Leveraging GWAS for complex traits to detect signatures of natural selection in humans

Fine-mapping and association analysis of candidate genes for papilla number in sea cucumber, Apostichopus japonicus

The papilla number is one of the most economically important traits of sea cucumber in the China marketing trade. However, the genetic basis for papilla number diversity in holothurians is still scarce. In the present study, we conducted genome-wide association studies (GWAS) for the trait papilla number of sea cucumbers utilizing a set of 400,186 high-quality SNPs derived from 200 sea cucumbers. Two significant trait-associated SNPs that passed Bonferroni correction (P < 1.25E-7) were located in the intergenic region near PATS1 and the genic region of EIF4G, which were reported to play a pivotal role in cell growth and proliferation. The fine-mapping regions around the top two lead SNPs provided precise causative loci/genes related to papilla formation and cellular activity, including PPP2R3C, GBP1, and BCAS3. Potential SNPs with P < 1E-4 were acquired for the following GO and KEGG enrichment analysis. Moreover, the two lead SNPs were verified in another population of sea cucumber, and the expressive detection of three potential candidate genes PATS1, PPP2R3C, and EIF4G that near or cover the two lead SNPs was conducted in papilla tissue of TG (Top papilla number group) and BG (Bottom papilla number group) by qRT-PCR. We found the significantly higher expression profile of PATS1 (3.34-fold), PPP2R3C (4.90-fold), and EIF4G (4.23-fold) in TG, implying their potential function in papilla polymorphism. The present results provide valuable information to decipher the phenotype differences of the papilla trait and will provide a scientific basis for selective breeding in sea cucumbers.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42995-022-00139-w.

Analysis of whole exome sequencing in severe mental illness hints at selection of brain development and immune related genes

Evolutionary trends may underlie some aspects of the risk for common, non-communicable disorders, including psychiatric disease. We analyzed whole exome sequencing data from 80 unique individuals from India coming from families with two or more individuals with severe mental illness. We used Population Branch Statistics (PBS) to identify variants and genes under positive selection and identified 74 genes as candidates for positive selection. Of these, 20 were previously associated with Schizophrenia, Alzheimer’s disease and cognitive abilities in genome wide association studies. We then checked whether any of these 74 genes were involved in common biological pathways or related to specific cellular or molecular functions. We found that immune related pathways and functions related to innate immunity such as antigen binding were over-represented. We also evaluated for the presence of Neanderthal introgressed segments in these genes and found Neanderthal introgression in a single gene out of the 74 candidate genes. However, the introgression pattern indicates the region is unlikely to be the source for selection. Our findings hint at how selection pressures in individuals from families with a history of severe mental illness may diverge from the general population. Further, it also provides insights into the genetic architecture of severe mental illness, such as schizophrenia and its link to immune factors.

Genomics at cellular resolution: insights into cognitive disorders and their evolution

High-throughput genomic sequencing approaches have held the promise of understanding and ultimately leading to treatments for cognitive disorders such as autism spectrum disorders, schizophrenia and Alzheimer's disease. Although significant progress has been made into identifying genetic variants associated with these diseases, these studies have also uncovered that these disorders are mostly genetically complex and thus challenging to model in non-human systems. Improvements in such models might benefit from understanding the evolution of the human genome and how such modifications have affected brain development and function. The intersection of genome-wide variant information with cell-type-specific expression and epigenetic information will further assist in resolving the contribution of particular cell types in evolution or disease. For example, the role of non-neuronal cells in brain evolution and cognitive disorders has gone mostly underappreciated until the recent availability of single-cell transcriptomic approaches. In this review, we discuss recent studies that carry out cell-type-specific assessments of gene expression in brain tissue across primates and between healthy and disease populations. The emerging results from these studies are beginning to elucidate how specific cell types in the evolved human brain are contributing to cognitive disorders.

Complex evolution of novel red floral color in Petunia

Red flower color has arisen multiple times and is generally associated with hummingbird pollination. The majority of evolutionary transitions to red color proceeded from purple lineages and tend to be genetically simple, almost always involving a few loss-of-function mutations of major phenotypic effect. Here we report on the complex evolution of a novel red floral color in the hummingbird-pollinated Petunia exserta (Solanaceae) from a colorless ancestor. The presence of a red color is remarkable because the genus cannot synthesize red anthocyanins and P. exserta retains a nonfunctional copy of the key MYB transcription factor AN2. We show that moderate upregulation and a shift in tissue specificity of an AN2 paralog, DEEP PURPLE, restores anthocyanin biosynthesis in P. exserta. An essential shift in anthocyanin hydroxylation occurred through rebalancing the expression of three hydroxylating genes. Furthermore, the downregulation of an acyltransferase promotes reddish hues in typically purple pigments by preventing acyl group decoration of anthocyanins. This study presents a rare case of a genetically complex evolutionary transition toward the gain of a novel red color.

Galton's Quincunx: Probabilistic causation in developmental behavior genetics

In what sense are associations between particular markers and complex behaviors made by genome-wide association studies (GWAS) and related techniques discoveries of, or entries into the study of, the causes of those behaviors? In this paper, we argue that when applied to individuals, the kinds of probabilistic 'causes' of complex traits that GWAS-style studies can point towards do not provide the kind of causal information that is useful for generating explanations; they do not, in other words, point towards useful explanations of why particular individuals have the traits that they do. We develop an analogy centered around Galton's "Quincunx" machine; while each pin might be associated with outcomes of a certain sort, in any particular trial, that pin might be entirely bypassed even if the ball eventually comes to rest in the box most strongly associated with that pin. Indeed, in any particular trial, the actual outcome of a ball hitting a pin might be the opposite of what is usually expected. While we might find particular pins associated with outcomes in the aggregate, these associations will not provide causally relevant information for understanding individual outcomes. In a similar way, the complexities of development likely render impossible any moves from population-level statistical associations between genetic markers and complex behaviors to an understanding of the causal processes by which individuals come to have the traits that they in fact have.

Recent selection of candidate genes for mammal domestication in Europeans and language change in Europe: a hypothesis

BACKGROUND AND AIM

Human evolution resulted from changes in our biology, behaviour, and culture. One source of these changes has been hypothesised to be our self-domestication (that is, the development in humans of features commonly found in domesticated strains of mammals, seemingly as a result of selection for reduced aggression). Signals of domestication, notably brain size reduction, have increased in recent times.

METHODS

In this paper, we compare whole-genome data between the Late Neolithic/Bronze Age individuals and modern Europeans.

RESULTS

We show that genes associated with mammal domestication and with neural crest development and function are significantly differently enriched in nonsynonymous single nucleotide polymorphisms between these two groups.

CONCLUSION

We hypothesise that these changes might account for the increased features of self-domestication in modern humans and, ultimately, for subtle recent changes in human cognition and behaviour, including language.

Identifying adaptive alleles in the human genome: from selection mapping to functional validation

The suite of phenotypic diversity across geographically distributed human populations is the outcome of genetic drift, gene flow, and natural selection throughout human evolution. Human genetic variation underlying local biological adaptations to selective pressures is incompletely characterized. With the emergence of population genetics modeling of large-scale genomic data derived from diverse populations, scientists are able to map signatures of natural selection in the genome in a process known as selection mapping. Inferred selection signals further can be used to identify candidate functional alleles that underlie putative adaptive phenotypes. Phenotypic association, fine mapping, and functional experiments facilitate the identification of candidate adaptive alleles. Functional investigation of candidate adaptive variation using novel techniques in molecular biology is slowly beginning to unravel how selection signals translate to changes in biology that underlie the phenotypic spectrum of our species. In addition to informing evolutionary hypotheses of adaptation, the discovery and functional annotation of adaptive alleles also may be of clinical significance. While selection mapping efforts in non-European populations are growing, there remains a stark under-representation of diverse human populations in current public genomic databases, of both clinical and non-clinical cohorts. This lack of inclusion limits the study of human biological variation. Identifying and functionally validating candidate adaptive alleles in more global populations is necessary for understanding basic human biology and human disease.

Accounting for diverse evolutionary forces reveals mosaic patterns of selection on human preterm birth loci

Currently, there is no comprehensive framework to evaluate the evolutionary forces acting on genomic regions associated with human complex traits and contextualize the relationship between evolution and molecular function. Here, we develop an approach to test for signatures of diverse evolutionary forces on trait-associated genomic regions. We apply our method to regions associated with spontaneous preterm birth (sPTB), a complex disorder of global health concern. We find that sPTB-associated regions harbor diverse evolutionary signatures including conservation, excess population differentiation, accelerated evolution, and balanced polymorphism. Furthermore, we integrate evolutionary context with molecular evidence to hypothesize how these regions contribute to sPTB risk. Finally, we observe enrichment in signatures of diverse evolutionary forces in sPTB-associated regions compared to genomic background. By quantifying multiple evolutionary forces acting on sPTB-associated regions, our approach improves understanding of both functional roles and the mosaic of evolutionary forces acting on loci. Our work provides a blueprint for investigating evolutionary pressures on complex traits.

Evolutionary perspectives on polygenic selection, missing heritability, and GWAS

Genome-wide association studies (GWAS) have successfully identified many trait-associated variants, but there is still much we do not know about the genetic basis of complex traits. Here, we review recent theoretical and empirical literature regarding selection on complex traits to argue that "missing heritability" is as much an evolutionary problem as it is a statistical problem. We discuss empirical findings that suggest a role for selection in shaping the effect sizes and allele frequencies of causal variation underlying complex traits, and the limitations of these studies. We then use simulations of selection, realistic genome structure, and complex human demography to illustrate the results of recent theoretical work on polygenic selection, and show that statistical inference of causal loci is sharply affected by evolutionary processes. In particular, when selection acts on causal alleles, it hampers the ability to detect causal loci and constrains the transferability of GWAS results across populations. Last, we discuss the implications of these findings for future association studies, and suggest that future statistical methods to infer causal loci for genetic traits will benefit from explicit modeling of the joint distribution of effect sizes and allele frequencies under plausible evolutionary models.

Assessing the potential for assisted gene flow using past introduction of Norway spruce in southern Sweden: Local adaptation and genetic basis of quantitative traits in trees

Norway spruce (Picea abies) is a dominant conifer species of major economic importance in northern Europe. Extensive breeding programs were established to improve phenotypic traits of economic interest. In southern Sweden, seeds used to create progeny tests were collected on about 3,000 trees of outstanding phenotype ('plus' trees) across the region. In a companion paper, we showed that some were of local origin but many were recent introductions from the rest of the natural range. The mixed origin of the trees together with partial sequencing of the exome of >1,500 of these trees and phenotypic data retrieved from the Swedish breeding program offered a unique opportunity to dissect the genetic basis of local adaptation of three quantitative traits (height, diameter and bud-burst) and assess the potential of assisted gene flow. Through a combination of multivariate analyses and genome-wide association studies, we showed that there was a very strong effect of geographical origin on growth (height and diameter) and phenology (bud-burst) with trees from southern origins outperforming local provenances. Association studies revealed that growth traits were highly polygenic and bud-burst somewhat less. Hence, our results suggest that assisted gene flow and genomic selection approaches could help to alleviate the effect of climate change on P. abies breeding programs in Sweden.

Association of RMND1/CCDC170-ESR1 single nucleotide polymorphisms with hip fracture and osteoporosis in postmenopausal women

OBJECTIVE

This study aimed to investigate the association of seven single nucleotide polymorphisms (SNPs) on the RMND1, CCDC170, and ESR1 genes with osteoporosis or hip fracture in a postmenopausal Mexican population.

METHODS

We included a group of 400 postmenopausal women from the Health Workers Cohort Study from the Mexican Institute of Social Security. As a replication sample, we recruited 423 postmenopausal women from the National Institute of Rehabilitation. Demographic data were collected through a structured questionnaire. Bone mineral density was assessed using dual X-ray absorptiometry. Individuals were classified as normal, osteopenia, osteoporosis, and fracture, according to World Health Organization criteria. Genotyping was performed using predesigned TaqMan Probes. Linear regression analysis was used to investigate association.

RESULTS

All of the analyzed SNPs showed association with at least one of the phenotypes of the study groups. In addition, we observed a region with linkage disequilibrium within the ESR1 gene in all groups.

CONCLUSION

This study shows that an association of the SNPs can exist with osteopenia, osteoporosis, or fragility fracture. Our results agree with data published elsewhere, supporting the potential of these loci for the identification of the population at risk. However, additional studies are required to determine the extent of this association for other geographic regions of Mexico.

Systems biology approaches in the study of Chinese herbal formulae

Systems biology is an academic field that attempts to integrate different levels of information to understand how biological systems function. It is the study of the composition of all components of a biological system and their interactions under specific conditions. The core of systems biology is holistic and systematic research, which is different from the manner of thinking and research of all other branches of biology to date. Chinese herbal formulae (CHF) are the main form of Chinese medicine and are composed of single Chinese herbal medicines (CHMs) with pharmacological and pharmacodynamic compatibility. When single CHMs are combined into CHF, the result is different from the original effect of a single drug and can be better adapted to more diseases with complex symptoms. CHF represent a complex system with multiple components, targets and effects. Therefore, the use of systems biology is conducive to revealing the complex characteristics of CHF. With the rapid development of omics technologies, systems biology has been widely and increasingly applied to the study of the basis of the pharmacological substances, action targets and mechanisms of CHF. To meet the challenges of multiomics synthesis-intensive studies and system dynamics research in CHF, this paper reviews the common techniques of genomics, transcriptomics, proteomics, metabolomics, and metagenomics and their applications in research on CHF.