research.
PCR was performed in a total volume of 20 µL containing 5 ng of template DNA, 30 mM Tricine pH 8.4-KOH, 50 mM KCl, 2 mM MgCl2, 125 µM of each dNTP, 0.2 µM reverse primer, 0.2 µM forward primer and 2 units of Taq polymerase. The PCR conditions involved a ‘touchdown’ protocol, as follows: 3 min at 95C; 10 cycles of 30 s at 94C, 30 s at 65C and 45 s at 72C, annealing temperature decreasing to 55C by 1C per cycle, followed by 30 cycles of 30 s at 94C, 30 s at 55C, 45 s at 72C, followed by 20 min at 72C. PCR products were checked for single-banded amplification via electrophoresis on 1% agarose gels. Amplification conditions were modified for loci that exhibited weak or non-specific amplification (i.e., faint or multiple bands, respectively) by either decreasing (i.e., starting at 60C and descending to 50C) or increasing (i.e., starting at 70C and descending to 60C) the annealing temperature.
PCR products were treated with 4 units Exonuclease I and 0.8 units Shrimp Alkaline Phosphatase (USB) at 37C for 45 min followed by enzyme denaturation at 80C for 15 min to prepare for sequencing using BigDye v3.1 (Applied Biosystems). The sequencing reactions were cleaned using Sephadex (Amersham) before being run on an ABI 3730xl (Applied Biosystems). In cases where direct sequencing results were unclear due to unresolvable heterozygous bases, indels, or short repeats, PCR products were TA-cloned into pGEM-T vectors (Promega), transformed into competent Escherichia coli (JM109; Promega), and screened for the presence of an insert. At least five positive colonies per individual were then sequenced as above except that vector primers [T7 and SP6] were used. Sequences have been deposited in the National Center for Biotechnology Information (NCBI) as BioProject PRJNA248055.
Sequence analyses and tests for selection
For all genes, sequences were aligned using Sequencher version 4.10 (GeneCodes), and FASTA files were generated for each. These FASTA files were then imported into DnaSP version 4.50.2 [30] for analysis. Where possible, individuals exhibiting heterozygous bases were resolved into haplotypes using the PHASE algorithm in DnaSP (or they were cloned and re-sequenced; see above). We then used DnaSP to compute the number of synonymous segregating sites (S), synonymous nucleotide diversity (π), Watterson's [31] estimate of synonymous diversity (θ), number of segregating indels, and the synonymous genetic distance from the outgroup for each gene. The distance (D), from the outgroup was determined by calculating the number of synonymous segregating sites in all pairwise comparisons among sequenced individuals within each panel and the outgroup and then averaging to obtain D (the authors of the program recommend using one sequence from each species; we used all individuals within a panel in order to provide a more robust value for D). We also compared levels of genetic diversity amongst the three panels: wild, primitive (for those genes with preliminary evidence of selection), and improved. For these comparisons, S and the angular transformation of π and θ values were analyzed. For all genes that were sequenced in all three panels, two-factor ANOVAs (panel and locus) were performed using JMP version 9 (SAS Institute, Cary, NC) and posterior Tukey-Kramer tests were used to test for significant differences amongst means.
For the selection analyses, we used the maximum likelihood (ML) version [32] of the Hudson-Kreitman-Aguade (HKA) test [33], which allows for an explicit test of selection at individual loci in a multilocus framework. The neutral theory of molecular evolution [34] predicts that the amount of within-species polymorphism should be correlated with levels of between-species divergence. The ML-HKA test evaluates this prediction in a locus-specific fashion, thereby allowing for the identification of individual genes showing evidence of selection. It does this by comparing the fit of two models to the observed data. In one model, all loci (a set of neutral controls +a locus of interest) are assumed to be evolving neutrally. In the second model, the locus of interest is deemed to be under selection. Significance is then evaluated by comparing twice the difference in the likelihoods of the two models against a chi-square distribution with one degree of freedom [35].
We first confirmed that the collection of neutral genes utilized herein were not themselves under selection. To do this, we performed a “round-robin” test of all 11 putative neutral genes against each other to confirm selective neutrality (i.e., that selection has not influenced their pattern of nucleotide polymorphism). For each gene, this entailed using the ML-HKA test to compare two models, one model in which all 11 genes were assumed to be neutral, and one in which 10 genes are neutral and one is selected. This process was repeated with five different seed numbers for each of the 11 putatively neutral genes in each of the panels and none exhibited evidence of selection.
Following confirmation that our control loci were indeed behaving in a neutral fashion, we performed the ML-HKA test for each of the candidate genes of interest. This initially involved comparing the levels of polymorphism and divergence in the wild panel and the improved panel. As noted above, when a gene showed significant evidence of positive selection in the improved lines, we also sequenced it in the primitive panel and tested for selection at that stage. All ML-HKA tests were performed with five different seed numbers and a chain length of 100,000 as recommended by the authors. The resulting maximum likelihoods were averaged across the five replicates and used to perform a likelihood-ratio test.
Genetic mapping of candidate genes
Candidate genes that demonstrated evidence of positive selection during domestication and/or improvement were screened for polymorphism in eight arbitrarily chosen individuals of one of two recombinant inbred line (RIL) mapping populations via Sanger sequencing: an improved x wild sunflower cross (HA89 x ANN1238; [18], [36]) for domestication candidates and an improved x primitive sunflower cross (NMS373 x Hopi; [37]) for improvement candidates. When a mappable polymorphism was identified, the locus was amplified from a larger set of 96 RILs from the appropriate cross and scored as either a length variant or via PCR-restriction fragment length polymorphism (PCR-RFLP). Loci were added to previously published linkage maps using either the data and methods of Baack et al. [36] for the HA89 x ANN1238 RILs or Bowers et al. [37] for the NMS373 x Hopi RILs. If no polymorphism in the amplified region was readily identified, we used BLAST similarity of the selected candidate genes to the consensus genetic map of Bowers et al. [37] or to an existing sequence-based map [38] to locate the genomic position of the locus. When possible, we also compared the genetic map positions of genes under selection to those of previously mapped QTL for the phenotypes of interest. This was done by projecting QTL from several previous studies [18], [19], [39], [40] onto the sunflower consensus map [37] based on shared markers. For the QTL mapping populations of Burke et al. [18] and Wills et al. [19], we used the sunflower CMap database (http://sunflower.uga.edu/cmap/) to identify markers that flanked the QTL of interest (i.e, those located near candidate genes for the same trait) and were also present on the sunflower consensus map [37]. We then used the genetic positions from the consensus map to display the QTL relative to the positions of the candidate genes (see below; note: when available, we used the 2-LOD interval for marking QTL regions as presented in the studies). The studies of Dechaine et al. [39] and Brunick [40] were not included in the CMap database, so the shared flanking markers were identified from the original source documents and projected as above.
Results And Discussion
As expected, we observed an overall, progressive loss of genetic diversity in the primitive and improved sunflower lines as compared to their wild progenitor (Table 2). Of the 76 candidate genes that we sequenced, 24 exhibited little or no nucleotide variation in a panel of 14 improved sunflower lines (π<0.0202, though most of these 24 were much lower than this value; see Table 3 and Table S3 for additional statistics), consistent with the possibility that they experienced positive selection during domestication and/or improvement. We then sequenced these 24 genes in a geographically diverse panel of eight wild sunflower individuals as well as outgroups and used the resulting data to test for selection. Seven of these genes exhibited significant departures from neutrality in the ML-HKA tests (Table 3; Figure 1), thereby providing strong evidence of past selection. Note also that some of the candidate genes harbored low genetic diversity in the wild panel as compared to the neutral genes. In fact, two candidate genes for branching (IPT5 and MAX2) were shown to be under selection in the wild. After sequencing these genes in the primitive landraces, we found that LATERAL SUPPRESSOR (LAS) showed evidence for selection in both the primitive and improved lines. Five other genes, including LOW PHOSPHATE ROOT (LPR), MORE AXILLARY GROWTH 2 (MAX2), PHENYLALANINE AMMONIA-LYASE 1 (PAL1), PHYTOCHROME B (PHYB), and RGA-LIKE 2 (RGL2), showed evidence of selection in the improved lines only. We thus conclude that LAS likely experienced selection during the initial phase of sunflower domestication, whereas selection on the remainder was likely restricted to the subsequent period of improvement. Note that a reliable PCR product was not obtained for ISOPENTENYLTRANSFERASE 5 in the primitive lines. We were thus unable to investigate the timing of selection for this gene.
Table 2. Population genetic diversity statistics for candidate and neutral/control genes.
| Type | Panel | N | S (SE) | Sig.1 | π (SE) | Sig.1 | θ (SE) | Sig.1 |
| Candidate | W | 24 | 6.25 (1.48) | X | 0.022 (0.005) | X | 0.024 (0.005) | X |
| P | 6 | 3.77 (1.68) | XY | 0.012 (0.008) | XY | 0.013 (0.006) | XY | |
| I | 24 | 0.91 (0.33) | Y | 0.0028 (0.001) | Y | 0.0029 (0.001) | Y | |
| Neutral | W | 11 | 7.18 (1.55) | A | 0.039 (0.006) | A | 0.043 (0.008) | A |
| P | 11 | 3.55 (0.93) | B | 0.027 (0.005) | B | 0.025 (0.005) | B | |
| I | 11 | 3.27 (1.10) | B | 0.020 (0.005) | B | 0.014 (0.004) | C |
Panel: W = wild, P = primitive, I = improved; N = number of genes sequenced; S = number of segregating synonymous sites; π = nucleotide diversity for synonymous sites; θ = Waterson's theta for synonymous sites; Sig. = results of posterior Tukey-Kramer test with different letters representing significantly different values. ANOVA results: Neutral genes: θ (F 2, 20 = 8.58, p<0.0001), π (F 2, 20 = 8.73, p<0.0001), S (F 2, 20 = 4.89, p = 0.0009). Candidate genes: π (F 2, 10 = 5.26, p = 0.001), θ (F 2, 10 = 5.19, p = 0.01), S, (F 2, 10 = 3.56, p = 0.03).
ANOVA for candidate genes performed on the six candidate genes that were sequenced in all three panels.
Table 3. Population genetic diversity statistics for the invariant genes tested for evidence of positive selection.
| Gene | Trait | Panel | L | l | S | π | θ | Sig. |
| ACTIN-RELATED PROTEIN 7 | Pleiotropic effects on | W | 549 | 48.67 | 2 | 0.01761 | 0.01585 | ns |
| plant development | P | - | - | - | - | - | - | |
| I | 549 | 48.67 | 0 | 0 | 0 | ns | ||
| BLIND | Branching | W | 383 | 12.17 | 0 | 0 | 0 | ns |
| P | - | - | - | - | - | - | ||
| I | 383 | 12.17 | 0 | 0 | 0 | ns | ||
| CHALCONE SYNTHASE | Plant growth; regulation | W | 310 | 40.81 | 0 | 0 | 0 | ns |
| of auxin | P | - | - | - | - | - | - | |
| I | 310 | 40.67 | 0 | 0 | 0 | ns | ||
| CONSTANS | Flowering | W | 483 | 114.17 | 9 | 0.03213 | 0.02787 | ns |
| P | - | - | - | - | - | - | ||
| I | 483 | 114.11 | 4 | 0.00518 | 0.00919 | ns | ||
| CYTOKININ OXIDASE/ | Plant growth | W | 375 | 88.67 | 3 | 0.01015 | 0.0136 | ns |
| DEHYDROGENASE 1 | P | - | - | - | - | - | - | |
| I | 375 | 88.67 | 0 | 0 | 0 | ns | ||
| ELONGATION FACTOR | Plant growth | W | 380 | 37.98 | 2 | 0.00943 | 0.01587 | ns |
| BINDING SITE 1B | P | - | - | - | - | - | - | |
| I | 380 | 38 | 0 | 0 | 0 | ns | ||
| FASCIATED | Fruit development | W | 435 | 43.17 | 0 | 0.02978 | 0.0268 | ns |
| P | - | - | - | - | - | - | ||
| I | 435 | 43.17 | 0 | 0 | 0 | ns | ||
| GLABRA 2 | Seed development | W | 639 | 88.31 | 7 | 0.028370.02493 | 0.02493 | ns |
| P | - | - | - | - | - | - | ||
| I | 639 | 89 | 4 | 0.0124 | 0.01204 | ns | ||
| GLABRA2-EXPRESSION | Cell fate/division affecting | W | 625 | 90.04 | 0 | 0 | 0 | ns |
| MODULATOR | plant development | P | - | - | - | - | - | - |
| I | 625 | 90.58 | 0 | 0 | 0 | ns | ||
| HEADING DATE 6 | Flowering | W | 737 | 38.67 | 0 | 0 | 0 | ns |
| P | - | - | - | - | - | - | ||
| I | 737 | 38.67 | 0 | 0 | 0 | ns | ||
| INOSITOL POLYPHOSPHATE | Branching | W | 367 | 86.11 | 11 | 0.02669 | 0.0385 | ns |
| 6-/3-KINASE 2B | P | - | - | - | - | - | - | |
| I | 367 | 85.98 | 2 | 0.00391 | 0.00598 | ns | ||
| ISOPENTENYLTRANSFERASE 5 | Plant growth | W | 486 | 116.52 | 1 | 0.00107 | 0.00108 | * |
| P | N/A | N/A | N/A | N/A | N/A | N/A | ||
| I | 486 | 116.50 | 0 | 0 | 0 | ** | ||
| LATERAL SUPPRESSOR | Branching | W | 532 | 103.67 | 7 | 0.02244 | 0.02035 | ns |
| P | 532 | 103.67 | 0 | 0 | 0 | * | ||
| I | 532 | 103.67 | 0 | 0 | 0 | ** | ||
| LOW PHOSPHATE ROOT | Root growth/development | W | 413 | 97.75 | 10 | 0.02774 | 0.03391 | ns |
| P | 413 | 98.06 | 11 | 0.01868 | 0.03715 | ns | ||
| I | 413 | 98 | 0 | 0 | 0 | *** | ||
| MORE AXILLARY GROWTH 2 | Branching | W | 468 | 86.5 | 1 | 0.00165 | 0.00364 | * |
| P | 468 | 86.44 | 4 | 0.00774 | 0.01532 | ns | ||
| I | 468 | 86.5 | 0 | 0 | 0 | ** | ||
| MORE AXILLARY GROWTH 4 | Branching | W | 104 | 0 | - | - | - | - |
| P | - | - | - | - | - | - | ||
| I | 104 | 0 | - | - | - | - | ||
| METHYL-CPG BINDING 9 | Branching | W | 227 | 52.25 | 11 | 0.05391 | 0.06345 | ns |
| P | - | - | - | - | - | - | ||
| I | 225 | 52.37 | 4 | 0.0202 | 0.0202 | ns | ||
| PHENYLALANINE | Plant growth | W | 473 | 105.54 | 12 | 0.02178 | 0.03427 | ns |
| AMMONIA-LYASE 1 | P | 473 | 105.5 | 1 | 0.00158 | 0.00314 | ns | |
| I | 473 | 105.5 | 0 | 0 | 0 | * | ||
| PHYTOCHROME A | Flowering | W | 447 | 46.5 | 2 | 0.02085 | 0.01424 | ns |
| P | - | - | - | - | - | - | ||
| I | 447 | 46.5 | 0 | 0 | 0 | ns | ||
| PHYTOCHROME B | Flowering | W | 683 | 166.83 | 13 | 0.02648 | 0.02639 | ns |
| P | 683 | 166.83 | 5 | 0.00908 | 0.00992 | ns | ||
| I | 683 | 166.83 | 0 | 0 | 0 | ** | ||
| PHYTOCHROME E | Flowering | W | 457 | 103.48 | 14 | 0.0379 | 0.04254 | ns |
| P | - | - | - | - | - | - | ||
| I | 457 | 103.42 | 5 | 0.01029 | 0.01267 | ns | ||
| PIN-FORMED 1 | Root/shoot development | W | 411 | 101.92 | 11 | 0.02743 | 0.03253 | ns |
| P | - | - | - | - | - | - | ||
| I | 411 | 101.93 | 2 | 0.0063 | 0.00504 | ns | ||
| PHOTOPERIOD -H1 | Flowering | W | 246 | 50.31 | 3 | 0.017560.01797 | 0.01797 | ns |
| P | - | - | - | - | - | - | ||
| I | 246 | 50.33 | 1 | 0.00841 | 0.00511 | ns | ||
| RGA-LIKE 2 | Germination | W | 377 | 89.5 | 31 | 0.11417 | 0.12297 | ns |
| P | 377 | 89.06 | 13 | 0.07069 | 0.04834 | ns | ||
| I | 377 | 88.83 | 0 | 0 | 0 | *** |
Panel, W = wild, P = primitive, I = improved; L = alignment length in basepairs; l = number of synonymous sites; S = number of segregating synonymous sites; π = nucleotide diversity for synonymous sites; θ = Waterson's theta for synonymous sites; Sig. = ML-HKA significance: ns = not significant, P<0.001 = ***, P<0.01 = **, P<0.05 = *. Bold genes are those that showed significant evidence of selection. Note: we were unable to successfully sequence the IPT5 gene in P.
Figure 1. Nucleotide diversity in wild, primitive, and improved sunflower for the genes shown to be under positive selection during the evolution of cultivated sunflower.
Error bars indicate standard deviations. Note that we were unable to obtain sequence information for the IPT5 gene in the primitive panel.
One of the selected genes, PHYB, is a photoperiod response gene that is thought to play a role in the transition from vegetative to reproductive growth (e.g., [41], [42]). This gene also has a possible role in seed germination [43] (see discussion of germination and seed dormancy in sunflower below). The control of flowering is an important agricultural trait, and the evolution of flowering time is known to have played a critical role in the success of many crop species, including sunflower [17], [23], [44], [45]. Wild sunflower exhibits extensive variation in flowering time [46], [47], whereas the primitive sunflowers typically flower later in the season [48], and modern varieties have been selected for relatively early flowering [44], [49] making it possible to produce sunflower across a broader range of environments [17].
Interestingly, Blackman et al. [23] included PHYB in their analysis of the role of flowering time genes in the evolution of cultivated sunflower and found marginally significant evidence for selection during improvement (P = 0.07). Though PHYB was found to have identical predicted protein sequences in the parents of an improved x wild sunflower mapping population that exhibits extensive variation in flowering time, this gene was consistently expressed at higher levels in the cultivar parent. We also found that PHYB co-localized with a previously identified QTL in an improved x wild sunflower mapping study ([39]; Figure 2). These results suggest that post-domestication selection may have targeted a cis-regulatory element that influences PHYB expression and that the diversity loss within PHYB itself is a byproduct of this selection.
Figure 2. Co-localization of candidates for genes under selection and QTL for flowering time, branching, germination.
, and a number of plant growth and development traits that were previously identified in an improved x wild (shown in blue) or in both an improved x wild and a primitive x wild (shown in purple) sunflower QTL mapping population. QTL presented as 1-LOD are marker with an asterisk. All QTL and candidate gene positions are presented in the context of the sunflower consensus map (Bowers et al. 2012).
Like flowering time, plant architecture changed dramatically during the evolution of cultivated sunflower. Initially, selection for increased apical dominance is thought to have resulted in a complete loss of branching [48], [50], [51]. In the mid-20th century, however, apical branching was re-introduced in a subset of cultivated sunflower lines as part of a transition to hybrid breeding and a concomitant desire to produce male lines with indeterminate flowering [52]. Consequently, branching is polymorphic within the cultivated sunflower gene pool. This re-introduction of branching is, however, due to the effects of a recessive allele at a single locus that maps to the upper third of linkage group (LG) 10 [53]. As such, other branching-related genes that were targeted by selection during sunflower domestication or improvement would still be expected to harbor low diversity. In fact, homologs of three genes known to influence branching in other species exhibited evidence of positive selection in sunflower, including one during domestication (LAS), one during improvement (MAX2), and one with unknown timing (IPT5) (Figure 1). LAS is a transcription factor and a positive regulator of bud, or branch, initiation [54]–[56], MAX2 is an F-box protein that is thought to influence lateral shoot growth [57], and IPT5 is known to be involved in cytokinin biosynthesis [58]. The genomic locations of LAS and IPT5 could not be determined in this study, but MAX2 (which also showed evidence of selection in wild sunflower) co-localized with a previously identified QTL for branching on LG 17.
Of the genes selected for analysis due to their potential role in other aspects of plant growth and development, two (LPR and PAL1) showed evidence of positive selection during improvement. LPR is a multicopper oxidase affecting root growth/development in Arabidopsis [59], whereas PAL1 is a component of the phenylpropanoid pathway having broad effects on plant growth/development [60]. These genes co-localized with previously known QTL for numerous plant growth traits in sunflower including inflorescence size, plant architecture, leaf shape, and seed size [18], [19], [36] (Figure 2), though a better understanding of the likely phenotypic effects of variation at these genes awaits further study. Finally, RGL2, which is a DELLA protein that represses germination in Arabidopsis [61], exhibited evidence of selection during improvement. Wild sunflower exhibits strong seed dormancy whereas the primitive and improved varieties have little or no dormancy [40]. Interestingly, RGL2 co-localized with a QTL for seed dormancy in an improved x wild sunflower cross [40] (Figure 2). These findings make this genomic region, and the RGL2 gene in particular, a promising target for functional studies involving seed dormancy and germination.
Of course, it is always possible that genes bearing the signature of selection such as those identified above were not themselves targeted by selection. Rather, these genes may simply be linked to the actual targets of selection (i.e., genetic hitchhiking). Though early studies of linkage disequilibrium (LD) in sunflower found that it decayed relatively rapidly (e.g., [62], [63]), more recent analyses have revealed the presence of extended islands of LD within the genome [21]. Importantly, none of our mapped genes that exhibit evidence of selection fall within regions that exhibit elevated LD in the sunflower genome. This pattern of selected genes falling in genomic regions with lower overall LD, along with multiple instances of co-localization with QTL for crop-related traits supports the notion that they were indeed targeted by selection. Through the joint application of molecular population genetic analyses and trait-based mapping approaches, we have thus identified a set of promising loci for future functional studies aimed at understanding the molecular basis of sunflower evolution.
Acknowledgments
We would like to thank Eleni Bachlava and Jeff Roeder for assistance in the laboratory and Mark Chapman for help with the selection analyses. We would also like to thank two anonymous reviewers for comments on a previous version of this manuscript.
Supporting Information
List of candidate genes, reference taxa where the gene was identified, and functional traits of interest.
(DOCX)
Primer sequences and information for candidate genes and control loci (second tab).
(XLSX)
Statistics for candidate and neutral genes for wild, primitive, and improved individuals.
(XLSX)
Funding Statement
This work was supported by funding from the USDA National Institute of Food and Agriculture (2008-35300-19263) and the NSF Plant Genome Research Program (DBI-0820451). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
References
- 1. Hammer K (1984) Das Domestikationssyndrom. Die Kult 32: 11–34. [Google Scholar]
- 2. Doebley JF, Gaut BS, Smith BD (2006) The molecular genetics of crop domestication. Cell 127: 1309–1321. [DOI] [PubMed] [Google Scholar]
- 3. Nesbitt TC, Tanksley SD (2001) fw2.2 directly affects the size of developing tomato fruit, with secondary effects on fruit number and photosynthate distribution. Plant Physiol 127: 575–583. [PMC free article] [PubMed] [Google Scholar]
- 4. Zhang N, Brewer MT, van der Knaap E (2012) Fine mapping of fw3.2 controlling fruit weight in tomato. Theor Appl Genet 125: 273–284. [DOI] [PubMed] [Google Scholar]
- 5. Chakrabarti M, Zhang N, Sauvage C, Muños S, Blanca J, et al. (2013) A cytochrome P450 regulates a domestication trait in cultivated tomato. Proc Natl Acad Sci U S A 110: 17125–17130. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Doebley J, Stec A, Gustus C (1995) Teosinte Branched1 and the Origin of Maize: Evidence for Epistasis and the Evolution of Dominance. Genetics 141: 333–346. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Li C, Zhou A, Sang T (2006) Rice domestication by reducing shattering. Science 311: 1936–1939. [DOI] [PubMed] [Google Scholar]
- 8. Lewontin RC, Krakauer J (1973) Distribution of gene frequency as a test of the theory of the selective neutrality of polymorphisms. Genet 74: 175–195. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Nielsen R (2005) Molecular signatures of natural selection. Annu Rev Genet 39: 197–218. [DOI] [PubMed] [Google Scholar]
- 10. Wright SI, Gaut BS (2005) Molecular population genetics and the search for adaptive evolution in plants. Mol Biol Evol 22: 506–519. [DOI] [PubMed] [Google Scholar]
- 11. Biswas S, Akey JM (2006) Genomic insights into positive selection. Trends Genet 22: 437–446. [DOI] [PubMed] [Google Scholar]
- 12. Ross-Ibarra J, Morrell PL, Gaut BS (2007) Colloquium Papers: Plant domestication, a unique opportunity to identify the genetic basis of adaptation. Proc Natl Acad Sci 104: 8641–8648. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Burke JM, Burger JC, Chapman M a (2007) Crop evolution: from genetics to genomics. Curr Opin Genet Dev 17: 525–532. [DOI] [PubMed] [Google Scholar]
- 14. Tanksley SD, McCouch SR (1997) Seed Banks and Molecular Maps: Unlocking Genetic Potential from the Wild. Science 277: 1063–1066. [DOI] [PubMed] [Google Scholar]
- 15. Innan H, Kim Y (2004) Pattern of polymorphism after strong artificial selection in a domestication event. Proc Natl Acad Sci U S A 101: 10667–10672. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Soleri D (1993) DAC (1993) Hopi crop diversity and change. J Ethnobiol 13: 203–231. [Google Scholar]
- 17.Putt ED (1997) Early history of sunflower. In: Schneiter A, editor. Sunflower production and technology. Madison, WI: American Society of Agronomy. pp. 1–19.
- 18. Burke JM, Tang S, Knapp SJ, Rieseberg LH (2002) Genetic analysis of sunflower domestication. Genetics 161: 1257–1267. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Wills DM, Burke JM (2007) Quantitative trait locus analysis of the early domestication of sunflower. Genetics 176: 2589–2599. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Wills DM, Abdel-Haleem H, Knapp SJ, Burke JM (2010) Genetic architecture of novel traits in the Hopi sunflower. J Hered 101: 727–736. [DOI] [PubMed] [Google Scholar]
- 21. Mandel JR, Nambeesan S, Bowers JE, Marek LF, Ebert D, et al. (2013) Association mapping and the genomic consequences of selection in sunflower. PLoS Genet 9: e1003378. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Chapman MA, Pashley CH, Wenzler J, Hvala J, Tang S, et al. (2008) A genomic scan for selection reveals candidates for genes involved in the evolution of cultivated sunflower (Helianthus annuus). Plant Cell 20: 2931–2945. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Blackman BK, Rasmussen DA, Strasburg JL, Raduski AR, Burke JM, et al. (2011) Contributions of flowering time genes to sunflower domestication and improvement. Genet 187: 271–287. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Chapman M, Burke J (2012) Evidence of selection on fatty acid biosynthetic genes during the evolution of cultivated sunflower. TAG Theor Appl Genet 125: 897–907. [DOI] [PubMed] [Google Scholar]
- 25. Bachlava E, Taylor CA, Tang S, Bowers JE, Mandel JR, et al. (2012) SNP discovery and development of a high-density genotyping array for sunflower. PLoS One 7: e29814. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. Mandel JR, Dechaine JM, Marek LF, Burke JM (2011) Genetic diversity and population structure in cultivated sunflower and a comparison to its wild progenitor, Helianthus annuus L. Theor Appl Genet 123: 693–704. [DOI] [PubMed] [Google Scholar]
- 27. Doyle JL DJ (1987) A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochem Bull 19: 11–15. [Google Scholar]
- 28. Yamasaki M, Tenaillon MI, Vroh Bi I, Schroeder SG, Sanchez-Villeda H, et al. (2005) A large-scale screen for artificial selection in maize identifies candidate agronomic loci for domestication and crop improvement. Plant Cell 17: 2859–2872. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Chapman MA, Mandel JR, Burke JM (2013) Sequence validation of candidates for selectively important genes in sunflower. PLoS One 8: e71941. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30. Rozas J, Sanchez-DelBarrio JC, Messeguer X, Rozas R (2003) DnaSP, DNA polymorphism analyses by the coalescent and other methods. Bioinformatics 19: 2496–2497. [DOI] [PubMed] [Google Scholar]
- 31. Watterson GA (1975) Number of Segregating Sites in Genetic Models without Recombination. Theor Popul Biol 7: 256–276. [DOI] [PubMed] [Google Scholar]
- 32. Wright SI, Charlesworth B (2004) The HKA test revisited: a maximum-likelihood-ratio test of the standard neutral model. Genet 168: 1071–1076. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33. Hudson RR, Kreitman M, Aguadé M (1987) A test of neutral molecular evolution based on nucleotide data. Genet 116: 153–159. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Kimura M (1983) The Neutral Theory of Molecular Evolution. Cambridge, UK: University Press.
- 35. Wright SI, Charlesworth B (2004) The HKA Test Revisited. Genet 168: 1071–1076. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36. Baack EJ, Sapir Y, Chapman MA, Burke JM, Rieseberg LH (2008) Selection on domestication traits and quantitative trait loci in crop-wild sunflower hybrids. Mol Ecol 17: 666–677. [DOI] [PubMed] [Google Scholar]
- 37. Bowers JE, Bachlava E, Brunick RK, Rieseberg LH, Knapp SJ, et al. (2012) Development of a 10,000 locus genetic map of the sunflower genome based on multiple crosses. G3 GENES, GENOMES, GENET 2: 721–729. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38. Renaut S, Grassa CJ, Yeaman S, Moyers BT, Lai Z, et al. (2013) Genomic islands of divergence are not affected by geography of speciation in sunflowers. Nat Commun 4: 1827. [DOI] [PubMed] [Google Scholar]
- 39. Dechaine JM, Burger JC, Chapman MA, Seiler GJ, Brunick R, et al. (2009) Fitness effects and genetic architecture of plant-herbivore interactions in sunflower crop-wild hybrids. New Phytol 184: 828–841. [DOI] [PubMed] [Google Scholar]
- 40.Brunick RL (2007) Dissertation for the degree of Doctor of Philosophy in Horticulture presented on November 29, 2007. Title: Seed Dormancy in Domesticated and Wild Sunflowers (Helianthus).
- 41. Filiault DL, Wessinger CA, Dinneny JR, Lutes J, Borevitz JO, et al. (2008) Amino acid polymorphisms in Arabidopsis phytochrome B cause differential responses to light. Proc Natl Acad Sci U S A 105: 3157–3162. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42. Neff MM (2012) Light-mediated seed germination: connecting phytochrome B to gibberellic acid. Dev Cell 22: 687–688. [DOI] [PubMed] [Google Scholar]
- 43. Casal JJ, Sánchez RA (1998) Phytochromes and seed germination. Seed Sci Res 8: 317–329. [Google Scholar]
- 44. Goyne PJ, Schneiter AA, Cleary KC, Creelman RA, Stegmeier WD, et al. (1989) Sunflower Genotype Response to Photoperiod and Temperature in Field Environments. Agron J 81: 826. [Google Scholar]
- 45. Blackman BK (2013) Interacting duplications, fluctuating selection, and convergence: the complex dynamics of flowering time evolution during sunflower domestication. J Exp Bot 64: 421–431. [DOI] [PubMed] [Google Scholar]
- 46. Heiser CB (1954) Variation and subspeciation in the common sunflower, Helianthus annuus. Am Midl Nat 51: 287–305. [Google Scholar]
- 47. Blackman BK, Michaels SD, Rieseberg LH (2011) Connecting the sun to flowering in sunflower adaptation. Mol Ecol 20: 3503–3512. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48. Heiser CB (1951) The sunflower among the North American Indians. Proc Am Philos Soc 95: 432–448. [Google Scholar]
- 49. Goyne PJ, Schneiter AA (1987) Photoperiod Influence on Development in Sunflower Genotypes. Agron J 79: 704–709. [Google Scholar]
- 50. Heiser CB (1945) The Hopi sunflower. Missouri Bot Gard Bull 3: 163–166. [Google Scholar]
- 51.Rogers C, Thompson T, Seiler G (1982) Sunflower species of the United States. Bismark, ND: National Sunflower Association.
- 52.Fick G, Miller J (1997) Sunflower breeding. In: AA S, editor. Sunflower production and technology. Madison: American Society of Agronomy. pp. 395–440.
- 53. Bachlava E, Tang S, Pizarro G, Schuppert GF, Brunick RK, et al. (2010) Pleiotropy of the branching locus (B) masks linked and unlinked quantitative trait loci affecting seed traits in sunflower. Theor Appl Genet 120: 829–842. [DOI] [PubMed] [Google Scholar]
- 54. Schumacher K, Schmitt T, Rossberg M, Schmitz G, Theres K (1999) The Lateral suppressor (Ls) gene of tomato encodes a new member of the VHIID protein family. Proc Natl Acad Sci U S A 96: 290–295. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55. Schmitz G, Tillmann E, Carriero F, Fiore C, Cellini F, et al. (2002) The tomato Blind gene encodes a MYB transcription factor that controls the formation of lateral meristems. Proc Natl Acad Sci U S A 99: 1064–1069. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56. Greb T, Clarenz O, Schafer E, Muller D, Herrero R, et al. (2003) Molecular analysis of the LATERAL SUPPRESSOR gene in Arabidopsis reveals a conserved control mechanism for axillary meristem formation. Genes Dev 17: 1175–1187. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57. Stirnberg P, van De Sande K, Leyser HMO (2002) MAX1 and MAX2 control shoot lateral branching in Arabidopsis. Development 129: 1131–1141. [DOI] [PubMed] [Google Scholar]
- 58. Miyawaki K, Tarkowski P, Matsumoto-Kitano M, Kato T, Sato S, et al. (2006) Roles of Arabidopsis ATP/ADP isopentenyltransferases and tRNA isopentenyltransferases in cytokinin biosynthesis. Proc Natl Acad Sci U S A 103: 16598–16603. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 59. Svistoonoff S, Creff A, Reymond M, Sigoillot-Claude C, Ricaud L, et al. (2007) Root tip contact with low-phosphate media reprograms plant root architecture. Nat Genet 39: 792–796. [DOI] [PubMed] [Google Scholar]
- 60. Huang J, Gu M, Lai Z, Fan B, Shi K, et al. (2010) Functional analysis of the Arabidopsis PAL gene family in plant growth, development, and response to environmental stress. Plant Physiol 153: 1526–1538. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 61. Piskurewicz U, Jikumaru Y, Kinoshita N, Nambara E, Kamiya Y, et al. (2008) The gibberellic acid signaling repressor RGL2 inhibits Arabidopsis seed germination by stimulating abscisic acid synthesis and ABI5 activity. Plant Cell 20: 2729–2745. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62. Liu A, Burke JM (2006) Patterns of nucleotide diversity in wild and cultivated sunflower. Genet 173: 321–330. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 63. Kolkman JM, Berry ST, Leon AJ, Slabaugh MB, Tang S, et al. (2007) Single nucleotide polymorphisms and linkage disequilibrium in sunflower. Genet 177: 457–468. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
List of candidate genes, reference taxa where the gene was identified, and functional traits of interest.
(DOCX)
Primer sequences and information for candidate genes and control loci (second tab).
(XLSX)
Statistics for candidate and neutral genes for wild, primitive, and improved individuals.
(XLSX)