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Nondisclosure of lesbian, gay, bisexual, transgender, asexual, or otherwise queer (LGBTQA) identities in the workplace is both common and stressful to those who do not disclose. However, we lack direct evidence that nondisclosure of LGBTQA identity affects worker productivity. In two surveys of LGBTQA-identified scientists, we found that those who did not disclose LGBTQA identities in professional settings authored fewer peer-reviewed publications—a concrete productivity cost. In the second survey, which included straight and cisgender participants as a comparison group, we found that LGBTQA participants who disclosed their sexual orientation had publication counts more like non-LGBTQA participants than those who did not disclose, and that all three groups had similar time since first publication given their academic career stage. These results are most consistent with a productivity cost to nondisclosure of LGBTQA identity in professional settings, and suggest a concrete need to improve scientific workplace climates for sexual and gender minorities.

Coevolutionary interactions between species are thought to be an important cause of evolutionary diversification. Despite this general belief, little theoretical basis exists for distinguishing between the types of interactions that promote diversification and those types that have no effect or that even restrict it. Using analytical models and simulations of phenotypic evolution across a metapopulation, we show that coevolutionary interactions promote diversification when they impose a cost of phenotype matching, as is the case for competition or host‐parasite antagonism. In contrast, classical coevolutionary arms races have no tendency to promote or inhibit diversification, and mutualistic interactions actually restrict diversification. Together with the results of recent phylogenetic and ecological studies, these results suggest that the causes of diversification in many coevolutionary systems may require reassessment.

Local adaptation and adaptive clines are pervasive in natural plant populations, yet the effects of these types of adaptation on genomic diversity are not well understood. With a data set of 202 accessions of Medicago truncatula genotyped at almost 2 million single nucleotide polymorphisms, we used mixed linear models to identify candidate loci responsible for adaptation to three climatic gradients—annual mean temperature (AMT), precipitation in the wettest month (PWM), and isothermality (ITH)—representing the major axes of climate variation across the species’ range. Loci with the strongest association to these climate gradients tagged genome regions with high sequence similarity to genes with functional roles in thermal tolerance, drought tolerance, or resistance to herbivores of pathogens. Genotypes at these candidate loci also predicted the performance of an independent sample of plant accessions grown in climate-controlled conditions. Compared to a genome-wide sample of randomly drawn reference SNPs, candidates for two climate gradients, AMT and PWM, were significantly enriched for genic regions, and genome segments flanking genic AMT and PWM candidates harbored less nucleotide diversity, elevated differentiation between haplotypes carrying alternate alleles, and an overrepresentation of the most common haplotypes. These patterns of diversity are consistent with a history of soft selective sweeps acting on loci underlying adaptation to climate, but not with a history of long-term balancing selection.

Decades of research on the evolution of mutualism has generated a wealth of possible ways whereby mutually beneficial interactions between species persist in spite of the apparent advantages to individuals that accept the benefits of mutualism without reciprocating — but identifying how any particular empirical system is stabilized against cheating remains challenging. Different hypothesized models of mutualism stability predict different forms of coevolutionary selection, and emerging high-throughput sequencing methods allow examination of the selective histories of mutualism genes and, thereby, the form of selection acting on those genes. Here, I review the evolutionary theory of mutualism stability and identify how differing models make contrasting predictions for the population genomic diversity and geographic differentiation of mutualism-related genes. As an example of the possibilities offered by genomic data, I analyze genes with roles in the symbiosis of Medicago truncatula and nitrogen-fixing rhizobial bacteria, the first classic mutualism in which extensive genomic resources have been developed for both partners. Medicago truncatula symbiosis genes, as a group, differ from the rest of the genome, but they vary in the form of selection indicated by their diversity and differentiation — some show signs of selection expected from roles in sanctioning noncooperative symbionts, while others show evidence of balancing selection expected from coevolution with symbiont signaling factors. I then assess the current state of development for similar resources in other mutualistic interactions and look ahead to identify ways in which modern sequencing technology can best inform our understanding of mutualists and mutualism.

Coevolution, reciprocal adaptation between two or more taxa, is commonly invoked as a primary mechanism responsible for generating much of Earth’s biodiversity. This conceptually appealing hypothesis is incredibly broad in evolutionary scope, encompassing diverse patterns and processes operating over timescales ranging from microbial generations to geological eras. However, we have surprisingly little evidence that large-scale associations between coevolution and diversity reflect a causal relationship at smaller timescales, in which coevolutionary selection is directly responsible for the formation of new species. In this synthesis, we critically evaluate evidence for the often-invoked hypothesis that coevolution is an important process promoting biological diversification. We conclude that the lack of widespread evidence for coevolutionary diversification may be best explained by the fact that coevolution’s importance in diversification varies depending on the type of interaction and the scale of the diversification under consideration.

Mutualistic interactions can be stabilized against invasion by noncooperative individuals by putting such “cheaters” at a selective disadvantage. Selection against cheaters should eliminate genetic variation in partner quality—yet such variation is often found in natural populations. One explanation for this paradox is that mutualism outcomes are determined not only by responses to partner performance but also by partner signals. Here, we build a model of coevolution in a symbiotic mutualism, in which hosts’ ability to sanction noncooperative symbionts and recognition of symbiont signals are determined by separate loci, as are symbionts’ cooperation and expression of signals. In the model, variation persists without destabilizing the interaction, in part because coevolution of symbiont signals and host recognition is altered by the coevolution of sanctions and cooperation, and vice versa. Individual-based simulations incorporating population structure strongly corroborate these results. The dual systems of sanctions and partner recognition converge toward conditions similar to some economic models of mutualistic symbiosis, in which hosts offering the right incentives to potential symbionts can initiate symbiosis without screening for partner quality. These results predict that mutualists can maintain variation in recognition of partner signals or in the ability to sanction noncooperators without destabilizing mutualism, and they reinforce the notion that studies of mutualism should consider communication between partners as well as the exchange of benefits.

We evaluate genomic data, relative to phenotypic and climatic data, as a basis for assisted gene flow and genetic conservation. Using a seedling common garden trial of 281 lodgepole pine (Pinus contorta) populations from across western Canada, we compare genomic data to phenotypic and climatic data to assess their effectiveness in characterizing the climatic drivers and spatial scale of local adaptation in this species. We find that phenotype‐associated loci are equivalent or slightly superior to climate data for describing local adaptation in seedling traits, but that climate data are superior to genomic data that have not been selected for phenotypic associations. We also find agreement between the climate variables associated with genomic variation and with 20‐year heights from a long‐term provenance trial, suggesting that genomic data may be a viable option for identifying climatic drivers of local adaptation where phenotypic data are unavailable. Genetic clines associated with the experimental traits occur at broad spatial scales, suggesting that standing variation of adaptive alleles for this and similar species does not require management at scales finer than those indicated by phenotypic data. This study demonstrates that genomic data are most useful when paired with phenotypic data, but can also fill some of the traditional roles of phenotypic data in management of species for which phenotypic trials are not feasible.

Continuing with our Q&A series discussing issues of diversity in STEM fields, Genome Biology spoke with three openly LGBT+ researchers on their experiences in biology.Continuing with our Q&A series discussing issues of diversity in STEM fields, Genome Biology spoke with three openly LGBT+ researchers on their experiences in biology.

Genome-wide association study (GWAS) has revolutionized the search for the genetic basis of complex traits. To date, GWAS have generally relied on relatively sparse sampling of nucleotide diversity, which is likely to bias results by preferentially sampling high-frequency SNPs not in complete linkage disequilibrium (LD) with causative SNPs. To avoid these limitations we conducted GWAS with >6 million SNPs identified by sequencing the genomes of 226 accessions of the model legume Medicago truncatula. We used these data to identify candidate genes and the genetic architecture underlying phenotypic variation in plant height, trichome density, flowering time, and nodulation. The characteristics of candidate SNPs differed among traits, with candidates for flowering time and trichome density in distinct clusters of high linkage disequilibrium (LD) and the minor allele frequencies (MAF) of candidates underlying variation in flowering time and height significantly greater than MAF of candidates underlying variation in other traits. Candidate SNPs tagged several characterized genes including nodulation related genes SERK2, MtnodGRP3, MtMMPL1, NFP, CaML3, MtnodGRP3A and flowering time gene MtFD as well as uncharacterized genes that become candidates for further molecular characterization. By comparing sequence-based candidates to candidates identified by in silico 250K SNP arrays, we provide an empirical example of how reliance on even high-density reduced representation genomic makers can bias GWAS results. Depending on the trait, only 30-70% of the top 20 in silico array candidates were within 1 kb of sequence-based candidates. Moreover, the sequence-based candidates tagged by array candidates were heavily biased towards common variants; these comparisons underscore the need for caution when interpreting results from GWAS conducted with sparsely covered genomes.

Theory suggests that coevolution drives diversification in obligate pollination mutualism, but it has been difficult to disentangle the effects of coevolution from other factors. We test the hypothesis that differential selection by two sister species of pollinating yucca moths (Tegeticulaspp.) drove divergence between two varieties of the Joshua tree (Yucca brevifolia) by comparing measures of differentiation in floral and vegetative features. We show that floral features associated with pollination evolved more rapidly than vegetative features extrinsic to the interaction and that a key floral feature involved in the mutualism is more differentiated than any other and matches equivalent differences in the morphology of the pollinating moths. A phylogenetically based, ancestral states reconstruction shows that differences in moth morphology arose in the time since they first became associated with Joshua trees. These results suggest that coevolution, rather than extrinsic environmental factors, has driven divergence in this obligate pollination mutualism.