The differential view of genotype-phenotype relationships

Review: Ruminant heat-stress terminology

With increasing climate variability, there is a rise in the exposure to, and incidence of, ruminant heat stress (HS), increasing the requirement for focused research. As such, precise terminology is crucial to maintain effective communication and knowledge advancement. Despite this, several key terms are currently defined inconsistently, leading to confusion and misinterpretation. This paper examines the historical and contemporary use of the terms 'resistance', 'tolerance', 'resilience', and 'susceptibility' across various disciplines, revealing significant ambiguities that hinder both research and practice. Through this comprehensive review, we propose new definitions for each term as they are used relating to HS, with a focus on ruminant production. Proposed definitions align with current scientific understanding, providing a robust framework for future research and application. As further research is conducted, we hope these definitions can be improved through the inclusion of quantitative measures which align with these classifications. This present review provides definition clarity for common heat abatement terminology, enabling consistency and from this, progress in the field to ameliorate HS for ruminants.

Robustness quantification of a mutant library screen revealed key genetic markers in yeast

BACKGROUND

Microbial robustness is crucial for developing cell factories that maintain consistent performance in a challenging environment such as large-scale bioreactors. Although tools exist to assess and understand robustness at a phenotypic level, the underlying metabolic and genetic mechanisms are not well defined, which limits our ability to engineer more strains with robust functions.

RESULTS

This study encompassed four steps. (I) Fitness and robustness were analyzed from a published dataset of yeast mutants grown in multiple environments. (II) Genes and metabolic processes affecting robustness or fitness were identified, and 14 of these genes were deleted in Saccharomyces cerevisiae CEN.PK113-7D. (III) The mutants bearing gene deletions were cultivated in three perturbation spaces mimicking typical industrial processes. (IV) Fitness and robustness were determined for each mutant in each perturbation space. We report that robustness varied according to the perturbation space. We identified genes associated with increased robustness such as MET28, linked to sulfur metabolism; as well as genes associated with decreased robustness, including TIR3 and WWM1, both involved in stress response and apoptosis.

CONCLUSION

The present study demonstrates how phenomics datasets can be analyzed to reveal the relationship between phenotypic response and associated genes. Specifically, robustness analysis makes it possible to study the influence of single genes and metabolic processes on stable microbial performance in different perturbation spaces. Ultimately, this information can be used to enhance robustness in targeted strains.

Comparison of the gene expression profile of testicular tissue before and after sexual maturity in Qianbei Ma goats

BACKGROUND

With long-term research on the reproductive ability of Qianbei Ma goat, we found that the puberty of the male goats comes at the age of 3 months and reaches sexual maturity at 4 months,the male goats are identified as physically mature at 9 months and able to mate. Compared with other kinds of breeds of goats, Qianbei Ma goat is featured with more faster growth and earlier sexual maturity.Therefore, in order to explore the laws of growth of Qianbei Ma goat before sexual maturity(3-month-old)and after sexual maturity (9-month-old). The testicular tissue was collected to explore their changes in morphology through HE staining, the serum was collected to detect the hormone content, and the mRNA expression profile of the testis was analyzed by transcriptomics. In this way, the effect of testicular development on the reproduction of Qianbei ma goats was further analyzed.

RESULTS

The results showed that the area and diameter of spermatogenic tubules were larger at 9 months than 3 months, and the number of spermatocytes, interstitial cells, spermatogonia and secondary spermatocytes in the lumen of the tubules showed a similar trend. The appearance of spermatozoa at age 3 months indicated that puberty had begun in Qianbei Ma goats. The Elasa test for testosterone, luteinizing hormone, follicle stimulating hormone and anti-Müllerian hormone showed that the levels of these hormones in the serum at age 9 months were all highly significantly different than those at age 3 months (P < 0.01). There were 490 differentially expressed genes (DEGs) between the (|log2(fold change)| > 1 and p value < 0.05) 3-month-old and 9-month-old groups, of which 233 genes were upregulated and 257 genes were downregulated (3 months of age was used as the control group and 9 months of age was used as the experimental group). According to the GO and KEGG enrichment analyses of DEGs, PRSS58, ECM1, WFDC8 and LHCGR are involved in testicular development and androgen secretion, which contribute to the sexual maturation of Qianbei Ma goats.

CONCLUSIONS

Potential biomarker genes and relevant pathways involved in the regulation of testicular development and spermatogenesis in Qianbei Ma goats were identified, providing a theoretical basis and data support for later studies on the influence of testicular development and spermatogenesis before and after sexual maturity in Qianbei Ma goats.

CyVerse: Cyberinfrastructure for open science

CyVerse, the largest publicly-funded open-source research cyberinfrastructure for life sciences, has played a crucial role in advancing data-driven research since the 2010s. As the technology landscape evolved with the emergence of cloud computing platforms, machine learning and artificial intelligence (AI) applications, CyVerse has enabled access by providing interfaces, Software as a Service (SaaS), and cloud-native Infrastructure as Code (IaC) to leverage new technologies. CyVerse services enable researchers to integrate institutional and private computational resources, custom software, perform analyses, and publish data in accordance with open science principles. Over the past 13 years, CyVerse has registered more than 124,000 verified accounts from 160 countries and was used for over 1,600 peer-reviewed publications. Since 2011, 45,000 students and researchers have been trained to use CyVerse. The platform has been replicated and deployed in three countries outside the US, with additional private deployments on commercial clouds for US government agencies and multinational corporations. In this manuscript, we present a strategic blueprint for creating and managing SaaS cyberinfrastructure and IaC as free and open-source software.

The balance of survival: Comparative drought response in wild and domesticated tomatoes

Plants have the ability to undergo reversible behavioral, morphological, or physiological changes in response to environmental conditions. This plasticity enables plants to cope with uncertain environmental conditions, such as drought. A primary plastic trait is the rate of stomatal response to changes in ambient conditions, which determines the amount of water lost via transpiration, as well as levels of CO2 absorption, growth, and productivity. Here, we examined the differences between domesticated (S. lycopersicum cv. M82) and wild tomato (S. pennellii) species and their responses to drought stress. The plants were grown in pots in a functional phenotyping platform (FPP) in a semi-controlled environment greenhouse. We found that the domesticated tomato had a higher transpiration rate (E) and higher stomatal conductance (gs). The domesticated tomato also had greater biomass and greater leaf area under drought conditions, as compared to the wild tomato. Despite the domesticated tomato's higher E and higher gs, there was no difference between the photosynthetic rates (An) of the two lines. Moreover, the wild tomato had a higher maximum rate of rubisco activity (Vcmax), which might explain its greater leaf level and whole canopy water-use efficiency. The domesticated tomato's higher E and greater leaf area led to its earlier exposure to drought stress, as compared to the wild tomato, which maintained higher levels of soil water, enabling it to maintain steady rates of whole-canopy stomatal conductance (gsc) for extended periods. The wild tomato was also more sensitive to soil water availability and lowered its maximum transpiration rate (Emax) at a higher soil-water-content (SWC) level compared to the domesticated species. Our results suggest that the domestication of tomatoes favored morphological/anatomical performance traits over physiological efficiency.

Discovering genotype-phenotype relationships with machine learning and the Visual Physiology Opsin Database (VPOD)

BACKGROUND

Predicting phenotypes from genetic variation is foundational for fields as diverse as bioengineering and global change biology, highlighting the importance of efficient methods to predict gene functions. Linking genetic changes to phenotypic changes has been a goal of decades of experimental work, especially for some model gene families, including light-sensitive opsin proteins. Opsins can be expressed in vitro to measure light absorption parameters, including λmax-the wavelength of maximum absorbance-which strongly affects organismal phenotypes like color vision. Despite extensive research on opsins, the data remain dispersed, uncompiled, and often challenging to access, thereby precluding systematic and comprehensive analyses of the intricate relationships between genotype and phenotype.

RESULTS

Here, we report a newly compiled database of all heterologously expressed opsin genes with λmax phenotypes that we call the Visual Physiology Opsin Database (VPOD). VPOD_1.0 contains 864 unique opsin genotypes and corresponding λmax phenotypes collected across all animals from 73 separate publications. We use VPOD data and deepBreaks to show regression-based machine learning (ML) models often reliably predict λmax, account for nonadditive effects of mutations on function, and identify functionally critical amino acid sites.

CONCLUSION

The ability to reliably predict functions from gene sequences alone using ML will allow robust exploration of molecular-evolutionary patterns governing phenotype, will inform functional and evolutionary connections to an organism's ecological niche, and may be used more broadly for de novo protein design. Together, our database, phenotype predictions, and model comparisons lay the groundwork for future research applicable to families of genes with quantifiable and comparable phenotypes.

Convergent genomic signatures of local adaptation across a continental-scale environmental gradient

Convergent local adaptation offers a glimpse into the role of constraint and stochasticity in adaptive evolution, in particular the extent to which similar genetic mechanisms drive adaptation to common selective forces. Here, we investigated the genomics of local adaptation in two nonsister woodpeckers that are codistributed across an entire continent and exhibit remarkably convergent patterns of geographic variation. We sequenced the genomes of 140 individuals of Downy (Dryobates pubescens) and Hairy (Dryobates villosus) woodpeckers and used a suite of genomic approaches to identify loci under selection. We showed evidence that convergent genes have been targeted by selection in response to shared environmental pressures, such as temperature and precipitation. Among candidates, we found multiple genes putatively linked to key phenotypic adaptations to climate, including differences in body size (e.g., IGFPB) and plumage (e.g., MREG). These results are consistent with genetic constraints limiting the pathways of adaptation to broad climatic gradients, even after genetic backgrounds diverge.

Functional comparison of metabolic networks across species

Metabolic phenotypes are pivotal for many areas, but disentangling how evolutionary history and environmental adaptation shape these phenotypes is an open problem. Especially for microbes, which are metabolically diverse and often interact in complex communities, few phenotypes can be determined directly. Instead, potential phenotypes are commonly inferred from genomic information, and rarely were model-predicted phenotypes employed beyond the species level. Here, we propose sensitivity correlations to quantify similarity of predicted metabolic network responses to perturbations, and thereby link genotype and environment to phenotype. We show that these correlations provide a consistent functional complement to genomic information by capturing how network context shapes gene function. This enables, for example, phylogenetic inference across all domains of life at the organism level. For 245 bacterial species, we identify conserved and variable metabolic functions, elucidate the quantitative impact of evolutionary history and ecological niche on these functions, and generate hypotheses on associated metabolic phenotypes. We expect our framework for the joint interpretation of metabolic phenotypes, evolution, and environment to help guide future empirical studies.

Genome-Wide association analysis of phenotypic traits in Bambara groundnut under drought-stressed and non-stressed conditions based on DArTseq SNP

INTRODUCTION

Bambara groundnut (BG) (Vigna subterranea [L.] Verdc) is an indigenous, resilient, but underutilized leguminous crop that occurs mostly as genetically heterogeneous landraces with limited information on the drought tolerant attributes. This study elucidates the associations between sequencing-based diversity array technology (DArTseq) and phenotypic character as well as differing indices related to drought tolerance in one hundred accessions of Bambara groundnut.

METHODS

The field experiments were conducted at IITA research stations in Kano and Ibadan between 2016 and 2018 planting seasons. The experiments were arranged in randomised complete block design with three replications, under the different water regimes. The phenotypic traits evaluated was further to construct the dendrogram. Genome-wide association mapping was conducted based on 5927 DArTs loci with < 20% missing data.

RESULTS AND DISCUSSIONS

The genome wide association study predicted drought tolerance in Bambara accessions for geometric mean productivity (GMP) and stress tolerance index (STI). TVSu-423 had the highest GMP and STI values (28.50, 2.40), while TVSu-2017 had the lowest at GMP (1.74) and STI (0.01) respectively. The relative water content (%) was significantly higher for accessions; TVSu-266 (60.35, 61.49), TVSu-2 (58.29, 53.94), and TVSu-411 (55.17, 58.92) in 2016/2017 and 2017/2018, respectively. The phenotypic characters studied delineated the accessions into two major clusters and five distinct sub-clusters, indicating variations across all the geographical locations. The 5,927 DArTseq genomic markers in association with STI further grouped the 100 accessions into two main clusters. TVSu-1897 from Botswana (Southern Africa) was in the first cluster, while the remaining 99 accessions from Western, Central, and Eastern Africa made up the second cluster. The eight significant Quantitative Trait Loci (QTLs) (24346377|F|0-22:A>G-22:A>G, 24384105|F|0-56:A>G33 :A> G, 24385643|F|0-53:G>C-53:G>C, 24385696|F|0-43:A>G-43:A>G, 4177257|F|0-44:A>T-44:A>T, 4182070|F|0-66:G>A-66:G>A, 4183483|F|0-24:G>A-24:G>A, 4183904|F|0-11:C>T-11:C>T) identified with Bonferroni threshold was in association with STI, indicative of variations under the drought-stressed condition. The observation of consistent SNPs in the 2016 and 2017 planting seasons, as well as in combination with the 2016 and 2017 planting seasons, led to the designation of these QTLs as significant. The drought selected accessions could form basis for hybridization breeding. The identified quantitative trait loci could be useful in marker-assisted selection in drought molecular breeding programs.

In silico analysis of substitution mutations in the β-globin gene in Turkish population of β-thalassemia

Beta-thalassemia is a genetic blood disorder represented by anomalies in hemoglobin's beta chain production. Most hemoglobin defects are a result of mutations of the structural β-globin gene. Many diseases, including β-thalassemia, benefit from computational studies that aid researchers in investigating the association of genotype and phenotype. In this study, the alanine substitution mutations of the β-globin protein sub-units in the Turkish population (Hb Ankara, Hb Siirt and Hb Izmir) and the effects of those mutations on the β-globin protein structure and performance are examined using molecular dynamics simulation. While Hb Ankara variant showed a non-conservative mutation, Hb Siirt and Hb Izmir showed a semi-conservative mutation. RMSF values of Hb Siirt, between residues 95 and 99, were higher than wild-type and the other mutant proteins. The residues of Hb Ankara showed lower fluctuation compared to the other structures. The mean ROG values were 1.47 nm, 1.46 nm, 1.49 nm and 1.48 and the average number of the hydrogen bonds were 92, 100, 99, and 89 for Hb Ankara, Hb Siirt and Hb Izmir, respectively. Moreover, a significant increase in overall motion in Hb Siirt was observed based on PCA analysis. Hb Siirt substitution mutation might cause an effect in β-globin proteins which could impact the protein function. This indicates a major role on beta globin subunit's stability for alanine on 27th position. However, Hb Ankara and Hb Izmir variants may act as a silent mutation, since these two mutations did not show a large change in the dynamics of the protein.Communicated by Ramaswamy H. Sarma.

Bioinformatic Analyses of Peripheral Blood Transcriptome Identify Altered Neutrophil-Related Pathway and Different Transcriptomic Profiles for Acute Pancreatitis in Patients with and without Chylomicronemia Syndrome

Acute pancreatitis (AP) is a serious inflammatory condition of the pancreas that can be associated with chylomicronemia syndrome (CS). Currently, no study has explored the differences between non-CS-associated AP and CS-associated AP in terms of gene expression. Transcriptomic profiles of blood samples from patients with AP were retrieved from GSE194331 (non-CS-associated) and GSE149607 (CS-associated). GSE31568 was used to examine the linkage between non-CS-associated AP and the expression of micro RNAs (miRNAs). Differentially expressed genes (DEGs) were identified, a gene regulatory network was constructed, and hub genes were defined. Subsequently, single-sample gene set enrichment analysis (ssGSEA) scores of hub genes were calculated to represent their regulatory-level activity. A total of 1851 shared DEGs were identified between non-CS-associated and CS-associated AP. Neutrophils were significantly enriched in both conditions. In non-CS-associated AP, miRNAs including hsa-miR-21, hsa-miR-146a, and hsa-miR-106a demonstrated a lower expression level as compared with the healthy control. Furthermore, the expression patterns and regulatory activities were largely opposite between non-CS-associated and CS-associated AP, with significantly lower estimated neutrophils in the latter case. In summary, we found that the regulation of neutrophils was altered in AP. There was a different gene expression pattern and lower estimated neutrophil infiltration in CS-associated AP. Whether these findings are clinically significant requires further investigation.

From head to rootlet: comparative transcriptomic analysis of a rhizocephalan barnacle Peltogaster reticulata (Crustacea: Rhizocephala)

Background: Rhizocephalan barnacles stand out in the diverse world of metazoan parasites. The body of a rhizocephalan female is modified beyond revealing any recognizable morphological features, consisting of the interna, a system of rootlets, and the externa, a sac-like reproductive body. Moreover, rhizocephalans have an outstanding ability to control their hosts, literally turning them into "zombies". Despite all these amazing traits, there are no genomic or transcriptomic data about any Rhizocephala. Methods: We collected transcriptomes from four body parts of an adult female rhizocephalan Peltogaster reticulata: the externa, and the main, growing, and thoracic parts of the interna. We used all prepared data for the de novo assembly of the reference transcriptome. Next, a set of encoded proteins was determined, the expression levels of protein-coding genes in different parts of the parasite's body were calculated and lists of enriched bioprocesses were identified. We also in silico identified and analyzed sets of potential excretory / secretory proteins. Finally, we applied phylostratigraphy and evolutionary transcriptomics approaches to our data.  Results: The assembled reference transcriptome included transcripts of 12,620 protein-coding genes and was the first for any rhizocephalan. Based on the results obtained, the spatial heterogeneity of protein-coding gene expression in different regions of the adult female body of P. reticulata was established. The results of both transcriptomic analysis and histological studies indicated the presence of germ-like cells in the lumen of the interna. The potential molecular basis of the interaction between the nervous system of the host and the parasite's interna was also determined. Given the prolonged expression of development-associated genes, we suggest that rhizocephalans "got stuck in their metamorphosis", even at the reproductive stage. Conclusions: The results of the first comparative transcriptomic analysis for Rhizocephala not only clarified but also expanded the existing ideas about the biology of these extraordinary parasites.

Contribution of Genetic Polymorphisms in Human Health

Human health is influenced by various factors; these include genetic inheritance, behavioral lifestyle, socioeconomic and environmental conditions, and public access to care and therapies in case of illness, with the support of the national health system. All these factors represent the starting point for the prevention and promotion of a healthy lifestyle. However, it is not yet clear to what extent these factors may actually affect the health of an entire population. The exposures to environmental and occupational factors are several, most of which might be poorly known, contributing to influencing individual health. Personal habits, including diet, smoking, alcohol, and drug consumption, together with unhealthy behaviors, may inevitably lead people to the development of chronic diseases, contributing to increasing aging and decreasing life expectancy. In this article, we highlight the role of susceptibility biomarkers, i.e., the genetic polymorphisms of individuals of different ethnicities, with particular attention to the risk factors in the response to specific exposures of Europeans. Moreover, we discuss the role of precision medicine which is representing a new way of treating and preventing diseases, taking into account the genetic variability of the individual with each own clinical history and lifestyle.

Biophysical informatics reveals distinctive phenotypic signatures and functional diversity of single-cell lineages

MOTIVATION

In this work, we present an analytical method for quantifying both single-cell morphologies and cell network topologies of tumor cell populations and use it to predict 3D cell behavior.

RESULTS

We utilized a supervised deep learning approach to perform instance segmentation on label-free live cell images across a wide range of cell densities. We measured cell shape properties and characterized network topologies for 136 single-cell clones derived from the YUMM1.7 and YUMMER1.7 mouse melanoma cell lines. Using an unsupervised clustering algorithm, we identified six distinct morphological subclasses. We further observed differences in tumor growth and invasion dynamics across subclasses in an in vitro 3D spheroid model. Compared to existing methods for quantifying 2D or 3D phenotype, our analytical method requires less time, needs no specialized equipment and is capable of much higher throughput, making it ideal for applications such as high-throughput drug screening and clinical diagnosis.

AVAILABILITY AND IMPLEMENTATION

https://github.com/trevor-chan/Melanoma_NetworkMorphology.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Genome-Wide Association Studies across Environmental and Genetic Contexts Reveal Complex Genetic Architecture of Symbiotic Extended Phenotypes

A goal of modern biology is to develop the genotype-phenotype (G→P) map, a predictive understanding of how genomic information generates trait variation that forms the basis of both natural and managed communities. As microbiome research advances, however, it has become clear that many of these traits are symbiotic extended phenotypes, being governed by genetic variation encoded not only by the host's own genome, but also by the genomes of myriad cryptic symbionts. Building a reliable G→P map therefore requires accounting for the multitude of interacting genes and even genomes involved in symbiosis. Here, we use naturally occurring genetic variation in 191 strains of the model microbial symbiont Sinorhizobium meliloti paired with two genotypes of the host Medicago truncatula in four genome-wide association studies (GWAS) to determine the genomic architecture of a key symbiotic extended phenotype-partner quality, or the fitness benefit conferred to a host by a particular symbiont genotype, within and across environmental contexts and host genotypes. We define three novel categories of loci in rhizobium genomes that must be accounted for if we want to build a reliable G→P map of partner quality; namely, (i) loci whose identities depend on the environment, (ii) those that depend on the host genotype with which rhizobia interact, and (iii) universal loci that are likely important in all or most environments. IMPORTANCE Given the rapid rise of research on how microbiomes can be harnessed to improve host health, understanding the contribution of microbial genetic variation to host phenotypic variation is pressing, and will better enable us to predict the evolution of (and select more precisely for) symbiotic extended phenotypes that impact host health. We uncover extensive context-dependency in both the identity and functions of symbiont loci that control host growth, which makes predicting the genes and pathways important for determining symbiotic outcomes under different conditions more challenging. Despite this context-dependency, we also resolve a core set of universal loci that are likely important in all or most environments, and thus, serve as excellent targets both for genetic engineering and future coevolutionary studies of symbiosis.

Computational approaches for predicting variant impact: An overview from resources, principles to applications

One objective of human genetics is to unveil the variants that contribute to human diseases. With the rapid development and wide use of next-generation sequencing (NGS), massive genomic sequence data have been created, making personal genetic information available. Conventional experimental evidence is critical in establishing the relationship between sequence variants and phenotype but with low efficiency. Due to the lack of comprehensive databases and resources which present clinical and experimental evidence on genotype-phenotype relationship, as well as accumulating variants found from NGS, different computational tools that can predict the impact of the variants on phenotype have been greatly developed to bridge the gap. In this review, we present a brief introduction and discussion about the computational approaches for variant impact prediction. Following an innovative manner, we mainly focus on approaches for non-synonymous variants (nsSNVs) impact prediction and categorize them into six classes. Their underlying rationale and constraints, together with the concerns and remedies raised from comparative studies are discussed. We also present how the predictive approaches employed in different research. Although diverse constraints exist, the computational predictive approaches are indispensable in exploring genotype-phenotype relationship.

Evaluating the drivers and engines of morphological diversification in the invasive gecko Hemidactylus mabouia (Moreau de Jonnès, 1818) (Squamata: Gekkonidae)

Development determines the range of possible phenotypes that can be produced and exposed to selection and has a major role in the evolutionary trajectories of species. Nevertheless, development is itself subject to evolutionary forces. Here, we describe differences at the ontogenetic and population levels in head and limb proportions of the invasive gecko Hemidactylus mabouia, to assess the developmental mechanisms and extrinsic forces associated with morphological diversification during colonization of novel habitats. We have found that allometric trajectories of most skeletal traits remain constant throughout postnatal development. Linear morphometric analysis did not find multivariate differences between ontogenetic stages or sexes. When comparing populations, our results showed that the divergence of the corresponding external measures was explained by shifts in the intercept of static allometry curves, indicating that differences arose early in development. Populations aggregated into two morphological groups that did not correspond to the groups formed on the basis of genetic structure. Using two different approaches, we found support for an adaptive hypothesis when comparing observed patterns of morphological variation with that expected under neutral evolutionary models.

Metabolomic characterization of 5 native Peruvian chili peppers (Capsicum spp.) as a tool for species discrimination

Many species of chili peppers have overlapping morphological characters and delimitation by visual descriptors in many cases fails to differentiate one species from another. In Peru, there are 413 accessions of native chili pepper and 296 accessions of rocotos conserved in the Germplasm Collections of the National Institute of Agrarian Innovation (INIA), of which five accessions (three species from three locations) were selected for the present metabolomic study. The Discrimination of the three species of native chili peppers and identification of biomarkers was performed using untargeted metabolomic approach based on profiling by UHPLC-HRMS and multivariate data analysis. The samples of fresh chili peppers (whole fruit) from Chincha area were used to construct an OPLS-DA model. To validate the biomarkers (identified 15 biomarkers, mainly flavonoids), an external validation set of the OPLS-DA model was constructed using Chiclayo and Huaral collection datasets. Consequently, the OPLS-DA based on Chincha samples model has a high predictive capacity demonstrating that the biomarkers have a high probability of continuity in any culture space, being successful in discriminating the species by untargeted metabolomics.

The genotype-phenotype distinction: from Mendelian genetics to 21st century biology

The Genotype-Phenotype (G-P) distinction was proposed in the context of Mendelian genetics, in the wake of late nineteenth century studies about heredity. In this paper, we provide a conceptual analysis that highlights that the G-P distinction was grounded on three pillars: observability, transmissibility, and causality. Originally, the genotype is the non-observable and transmissible cause of its observable and non-transmissible effect, the phenotype. We argue that the current developments of biology have called the validity of such pillars into question. First, molecular biology has unveiled the putative material substrate of the genotype (qua DNA), making it an observable object. Second, numerous findings on non-genetic heredity suggest that some phenotypic traits can be directly transmitted. Third, recent organicist approaches to biological phenomena have emphasized the reciprocal causality between parts of a biological system, which notably applies to the relation between genotypes and phenotypes. As a consequence, we submit that the G-P distinction has lost its general validity, although it can still apply to specific situations. This calls for forging new frameworks and concepts to better describe heredity and development.

A joint learning approach for genomic prediction in polyploid grasses

Poaceae, among the most abundant plant families, includes many economically important polyploid species, such as forage grasses and sugarcane (Saccharum spp.). These species have elevated genomic complexities and limited genetic resources, hindering the application of marker-assisted selection strategies. Currently, the most promising approach for increasing genetic gains in plant breeding is genomic selection. However, due to the polyploidy nature of these polyploid species, more accurate models for incorporating genomic selection into breeding schemes are needed. This study aims to develop a machine learning method by using a joint learning approach to predict complex traits from genotypic data. Biparental populations of sugarcane and two species of forage grasses (Urochloa decumbens, Megathyrsus maximus) were genotyped, and several quantitative traits were measured. High-quality markers were used to predict several traits in different cross-validation scenarios. By combining classification and regression strategies, we developed a predictive system with promising results. Compared with traditional genomic prediction methods, the proposed strategy achieved accuracy improvements exceeding 50%. Our results suggest that the developed methodology could be implemented in breeding programs, helping reduce breeding cycles and increase genetic gains.

Beyond genotype-phenotype maps: Toward a phenotype-centered perspective on evolution

Evolutionary biology is paying increasing attention to the mechanisms that enable phenotypic plasticity, evolvability, and extra-genetic inheritance. Yet, there is a concern that these phenomena remain insufficiently integrated within evolutionary theory. Understanding their evolutionary implications would require focusing on phenotypes and their variation, but this does not always fit well with the prevalent genetic representation of evolution that screens off developmental mechanisms. Here, we instead use development as a starting point, and represent it in a way that allows genetic, environmental and epigenetic sources of phenotypic variation to be independent. We show why this representation helps to understand the evolutionary consequences of both genetic and non-genetic phenotype determinants, and discuss how this approach can instigate future areas of empirical and theoretical research.

From head to rootlet: comparative transcriptomic analysis of a rhizocephalan barnacle Peltogaster reticulata (Crustacea: Rhizocephala)

Background: Rhizocephalan barnacles stand out in the diverse world of metazoan parasites. The body of a rhizocephalan female is modified beyond revealing any recognizable morphological features, consisting of the interna, a system of rootlets, and the externa, a sac-like reproductive body. Moreover, rhizocephalans have an outstanding ability to control their hosts, literally turning them into "zombies". Despite all these amazing traits, there are no genomic or transcriptomic data about any Rhizocephala. Methods: We collected transcriptomes from four body parts of an adult female rhizocephalan Peltogaster reticulata: the externa, and the main, growing, and thoracic parts of the interna. We used all prepared data for the de novo assembly of the reference transcriptome. Next, a set of encoded proteins was determined, the expression levels of protein-coding genes in different parts of the parasite's body were calculated and lists of enriched bioprocesses were identified. We also in silico identified and analyzed sets of potential excretory / secretory proteins. Finally, we applied phylostratigraphy and evolutionary transcriptomics approaches to our data.  Results: The assembled reference transcriptome included transcripts of 12,620 protein-coding genes and was the first for any rhizocephalan. Based on the results obtained, the spatial heterogeneity of protein-coding gene expression in different regions of the adult female body of P. reticulata was established. The results of both transcriptomic analysis and histological studies indicated the presence of germ-like cells in the lumen of the interna. The potential molecular basis of the interaction between the nervous system of the host and the parasite's interna was also determined. Given the prolonged expression of development-associated genes, we suggest that rhizocephalans "got stuck in their metamorphosis", even at the reproductive stage. Conclusions: The results of the first comparative transcriptomic analysis for Rhizocephala not only clarified but also expanded the existing ideas about the biology of these extraordinary parasites.

Increase Crop Resilience to Heat Stress Using Omic Strategies

Varieties of various crops with high resilience are urgently needed to feed the increased population in climate change conditions. Human activities and climate change have led to frequent and strong weather fluctuation, which cause various abiotic stresses to crops. The understanding of crops' responses to abiotic stresses in different aspects including genes, RNAs, proteins, metabolites, and phenotypes can facilitate crop breeding. Using multi-omics methods, mainly genomics, transcriptomics, proteomics, metabolomics, and phenomics, to study crops' responses to abiotic stresses will generate a better, deeper, and more comprehensive understanding. More importantly, multi-omics can provide multiple layers of information on biological data to understand plant biology, which will open windows for new opportunities to improve crop resilience and tolerance. However, the opportunities and challenges coexist. Interpretation of the multidimensional data from multi-omics and translation of the data into biological meaningful context remained a challenge. More reasonable experimental designs starting from sowing seed, cultivating the plant, and collecting and extracting samples were necessary for a multi-omics study as the first step. The normalization, transformation, and scaling of single-omics data should consider the integration of multi-omics. This review reports the current study of crops at abiotic stresses in particular heat stress using omics, which will help to accelerate crop improvement to better tolerate and adapt to climate change.

Unraveling the heritage of lost traits

We synthesize ontogenetic work spanning the past century that show evolutionarily lost structures are rarely entirely absent from earlier developmental stages. We discuss morphological and genetic insights from developmental studies reveal about the evolution of trait loss and regain.

An SNP at the target site of cid-miR-nov-1043 in the TOLLIP 3' UTR decreases mortality rate in grass carp subjected to ENU-induced mutagenesis following grass carp reovirus infection

N-ethyl-N-nitrosourea (ENU) selection is a useful technique to generate new mutations that may cause some functional changes in the gene. Through our previous genomic bulked segregant analysis (BSA), one single nucleotide polymorphism (SNP) at the 3' UTR of Toll interacting protein gene (TOLLIP^982T>C) was identified in grass carp (Ctenopharyngodon idella) subjected to ENU-induced mutagenesis. We found that the overexpression of cid-miR-nov-1043 mimics significantly suppressed the luciferase activity of the TOLLIP 3' UTR, but TOLLIP^982T>C mutation at the target site can decrease the binding affinity between the miRNA cid-miR-nov-1043 and TOLLIP 3' UTR, reducing the inhibition of TOLLIP mRNA transcription in grass carp subjected to ENU-induced mutagenesis. More importantly, we demonstrated that TOLLIP mRNA transcription levels in the gills, liver, kidney and the isolate white cells of the mutant grass carp were significantly (p < 0.01) higher than those in the corresponding tissues from the wild-type grass carp following infection with Grass Carp Reovirus (GCRV) for seven days, while the downstream gene of TOLLIP transforming growth factor β-activated kinase 1 (TAK1) and TAK1-binding protein 1 (TAB1), were higher expressed in wild-type grass carp. As a negative regulator in the pro-inflammatory pathway of NF-κB, TOLLIP inhibits the excessive inflammation in ENU grass carp after GCRV infection. Consistent with the TOLLIP expression, histopathological results demonstrated more severe inflammation in wild-type grass carp, compared to the TOLLIP^982T>C mutant grass carp on the seventh day. Severe inflammation will lead to thoroughly infiltration of chloride and inflammatory cells in the gill filaments. This seriously hindered the exchange of oxygen, which ultimately disrupted blood circulation. Meanwhile, the survival rate of the mutant grass carp was significantly (p < 0.01) higher than that of the wild-type grass carp, indicating that the TOLLIP^982T>C mutants showed strong anti-viral abilities. Our results revealed that an SNP in the TOLLIP 3' UTR may contribute to the suppression of serve inflammation subjected to ENU-induced mutagenesis following GCRV infection, which may be helpful for future resistant breeding development of grass carp.

What do cellular responses to acidity tell us about cancer?

The notion that invasive cancer is a product of somatic evolution is a well-established theory that can be modelled mathematically and demonstrated empirically from therapeutic responses. Somatic evolution is by no means deterministic, and ample opportunities exist to steer its trajectory towards cancer cell extinction. One such strategy is to alter the chemical microenvironment shared between host and cancer cells in a way that no longer favours the latter. Ever since the first description of the Warburg effect, acidosis has been recognised as a key chemical signature of the tumour microenvironment. Recent findings have suggested that responses to acidosis, arising through a process of selection and adaptation, give cancer cells a competitive advantage over the host. A surge of research efforts has attempted to understand the basis of this advantage and seek ways of exploiting it therapeutically. Here, we review key findings and place these in the context of a mathematical framework. Looking ahead, we highlight areas relating to cellular adaptation, selection, and heterogeneity that merit more research efforts in order to close in on the goal of exploiting tumour acidity in future therapies.

What is a phenotype? History and new developments of the concept

Even though the word "phenotype", as well as the expression "genotype-phenotype relationship", are a part of the everyday language of biologists, they remain abstract notions that are sometimes misunderstood or misused. In this article, I begin with a review of  the genesis of the concept of phenotype and of the meaning of the genotype-phenotype "relationship" from a historical perspective. I then illustrate how the development of new approaches for exploring the living world has enabled us to phenotype organisms at multiple levels, with traits that can either be measures or parameters of functions, leading to a virtually unlimited amount of phenotypic data. Thus, pleiotropy becomes a central issue in the study of the genotype-phenotype relationship. Finally, I provide a few examples showing that important genetic and evolutionary features clearly differ with the phenotypic level considered. The way genotypic variation propagates across the phenotypic levels to shape fitness variation is an essential research program in biology.

Hydrodynamic stress and phenotypic plasticity of the zebrafish regenerating fin

Understanding how extrinsic factors modulate genetically encoded information to produce a specific phenotype is of prime scientific interest. In particular, the feedback mechanism between abiotic forces and locomotory organs during morphogenesis to achieve efficient movement is a highly relevant example of such modulation. The study of this developmental process can provide unique insights on the transduction of cues at the interface between physics and biology. Here, we take advantage of the natural ability of adult zebrafish to regenerate their amputated fins to assess its morphogenic plasticity upon external modulations. Using a variety of surgical and chemical treatments, we could induce phenotypic responses to the structure of the fin. Through the ablation of specific rays in regenerating caudal fins, we generated artificially narrowed appendages in which the fin cleft depth and the positioning of rays bifurcations were perturbed compared with normal regenerates. To dissect the role of mechanotransduction in this process, we investigated the patterns of hydrodynamic forces acting on the surface of a zebrafish fin during regeneration by using particle tracking velocimetry on a range of biomimetic hydrofoils. This experimental approach enabled us to quantitatively compare hydrodynamic stress distributions over flapping fins of varying sizes and shapes. As a result, viscous shear stress acting on the distal margin of regenerating fins and the resulting internal tension are proposed as suitable signals for guiding the regulation of ray growth dynamics and branching pattern. Our findings suggest that mechanical forces are involved in the fine-tuning of the locomotory organ during fin morphogenesis.

Critical review of the evidence base regarding theories conceptualising the aetiology of psychosis

A critical review of literature related to the aetiology of psychosis was conducted with specific emphasis on genetics. It was found that, although many published articles were retrieved via database searches, the format of the information was disparate in presentation leading to unnecessary inconsistences. This suggests the need for insightful collaboration by authors and standardisation of published articles to prevent academic and specialism barriers remaining as a discouragement to non-specialists wishing to access this information.

Complex Temporal Biology: Towards A Unified Multi-Scale Approach to Predict the Flow of Information

Two hallmarks of biological processes are complexity and time. While complexity can have many meanings, in this paper we propose an explicit link to the flow of time and how it is experienced by the organism. While the flow of time is rooted in constraints of fundamental physics, understanding the operation of biological systems in terms of processual flow and tempo is more elusive. Fortunately, the convergence of new computational and methodological perspectives will provide a means to transform complicated, nonlinear paths between related phenomena at different time scales into dynamic four-dimensional perspectives. According to the complex temporal biology approach, information flow between time scales of multiple lengths is a transformational process that acts to regulate life's complexity. Interactions between temporal intervals of differing magnitude and otherwise loosely-related mechanisms can be understood as inter-timescale information flow. We further propose that informational flow between time scales is the glue that binds the multiple vertical layers of biocomplexity, as well as yielding surprising outcomes ranging from complex behaviors to the persistence of lineages. Building a foundation of rules based on common interactions between orders of time and common experiential contexts would help to reintegrate biology. Emerging methodologies such as state-of-the-art imaging, visualization techniques, and computational data analysis can help us uncover these interactions. In conclusion, we propose educational and community-level changes that would better enable our vision.

Evolution of plasticity in production and transgenerational inheritance of small RNAs under dynamic environmental conditions

In a changing environment, small RNAs (sRNAs) play an important role in the post-transcriptional regulation of gene expression and can vary in abundance depending on the conditions experienced by an individual (phenotypic plasticity) and its parents (non-genetic inheritance). Many sRNAs are unusual in that they can be produced in two ways, either using genomic DNA as the template (primary sRNAs) or existing sRNAs as the template (secondary sRNAs). Thus, organisms can evolve rapid plastic responses to their current environment by adjusting the amplification rate of sRNA templates. sRNA levels can also be transmitted transgenerationally by the direct transfer of either sRNAs or the proteins involved in amplification. Theory is needed to describe the selective forces acting on sRNA levels, accounting for the dual nature of sRNAs as regulatory elements and templates for amplification and for the potential to transmit sRNAs and their amplification agents to offspring. Here, we develop a model to study the dynamics of sRNA production and inheritance in a fluctuating environment. We tested the selective advantage of mutants capable of sRNA-mediated phenotypic plasticity within resident populations with fixed levels of sRNA transcription. Even when the resident was allowed to evolve an optimal constant rate of sRNA production, plastic amplification rates capable of responding to environmental conditions were favored. Mechanisms allowing sRNA transcripts or amplification agents to be inherited were favored primarily when parents and offspring face similar environments and when selection acts before the optimal level of sRNA can be reached within the organism. Our study provides a clear set of testable predictions for the evolution of sRNA-related mechanisms of phenotypic plasticity and transgenerational inheritance.

From genotypes to organisms: State-of-the-art and perspectives of a cornerstone in evolutionary dynamics

Understanding how genotypes map onto phenotypes, fitness, and eventually organisms is arguably the next major missing piece in a fully predictive theory of evolution. We refer to this generally as the problem of the genotype-phenotype map. Though we are still far from achieving a complete picture of these relationships, our current understanding of simpler questions, such as the structure induced in the space of genotypes by sequences mapped to molecular structures, has revealed important facts that deeply affect the dynamical description of evolutionary processes. Empirical evidence supporting the fundamental relevance of features such as phenotypic bias is mounting as well, while the synthesis of conceptual and experimental progress leads to questioning current assumptions on the nature of evolutionary dynamics-cancer progression models or synthetic biology approaches being notable examples. This work delves with a critical and constructive attitude into our current knowledge of how genotypes map onto molecular phenotypes and organismal functions, and discusses theoretical and empirical avenues to broaden and improve this comprehension. As a final goal, this community should aim at deriving an updated picture of evolutionary processes soundly relying on the structural properties of genotype spaces, as revealed by modern techniques of molecular and functional analysis.

Significant Association Between XRCC1 Expression and Its rs25487 Polymorphism and Radiotherapy-Related Cancer Prognosis

Background/Aims

XRCC1 (X-ray repair cross-complementing protein 1) expression and its single nucleotide polymorphism XRCC1 rs25487 (G>A) may be related to radiotherapy-related cancer prognosis or radiation-induced side effects. However, this association is controversial. We performed a bioinformatic analysis and a meta-analysis to obtain comprehensive results.

Results

Sixty nine articles with 10232 patients and 17 TCGA data sets with 2705 patients were included in the analysis. We observed that high XRCC1 expression was associated with an increased risk of minor treatment response and poor overall survival, XRCC1 rs25487 was associated with reduced risk of minor treatment response in esophageal cancer and an increased risk of high-grade side effects in head and neck cancer.

Conclusion

The results suggest that XRCC1 expression and rs25487 polymorphism are prognostic factors for patients receiving radiotherapy-related treatment. Considering the insufficient treatment parameters provided and the various sample sizes in most of the studies, we suggest that genetic association studies related to radiation-based treatment should include more cancer types with sufficient statistical power and more detailed clinical parameters.

Positive Selection in Gene Regulatory Factors Suggests Adaptive Pleiotropic Changes During Human Evolution

Gene regulatory factors (GRFs), such as transcription factors, co-factors and histone-modifying enzymes, play many important roles in modifying gene expression in biological processes. They have also been proposed to underlie speciation and adaptation. To investigate potential contributions of GRFs to primate evolution, we analyzed GRF genes in 27 publicly available primate genomes. Genes coding for zinc finger (ZNF) proteins, especially ZNFs with a Krüppel-associated box (KRAB) domain were the most abundant TFs in all genomes. Gene numbers per TF family differed between all species. To detect signs of positive selection in GRF genes we investigated more than 3,000 human GRFs with their more than 70,000 orthologs in 26 non-human primates. We implemented two independent tests for positive selection, the branch-site-model of the PAML suite and aBSREL of the HyPhy suite, focusing on the human and great ape branch. Our workflow included rigorous procedures to reduce the number of false positives: excluding distantly similar orthologs, manual corrections of alignments, and considering only genes and sites detected by both tests for positive selection. Furthermore, we verified the candidate sites for selection by investigating their variation within human and non-human great ape population data. In order to approximately assign a date to positively selected sites in the human lineage, we analyzed archaic human genomes. Our work revealed with high confidence five GRFs that have been positively selected on the human lineage and one GRF that has been positively selected on the great ape lineage. These GRFs are scattered on different chromosomes and have been previously linked to diverse functions. For some of them a role in speciation and/or adaptation can be proposed based on the expression pattern or association with human diseases, but it seems that they all contributed independently to human evolution. Four of the positively selected GRFs are KRAB-ZNF proteins, that induce changes in target genes co-expression and/or through arms race with transposable elements. Since each positively selected GRF contains several sites with evidence for positive selection, we suggest that these GRFs participated pleiotropically to phenotypic adaptations in humans.

Computer Vision, Machine Learning, and the Promise of Phenomics in Ecology and Evolutionary Biology

For centuries, ecologists and evolutionary biologists have used images such as drawings, paintings and photographs to record and quantify the shapes and patterns of life. With the advent of digital imaging, biologists continue to collect image data at an ever-increasing rate. This immense body of data provides insight into a wide range of biological phenomena, including phenotypic diversity, population dynamics, mechanisms of divergence and adaptation, and evolutionary change. However, the rate of image acquisition frequently outpaces our capacity to manually extract meaningful information from images. Moreover, manual image analysis is low-throughput, difficult to reproduce, and typically measures only a few traits at a time. This has proven to be an impediment to the growing field of phenomics – the study of many phenotypic dimensions together. Computer vision (CV), the automated extraction and processing of information from digital images, provides the opportunity to alleviate this longstanding analytical bottleneck. In this review, we illustrate the capabilities of CV as an efficient and comprehensive method to collect phenomic data in ecological and evolutionary research. First, we briefly review phenomics, arguing that ecologists and evolutionary biologists can effectively capture phenomic-level data by taking pictures and analyzing them using CV. Next we describe the primary types of image-based data, review CV approaches for extracting them (including techniques that entail machine learning and others that do not), and identify the most common hurdles and pitfalls. Finally, we highlight recent successful implementations and promising future applications of CV in the study of phenotypes. In anticipation that CV will become a basic component of the biologist’s toolkit, our review is intended as an entry point for ecologists and evolutionary biologists that are interested in extracting phenotypic information from digital images.

Current and Forthcoming Approaches for Benchmarking Genetic and Genomic Diversity

The current attrition of biodiversity extends beyond loss of species and unique populations to steady loss of a vast genomic diversity that remains largely undescribed. Yet the accelerating development of new techniques allows us to survey entire genomes ever faster and cheaper, to obtain robust samples from a diversity of sources including degraded DNA and residual DNA in the environment, and to address conservation efforts in new and innovative ways. Here we review recent studies that highlight the importance of carefully considering where to prioritize collection of genetic samples (e.g., organisms in rapidly changing landscapes or along edges of geographic ranges) and what samples to collect and archive (e.g., from individuals of little-known subspecies or populations, even of species not currently considered endangered). Those decisions will provide the sample infrastructure to detect the disappearance of certain genotypes or gene complexes, increases in inbreeding levels, and loss of genomic diversity as environmental conditions change. Obtaining samples from currently endangered, protected, and rare species can be particularly difficult, thus we also focus on studies that use new, non-invasive ways of obtaining genomic samples and analyzing them in these cases where other sampling options are highly constrained. Finally, biological collections archiving such samples face an inherent contradiction: their main goal is to preserve biological material in good shape so it can be used for scientific research for centuries to come, yet the technologies that can make use of such materials are advancing faster than collections can change their standardized practices. Thus, we also discuss current and potential new practices in biological collections that might bolster their usefulness for future biodiversity conservation research.

Topological signatures in regulatory network enable phenotypic heterogeneity in small cell lung cancer

Phenotypic (non-genetic) heterogeneity has significant implications for the development and evolution of organs, organisms, and populations. Recent observations in multiple cancers have unraveled the role of phenotypic heterogeneity in driving metastasis and therapy recalcitrance. However, the origins of such phenotypic heterogeneity are poorly understood in most cancers. Here, we investigate a regulatory network underlying phenotypic heterogeneity in small cell lung cancer, a devastating disease with no molecular targeted therapy. Discrete and continuous dynamical simulations of this network reveal its multistable behavior that can explain co-existence of four experimentally observed phenotypes. Analysis of the network topology uncovers that multistability emerges from two teams of players that mutually inhibit each other, but members of a team activate one another, forming a 'toggle switch' between the two teams. Deciphering these topological signatures in cancer-related regulatory networks can unravel their 'latent' design principles and offer a rational approach to characterize phenotypic heterogeneity in a tumor.

Genetic and environmental canalization are not associated among altitudinally varying populations of Drosophila melanogaster

Organisms are exposed to environmental and mutational effects influencing both mean and variance of phenotypes. Potentially deleterious effects arising from this variation can be reduced by the evolution of buffering (canalizing) mechanisms, ultimately reducing phenotypic variability. There has been interest regarding the conditions enabling the evolution of canalization. Under some models, the circumstances under which genetic canalization evolves are limited despite apparent empirical evidence for it. It has been argued that genetic canalization evolves as a correlated response to environmental canalization (congruence model). Yet, empirical evidence has not consistently supported predictions of a correlation between genetic and environmental canalization. In a recent study, a population of Drosophila adapted to high altitude showed evidence of genetic decanalization relative to those from low altitudes. Using strains derived from these populations, we tested if they varied for multiple aspects of environmental canalization We observed the expected differences in wing size, shape, cell (trichome) density and mutational defects between high- and low-altitude populations. However, we observed little evidence for a relationship between measures of environmental canalization with population or with defect frequency. Our results do not support the predicted association between genetic and environmental canalization.

Transposable elements contribute to the genomic response to insecticides in Drosophila melanogaster

Most of the genotype–phenotype analyses to date have largely centred attention on single nucleotide polymorphisms. However, transposable element (TE) insertions have arisen as a plausible addition to the study of the genotypic–phenotypic link because of to their role in genome function and evolution. In this work, we investigate the contribution of TE insertions to the regulation of gene expression in response to insecticides. We exposed four Drosophila melanogaster strains to malathion, a commonly used organophosphate insecticide. By combining information from different approaches, including RNA-seq and ATAC-seq, we found that TEs can contribute to the regulation of gene expression under insecticide exposure by rewiring cis-regulatory networks.

This article is part of a discussion meeting issue ‘Crossroads between transposons and gene regulation’.

Crop Phenomics and High-Throughput Phenotyping: Past Decades, Current Challenges, and Future Perspectives

Since whole-genome sequencing of many crops has been achieved, crop functional genomics studies have stepped into the big-data and high-throughput era. However, acquisition of large-scale phenotypic data has become one of the major bottlenecks hindering crop breeding and functional genomics studies. Nevertheless, recent technological advances provide us potential solutions to relieve this bottleneck and to explore advanced methods for large-scale phenotyping data acquisition and processing in the coming years. In this article, we review the major progress on high-throughput phenotyping in controlled environments and field conditions as well as its use for post-harvest yield and quality assessment in the past decades. We then discuss the latest multi-omics research combining high-throughput phenotyping with genetic studies. Finally, we propose some conceptual challenges and provide our perspectives on how to bridge the phenotype-genotype gap. It is no doubt that accurate high-throughput phenotyping will accelerate plant genetic improvements and promote the next green revolution in crop breeding.

The coding loci of evolution and domestication: current knowledge and implications for bio-inspired genome editing

One promising application of CRISPR/Cas9 is to create targeted mutations to introduce traits of interest into domesticated organisms. However, a major current limitation for crop and livestock improvement is to identify the precise genes and genetic changes that must be engineered to obtain traits of interest. Here, we discuss the advantages of bio-inspired genome editing, i.e. the engineered introduction of natural mutations that have already been associated with traits of interest in other lineages (breeds, populations or species). To obtain a landscape view of potential targets for genome editing, we used Gephebase (www.gephebase.org), a manually curated database compiling published data about the genes responsible for evolutionary and domesticated changes across eukaryotes, and examined the &gt;1200 mutations that have been identified in the coding regions of more than 700 genes in animals, plants and yeasts. We observe that our genetic knowledge is relatively important for certain traits, such as xenobiotic resistance, and poor for others. We also note that protein-null alleles, often owing to nonsense and frameshift mutations, represent a large fraction of the known loci of domestication (42% of identified coding mutations), compared with intraspecific (27%) and interspecific evolution (11%). Although this trend may be subject to detection, publication and curation biases, it is consistent with the idea that breeders have selected large-effect mutations underlying adaptive traits in specific settings, but that these mutations and associated phenotypes would not survive the vagaries of changing external and internal environments. Our compilation of the loci of evolution and domestication uncovers interesting options for bio-inspired and transgene-free genome editing.

Trilayered tissue structure with leaflet-like orientations developed through in vivo tissue engineering

A tissue-engineered heart valve can be an alternative to current mechanical or bioprosthetic valves that face limitations, especially in pediatric patients. However, it remains challenging to produce a functional tissue-engineered heart valve with three leaflets mimicking the trilayered, oriented structure of a native valve leaflet. In our previous study, a flat, trilayered nanofibrous substrate mimicking the orientations of three layers in a native leaflet-circumferential, random and radial orientations in fibrosa, spongiosa and ventricularis layers, respectively, was developed through electrospinning. In this study, we sought to develop a trilayered tissue structure mimicking the orientations of a native valve leaflet through in vivo tissue engineering, a practical regenerative medicine technology that can be used to develop an autologous heart valve. Thus, the nanofibrous substrate was placed inside the closed trileaflet-shaped cavity of a mold and implanted subcutaneously in a rat model for in vivo tissue engineering. After two months, the explanted tissue construct had a trilayered structure mimicking the orientations of a native valve leaflet. The infiltrated cells and their deposited collagen fibrils were oriented along the nanofibers in each layer of the substrate. Besides collagen, presence of glycosaminoglycans and elastin in the construct was observed.

Protein ensembles link genotype to phenotype

Classically, phenotype is what is observed, and genotype is the genetic makeup. Statistical studies aim to project phenotypic likelihoods of genotypic patterns. The traditional genotype-to-phenotype theory embraces the view that the encoded protein shape together with gene expression level largely determines the resulting phenotypic trait. Here, we point out that the molecular biology revolution at the turn of the century explained that the gene encodes not one but ensembles of conformations, which in turn spell all possible gene-associated phenotypes. The significance of a dynamic ensemble view is in understanding the linkage between genetic change and the gained observable physical or biochemical characteristics. Thus, despite the transformative shift in our understanding of the basis of protein structure and function, the literature still commonly relates to the classical genotype-phenotype paradigm. This is important because an ensemble view clarifies how even seemingly small genetic alterations can lead to pleiotropic traits in adaptive evolution and in disease, why cellular pathways can be modified in monogenic and polygenic traits, and how the environment may tweak protein function.

Inter-rater reliability of phenotypes and exploratory genotype-phenotype analysis in inherited hidradenitis suppurativa

BACKGROUND

Genotype-phenotype correlation measures the correlation between the presence of a physical trait with a group of similar mutations but is dependent on reliable phenotyping. It can provide information on disease pathogenesis, future disease progression, severity or activity. Such indicators would be valuable in hidradenitis suppurativa (HS).

OBJECTIVES

To assess inter-rater reliability (IRR) of HS clinical phenotypes and perform exploratory genotype-phenotype correlation in cases of HS with identified sequence variants.

METHODS

Linkage disequilibrium between variants was assessed. Genotype-phenotype correlations were explored using Spearman correlation coefficients. IRR was calculated using Cohen's κ. Correlation between phenotype classifications was assessed using the χ² statistic.

RESULTS

Forty-three sequence variants with clinical information were identified. Clinical phenotypes were classified as LC2 (n = 29; 67%), scarring folliculitis (n = 18; 42%), atypical (n = 38; 88%) and nodular (n = 26; 60%). LC1 phenotype was associated with regular (χ² = 41·289, P < 0·001) and typical (χ² = 29·013, P < 0·001) phenotypes. Cohen's κ was highest for van der Zee and Jemec (0·815), followed by Martorell-Calatayud et al. (0·813), Naasan and Affleck (0·774) and Canoui-Poitrine et al. (0·435) classifications. High linkage disequilibrium was seen between variants of Han Chinese pedigrees. No significant genotype-phenotype correlations were identified.

CONCLUSIONS

These findings may be influenced by selection, publication bias and the assumption that HS is a monogenic disorder. The poor IRR of existing phenotype measures suggests limited utility of existing measures. Further investigations into the correlation of clinical phenotypes with inflammatory biomarkers may aid in prognostic efforts for this disease. What's already known about this topic? Genotype-phenotype correlation can provide information regarding disease pathogenesis and predictions for future disease progression, severity or activity. The identification of such indicators in hidradenitis suppurativa (HS) would be valuable for patients and clinicians alike, given the lack of biomarkers or clinical predictors of disease. What does this study add? Sixty-five sequence variants across 20 separate genes were identified. There was no significant correlation between phenotype classification in four separate classification schema and gene, mutation type or impact on Notch signalling. Utility of current phenotype measurements are limited. The lack of genotype-phenotype correlation in HS is suggestive that the underlying assumption of inherited HS as a monogenic disorder may need revision.

Modeling genotypes in their microenvironment to predict single- and multi-cellular behavior

A cell's phenotype is the set of observable characteristics resulting from the interaction of the genotype with the surrounding environment, determining cell behavior. Deciphering genotype-phenotype relationships has been crucial to understanding normal and disease biology. Analysis of molecular pathways has provided an invaluable tool to such understanding; however, typically it does not consider the physical microenvironment, which is a key determinant of phenotype. In this study, we present a novel modeling framework that enables the study of the link between genotype, signaling networks, and cell behavior in a three-dimensional microenvironment. To achieve this, we bring together Agent-Based Modeling, a powerful computational modeling technique, and gene networks. This combination allows biological hypotheses to be tested in a controlled stepwise fashion, and it lends itself naturally to model a heterogeneous population of cells acting and evolving in a dynamic microenvironment, which is needed to predict the evolution of complex multi-cellular dynamics. Importantly, this enables modeling co-occurring intrinsic perturbations, such as mutations, and extrinsic perturbations, such as nutrient availability, and their interactions. Using cancer as a model system, we illustrate how this framework delivers a unique opportunity to identify determinants of single-cell behavior, while uncovering emerging properties of multi-cellular growth. This framework is freely available at http://www.microc.org.

The many faces of mathematical modelling in oncology

The application of modelling to solve problems in biology and medicine, and specifically in oncology and radiation therapy, is increasingly established and holds big promise. We provide an overview of the basic concepts of the field and its current state, along with new tools available and future directions for research. We will outline radiobiology models, examples of other anticancer therapy models, multiscale modelling, and we will discuss mechanistic and phenomenological approaches to modelling.