Rethinking eco-evo studies of gene expression for non-model organisms in the genomic era.

Recent advances in genomic technology, including the rapid development of long-read sequencing technology and single-cell RNA-sequencing methods, are poised to significantly expand the kinds of studies that are feasible in ecological genomics. In this perspective, we review these new technologies and discuss their potential impact on gene expression studies in non-model organisms. Although traditional RNA-sequencing methods have been an extraordinarily powerful tool to apply functional genomics in an ecological context, bulk RNA-seq approaches often rely on de novo transcriptome assembly, and cannot capture expression changes in rare cell populations or distinguish shifts in cell type abundance. Advancements in genome assembly technology, particularly long-read sequencing, and improvements in the scalability of single-cell RNA-sequencing (scRNA-seq) offer unprecedented resolution in understanding cellular heterogeneity and gene regulation. We discuss the potential of these technologies to enable disentangling differential gene regulation from cell type composition differences and uncovering subtle expression patterns masked by bulk RNA-seq. The integration of these approaches provides a more nuanced understanding of the ecological and evolutionary dynamics of gene expression, paving the way for refined models and deeper insights into the generation of biodiversity.

Evidence for ecotone speciation across an African rainforest-savanna gradient.

Accelerating climate change and habitat loss make it imperative that plans to conserve biodiversity consider species' ability to adapt to changing environments. However, in biomes where biodiversity is highest, the evolutionary mechanisms responsible for generating adaptative variation and, ultimately, new species are frequently poorly understood. African rainforests represent one such biome, as decadal debates continue concerning the mechanisms generating African rainforest biodiversity. These debates hinge on the relative importance of geographic isolation versus divergent natural selection across environmental gradients. Hindering progress is a lack of robust tests of these competing hypotheses. Because African rainforests are severely at-risk due to climate change and other anthropogenic activities, addressing this long-standing debate is critical for making informed conservation decisions. We use demographic inference and allele frequency-environment relationships to investigate mechanisms of diversification in an African rainforest skink, Trachylepis affinis, a species inhabiting the gradient between rainforest and rainforest-savanna mosaic (ecotone). We provide compelling evidence of ecotone speciation, in which gene flow has all but ceased between rainforest and ecotone populations, at a level consistent with infrequent hybridization between sister species. Parallel patterns of genomic, morphological, and physiological divergence across this environmental gradient and pronounced allele frequency-environment correlation indicate speciation is mostly probably driven by ecological divergence, supporting a central role for divergent natural selection. Our results provide strong evidence for the importance of ecological gradients in African rainforest speciation and inform conservation strategies that preserve the processes that produce and maintain biodiversity.

Error, noise and bias in de novo transcriptome assemblies.

De novo transcriptome assembly is a powerful tool, and has been widely used over the last decade for making evolutionary inferences. However, it relies on two implicit assumptions: that the assembled transcriptome is an unbiased representation of the underlying expressed transcriptome, and that expression estimates from the assembly are good, if noisy approximations of the relative abundance of expressed transcripts. Using publicly available data for model organisms, we demonstrate that, across assembly algorithms and data sets, these assumptions are consistently violated. Bias exists at the nucleotide level, with genotyping error rates ranging from 30% to 83%. As a result, diversity is underestimated in transcriptome assemblies, with consistent underestimation of heterozygosity in all but the most inbred samples. Even at the gene level, expression estimates show wide deviations from map-to-reference estimates, and positive bias at lower expression levels. Standard filtering of transcriptome assemblies improves the robustness of gene expression estimates but leads to the loss of a meaningful number of protein-coding genes, including many that are highly expressed. We demonstrate a computational method, length-rescaled CPM, to partly alleviate noise and bias in expression estimates. Researchers should consider ways to minimize the impact of bias in transcriptome assemblies.

Short paired-end reads trump long single-end reads for expression analysis.

BACKGROUND: Typical experimental design advice for expression analyses using RNA-seq generally assumes that single-end reads provide robust gene-level expression estimates in a cost-effective manner, and that the additional benefits obtained from paired-end sequencing are not worth the additional cost. However, in many cases (e.g., with Illumina NextSeq and NovaSeq instruments), shorter paired-end reads and longer single-end reads can be generated for the same cost, and it is not obvious which strategy should be preferred. Using publicly available data, we test whether short-paired end reads can achieve more robust expression estimates and differential expression results than single-end reads of approximately the same total number of sequenced bases. RESULTS: At both the transcript and gene levels, 2 × 40 paired-end reads unequivocally provide expression estimates that are more highly correlated with 2 × 125 than 1 × 75 reads; in nearly all cases, those correlations are also greater than for 1 × 125, despite the greater total number of sequenced bases for the latter. Across an array of metrics, differential expression tests based upon 2 × 40 consistently outperform those using 1 × 75. CONCLUSION: Researchers seeking a cost-effective approach for gene-level expression analysis should prefer short paired-end reads over a longer single-end strategy. Short paired-end reads will also give reasonably robust expression estimates and differential expression results at the isoform level.

Similar genomic proportions of copy number variation within gray wolves and modern dog breeds inferred from whole genome sequencing.

BACKGROUND: Whole genome re-sequencing data from dogs and wolves are now commonly used to study how natural and artificial selection have shaped the patterns of genetic diversity. Single nucleotide polymorphisms, microsatellites and variants in mitochondrial DNA have been interrogated for links to specific phenotypes or signals of domestication. However, copy number variation (CNV), despite its increasingly recognized importance as a contributor to phenotypic diversity, has not been extensively explored in canids. RESULTS: Here, we develop a new accurate probabilistic framework to create fine-scale genomic maps of segmental duplications (SDs), compare patterns of CNV across groups and investigate their role in the evolution of the domestic dog by using information from 34 canine genomes. Our analyses show that duplicated regions are enriched in genes and hence likely possess functional importance. We identify 86 loci with large CNV differences between dogs and wolves, enriched in genes responsible for sensory perception, immune response, metabolic processes, etc. In striking contrast to the observed loss of nucleotide diversity in domestic dogs following the population bottlenecks that occurred during domestication and breed creation, we find a similar proportion of CNV loci in dogs and wolves, suggesting that other dynamics are acting to particularly select for CNVs with potentially functional impacts. CONCLUSIONS: This work is the first comparison of genome wide CNV patterns in domestic and wild canids using whole-genome sequencing data and our findings contribute to study the impact of novel kinds of genetic changes on the evolution of the domestic dog.

Demographic history, selection and functional diversity of the canine genome.

The domestic dog represents one of the most dramatic long-term evolutionary experiments undertaken by humans. From a large wolf-like progenitor, unparalleled diversity in phenotype and behaviour has developed in dogs, providing a model for understanding the developmental and genomic mechanisms of diversification. We discuss pattern and process in domestication, beginning with general findings about early domestication and problems in documenting selection at the genomic level. Furthermore, we summarize genotype-phenotype studies based first on single nucleotide polymorphism (SNP) genotyping and then with whole-genome data and show how an understanding of evolution informs topics as different as human history, adaptive and deleterious variation, morphological development, ageing, cancer and behaviour.

Deciphering the Origin of Dogs: From Fossils to Genomes.

Understanding the timing and geographic context of dog origins is a crucial component for understanding human history, as well as the evolutionary context in which the morphological and behavioral divergence of dogs from wolves occurred. A substantial challenge to understanding domestication is that dogs have experienced a complicated demographic history. An initial severe bottleneck was associated with domestication followed by postdivergence gene flow between dogs and wolves, as well as population expansions, contractions, and replacements. In addition, because the domestication of dogs occurred in the relatively recent past, much of the observed polymorphism may be shared between dogs and wolves, limiting the power to distinguish between alternative models of dog history. Greater insight into the domestication process will require explicit tests of alternative models of domestication through the joint analysis of whole genomes from modern lineages and ancient wolves and dogs from across Eurasia.

Demographically-Based Evaluation of Genomic Regions under Selection in Domestic Dogs.

Controlling for background demographic effects is important for accurately identifying loci that have recently undergone positive selection. To date, the effects of demography have not yet been explicitly considered when identifying loci under selection during dog domestication. To investigate positive selection on the dog lineage early in the domestication, we examined patterns of polymorphism in six canid genomes that were previously used to infer a demographic model of dog domestication. Using an inferred demographic model, we computed false discovery rates (FDR) and identified 349 outlier regions consistent with positive selection at a low FDR. The signals in the top 100 regions were frequently centered on candidate genes related to brain function and behavior, including LHFPL3, CADM2, GRIK3, SH3GL2, MBP, PDE7B, NTAN1, and GLRA1. These regions contained significant enrichments in behavioral ontology categories. The 3rd top hit, CCRN4L, plays a major role in lipid metabolism, that is supported by additional metabolism related candidates revealed in our scan, including SCP2D1 and PDXC1. Comparing our method to an empirical outlier approach that does not directly account for demography, we found only modest overlaps between the two methods, with 60% of empirical outliers having no overlap with our demography-based outlier detection approach. Demography-aware approaches have lower-rates of false discovery. Our top candidates for selection, in addition to expanding the set of neurobehavioral candidate genes, include genes related to lipid metabolism, suggesting a dietary target of selection that was important during the period when proto-dogs hunted and fed alongside hunter-gatherers.

Genome sequencing highlights the dynamic early history of dogs.

To identify genetic changes underlying dog domestication and reconstruct their early evolutionary history, we generated high-quality genome sequences from three gray wolves, one from each of the three putative centers of dog domestication, two basal dog lineages (Basenji and Dingo) and a golden jackal as an outgroup. Analysis of these sequences supports a demographic model in which dogs and wolves diverged through a dynamic process involving population bottlenecks in both lineages and post-divergence gene flow. In dogs, the domestication bottleneck involved at least a 16-fold reduction in population size, a much more severe bottleneck than estimated previously. A sharp bottleneck in wolves occurred soon after their divergence from dogs, implying that the pool of diversity from which dogs arose was substantially larger than represented by modern wolf populations. We narrow the plausible range for the date of initial dog domestication to an interval spanning 11-16 thousand years ago, predating the rise of agriculture. In light of this finding, we expand upon previous work regarding the increase in copy number of the amylase gene (AMY2B) in dogs, which is believed to have aided digestion of starch in agricultural refuse. We find standing variation for amylase copy number variation in wolves and little or no copy number increase in the Dingo and Husky lineages. In conjunction with the estimated timing of dog origins, these results provide additional support to archaeological finds, suggesting the earliest dogs arose alongside hunter-gathers rather than agriculturists. Regarding the geographic origin of dogs, we find that, surprisingly, none of the extant wolf lineages from putative domestication centers is more closely related to dogs, and, instead, the sampled wolves form a sister monophyletic clade. This result, in combination with dog-wolf admixture during the process of domestication, suggests that a re-evaluation of past hypotheses regarding dog origins is necessary.

Regional differences in seasonal timing of rainfall discriminate between genetically distinct East African giraffe taxa.

Masai (Giraffa tippelskirchi), Reticulated (G. reticulata) and Rothschild's (G. camelopardalis) giraffe lineages in East Africa are morphologically and genetically distinct, yet in Kenya their ranges abut. This raises the question of how divergence is maintained among populations of a large mammal capable of long-distance travel, and which readily hybridize in zoos. Here we test four hypotheses concerning the maintenance of the phylogeographic boundaries among the three taxa: 1) isolation-by-distance; 2) physical barriers to dispersal; 3) general habitat differences resulting in habitat segregation; or 4) regional differences in the seasonal timing of rainfall, and resultant timing of browse availability. We used satellite remotely sensed and climate data to characterize the environment at the locations of genotyped giraffes. Canonical variate analysis, random forest algorithms, and generalized dissimilarity modelling were employed in a landscape genetics framework to identify the predictor variables that best explained giraffes' genetic divergence. We found that regional differences in the timing of precipitation, and resulting green-up associated with the abundance of browse, effectively discriminate between taxa. Local habitat conditions, topographic and human-induced barriers, and geographic distance did not aid in discriminating among lineages. Our results suggest that selection associated with regional timing of events in the annual climatic cycle may help maintain genetic and phenotypic divergence in giraffes. We discuss potential mechanisms of maintaining divergence, and suggest that synchronization of reproduction with seasonal rainfall cycles that are geographically distinct may contribute to reproductive isolation. Coordination of weaning with green-up cycles could minimize the costs of lactation and predation on the young. Our findings are consistent with theory and empirical results demonstrating the efficacy of seasonal or phenologically dictated selection pressures in contributing to the reproductive isolation of parapatric populations.

Human impacts flatten rainforest-savanna gradient and reduce adaptive diversity in a rainforest bird.

Ecological gradients have long been recognized as important regions for diversification and speciation. However, little attention has been paid to the evolutionary consequences or conservation implications of human activities that fundamentally change the environmental features of such gradients. Here we show that recent deforestation in West Africa has homogenized the rainforest-savanna gradient, causing a loss of adaptive phenotypic diversity in a common rainforest bird, the little greenbul (Andropadus virens). Previously, this species was shown to exhibit morphological and song divergence along this gradient in Central Africa. Using satellite-based estimates of forest cover, recent morphological data, and historical data from museum specimens collected prior to widespread deforestation, we show that the gradient has become shallower in West Africa and that A. virens populations there have lost morphological variation in traits important to fitness. In contrast, we find no loss of morphological variation in Central Africa where there has been less deforestation and gradients have remained more intact. While rainforest deforestation is a leading cause of species extinction, the potential of deforestation to flatten gradients and inhibit rainforest diversification has not been previously recognized. More deforestation will likely lead to further flattening of the gradient and loss of diversity, and may limit the ability of species to persist under future environmental conditions.

Spatial modelling and landscape-level approaches for visualizing intra-specific variation.

Spatial analytical methods have been used by biologists for decades, but with new modelling approaches and data availability their application is accelerating. While early approaches were purely spatial in nature, it is now possible to explore the underlying causes of spatial heterogeneity of biological variation using a wealth of environmental data, especially from satellite remote sensing. Recent methods can not only make inferences regarding spatial relationships and the causes of spatial heterogeneity, but also create predictive maps of patterns of biological variation under changing environmental conditions. Here, we review the methods involved in making continuous spatial predictions from biological variation using spatial and environmental predictor variables, provide examples of their use and critically evaluate the advantages and limitations. In the final section, we discuss some of the key challenges and opportunities for future work.

Genomic signals of diversification along ecological gradients in a tropical lizard.

Studies of rainforest diversification that simultaneously consider the effects of genetic drift and natural selection are rare. We use Amplified Fragment Length Polymorphism genome scans of the African rainforest lizard Trachylepis affinis from Cameroon to examine the spatial patterns and environmental associations of both neutrally evolving loci and those thought to be under selection. Bayesian selection scans revealed that approximately 7% of the genome may be under divergent selection. Using non-linear environmental modelling techniques, we fit patterns of genetic differentiation recovered from the pooled neutral data and from individual loci showing a signature of natural selection. Neutral differentiation occurred along a cline from coastal lowland rainforest inland toward the gallery forests-savanna mosaic (ecotone), and was associated with both geographic distance and changing precipitation patterns. Loci under selection were differentiated predominantly along the forest-ecotone gradient-in concordance with morphological divergence in traits related to fitness. A second set of these loci was differentiated between lowland and montane habitats. A third set of loci was indicative of divergent selection between rainforest refugia. Niche models and demographic signals in mitochondrial sequence data support a population expansion out of a core rainforest area into savanna since the last glacial maximum. Our findings indicate adaptive diversification in T. affinis may be taking place along the forest-ecotone gradient during range expansions or contractions, and that refugial isolation augmented by divergent adaptation to different rainforest environments appears to play a less significant role.

Landscape genetics of California mule deer (Odocoileus hemionus): the roles of ecological and historical factors in generating differentiation.

Landscape genetics is an emerging discipline that utilizes environmental and historical data to understand geographic patterns of genetic diversity. Niche modelling has added a new dimension to such efforts by allowing species-environmental associations to be projected into the past so that hypotheses about historical vicariance can be generated and tested independently with genetic data. However, previous approaches have primarily utilized DNA sequence data to test inferences about historical isolation and may have missed very recent episodes of environmentally mediated divergence. We type 15 microsatellite loci in California mule deer and identify five genetic groupings through a Structure analysis that are also well predicted by environmental data. We project the niches of these five deer ecotypes to the last glacial maximum (LGM) and show they overlap to a much greater extent than today, suggesting that vicariance associated with the LGM cannot explain the present-day genetic patterns. Further, we analyse mitochondrial DNA (mtDNA) sequence trees to search for evidence of historical vicariance and find only two well-supported clades. A coalescence-based analysis of mtDNA data shows that the genetic divergence of the mule deer genetic clusters in California is recent and appears to be mediated by ecological factors. The importance of environmental factors in explaining the genetic diversity of California mule deer is unexpected given that they are highly mobile species and have a broad habitat distribution. Geographic differences in the timing of reproduction and peak vegetation as well as habitat choice reflecting natal origin may explain the persistence of genetic subdivision.

Modeling the effects of anthropogenic habitat change on savanna snake invasions into African rainforest.

We used a species-distribution modeling approach, ground-based climate data sets, and newly available remote-sensing data on vegetation from the MODIS and Quick Scatterometer sensors to investigate the combined effects of human-caused habitat alterations and climate on potential invasions of rainforest by 3 savanna snake species in Cameroon, Central Africa: the night adder (Causus maculatus), olympic lined snake (Dromophis lineatus), and African house snake (Lamprophis fuliginosus). Models with contemporary climate variables and localities from native savanna habitats showed that the current climate in undisturbed rainforest was unsuitable for any of the snake species due to high precipitation. Limited availability of thermally suitable nest sites and mismatches between important life-history events and prey availability are a likely explanation for the predicted exclusion from undisturbed rainforest. Models with only MODIS-derived vegetation variables and savanna localities predicted invasion in disturbed areas within the rainforest zone, which suggests that human removal of forest cover creates suitable microhabitats that facilitate invasions into rainforest. Models with a combination of contemporary climate, MODIS- and Quick Scatterometer-derived vegetation variables, and forest and savanna localities predicted extensive invasion into rainforest caused by rainforest loss. In contrast, a projection of the present-day species-climate envelope on future climate suggested a reduction in invasion potential within the rainforest zone as a consequence of predicted increases in precipitation. These results emphasize that the combined responses of deforestation and climate change will likely be complex in tropical rainforest systems.