From population genetics to population genomics of forest trees: Integrated population genomics approach

Early works by Altukhov and his associates on pine and spruce laid the foundation for Russian population genetic studies on tree species with the use of molecular genetic markers. In recent years, these species have become especially popular as nontraditional eukaryotic models for population and evolutionary genome-wide research. Tree species with large, cross-pollinating native populations, high genetic and phenotypic variation, growing in diverse environments and affected by environmental changes during hundreds of years of their individual development, are an ideal model for studying the molecular genetic basis of adaptation. The great advance in this field is due to the rapid development of population genomics in the last few years. In the broad sense, population genomics is a novel, fast-developing discipline, combining traditional population genetic approaches with the genome-wide level of analysis. Thousands of genes with known function and sometimes known genome-wide localization can be simultaneously studied in many individuals. This opens new prospects for obtaining statistical estimates for a great number of genes and segregating elements. Mating system, gene exchange, reproductive population size, population disequilibrium, interaction among populations, and many other traditional problems of population genetics can be now studied using data on variation in many genes. Moreover, population genome-wide analysis allows one to distinguish factors that affect individual genes, allelles, or nucleotides (such as, for example, natural selection) from factors affecting the entire genome (e.g., demography). This paper presents a brief review of traditional methods of studying genetic variation in forest tree species and introduces a new, integrated population genomics approach. The main stages of the latter are: (1) selection of genes, which are tentatively involved in variation of adaptive traits, by means of a detailed examination of the regulation and the expression of individual genes and genotypes, with subsequent determination of their complete allelic composition by direct nucleotide sequencing; (2) examination of the phenotypic effects of individual alleles by, e.g., association mapping; and (3) determining the frequencies of the selected alleles in natural population for identification of the adaptive variation pattern in the heterogeneous environment. Through decoding the phenotypic effects of individual alleles and identification of adaptive variation patterns at the population level, population genomics in the future will serve as a very helpful, efficient, and economical tool, essential for developing a correct strategy for conserving and increasing forests and other commercially valuable plant and animal species.     

From population genetics to population genomics of forest trees: integrated population genomics approach

Early works by Altukhov and his associates on pine and spruce laid the foundation for Russian population genetic studies on tree species with the use of molecular genetic markers. In recent years, these species have become especially popular as nontraditional eukaryotic models for population and evolutionary genomic research. Tree species with large, cross-pollinating native populations, high genetic and phenotypic variation, growing in diverse environments and affected by environmental changes during hundreds of years of their individual development, are an ideal model for studying the molecular genetic basis of adaptation. The great advance in this field is due to the rapid development of population genomics in the last few years. In the broad sense, population genomics is a novel, fast-developing discipline, combining traditional population genetic approaches with the genomic level of analysis. Thousands of genes with known function and sometimes known genomic localization can be simultaneously studied in many individuals. This opens new prospects for obtaining statistical estimates for a great number of genes and segregating elements. Mating system, gene exchange, reproductive population size, population disequilibrium, interaction among populations, and many other traditional problems of population genetics can be now studied using data on variation in many genes. Moreover, population genomic analysis allows one to distinguish factors that affect individual genes, alleles, or nucleotides (such as, for example, natural selection) from factors affecting the entire genome (e.g., demography). This paper presents a brief review of traditional methods of studying genetic variation in forest tree species and introduces a new, integrated population genomics approach. The main stages of the latter are : (1) selection of genes, which are tentatively involved in variation of adaptive traits, by means of a detailed examination of the regulation and the expression of individual genes and genotypes, with subsequent determination of their complete allelic composition by direct nucleotide sequencing; (2) examination of the phenotypic effects of individual alleles by, e.g., association mapping; and (3) determining the frequencies of the selected alleles in natural population for identification of the adaptive variation pattern in the heterogeneous environment. Through decoding the phenotypic effects of individual alleles and identification of adaptive variation patterns at the population level, population genomics in the future will serve as a very helpful, efficient, and economical tool, essential for developing a correct strategy for conserving and increasing forests and other commercially valuable plant and animal species.     

Cytonuclear coevolution: the genomics of cooperation

Without mitochondria we would be in big trouble, and there would be a global biological energy crisis if it were not for chloroplasts. Fortunately, genomic evolution over the past two billion years has ensured that the functions of these key organelles are with us to stay. Whole-genome analyses have not only proven that mitochondria and chloroplasts are descended from formerly free-living bacteria, but have also shown that it is difficult to define eukaryotes without reference to the fusion and coevolution of host and endosymbiont genomes. Here, we review how the macro- and microevolutionary insights that follow from the genomics of cytonuclear interactions are uniting molecular evolution, structural proteomics, population genetics and problems in aging and disease. Our goals are to clarify the coevolutionary events that have governed nuclear and organelle evolution, and to encourage further critical analyses of these interactions as problems in the study of co-adapted gene complexes.     

The rise of yeast population genomics

Genome sequences of multiple individuals are essential to determine the forces shaping sequence variation as well as to understand the relationship between genotype and phenotype. Because of their wide ecological, geographical and genetic diversity, yeast species represent an ideal model system for population genomics. Recently, there has been a renewed interest in characterizing the genetic diversity within yeast species such as Saccharomyces cerevisiae and Saccharomyces paradoxus. Here, we review recent progress in the exploration of the intraspecific diversity using large collections of yeast isolates. These recent large-scale polymorphism surveys have increased our understanding of the population structures as well as the evolutionary history of the species. In addition, these resources represent a powerful framework for dissecting the relationship between genotype and phenotype.     

Dos and don'ts of testing the geographic mosaic theory of coevolution

The geographic mosaic theory of coevolution is stimulating much new research on interspecific interactions. We provide a guide to the fundamental components of the theory, its processes and main predictions. Our primary objectives are to clarify misconceptions regarding the geographic mosaic theory of coevolution and to describe how empiricists can test the theory rigorously. In particular, we explain why confirming the three main predicted empirical patterns (spatial variation in traits mediating interactions among species, trait mismatching among interacting species and few species-level coevolved traits) does not provide unequivocal support for the theory. We suggest that strong empirical tests of the geographic mosaic theory of coevolution should focus on its underlying processes: coevolutionary hot and cold spots, selection mosaics and trait remixing. We describe these processes and discuss potential ways each can be tested.     

The population genomics of hepatitis B virus

Hepatitis B virus (HBV) infection is considered as the fifth leading cause of death due to infectious diseases and has a worldwide prevalence. The particular geographical distribution of the eight previously defined genotypes of HBV suggests that the viral population is highly structured. The presence of such population structure is likely to affect the geographical distribution of polymorphisms involved in disease progression. In this study, we determined the structure of the HBV population using a clustering approach based on the observed allele frequencies at the polymorphic loci. We used all full-genome sequences publicly available and obtained a significant clustering of the HBV population into four main clusters, strongly associated with the current classification into genotypes. One of these main clusters could itself be split into three well-supported subclusters, highlighting the hierarchical nature of the population differentiation between HBV strains. The extremely clear-cut subdivision of the HBV population further indicates that recombination in HBV is not as extensive as previously assumed.     

The demography and population genomics of evolutionary transitions to self-fertilization in plants

The evolution of self-fertilization from outcrossing has occurred on numerous occasions in flowering plants. This shift in mating system profoundly influences the morphology, ecology, genetics and evolution of selfing lineages. As a result, there has been sustained interest in understanding the mechanisms driving the evolution of selfing and its environmental context. Recently, patterns of molecular variation have been used to make inferences about the selective mechanisms associated with mating system transitions. However, these inferences can be complicated by the action of linked selection following the transition. Here, using multilocus simulations and comparative molecular data from related selfers and outcrossers, we demonstrate that there is little evidence for strong bottlenecks associated with initial transitions to selfing, and our simulation results cast doubt on whether it is possible to infer the role of bottlenecks associated with reproductive assurance in the evolution of selfing. They indicate that the effects of background selection on the loss of diversity and efficacy of selection occur rapidly following the shift to high selfing. Future comparative studies that integrate explicit ecological and genomic details are necessary for quantifying the independent and joint effects of selection and demography on transitions to selfing and the loss of genetic diversity.     

The n = 1 constraint in population genomics

A key objective of population genomics is to identify portions of the genome that have been shaped by natural selection rather than by neutral divergence. A previously recognized but underappreciated challenge to this objective is that observations of allele frequencies across genomes in natural populations often correspond to a single, unreplicated instance of the outcome of evolution. This is because the composition of each individual genomic region and population is expected to be the outcome of a unique array of evolutionary processes. Given a single observation, inference of the evolutionary processes that led to the observed state of a locus is associated with considerable uncertainty. This constraint on inference can be ameliorated by utilizing multi-allelic (e.g. DNA haplotypes) rather than bi-allelic markers, by analysing two or more populations with certain models and by utilizing studies of replicated experimental evolution. Future progress in population genomics will follow from research that recognizes the 'n = 1 constraint' and that utilizes appropriate and explicit evolutionary models for analysis.     

A new numerical approach to mechanically analyse biological structures

In this work, an advanced discretization meshless technique is used to study the structural response of a human brain due to an impact load. The 2D and 3D brain geometrical models, and surrounding structures, were obtained through the processing of medical images, allowing to achieve a realistic geometry for the virtual model and to define the distribution of the mechanical properties accordingly with the medical images colour scale. Additionally, a set of essential and natural boundary conditions were assumed in order to reproduce a sudden impact force applied to the cranium. Then, a structural numerical analysis was performed using the Natural Neighbour Radial Point Interpolation Method (NNRPIM). The obtained results were compared with the finite element method (FEM) and a solution available in the literature. This work shows that the NNRPIM is a robust and accurate numerical technique, capable to produce results very close to other numerical approaches. In addition, the variable fields obtained with the meshless method are much smoother than the FEM corresponding solution.     

Linking phylogenetics with population genetics to reconstruct the geographic origin of a species

Reconstructing ancestral geographic origins is critical for understanding the long-term evolution of a species. Bayesian methods have been proposed to test biogeographic hypotheses while accommodating uncertainty in phylogenetic reconstruction. However, the problem that certain taxa may have a disproportionate influence on conclusions has not been addressed. Here, we infer the geographic origin of Drosophila simulans using 2,014 bp of the period locus from 63 lines collected from 18 countries. We also analyze two previously published datasets, alcohol dehydrogenase related and NADH:ubiquinone reductase 75 kDa subunit precursor. Phylogenetic inferences of all three loci support Madagascar as the geographic origin of D. simulans. Our phylogenetic conclusions are robust to taxon resampling and to the potentially confounding effects of recombination. To test our phylogenetically derived hypothesis we develop a randomization test of the population genetics prediction that sequences from the geographic origin should contain more genetic polymorphism than those from derived populations. We find that the Madagascar population has elevated genetic polymorphism relative to non-Madagascar sequences. These data are corroborated by mitochondrial DNA sequence data.     

Tagged library approach to chemical genomics and proteomics

Proteomics and chemical genomics face great challenges in the form of molecular libraries of ever increasing size and diversity requiring rapid screening, coupled with a growing number of target proteins for which complimentary molecular ligands are sought. Proteomics and chemical genomics are at a stage that requires techniques which can dramatically accelerate the discovery process. One technique that has shown great promise in accomplishing this is the tagged library approach. It entails the synthetic inclusion of an internal tag from the beginning of the synthesis. This tag adds another degree of functionality to the molecule, in addition to mere ligation, that eliminates the need for time-consuming steps downstream in the process. The tag's functional possibilities span a variety of uses including internal fluorophores, intrinsic binding motifs that enable compound identification, functionalities that play the major role in the synthesis of the ligand itself, and internal linkers that eliminate the need for lengthy 'tether effect' structure-activity relationship studies.     

The potential of nucleic acid repair in functional genomics

Chimeric RNA/DNA oligonucleotides have been used successfully to correct point and frameshift mutations in cells as well as in animal and plant models. This approach is one of several nucleic acid repair technologies that will help elucidate the function of newly discovered genes. Understanding the mechanisms by which these different technologies direct gene alteration is essential for progress in their application to functional genomics.