The Power and Perils of De Novo Domestication Using Genome Editing.

There is intense interest in using genome editing technologies to domesticate wild plants, or accelerate the improvement of weakly domesticated crops, in de novo domestication. Here, we discuss promising genetic strategies, with a focus on plant development. Importantly, genome editing releases us from dependence on random mutagenesis or intraspecific diversity, allowing us to draw solutions more broadly from diversity. However, sparse understanding of the complex genetics of diversity limits innovation. Beyond genetics, we urge the ethical use of indigenous knowledge, indigenous plants, and ethnobotany. De novo domestication still requires conventional breeding by phenotypic selection, especially in the development of crops for diverse environments and cultures. Indeed, uniting genome editing with selective breeding could facilitate faster and better outcomes than either technology alone. Domestication is complex and incompletely understood, involving changes to many aspects of plant biology and human culture. Success in de novo domestication requires careful attention to history and collaboration across traditional boundaries.

Stacking up RADSeq assembly programs: From complete hit to completely abysmal.

Decreasing sequencing costs have driven a rapid expansion of novel genotyping methods. One of these methods is the exploitation of restriction enzyme cut sites to generate genome-wide but reduced representation sequencing libraries (RRLs), alternatively termed genotyping by sequencing or restriction-site associated DNA sequencing. Without a reference genome, the resulting short sequence reads must be assembled de novo. There are many possible assembly programs, most not explicitly developed for RRL data, and we know little of their effectiveness. In this issue of Molecular Ecology Resources, LaCava et al. (2020) systematically evaluate six commonly used programs and two commonly varied parameters for complete and accurate assembly of RRLs, using simulated double digests of Homo sapiens and Arabidopsis thaliana genomes with varied mutation rates and types. The authors find substantial variation in performance across assembly programs. The most consistently high-performing assembler is infrequently used in their literature survey (CD-HIT; Li and Godzik, 2006), while several others fail to produce complete, accurate assemblies under many conditions. LaCava et al. additionally recommend best practices in parameter choice and evaluation of future assembly programs-advice that molecular ecologists working to assemble sequences of all kinds should take to heart.

Sunflower pan-genome analysis shows that hybridization altered gene content and disease resistance.

Domesticated plants and animals often display dramatic responses to selection, but the origins of the genetic diversity underlying these responses remain poorly understood. Despite domestication and improvement bottlenecks, the cultivated sunflower remains highly variable genetically, possibly due to hybridization with wild relatives. To characterize genetic diversity in the sunflower and to quantify contributions from wild relatives, we sequenced 287 cultivated lines, 17 Native American landraces and 189 wild accessions representing 11 compatible wild species. Cultivar sequences failing to map to the sunflower reference were assembled de novo for each genotype to determine the gene repertoire, or 'pan-genome', of the cultivated sunflower. Assembled genes were then compared to the wild species to estimate origins. Results indicate that the cultivated sunflower pan-genome comprises 61,205 genes, of which 27% vary across genotypes. Approximately 10% of the cultivated sunflower pan-genome is derived through introgression from wild sunflower species, and 1.5% of genes originated solely through introgression. Gene ontology functional analyses further indicate that genes associated with biotic resistance are over-represented among introgressed regions, an observation consistent with breeding records. Analyses of allelic variation associated with downy mildew resistance provide an example in which such introgressions have contributed to resistance to a globally challenging disease.

Combining population genomics and fitness QTLs to identify the genetics of local adaptation in Arabidopsis thaliana.

Evidence for adaptation to different climates in the model species Arabidopsis thaliana is seen in reciprocal transplant experiments, but the genetic basis of this adaptation remains poorly understood. Field-based quantitative trait locus (QTL) studies provide direct but low-resolution evidence for the genetic basis of local adaptation. Using high-resolution population genomic approaches, we examine local adaptation along previously identified genetic trade-off (GT) and conditionally neutral (CN) QTLs for fitness between locally adapted Italian and Swedish A. thaliana populations [Ågren J, et al. (2013) Proc Natl Acad Sci USA 110:21077-21082]. We find that genomic regions enriched in high FST SNPs colocalize with GT QTL peaks. Many of these high FST regions also colocalize with regions enriched for SNPs significantly correlated to climate in Eurasia and evidence of recent selective sweeps in Sweden. Examining unfolded site frequency spectra across genes containing high FST SNPs suggests GTs may be due to more recent adaptation in Sweden than Italy. Finally, we collapse a list of thousands of genes spanning GT QTLs to 42 genes that likely underlie the observed GTs and explore potential biological processes driving these trade-offs, from protein phosphorylation, to seed dormancy and longevity. Our analyses link population genomic analyses and field-based QTL studies of local adaptation, and emphasize that GTs play an important role in the process of local adaptation.

Genetic Costs of Domestication and Improvement.

The "cost of domestication" hypothesis posits that the process of domesticating wild species can result in an increase in the number, frequency, and/or proportion of deleterious genetic variants that are fixed or segregating in the genomes of domesticated species. This cost may limit the efficacy of selection and thus reduce genetic gains in breeding programs for these species. Understanding when and how deleterious mutations accumulate can also provide insight into fundamental questions about the interplay of demography and selection. Here we describe the evolutionary processes that may contribute to deleterious variation accrued during domestication and improvement, and review the available evidence for "the cost of domestication" in animal and plant genomes. We identify gaps and explore opportunities in this emerging field, and finally offer suggestions for researchers and breeders interested in understanding or avoiding the consequences of an increased number or frequency of deleterious variants in domesticated species.

TSPmap, a tool making use of traveling salesperson problem solvers in the efficient and accurate construction of high-density genetic linkage maps.

BACKGROUND: Recent advances in nucleic acid sequencing technologies have led to a dramatic increase in the number of markers available to generate genetic linkage maps. This increased marker density can be used to improve genome assemblies as well as add much needed resolution for loci controlling variation in ecologically and agriculturally important traits. However, traditional genetic map construction methods from these large marker datasets can be computationally prohibitive and highly error prone. RESULTS: We present TSPmap, a method which implements both approximate and exact Traveling Salesperson Problem solvers to generate linkage maps. We demonstrate that for datasets with large numbers of genomic markers (e.g. 10,000) and in multiple population types generated from inbred parents, TSPmap can rapidly produce high quality linkage maps with low sensitivity to missing and erroneous genotyping data compared to two other benchmark methods, JoinMap and MSTmap. TSPmap is open source and freely available as an R package. CONCLUSIONS: With the advancement of low cost sequencing technologies, the number of markers used in the generation of genetic maps is expected to continue to rise. TSPmap will be a useful tool to handle such large datasets into the future, quickly producing high quality maps using a large number of genomic markers.

The genetic architecture of UV floral patterning in sunflower.

Background and Aims: The patterning of floral ultraviolet (UV) pigmentation varies both intra- and interspecifically in sunflowers and many other plant species, impacts pollinator attraction, and can be critical to reproductive success and crop yields. However, the genetic basis for variation in UV patterning is largely unknown. This study examines the genetic architecture for proportional and absolute size of the UV bullseye in Helianthus argophyllus , a close relative of the domesticated sunflower. Methods: A camera modified to capture UV light (320-380 nm) was used to phenotype floral UV patterning in an F 2 mapping population, then quantitative trait loci (QTL) were identified using genotyping-by-sequencing and linkage mapping. The ability of these QTL to predict the UV patterning of natural population individuals was also assessed. Key Results: Proportional UV pigmentation is additively controlled by six moderate effect QTL that are predictive of this phenotype in natural populations. In contrast, UV bullseye size is controlled by a single large effect QTL that also controls flowerhead size and co-localizes with a major flowering time QTL in Helianthus . Conclusions: The co-localization of the UV bullseye size QTL, flowerhead size QTL and a previously known flowering time QTL may indicate a single highly pleiotropic locus or several closely linked loci, which could inhibit UV bullseye size from responding to selection without change in correlated characters. The genetic architecture of proportional UV pigmentation is relatively simple and different from that of UV bullseye size, and so should be able to respond to natural or artificial selection independently.

Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice.

To ensure food security in the face of population growth, decreasing water and land for agriculture, and increasing climate variability, crop yields must increase faster than the current rates. Increased yields will require implementing novel approaches in genetic discovery and breeding. Here we demonstrate the potential of field-based high throughput phenotyping (HTP) on a large recombinant population of rice to identify genetic variation underlying important traits. We find that detecting quantitative trait loci (QTL) with HTP phenotyping is as accurate and effective as traditional labor-intensive measures of flowering time, height, biomass, grain yield, and harvest index. Genetic mapping in this population, derived from a cross of an modern cultivar (IR64) with a landrace (Aswina), identified four alleles with negative effect on grain yield that are fixed in IR64, demonstrating the potential for HTP of large populations as a strategy for the second green revolution.

Hybridization and extinction.

Hybridization may drive rare taxa to extinction through genetic swamping, where the rare form is replaced by hybrids, or by demographic swamping, where population growth rates are reduced due to the wasteful production of maladaptive hybrids. Conversely, hybridization may rescue the viability of small, inbred populations. Understanding the factors that contribute to destructive versus constructive outcomes of hybridization is key to managing conservation concerns. Here, we survey the literature for studies of hybridization and extinction to identify the ecological, evolutionary, and genetic factors that critically affect extinction risk through hybridization. We find that while extinction risk is highly situation dependent, genetic swamping is much more frequent than demographic swamping. In addition, human involvement is associated with increased risk and high reproductive isolation with reduced risk. Although climate change is predicted to increase the risk of hybridization-induced extinction, we find little empirical support for this prediction. Similarly, theoretical and experimental studies imply that genetic rescue through hybridization may be equally or more probable than demographic swamping, but our literature survey failed to support this claim. We conclude that halting the introduction of hybridization-prone exotics and restoring mature and diverse habitats that are resistant to hybrid establishment should be management priorities.

Remarkable life history polymorphism may be evolving under divergent selection in the silverleaf sunflower.

Substantial intraspecific variation in life history is rare and potentially a signal of incipient ecological speciation, if variation is driven by geographically heterogenous natural selection. We present the first report of extensive life history polymorphism in Helianthus argophyllus, the silverleaf sunflower, and examine evidence for its evolution by divergent selection. In 18 populations sampled from across the species range and grown in a common garden, most quantitative traits covaried such that individuals could be assigned to two distinct life history syndromes: tall and late flowering with small initial flowerheads, or short and early flowering with larger initial flowerheads. Helianthus argophyllus exhibits regional genetic structure, but this population structure does not closely correspond with patterns of phenotypic variation. The early-flowering syndrome is primarily observed in populations from coastal barrier islands, while populations from the nearby mainland coast, although geographically and genetically close, are primarily late flowering. Additionally, several traits are more differentiated among regions than expected based on neutral genetic divergence (QST  > FST ), including the first principal component score corresponding with life history syndrome. This discordance between patterns of phenotypic and genetic variation suggests that divergent selection is driving genetic differences in life history across the species range. If so, the silverleaf sunflower may be in early stages of ecological speciation.

Paths to selection on life history loci in different natural environments across the native range of Arabidopsis thaliana.

Selection on quantitative trait loci (QTL) may vary among natural environments due to differences in the genetic architecture of traits, environment-specific allelic effects or changes in the direction and magnitude of selection on specific traits. To dissect the environmental differences in selection on life history QTL across climatic regions, we grew a panel of interconnected recombinant inbred lines (RILs) of Arabidopsis thaliana in four field sites across its native European range. For each environment, we mapped QTL for growth, reproductive timing and development. Several QTL were pleiotropic across environments, three colocalizing with known functional polymorphisms in flowering time genes (CRY2, FRI and MAF2-5), but major QTL differed across field sites, showing conditional neutrality. We used structural equation models to trace selection paths from QTL to lifetime fitness in each environment. Only three QTL directly affected fruit number, measuring fitness. Most QTL had an indirect effect on fitness through their effect on bolting time or leaf length. Influence of life history traits on fitness differed dramatically across sites, resulting in different patterns of selection on reproductive timing and underlying QTL. In two oceanic field sites with high prereproductive mortality, QTL alleles contributing to early reproduction resulted in greater fruit production, conferring selective advantage, whereas alleles contributing to later reproduction resulted in larger size and higher fitness in a continental site. This demonstrates how environmental variation leads to change in both QTL effect sizes and direction of selection on traits, justifying the persistence of allelic polymorphism at life history QTL across the species range.

Mandated data archiving greatly improves access to research data.

The data underlying scientific papers should be accessible to researchers both now and in the future, but how best can we ensure that these data are available? Here we examine the effectiveness of four approaches to data archiving: no stated archiving policy, recommending (but not requiring) archiving, and two versions of mandating data deposition at acceptance. We control for differences between data types by trying to obtain data from papers that use a single, widespread population genetic analysis, structure. At one extreme, we found that mandated data archiving policies that require the inclusion of a data availability statement in the manuscript improve the odds of finding the data online almost 1000-fold compared to having no policy. However, archiving rates at journals with less stringent policies were only very slightly higher than those with no policy at all. We also assessed the effectiveness of asking for data directly from authors and obtained over half of the requested datasets, albeit with ∼8 d delay and some disagreement with authors. Given the long-term benefits of data accessibility to the academic community, we believe that journal-based mandatory data archiving policies and mandatory data availability statements should be more widely adopted.

Recommendations for utilizing and reporting population genetic analyses: the reproducibility of genetic clustering using the program STRUCTURE.

Reproducibility is the benchmark for results and conclusions drawn from scientific studies, but systematic studies on the reproducibility of scientific results are surprisingly rare. Moreover, many modern statistical methods make use of 'random walk' model fitting procedures, and these are inherently stochastic in their output. Does the combination of these statistical procedures and current standards of data archiving and method reporting permit the reproduction of the authors' results? To test this, we reanalysed data sets gathered from papers using the software package STRUCTURE to identify genetically similar clusters of individuals. We find that reproducing structure results can be difficult despite the straightforward requirements of the program. Our results indicate that 30% of analyses were unable to reproduce the same number of population clusters. To improve this, we make recommendations for future use of the software and for reporting STRUCTURE analyses and results in published works.

The Population Genomics of Sunflowers and Genomic Determinants of Protein Evolution Revealed by RNAseq.

Few studies have investigated the causes of evolutionary rate variation among plant nuclear genes, especially in recently diverged species still capable of hybridizing in the wild. The recent advent of Next Generation Sequencing (NGS) permits investigation of genome wide rates of protein evolution and the role of selection in generating and maintaining divergence. Here, we use individual whole-transcriptome sequencing (RNAseq) to refine our understanding of the population genomics of wild species of sunflowers (Helianthus spp.) and the factors that affect rates of protein evolution. We aligned 35 GB of transcriptome sequencing data and identified 433,257 polymorphic sites (SNPs) in a reference transcriptome comprising 16,312 genes. Using SNP markers, we identified strong population clustering largely corresponding to the three species analyzed here (Helianthus annuus, H. petiolaris, H. debilis), with one distinct early generation hybrid. Then, we calculated the proportions of adaptive substitution fixed by selection (alpha) and identified gene ontology categories with elevated values of alpha. The "response to biotic stimulus" category had the highest mean alpha across the three interspecific comparisons, implying that natural selection imposed by other organisms plays an important role in driving protein evolution in wild sunflowers. Finally, we examined the relationship between protein evolution (dN/dS ratio) and several genomic factors predicted to co-vary with protein evolution (gene expression level, divergence and specificity, genetic divergence [FST], and nucleotide diversity pi). We find that variation in rates of protein divergence was correlated with gene expression level and specificity, consistent with results from a broad range of taxa and timescales. This would in turn imply that these factors govern protein evolution both at a microevolutionary and macroevolutionary timescale. Our results contribute to a general understanding of the determinants of rates of protein evolution and the impact of selection on patterns of polymorphism and divergence.

The genetics of adaptation to novel environments: selection on germination timing in Arabidopsis thaliana.

When studying selection during adaptation to novel environments, researchers have often paid little attention to an organism's earliest developmental stages. Despite this lack of attention, early life history traits may be under strong selection during colonization, as the expression of adaptive phenotypes at later points is contingent upon early survival. Moreover, the timing of early developmental transitions can constrain the timing of later transitions, with potentially large effects on fitness. In this issue, Huang et al. (2010) underscore the importance of early life history traits in the adaptation of Arabidopsis thaliana to old-field sites in North America. Using a new population of mapped recombinant inbred lines, the authors examined germination timing and total lifetime fitness of A. thaliana while varying site latitude, dispersal season, and maternal photoperiod. Huang et al. (2010) discovered several Quantitative Trait Loci (QTL) with large effects on fitness that colocalized with QTL for field germination timing and seed dormancy-demonstrating that fitness is genetically associated with these early life history traits, and that these loci are likely under strong selection during adaptation to novel environments. In the epistatic interactions of some loci, recombinant genotypes outperformed parental genotypes, supporting the potentially adaptive role of recombination. This study provides elegant evidence that traits expressed early in an organism's development can play an important role during adaptive evolution.

Effects of genetic perturbation on seasonal life history plasticity.

Like many species, the model plant Arabidopsis thaliana exhibits multiple different life histories in natural environments. We grew mutants impaired in different signaling pathways in field experiments across the species' native European range in order to dissect the mechanisms underlying this variation. Unexpectedly, mutational loss at loci implicated in the cold requirement for flowering had little effect on life history except in late-summer cohorts. A genetically informed photothermal model of progression toward flowering explained most of the observed variation and predicted an abrupt transition from autumn flowering to spring flowering in late-summer germinants. Environmental signals control the timing of this transition, creating a critical window of acute sensitivity to genetic and climatic change that may be common for seasonally regulated life history traits.