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Gene regulatory networks control the complex programs that drive development. Deciphering the connections between transcription factors (TFs) and target genes is challenging, in part because TFs bind to thousands of places in the genome but control expression through a subset of these binding events. We hypothesize that we can combine natural variation of expression levels and predictions of TF binding sites to identify TF targets. We gather RNA-seq data from 71 genetically distinct F1 Drosophila melanogaster embryos and calculate the correlations between TF and potential target genes' expression levels, which we call "regulatory strength." To separate direct and indirect TF targets, we hypothesize that direct TF targets will have a preponderance of binding sites in their upstream regions. Using 14 TFs active during embryogenesis, we find that 12 TFs showed a significant correlation between their binding strength and regulatory strength on downstream targets, and 10 TFs showed a significant correlation between the number of binding sites and the regulatory effect on target genes. The general roles, e.g. bicoid's role as an activator, and the particular interactions we observed between our TFs, e.g. twist's role as a repressor of sloppy paired and odd paired, generally coincide with the literature.

Microbial inoculants can increase the yield of cultivated crops and are successful in independent trials; however, efficacy drops in large-scale applications due to insufficient consideration of microbial community dynamics. The structure of microbiomes, in addition to the impact of individual taxa, is an important factor to consider when designing growth-promoting inoculants. Here, we investigate the microbial network and community assembly patterns of Macrocystis pyrifera gametophyte germplasm cultures (collectively referred to as a "seedbank") used to cultivate an offshore farm in Santa Barbara, California, and identify network features associated with increased biomass of mature sporophytes. We found that [1] several network features, such as clustering coefficient and edge ratios, significantly vary with biomass outcomes; [2] gametophytes that become low- or high-biomass sporophytes have different hub taxa; and [3] microbial community assembly of gametophyte germplasm cultures is niche-driven. Overall, this study describes microbial community dynamics in M. pyrifera germplasm cultures and ultimately supports the development of early life stage inoculants that can be used on seaweed cultivars to increase biomass yield., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Osborne et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Macrocystis pyrifera (giant kelp), is a brown macroalga of great ecological importance as a primary producer and structure-forming foundational species that provides habitat for hundreds of species. It has many commercial uses (e.g. source of alginate, fertilizer, cosmetics, feedstock). One of the limitations to exploiting giant kelp's economic potential and assisting in giant kelp conservation efforts is a lack of genomic tools like a high quality, contiguous reference genome with accurate gene annotations. Reference genomes attempt to capture the complete genomic sequence of an individual or species, and importantly provide a universal structure for comparison across a multitude of genetic experiments, both within and between species. We assembled the giant kelp genome of a haploid female gametophyte de novo using PacBio reads, then ordered contigs into chromosome level scaffolds using Hi-C. We found the giant kelp genome to be 537 MB, with a total of 35 scaffolds and 188 contigs. The assembly N50 is 13,669,674 with GC content of 50.37%. We assessed the genome completeness using BUSCO, and found giant kelp contained 94% of the BUSCO genes from the stramenopile clade. Annotation of the giant kelp genome revealed 25,919 genes. Additionally, we present genetic variation data based on 48 diploid giant kelp sporophytes from three different Southern California populations that confirms the population structure found in other studies of these populations. This work resulted in a high-quality giant kelp genome that greatly increases the genetic knowledge of this ecologically and economically vital species., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Many marine bivalves have complex life histories with distinct developmental processes and genetic mechanisms. Larval development for most bivalves is often a prolonged and crucial physiological stage, where they suffer mass mortality due to early-acting genetic load. In this study, we describe genetic changes taking place within a single generation of families of the Mediterranean mussel Mytilus galloprovincialis over 23 days of larval development. Using replicated cultures and a pooled sequencing approach, we demonstrate that temporal balancing selection at the majority of loci preserve genetic variation in the early developmental stages of M. galloprovincialis. Balancing selection may be the mechanism which maintains standing genetic variation within the mussel genome and may improve the chances of survival and shield larvae from high levels of genetic load. Additionally, we used changes in allele frequencies to identify potential size-associated SNPs and viability-associated SNPs and found that patterns of genetic changes in directionally selected SNPs cannot be simply explained by traditional theories of genetic purging or directional selection without consideration of balancing selection. Finally, we observed a negative correlation between larval growth rates and survival, implying a potential trade-off relationship between the 2 commercially relevant phenotypes., Competing Interests: Conflicts of interest The author(s) declare no conflict of interest., (© The Author(s) 2023. Published by Oxford University Press on behalf of The Genetics Society of America.)

According to archaeological records, chickpea (Cicer arietinum) was first domesticated in the Fertile Crescent about 10,000 years BP. Its subsequent diversification in Middle East, South Asia, Ethiopia, and the Western Mediterranean, however, remains obscure and cannot be resolved using only archeological and historical evidence. Moreover, chickpea has two market types: "desi" and "kabuli," for which the geographic origin is a matter of debate. To decipher chickpea history, we took the genetic data from 421 chickpea landraces unaffected by the green revolution and tested complex historical hypotheses of chickpea migration and admixture on two hierarchical spatial levels: within and between major regions of cultivation. For chickpea migration within regions, we developed popdisp, a Bayesian model of population dispersal from a regional representative center toward the sampling sites that considers geographical proximities between sites. This method confirmed that chickpea spreads within each geographical region along optimal geographical routes rather than by simple diffusion and estimated representative allele frequencies for each region. For chickpea migration between regions, we developed another model, migadmi, that takes allele frequencies of populations and evaluates multiple and nested admixture events. Applying this model to desi populations, we found both Indian and Middle Eastern traces in Ethiopian chickpea, suggesting the presence of a seaway from South Asia to Ethiopia. As for the origin of kabuli chickpeas, we found significant evidence for its origin from Turkey rather than Central Asia., (© The Author(s) 2023. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.)

In Drosophila melanogaster and D. simulans head tissue, 60% of orthologous genes show evidence of sex-biased expression in at least one species. Of these, ∼39% (2,192) are conserved in direction. We hypothesize enrichment of open chromatin in the sex where we see expression bias and closed chromatin in the opposite sex. Male-biased orthologs are significantly enriched for H3K4me3 marks in males of both species (∼89% of male-biased orthologs vs. ∼76% of unbiased orthologs). Similarly, female-biased orthologs are significantly enriched for H3K4me3 marks in females of both species (∼90% of female-biased orthologs vs. ∼73% of unbiased orthologs). The sex-bias ratio in female-biased orthologs was similar in magnitude between the two species, regardless of the closed chromatin (H3K27me2me3) marks in males. However, in male-biased orthologs, the presence of H3K27me2me3 in both species significantly reduced the correlation between D. melanogaster sex-bias ratio and the D. simulans sex-bias ratio. Male-biased orthologs are enriched for evidence of positive selection in the D. melanogaster group. There are more male-biased genes than female-biased genes in both species. For orthologs with gains/losses of sex-bias between the two species, there is an excess of male-bias compared to female-bias, but there is no consistent pattern in the relationship between H3K4me3 or H3K27me2me3 chromatin marks and expression. These data suggest chromatin state is a component of the maintenance of sex-biased expression and divergence of sex-bias between species is reflected in the complexity of the chromatin status., (© The Author(s) 2023. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.)

With national interest in seaweed-based biofuels as a sustainable alternative to fossil fuels, there is a need for tools that produce high-yield seaweed cultivars and increase the efficiency of offshore farms. Several agricultural studies have demonstrated that the application of microbial inoculants at an early life stage can improve crop yield, and there is an opportunity to use similar techniques in seaweed aquaculture. However, there is a critical knowledge gap regarding host-microbiome associations of macroalgae gametophytes in germplasm cultures. Here, we investigate the microbial community of Macrocystis pyrifera gametophyte germplasm cultures that were used to cultivate an offshore farm in Santa Barbara, California and identify key taxa correlated with increased biomass of mature sporophytes. This work provides a valuable knowledge base for the development of microbial inoculants that produce high-biomass M. pyrifera cultivars to ultimately be used as biofuel feedstocks., (© 2023 The Authors. Journal of Phycology published by Wiley Periodicals LLC on behalf of Phycological Society of America.)

The molecular factors and gene regulation involved in sex determination and gonad differentiation in bivalve molluscs are unknown. It has been suggested that doubly uniparental inheritance (DUI) of mitochondria may be involved in these processes in species such as the ubiquitous and commercially relevant Manila clam, Ruditapes philippinarum. We present the first long-read-based de novo genome assembly of a Manila clam, and a RNA-Seq multi-tissue analysis of 15 females and 15 males. The highly contiguous genome assembly was used as reference to investigate gene expression, alternative splicing, sequence evolution, tissue-specific co-expression networks, and sexual contrasting SNPs. Differential expression (DE) and differential splicing (DS) analyses revealed sex-specific transcriptional regulation in gonads, but not in somatic tissues. Co-expression networks revealed complex gene regulation in gonads, and genes in gonad-associated modules showed high tissue specificity. However, male gonad-associated modules showed contrasting patterns of sequence evolution and tissue specificity. One gene set was related to the structural organization of male gametes and presented slow sequence evolution but high pleiotropy, whereas another gene set was enriched in reproduction-related processes and characterized by fast sequence evolution and tissue specificity. Sexual contrasting SNPs were found in genes overrepresented in mitochondrial-related functions, providing new candidates for investigating the relationship between mitochondria and sex in DUI species. Together, these results increase our understanding of the role of DE, DS, and sequence evolution of sex-specific genes in an understudied taxon. We also provide resourceful genomic data for studies regarding sex diagnosis and breeding in bivalves., (© The Author(s) 2022. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.)

Flowering time is an important target for breeders in developing new varieties adapted to changing conditions. In this work, a new approach is proposed in which the SNP markers influencing time to flowering in mung bean are selected as important features in a random forest model. The genotypic and weather data are encoded in artificial image objects, and a model for flowering time prediction is constructed as a convolutional neural network. The model uses weather data for only a limited time period of 5 days before and 20 days after planting and is capable of predicting the time to flowering with high accuracy. The most important factors for model solution were identified using saliency maps and a Score-CAM method. Our approach can help breeding programs harness genotypic and phenotypic diversity to more effectively produce varieties with a desired flowering time.

Epithelial tissues constitute an exotic type of active matter with non-linear properties reminiscent of amorphous materials. In the context of a proliferating epithelium, modeled by the quasistatic vertex model, we identify novel discrete tissue scale rearrangements, i.e. cellular rearrangement avalanches, which are a form of collective cell movement. During the avalanches, the vast majority of cells retain their neighbors, and the resulting cellular trajectories are radial in the periphery, a vortex in the core. After the onset of these avalanches, the epithelial area grows discontinuously. The avalanches are found to be stochastic, and their strength is correlated with the density of cells in the tissue. Overall, avalanches redistribute accumulated local spatial pressure along the tissue. Furthermore, the distribution of avalanche magnitudes is found to obey a power law, with an exponent consistent with sheer induced avalanches in amorphous materials. To understand the role of avalanches in organ development, we simulate epithelial growth of the Drosophila eye disc during the third instar using a computational model, which includes both chemical and mechanistic signaling. During the third instar, the morphogenetic furrow (MF), a ~10 cell wide wave of apical area constriction propagates through the epithelium. These simulations are used to understand the details of the growth process, the effect of the MF on the growth dynamics on the tissue scale, and to make predictions for experimental observations. The avalanches are found to depend on the strength of the apical constriction of cells in the MF, with a stronger apical constriction leading to less frequent and more pronounced avalanches. The results herein highlight the dependence of simulated tissue growth dynamics on relaxation timescales, and serve as a guide for in vitro experiments., Competing Interests: The authors have declared that no competing interests exist.

Objective: Allelic imbalance (AI) is the differential expression of the two alleles in a diploid. AI can vary between tissues, treatments, and environments. Methods for testing AI exist, but methods are needed to estimate type I error and power for detecting AI and difference of AI between conditions. As the costs of the technology plummet, what is more important: reads or replicates?, Results: We find that a minimum of 2400, 480, and 240 allele specific reads divided equally among 12, 5, and 3 replicates is needed to detect a 10, 20, and 30%, respectively, deviation from allelic balance in a condition with power > 80%. A minimum of 960 and 240 allele specific reads divided equally among 8 replicates is needed to detect a 20 or 30% difference in AI between conditions with comparable power. Higher numbers of replicates increase power more than adding coverage without affecting type I error. We provide a Python package that enables simulation of AI scenarios and enables individuals to estimate type I error and power in detecting AI and differences in AI between conditions., (© 2021. The Author(s).)

Due to increasing demand for new advanced crops, considerable efforts have been made to explore the improvement of stress and disease resistance cultivar traits through the study of wild crops. When both wild and interspecific hybrid materials are available, a common approach has been to study two types of materials separately and simply compare the quantitative trait locus (QTL) regions. However, combining the two types of materials can potentially create a more efficient method of finding predictive QTLs. In this simulation study, we focused on scenarios involving causal marker expression suppressed by trans- regulatory mechanisms, where the otherwise easily lost associated signals benefit the most from combining the two types of data. A probabilistic sampling approach was used to prioritize consistent genotypic phenotypic patterns across both types of data sets. We chose random forest and gradient boosting to apply the prioritization scheme and found that both facilitated the investigation of predictive causal markers in most of the biological scenarios simulated., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Shin and Nuzhdin.)

Background: Sunflower is an important oilseed crop domesticated in North America approximately 4000 years ago. During the last century, oil content in sunflower was under strong selection. Further improvement of oil properties achieved by modulating its fatty acid composition is one of the main directions in modern oilseed crop breeding., Results: We searched for the genetic basis of fatty acid content variation by genotyping 601 inbred sunflower lines and assessing their lipid and fatty acid composition. Our genome-wide association analysis based on the genotypes for 15,483 SNPs and the concentrations of 23 fatty acids, including minor fatty acids, revealed significant genetic associations for eleven of them. Identified genomic regions included the loci involved in rare fatty acids variation on chromosomes 3 and 14, explaining up to 34.5% of the total variation of docosanoic acid (22:0) in sunflower oil., Conclusions: This is the first large scale implementation of high-throughput lipidomic profiling to sunflower germplasm characterization. This study contributes to the genetic characterization of Russian sunflower collections, which made a substantial contribution to the development of sunflower as the oilseed crop worldwide, and provides new insights into the genetic control of oil composition that can be implemented in future studies.

Existing Elaeis guineensis cultivars lack sufficient genetic diversity due to extensive breeding. Harnessing variation in wild crop relatives is necessary to expand the breadth of agronomically valuable traits. Using RAD sequencing, we examine the natural diversity of wild American oil palm populations (Elaeis oleifera), a sister species of the cultivated Elaeis guineensis oil palm. We genotyped 192 wild E. oleifera palms collected from seven Latin American countries along with four cultivated E. guineensis palms. Honduras, Costa Rica, Panama and Colombia palms are panmictic and genetically similar. Genomic patterns of diversity suggest that these populations likely originated from the Amazon Basin. Despite evidence of a genetic bottleneck and high inbreeding observed in these populations, there is considerable genetic and phenotypic variation for agronomically valuable traits. Genome-wide association revealed several candidate genes associated with fatty acid composition along with vegetative and yield-related traits. These observations provide valuable insight into the geographic distribution of diversity, phenotypic variation and its genetic architecture that will guide choices of wild genotypes for crop improvement., (Copyright © 2020. Published by Elsevier B.V.)

Enteric methane emissions are the single largest source of direct greenhouse gas emissions (GHG) in beef and dairy value chains and a substantial contributor to anthropogenic methane emissions globally. In late 2019, the World Wildlife Fund (WWF), the Advanced Research Projects Agency-Energy (ARPA-E) and the Foundation for Food and Agriculture Research (FFAR) convened approximately 50 stakeholders representing research and production of seaweeds, animal feeds, dairy cattle, and beef and dairy foods to discuss challenges and opportunities associated with the use of seaweed-based ingredients to reduce enteric methane emissions. This Perspective article describes the considerations identified by the workshop participants and suggests next steps for the further development and evaluation of seaweed-based feed ingredients as enteric methane mitigants. Although numerous compounds derived from sources other than seaweed have been identified as having enteric methane mitigation potential, these mitigants are outside the scope of this article., Competing Interests: DC and YS were employed by the companies Land O'Lakes Inc. and Cargill Inc., respectively. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer MH declared a past co-authorship with the authors AN and EK to the handling editor. The handling editor declared a past co-authorship with one of the authors EK., (Copyright © 2020 Vijn, Compart, Dutta, Foukis, Hess, Hristov, Kalscheur, Kebreab, Nuzhdin, Price, Sun, Tricarico, Turzillo, Weisbjerg, Yarish and Kurt.)

Evaluation of transcriptome data in combination with QTL information has been applied in many crops to study the expression of genes responsible for specific phenotypes. In oil palm, the mesocarp oil extracted from E. oleifera × E. guineensis interspecific hybrids is known to have lower palmitic acid (C16:0) content compared to pure African palms. The present study demonstrates the effectiveness of transcriptome data in revealing the expression profiles of genes in the fatty acid (FA) and triacylglycerol (TAG) biosynthesis processes in interspecific hybrids. The transcriptome assembly yielded 43,920 putative genes of which a large proportion were homologous to known genes in the public databases. Most of the genes encoding key enzymes involved in the FA and TAG synthesis pathways were identified. Of these, 27, including two candidate genes located within the QTL associated with C16:0 content, showed differential expression between developmental stages, populations and/or palms with contrasting C16:0 content. Further evaluation using quantitative real-time PCR revealed that differentially expressed patterns are generally consistent with those observed in the transcriptome data. Our results also suggest that different isoforms are likely to be responsible for some of the variation observed in FA composition of interspecific hybrids.

Background: There is a plethora of methods for genome-wide association studies. However, only a few of them may be classified as multi-trait and multi-locus, i.e. consider the influence of multiple genetic variants to several correlated phenotypes., Results: We propose a multi-trait multi-locus model which employs structural equation modeling (SEM) to describe complex associations between SNPs and traits - multi-trait multi-locus SEM (mtmlSEM). The structure of our model makes it possible to discriminate pleiotropic and single-trait SNPs of direct and indirect effect. We also propose an automatic procedure to construct the model using factor analysis and the maximum likelihood method. For estimating a large number of parameters in the model, we performed Bayesian inference and implemented Gibbs sampling. An important feature of the model is that it correctly copes with non-normally distributed variables, such as some traits and variants., Conclusions: We applied the model to Vavilov's collection of 404 chickpea (Cicer arietinum L.) accessions with 20-fold cross-validation. We analyzed 16 phenotypic traits which we organized into five groups and found around 230 SNPs associated with traits, 60 of which were of pleiotropic effect. The model demonstrated high accuracy in predicting trait values.

A defining challenge of the 21st century is meeting the nutritional demands of the growing human population, under a scenario of limited land and water resources and under the specter of climate change. The Vavilov seed bank contains numerous landraces collected nearly a hundred years ago, and thus may contain 'genetic gems' with the potential to enhance modern breeding efforts. Here, we analyze 407 landraces, sampled from major historic centers of chickpea cultivation and secondary diversification. Genome-Wide Association Studies (GWAS) conducted on both phenotypic traits and bioclimatic variables at landraces sampling sites as extended phenotypes resulted in 84 GWAS hits associated to various regions. The novel haploblock-based test identified haploblocks enriched for single nucleotide polymorphisms (SNPs) associated with phenotypes and bioclimatic variables. Subsequent bi-clustering of traits sharing enriched haploblocks underscored both non-random distribution of SNPs among several haploblocks and their association with multiple traits. We hypothesize that these clusters of pleiotropic SNPs represent co-adapted genetic complexes to a range of environmental conditions that chickpea experienced during domestication and subsequent geographic radiation. Linking genetic variation to phenotypic data and a wealth of historic information preserved in historic seed banks are the keys for genome-based and environment-informed breeding intensification.

Examining cross-tissue interactions is important for understanding physiology and homeostasis. In animals, the female gonad produces signaling molecules that act distally. We examine gene expression in Drosophila melanogaster female head tissues in 1) virgins without a germline compared to virgins with a germline, 2) post-mated females with and without a germline compared to virgins, and 3) post-mated females mated to males with and without a germline compared to virgins. In virgins, the absence of a female germline results in expression changes in genes with known roles in nutrient homeostasis. At one- and three-day(s) post-mating, genes that change expression are enriched with those that function in metabolic pathways, in all conditions. We systematically examine female post-mating impacts on sleep, food preference and re-mating, in the strains and time points used for gene expression analyses and compare to published studies. We show that post-mating, gene expression changes vary by strain, prompting us to examine variation in female re-mating. We perform a genome-wide association study that identifies several DNA polymorphisms, including four in/near Wnt signaling pathway genes. Together, these data reveal how gene expression and behavior in females are influenced by cross-tissue interactions, by examining the impact of mating, fertility, and genotype., (Copyright © 2020 Newell et al.)

Domestication and subsequent breeding have eroded genetic diversity in the modern chickpea crop by ˜100-fold. Corresponding reductions to trait variation create the need, and an opportunity, to identify and harness the genetic capacity of wild species for crop improvement. Here we analyze trait segregation in a series of wild x cultivated hybrid populations to delineate the genetic underpinnings of domestication traits. Two species of wild chickpea, C. reticulatum and C. echinospermum, were crossed with the elite, early flowering C. arietinum cultivar ICCV96029. KASP genotyping of F2 parents with an FT-linked molecular marker enabled selection of 284 F3 families with reduced phenological variation: 255 F3 families of C. arietinum x reticulatum (AR) derived from 17 diverse wild parents and 29 F3 families of C. arietinum x echinospermum (AE) from 3 wild parents. The combined 284 lineages were genotyped using a genotyping-by-sequencing strategy and phenotyped for agronomic traits. 50 QTLs in 11 traits were detected from AR and 35 QTLs in 10 traits from the combined data. Using hierarchical clustering to assign traits to six correlated groups and mixed model based multi-trait mapping, four pleiotropic loci were identified. Bayesian analysis further identified four inter-trait relationships controlling the duration of vegetative growth and seed maturation, for which the underlying pleiotropic genes were mapped. A random forest approach was used to explore the most extreme trait differences between AR and AE progenies, identifying traits most characteristic of wild species origin. Knowledge of the genomic basis of traits that segregate in wild-cultivated hybrid populations will facilitate chickpea improvement by linking genetic and phenotypic variation in a quantitative genetic framework., (Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: The gap gene system controls the early cascade of the segmentation pathway in Drosophila melanogaster as well as other insects. Owing to its tractability and key role in embryo patterning, this system has been the focus for both computational modelers and experimentalists. The gap gene expression dynamics can be considered strictly as a one-dimensional process and modeled as a system of reaction-diffusion equations. While substantial progress has been made in modeling this phenomenon, there still remains a deficit of approaches to evaluate competing hypotheses. Most of the model development has happened in isolation and there has been little attempt to compare candidate models., Results: The Bayesian framework offers a means of doing formal model evaluation. Here, we demonstrate how this framework can be used to compare different models of gene expression. We focus on the Papatsenko-Levine formalism, which exploits a fractional occupancy based approach to incorporate activation of the gap genes by the maternal genes and cross-regulation by the gap genes themselves. The Bayesian approach provides insight about relationship between system parameters. In the regulatory pathway of segmentation, the parameters for number of binding sites and binding affinity have a negative correlation. The model selection analysis supports a stronger binding affinity for Bicoid compared to other regulatory edges, as shown by a larger posterior mean. The procedure doesn't show support for activation of Kruppel by Bicoid., Conclusions: We provide an efficient solver for the general representation of the Papatsenko-Levine model. We also demonstrate the utility of Bayes factor for evaluating candidate models for spatial pattering models. In addition, by using the parallel tempering sampler, the convergence of Markov chains can be remarkably improved and robust estimates of Bayes factors obtained.

The explosive growth of genomic data provides an opportunity to make increased use of sequence variations for phenotype prediction. We have developed a prediction machine for quantitative phenotypes (WhoGEM) that overcomes some of the bottlenecks limiting the current methods. We demonstrated its performance by predicting quantitative disease resistance and quantitative functional traits in the wild model plant species, Medicago truncatula, using geographical locations as covariates for admixture analysis. The method's prediction reliability equals or outperforms all existing algorithms for quantitative phenotype prediction. WhoGEM analysis produces evidence that variation in genome admixture proportions explains most of the phenotypic variation for quantitative phenotypes.

Robustness in development allows for the accumulation of genetically based variation in expression. However, this variation is usually examined in response to large perturbations, and examination of this variation has been limited to being spatial, or quantitative, but because of technical restrictions not both. Here we bridge these gaps by investigating replicated quantitative spatial gene expression using rigorous statistical models, in different genotypes, sexes, and species (Drosophila melanogaster and D. simulans). Using this type of quantitative approach with molecular developmental data allows for comparison among conditions, such as different genetic backgrounds. We apply this approach to the morphogenetic furrow, a wave of differentiation that patterns the developing eye disc. Within the morphogenetic furrow, we focus on four genes, hairy, atonal, hedgehog, and Delta. Hybridization chain reaction quantitatively measures spatial gene expression, co-staining for all four genes simultaneously. We find considerable variation in the spatial expression pattern of these genes in the eye between species, genotypes, and sexes. We also find that there has been evolution of the regulatory relationship between these genes, and that their spatial interrelationships have evolved between species. This variation has no phenotypic effect, and could be buffered by network thresholds or compensation from other genes. Both of these mechanisms could potentially be contributing to long term developmental systems drift., (© 2019 Wiley Periodicals, Inc.)

In many biological systems gene expression at mRNA and protein levels is not identical. Rigorous comparison of such differences on a spatio-temporal scale is still not feasible by high-throughput transcriptomic and proteomic analyses of early embryo development. Here, we characterize differences between mRNA and protein expression of Drosophila segmentation genes at the level of individual gene expression domains. We obtained quantitative imaging data on expression of gap genes gt and hb and pair-rule gene eve for Drosophila wild type embryos, Kr null mutants and Kr+/Kr- heterozygotes. To compare mRNA and protein expression we use several criteria including difference in amplitude and positions of expression domains, pattern shape and positional variability. For a number of gene expression domains we show examples where protein expression does not repeat mRNA expression even after a temporal delay. We calculated time delays between eve pattern formation at the level of mRNA and protein for wild type embryos, Kr mutants and Kr+/Kr- heterozygotes. We detect that in wild type embryos, the amplitudes of eve stripes 3 and 7 do not differ significantly at the level of mRNA, however, stripe 3 is higher than stripe 7 at the protein level. We further show that hb mRNA and protein expression in both anterior and posterior domains significantly differs at specific time points. The formation of hb PS4 stripe at the mRNA level proceeds five times faster than at the level of protein. With regard to spatial expression, we show that the offset between posterior gt mRNA and protein domains is much larger in Kr mutants than in wild type embryos and heterozygotes. Finally, we analyze differences in positional variability of eve stripe 7 expression in Kr mutants and Kr+/Kr- heterozygotes at the level of mRNA and protein. These results enable further perspectives to uncover mechanisms underlying discrepancies between mRNA and protein expression in early embryo., (Copyright © 2019 Elsevier Inc. All rights reserved.)

During development of biological organisms, multiple complex structures are formed. In many instances, these structures need to exhibit a high degree of order to be functional, although many of their constituents are intrinsically stochastic. Hence, it has been suggested that biological robustness ultimately must rely on complex gene regulatory networks and clean-up mechanisms. Here we explore developmental processes that have evolved inherent robustness against stochasticity. In the context of the Drosophila eye disc, multiple optical units, ommatidia, develop into crystal-like patterns. During the larva-to-pupa stage of metamorphosis, the centers of the ommatidia are specified initially through the diffusion of morphogens, followed by the specification of R8 cells. Establishing the R8 cell is crucial in setting up the geometric, and functional, relationships of cells within an ommatidium and among neighboring ommatidia. Here we study an PDE mathematical model of these spatio-temporal processes in the presence of parametric stochasticity, defining and applying measures that quantify order within the resulting spatial patterns. We observe a universal sigmoidal response to increasing transcriptional noise. Ordered patterns persist up to a threshold noise level in the model parameters. In accordance with prior qualitative observations, as the noise is further increased past a threshold point of no return, these ordered patterns rapidly become disordered. Such robustness in development allows for the accumulation of genetic variation without any observable changes in phenotype. We argue that the observed sigmoidal dependence introduces robustness allowing for sizable amounts of genetic variation and transcriptional noise to be tolerated in natural populations without resulting in phenotype variation., Competing Interests: The authors have declared that no competing interests exist.

The impact of deleterious variation on both plant fitness and crop productivity is not completely understood and is a hot topic of debates. The deleterious mutations in plants have been solely predicted using sequence conservation methods rather than function-based classifiers due to lack of well-annotated mutational datasets in these organisms. Here, we developed a machine learning classifier based on a dataset of deleterious and neutral mutations in Arabidopsis thaliana by extracting 18 informative features that discriminate deleterious mutations from neutral, including 9 novel features not used in previous studies. We examined linear SVM, Gaussian SVM, and Random Forest classifiers, with the latter performing best. Random Forest classifiers exhibited a markedly higher accuracy than the popular PolyPhen-2 tool in the Arabidopsis dataset. Additionally, we tested whether the Random Forest, trained on the Arabidopsis dataset, accurately predicts deleterious mutations in Orýza sativa and Pisum sativum and observed satisfactory levels of performance accuracy (87% and 93%, respectively) higher than obtained by the PolyPhen-2. Application of Transfer learning in classifiers did not improve their performance. To additionally test the performance of the Random Forest classifier across different angiosperm species, we applied it to annotate deleterious mutations in Cicer arietinum and validated them using population frequency data. Overall, we devised a classifier with the potential to improve the annotation of putative functional mutations in QTL and GWAS hit regions, as well as for the evolutionary analysis of proliferation of deleterious mutations during plant domestication; thus optimizing breeding improvement and development of new cultivars.

Initiation of flowering moves plants from vegetative to reproductive development. The time when this transition happens (flowering time), an important indicator of productivity, depends on both endogenous and environmental factors. The core genetic regulatory network canalizing the flowering signals to the decision to flower has been studied extensively in the model plant Arabidopsis thaliana and has been shown to preserve its main regulatory blocks in other species. It integrates activation from the FLOWERING LOCUS T ( FT ) gene or its homologs to the flowering decision expressed as high expression of the meristem identity genes, including AP1 . We elaborated a dynamical model of this flowering gene regulatory network and applied it to the previously published expression data from two cultivars of domesticated chickpea ( Cicer arietinum ), obtained for two photoperiod durations. Due to a large number of free parameters in the model, we used an ensemble approach analyzing the model solutions at many parameter sets that provide equally good fit to data. Testing several alternative hypotheses about regulatory roles of the five FT homologs present in chickpea revealed no preference in segregating individual FT copies as singled-out activators with their own regulatory parameters, thus favoring the hypothesis that the five genes possess similar regulatory properties and provide cumulative activation in the network. The analysis reveals that different levels of activation from AP1 can explain a small difference observed in the expression of the two homologs of the repressor gene TFL1 . Finally, the model predicts highly reduced activation between LFY and AP1 , thus suggesting that this regulatory block is not conserved in chickpea and needs other mechanisms. Overall, this study provides the first attempt to quantitatively test the flowering time gene network in chickpea based on data-driven modeling.

Noncoding DNA sequences, which play various roles in gene expression and regulation, are under evolutionary pressure. Gene regulation requires specific protein-DNA binding events, and our previous studies showed that both DNA sequence and shape readout are employed by transcription factors (TFs) to achieve DNA binding specificity. By investigating the shape-disrupting properties of single nucleotide polymorphisms (SNPs) in human regulatory regions, we established a link between disruptive local DNA shape changes and loss of specific TF binding. Furthermore, we described cases where disease-associated SNPs may alter TF binding through DNA shape changes. This link led us to hypothesize that local DNA shape within and around TF binding sites is under selection pressure. To verify this hypothesis, we analyzed SNP data derived from 216 natural strains of Drosophila melanogaster. Comparing SNPs located in functional and nonfunctional regions within experimentally validated cis-regulatory modules (CRMs) from D. melanogaster that are active in the blastoderm stage of development, we found that SNPs within functional regions tended to cause smaller DNA shape variations. Furthermore, SNPs with higher minor allele frequency were more likely to result in smaller DNA shape variations. The same analysis based on a large number of SNPs in putative CRMs of the D. melanogaster genome derived from DNase I accessibility data confirmed these observations. Taken together, our results indicate that common SNPs in functional regions tend to maintain DNA shape, whereas shape-disrupting SNPs are more likely to be eliminated through purifying selection.

There is abundant variation in gene expression between individuals, populations, and species. The evolution of gene regulation and expression within and between species is thought to frequently contribute to adaptation. Yet considerable evidence suggests that the primary evolutionary force acting on variation in gene expression is stabilizing selection. We review here the results of recent studies characterizing the evolution of gene expression occurring in cis (via linked polymorphisms) or in trans (through diffusible products of other genes) and their contribution to adaptation and response to the environment. We review the evidence for buffering of variation in gene expression at the level of both transcription and translation, and the possible mechanisms for this buffering. Lastly, we summarize unresolved questions about the evolution of gene regulation., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Schizophrenia (SCZ) is a psychiatric disorder of unknown etiology. There is evidence suggesting that aberrations in neurodevelopment are a significant attribute of schizophrenia pathogenesis and progression. To identify biologically relevant molecular abnormalities affecting neurodevelopment in SCZ we used cultured neural progenitor cells derived from olfactory neuroepithelium (CNON cells). Here, we tested the hypothesis that variance in gene expression differs between individuals from SCZ and control groups. In CNON cells, variance in gene expression was significantly higher in SCZ samples in comparison with control samples. Variance in gene expression was enriched in five molecular pathways: serine biosynthesis, PI3K-Akt, MAPK, neurotrophin and focal adhesion. More than 14% of variance in disease status was explained within the logistic regression model (C-value = 0.70) by predictors accounting for gene expression in 69 genes from these five pathways. Structural equation modeling (SEM) was applied to explore how the structure of these five pathways was altered between SCZ patients and controls. Four out of five pathways showed differences in the estimated relationships among genes: between KRAS and NF1, and KRAS and SOS1 in the MAPK pathway; between PSPH and SHMT2 in serine biosynthesis; between AKT3 and TSC2 in the PI3K-Akt signaling pathway; and between CRK and RAPGEF1 in the focal adhesion pathway. Our analysis provides evidence that variance in gene expression is an important characteristic of SCZ, and SEM is a promising method for uncovering altered relationships between specific genes thus suggesting affected gene regulation associated with the disease. We identified altered gene-gene interactions in pathways enriched for genes with increased variance in expression in SCZ. These pathways and loci were previously implicated in SCZ, providing further support for the hypothesis that gene expression variance plays important role in the etiology of SCZ.

Comparative genomics has become a central tool for evolutionary biology, and a better knowledge of understudied taxa represents the foundation for future work. In this study, we characterized the transcriptome of male and female mature gonads in the European clam Ruditapes decussatus, compared with that in the Manila clam Ruditapes philippinarum providing, for the first time in bivalves, information about transcription dynamics and sequence evolution of sex-biased genes. In both the species, we found a relatively low number of sex-biased genes (1,284, corresponding to 41.3% of the orthologous genes between the two species), probably due to the absence of sexual dimorphism, and the transcriptional bias is maintained in only 33% of the orthologs. The dN/dS is generally low, indicating purifying selection, with genes where the female-biased transcription is maintained between the two species showing a significantly higher dN/dS. Genes involved in embryo development, cell proliferation, and maintenance of genome stability show a faster sequence evolution. Finally, we report a lack of clear correlation between transcription level and evolutionary rate in these species, in contrast with studies that reported a negative correlation. We discuss such discrepancy and call into question some methodological approaches and rationales generally used in this type of comparative studies.

The genomes of mammals contain thousands of deleterious mutations. It is important to be able to recognize them with high precision. In conservation biology, the small size of fragmented populations results in accumulation of damaging variants. Preserving animals with less damaged genomes could optimize conservation efforts. In breeding of farm animals, trade-offs between farm performance versus general fitness might be better avoided if deleterious mutations are well classified. In humans, the problem of such a precise classification has been successfully solved, in large part due to large databases of disease-causing mutations. However, this kind of information is very limited for other mammals. Here, we propose to better use information available on human mutations to enable classification of damaging mutations in other mammalian species. Specifically, we apply transfer learning-machine learning methods-improving small dataset for solving a focal problem (recognizing damaging mutations in our companion and farm animals) due to the use of much large datasets available for solving a related problem (recognizing damaging mutations in humans). We validate our tools using mouse and dog annotated datasets and obtain significantly better results in companion to the SIFT classifier. Then, we apply them to predict deleterious mutations in cattle genomewide dataset.

Chickpea ( L.) production in arid regions, such as those predominant in Pakistan, faces immense challenges of drought and heat stress. Addressing these challenges is made more difficult by the lack of genetic and phenotypic characterization of available cultivated varieties and breeding materials. Genotyping-by-sequencing offers a rapid and cost-effective means to identify genome-wide nucleotide variation in crop germplasm. When combined with extended crop phenotypes deduced from climatic variation at sites of collection, the data can predict which portions of genetic variation might have roles in climate resilience. Here we use 8113 single nucleotide polymorphism markers to determine genetic variation and compare population structure within a previously uncharacterized collection of 77 landraces and 5 elite cultivars, currently grown in situ on farms throughout the chickpea growing regions of Pakistan. The compiled landraces span a striking aridity gradient into the Thal Desert of the Punjab. Despite low levels of variation across the collection and limited genetic structure, we found some differentiation between accessions from arid, semiarid, irrigated, and coastal areas. In a subset of 232 markers, we found evidence of differentiation along gradients of elevation and isothermality. Our results highlight the utility of exploring large germplasm collections for nucleotide variation associated with environmental extremes, and the use of such data to nominate germplasm accessions with the potential to improve crop drought tolerance and other environmental traits., (Copyright © 2018 Crop Science Society of America.)

Domesticated species are impacted in unintended ways during domestication and breeding. Changes in the nature and intensity of selection impart genetic drift, reduce diversity, and increase the frequency of deleterious alleles. Such outcomes constrain our ability to expand the cultivation of crops into environments that differ from those under which domestication occurred. We address this need in chickpea, an important pulse legume, by harnessing the diversity of wild crop relatives. We document an extreme domestication-related genetic bottleneck and decipher the genetic history of wild populations. We provide evidence of ancestral adaptations for seed coat color crypsis, estimate the impact of environment on genetic structure and trait values, and demonstrate variation between wild and cultivated accessions for agronomic properties. A resource of genotyped, association mapping progeny functionally links the wild and cultivated gene pools and is an essential resource chickpea for improvement, while our methods inform collection of other wild crop progenitor species.

Background: Restriction-site associated DNA sequencing (RADseq) technology was recently employed to identify a large number of single nucleotide polymorphisms (SNP) for linkage mapping of a North American and Eastern Asian Populus species. However, there is also the need for high-density genetic linkage maps for the European aspen (P. tremula) as a tool for further mapping of quantitative trait loci (QTLs) and marker-assisted selection of the Populus species native to Europe., Results: We established a hybrid F1 population from the cross of two aspen parental genotypes diverged in their phenological and morphological traits. We performed RADseq of 122 F1 progenies and two parents yielding 15,732 high-quality SNPs that were successfully identified using the reference genome of P. trichocarpa. 2055 SNPs were employed for the construction of maternal and paternal linkage maps. The maternal linkage map was assembled with 1000 SNPs, containing 19 linkage groups and spanning 3054.9 cM of the genome, with an average distance of 3.05 cM between adjacent markers. The paternal map consisted of 1055 SNPs and the same number of linkage groups with a total length of 3090.56 cM and average interval distance of 2.93 cM. The linkage maps were employed for QTL mapping of one-year-old seedlings height variation. The most significant QTL (LOD = 5.73) was localized to LG5 (96.94 cM) of the male linkage map, explaining 18% of the phenotypic variation., Conclusions: The set of 15,732 SNPs polymorphic in aspen and high-density genetic linkage maps constructed for the P. tremula intra-specific cross will provide a valuable source for QTL mapping and identification of candidate genes facilitating marker-assisted selection in European aspen.

Indirect genetic effects (IGEs) describe the effect of the genes of social partners on the phenotype of a focal individual. Here, we measure indirect genetic effects using the "coefficient of interaction" (Ψ) to test whether Ψ evolved between Drosophila melanogaster and D. simulans . We compare Ψ for locomotion between ethanol and nonethanol environments in both species, but only D. melanogaster utilizes ethanol ecologically. We find that while sexual dimorphism for locomotion has been reversed in D. simulans , there has been no evolution of social effects between these two species. What did evolve was the interaction between genotype-specific Ψ and the environment, as D. melanogaster  varies unpredictably between environments and D. simulans  does not. In this system, this suggests evolutionary lability of sexual dimorphism but a conservation of social effects, which brings forth interesting questions about the role of the social environment in sexual selection.

Despite the significant advance in our understanding of the molecular basis of light entrainment of the circadian clock in Drosophila, the underlying genetic architecture is still largely unknown. The aim of this study was to identify loci associated with variation in circadian photosensitivity, which are important for the evolution of this trait. We have used complementary approaches that combined quantitative trait loci (QTL) mapping, complementation testing, and transcriptome profiling to dissect this variation. We identified a major QTL on chromosome 2, which was subsequently fine mapped using deficiency complementation mapping into 2 smaller regions spanning 139 genes, some of which are known to be involved in functions that have been previously implicated in light entrainment. Two genes implicated with the clock and located within that interval, timeless and cycle, failed to complement the QTL, indicating that alleles of these genes contribute to the variation in light response. Specifically, we find that the timeless s/ ls polymorphism that has been previously shown to constitute a latitudinal cline in Europe is also segregating in our recombinant inbred lines and is contributing to the phenotypic variation in light sensitivity. We also profiled gene expression in 2 recombinant inbred strains that differ significantly in their photosensitivity and identified a total of 368 transcripts that showed differential expression (false discovery rate < 0.1). Of 131 transcripts that showed a significant recombinant inbred line by treatment interaction (i.e., putative expression QTL), 4 are located within QTL2.

Annotating the genotype-phenotype relationship, and developing a proper quantitative description of the relationship, requires understanding the impact of natural genomic variation on gene expression. We apply a sequence-level model of gap gene expression in the early development of Drosophila to analyze single nucleotide polymorphisms (SNPs) in a panel of natural sequenced D. melanogaster lines. Using a thermodynamic modeling framework, we provide both analytical and computational descriptions of how single-nucleotide variants affect gene expression. The analysis reveals that the sequence variants increase (decrease) gene expression if located within binding sites of repressors (activators). We show that the sign of SNP influence (activation or repression) may change in time and space and elucidate the origin of this change in specific examples. The thermodynamic modeling approach predicts non-local and non-linear effects arising from SNPs, and combinations of SNPs, in individual fly genotypes. Simulation of individual fly genotypes using our model reveals that this non-linearity reduces to almost additive inputs from multiple SNPs. Further, we see signatures of the action of purifying selection in the gap gene regulatory regions. To infer the specific targets of purifying selection, we analyze the patterns of polymorphism in the data at two phenotypic levels: the strengths of binding and expression. We find that combinations of SNPs show evidence of being under selective pressure, while individual SNPs do not. The model predicts that SNPs appear to accumulate in the genotypes of the natural population in a way biased towards small increases in activating action on the expression pattern. Taken together, these results provide a systems-level view of how genetic variation translates to the level of gene regulatory networks via combinatorial SNP effects.

Despite the large number of animal complete mitochondrial genomes currently available in public databases, knowledge about mitochondrial genomics in invertebrates is uneven. This paper reports, for the first time, the complete mitochondrial genome of the grooved carpet shell, Ruditapes decussatus , also known as the European clam. Ruditapes decussatus is morphologically and ecologically similar to the Manila clam Ruditapes philippinarum , which has been recently introduced for aquaculture in the very same habitats of Ruditapes decussatus , and that is replacing the native species. Currently the production of the European clam is almost insignificant, nonetheless it is considered a high value product, and therefore it is an economically important species, especially in Portugal, Spain and Italy. In this work we: (i) assembled Ruditapes decussatus mitochondrial genome from RNA-Seq data, and validated it by Sanger sequencing; (ii) analyzed and characterized the Ruditapes decussatus mitochondrial genome, comparing its features with those of other venerid bivalves; (iii) assessed mitochondrial sequence polymorphism (SP) and copy number variation (CNV) of tandem repeats across 26 samples. Despite using high-throughput approaches we did not find evidence for the presence of two sex-linked mitochondrial genomes, typical of the doubly uniparental inheritance of mitochondria, a phenomenon known in ∼100 bivalve species. According to our analyses, Ruditapes decussatus is more genetically similar to species of the Genus Paphia than to the congeneric Ruditapes philippinarum , a finding that bolsters the already-proposed need of a taxonomic revision. We also found a quite low genetic variability across the examined samples, with few SPs and little variability of the sequences flanking the control region (Largest Unassigned Regions (LURs). Strikingly, although we found low nucleotide variability along the entire mitochondrial genome, we observed high levels of length polymorphism in the LUR due to CNV of tandem repeats, and even a LUR length heteroplasmy in two samples. It is not clear if the lack of genetic variability in the mitochondrial genome of Ruditapes decussatus is a cause or an effect of the ongoing replacement of Ruditapes decussatus with the invasive Ruditapes philippinarum , and more analyses, especially on nuclear sequences, are required to assess this point., Competing Interests: The authors declare that they have no competing interests.

The most basic models of learning are reinforcement learning models (for instance, classical and operant conditioning) that posit a constant learning rate; however many animals change their learning rates with experience. This process is sometimes studied by reversing an existing association between cues and rewards, and measuring the rate of relearning. Augmented reversal-learning, where learning rates increase with practice, can be an important component of behavioral flexibility; and may provide insight into higher cognition. Previous studies of reversal-learning in Drosophila have not measured learning rates, but have tended to focus on measuring gross deficits in reversal-learning, as the ratio of two timepoints. These studies have uncovered a diversity of mechanisms underlying reversal-learning, but natural genetic variation in this trait has yet to be assessed. We conducted a reversal-learning regime on a diverse panel of Drosophila melanogaster genotypes. We found highly significant genetic variation in their baseline ability to learn. We also found that they have a consistent, and strong (1.3×), increase in their learning speed with reversal. We found no evidence, however, that there was genetic variation in their ability to increase their learning rates with experience. This may suggest that Drosophila have a hitherto unrecognized ability to integrate acquired information, and improve their decision making; but that their mechanisms for doing so are under strong constraints.

The Vavilov Institute of Plant Genetic Resources (VIR), in St. Petersburg, Russia, houses a unique genebank, with historical collections of landraces. When they were collected, the geographical distribution and genetic diversity of most crops closely reflected their historical patterns of cultivation established over the preceding millennia. We employed a combination of genomics, computational biology and phenotyping to characterize VIR's 147 chickpea accessions from Turkey and Ethiopia, representing chickpea's center of origin and a major location of secondary diversity. Genotyping by sequencing identified 14,059 segregating polymorphisms and genome-wide association studies revealed 28 GWAS hits in potential candidate genes likely to affect traits of agricultural importance. The proportion of polymorphisms shared among accessions is a strong predictor of phenotypic resemblance, and of environmental similarity between historical sampling sites. We found that 20 out of 28 polymorphisms, associated with multiple traits, including days to maturity, plant phenology, and yield-related traits such as pod number, localized to chromosome 4. We hypothesize that selection and introgression via inadvertent hybridization between more and less advanced morphotypes might have resulted in agricultural improvement genes being aggregated to genomic 'agro islands', and in genotype-to-phenotype relationships resembling widespread pleiotropy.

Correlations among traits, including behaviors, are important because traits that are genetically correlated may not evolve independently. Recently, behavioral-correlations research has expanded to include correlations not only in mean-level behaviors but also in behavioral plasticity, that is, the degree to which individuals change their behavior in response to environmental stimuli. Positive correlations among behavioral plasticities would imply that individuals or genotypes that are behaviorally plastic in one way may also be plastic in other ways; negative correlations could imply trade-offs. Here, we examine aversive odor conditioning (learning) at two time points and plasticity in pupation site selection behavior across substrates in a panel of Drosophila genotypes. These behaviors represent different types of behavioral plasticity: contextual plasticity describes behavioral responses to stimuli that are currently present, while developmental plasticity describes behavioral responses to remembered experiences with stimuli in the recent past. We find that learning scores and plasticity in pupation site selection behavior are positively genetically correlated, representing the first example of a genetic correlation between developmental and contextual plasticity. These findings imply that ecological and evolutionary theories focusing on variation in a single dimension of behavioral plasticity may be incomplete.

Despite strong purifying or directional selection, variation is ubiquitous in populations. One mechanism for the maintenance of variation is indirect genetic effects (IGEs), as the fitness of a given genotype will depend somewhat on the genes of its social partners. IGEs describe the effect of genes in social partners on the expression of the phenotype of a focal individual. Here, we ask what effect IGEs, and variation in IGEs between abiotic environments, has on locomotion in Drosophila. This trait is known to be subject to intralocus sexually antagonistic selection. We estimate the coefficient of interaction, Ψ, using six inbred lines of Drosophila. We found that Ψ varied between abiotic environments, and that it may vary across among male genotypes in an abiotic environment specific manner. We also found evidence that social effects of males alter the value of a sexually dimorphic trait in females, highlighting an interesting avenue for future research into sexual antagonism. We conclude that IGEs are an important component of social and sexual interactions and that they vary between individuals and abiotic environments in complex ways, with the potential to promote the maintenance of phenotypic variation., (© 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.)

Background: Cis-regulatory sequences are often composed of many low-affinity transcription factor binding sites (TFBSs). Determining the evolutionary and functional importance of regulatory sequence composition is impeded without a detailed knowledge of the genotype-phenotype map., Results: We simulate the evolution of regulatory sequences involved in Drosophila melanogaster embryo segmentation during early development. Natural selection evaluates gene expression dynamics produced by a computational model of the developmental network. We observe a dramatic decrease in the total number of transcription factor binding sites through the course of evolution. Despite a decrease in average sequence binding energies through time, the regulatory sequences tend towards organisations containing increased high affinity transcription factor binding sites. Additionally, the binding energies of separate sequence segments demonstrate ubiquitous mutual correlations through time. Fewer than 10% of initial TFBSs are maintained throughout the entire simulation, deemed 'core' sites. These sites have increased functional importance as assessed under wild-type conditions and their binding energy distributions are highly conserved. Furthermore, TFBSs within close proximity of core sites exhibit increased longevity, reflecting functional regulatory interactions with core sites., Conclusion: In response to elevated mutational pressure, evolution tends to sample regulatory sequence organisations with fewer, albeit on average, stronger functional transcription factor binding sites. These organisations are also shaped by the regulatory interactions among core binding sites with sites in their local vicinity.

Background: The world is rapidly urbanizing, and only a subset of species are able to succeed in stressful city environments. Efficient genome-enabled stress response appears to be a likely prerequisite for urban adaptation. Despite the important role ants play in the ecosytem, only the genomes of ~13 have been sequenced so far. Here, we present the draft genome assembly of the black garden ant Lasius niger - the most successful urban inhabitant of all ants - and we compare it with the genomes of other ant species, including the closely related Camponotus floridanus., Results: Sequences from 272 M Illumina reads were assembled into 41,406 contigs with total length of 245 MB, and N50 of 16,382 bp, similar to other ant genome assemblies enabling comparative genomic analysis. Remarkably, the predicted proteome of L. niger is significantly enriched relative to other ant genomes in terms of abundance of domains involved in nucleic acid binding, DNA repair, and nucleotidyl transferase activity, reflecting transposable element proliferation and a likely genomic response. With respect to environmental stress, we note a proliferation of various detoxification genes, including glutatione-S-transferases and those in the cytochrome P450 families. Notably, the CYP9 family is highly expanded with 19 complete and 21 nearly complete members - over twice as many compared to other ants. This family exhibits the signatures of strong directional selection, with eleven positively selected positions in ligand-binding pockets of enzymes. Gene family contraction was detected for several components of the olfactory system, accompanied by instances of both directional selection and relaxation., Conclusions: Our results suggest that the success of L. niger in urbanized areas may be the result of fortuitous coincidence of several factors, including the expansion of the CYP9 cytochrome family due to coevolution with parasitic fungi, the diversification of DNA repair systems as an answer to proliferation of retroelements, and the reduction of olfactory system and behavioral preadaptations from non-territorial subdominant life strategies found in natural environments. Diversification of cytochromes and DNA repair systems along with reduced odorant communication are the basis of L. niger pollutant resistance and polyphagy, while non-territorial and mobilization strategies allows more efficient exploitation of large but patchy food sources.

Regulatory variation in gene expression can be described by cis- and trans-genetic components. Here we used RNA-seq data from a population panel of Drosophila melanogaster test crosses to compare allelic imbalance (AI) in female head tissue between mated and virgin flies, an environmental change known to affect transcription. Indeed, 3048 exons (1610 genes) are differentially expressed in this study. A Bayesian model for AI, with an intersection test, controls type I error. There are ∼200 genes with AI exclusively in mated or virgin flies, indicating an environmental component of expression regulation. On average 34% of genes within a cross and 54% of all genes show evidence for genetic regulation of transcription. Nearly all differentially regulated genes are affected in cis, with an average of 63% of expression variation explained by the cis-effects. Trans-effects explain 8% of the variance in AI on average and the interaction between cis and trans explains an average of 11% of the total variance in AI. In both environments cis- and trans-effects are compensatory in their overall effect, with a negative association between cis- and trans-effects in 85% of the exons examined. We hypothesize that the gene expression level perturbed by cis-regulatory mutations is compensated through trans-regulatory mechanisms, e.g., trans and cis by trans-factors buffering cis-mutations. In addition, when AI is detected in both environments, cis-mated, cis-virgin, and trans-mated-trans-virgin estimates are highly concordant with 99% of all exons positively correlated with a median correlation of 0.83 for cis and 0.95 for trans We conclude that the gene regulatory networks (GRNs) are robust and that trans-buffering explains robustness., (Copyright © 2016 by the Genetics Society of America.)

Rhynchospio Hartman, 1936 is a small group of spionid polychaetes currently comprising ten described species distributed mainly in the Pacific. Five species examined to date are hermaphrodites producing spermatozoa with long nuclei, oocytes with thin and smooth envelopes, and dorsally brooding their offspring. Since our first molecular analysis of four Rhynchospio species, we have collected additional material from Northern Territory, Australia, and Oregon, USA. Herein, we describe the gamete and adult morphology of the newly collected material and use molecular analyses to provide new insight on the phylogenetic relationships of six Rhynchospio species. Adults of R. cf. foliosa from Oregon are hermaphrodites, but in contrast to other Rhynchospio, they produce spermatozoa with short nuclei (ect-aquasperm), oocytes with thick vesiculate envelopes, and likely have a holopelagic larval development. Analysis of four gene fragments, comprising mitochondrial 16S rDNA, and nuclear 18S, 28S rDNA, and Histone 3 (2516 bp in total) showed Rhynchospio to be a monophyletic group, with R. cf. foliosa being a distant sister to the five other species. Rhynchospio cf. foliosa was closer to M. arctia having ect-aquasperm and vesiculate thick-envelop oocytes (p = 14.40%) than to Spioninae members B. proboscidea and P. elegans, having introsperm and oocytes with thin and smooth envelopes (p = 15.39 and 16.54%, respectively). We hypothesize that brooding might have evolved from free-spawning inside the Rhynchospio clade, but this hypothesis should be tested in a future analysis.

Animal development is the product of distinct components and interactions-genes, regulatory networks, and cells-and it exhibits emergent properties that cannot be inferred from the components in isolation. Often the focus is on the genotype-to-phenotype map, overlooking the process of development that turns one into the other. We propose a move toward micro-evolutionary analysis of development, incorporating new tools that enable cell type resolution and single-cell microscopy. Using the sex determination pathway in Drosophila to illustrate potential avenues of research, we highlight some of the questions that these emerging technologies can address. For example, they provide an unprecedented opportunity to study heterogeneity within cell populations, and the potential to add the dimension of time to gene regulatory network analysis. Challenges still remain in developing methods to analyze this data and to increase the throughput. However this line of research has the potential to bridge the gaps between previously more disparate fields, such as population genetics and development, opening up new avenues of research., (© 2016 Wiley Periodicals, Inc.)