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.     

Hitchhiking mapping--functional genomics from the population genetics perspective

Several statistical tests based on population genetic theory are used to identify genes that have recently acquired a beneficial mutation. Here, I describe the extension of these tests to a multilocus approach for a genome-wide survey for genes that have been under recent positive selection. As this strategy could potentially identify genes with weak phenotypic effects, it will be very useful in population genetic approaches aimed at understanding adaptation processes in natural populations. Furthermore, this 'hitchhiking mapping' could also help in the functional characterization of genomes.     

Integrating population genetics and conservation biology in the era of genomics

As one of the final activities of the ESF-CONGEN Networking programme, a conference entitled ‘Integrating Population Genetics and Conservation Biology’ was held at Trondheim, Norway, from 23 to 26 May 2009. Conference speakers and poster presenters gave a display of the state-of-the-art developments in the field of conservation genetics. Over the five-year running period of the successful ESF-CONGEN Networking programme, much progress has been made in theoretical approaches, basic research on inbreeding depression and other genetic processes associated with habitat fragmentation and conservation issues, and with applying principles of conservation genetics in the conservation of many species. Future perspectives were also discussed in the conference, and it was concluded that conservation genetics is evolving into conservation genomics, while at the same time basic and applied research on threatened species and populations from a population genetic point of view continues to be emphasized.     

Marsupial genetics and genomics

Marsupials, the 'other' mammals, are found only in Australasia and the Americas. They are quite different from eutherian ('placental') mammals, as well they might be after 130 million years of separate evolution. They display a unique pattern of mammalian organization and development that is reflected by differences in their genomes. Here, we introduce marsupials as alternative (but not inferior!) mammals and summarize the state of knowledge of marsupial relationships, marsupial chromosomes, maps, genes and genetic regulatory systems. We shamelessly present the case for a Kangaroo Genome Project.     

Advances in rice breeding,genetics and genomics

Molecular Breeding -     

Domestication evolution,genetics and genomics in wheat

Domestication of plants and animals is the major factor underlying human civilization and is a gigantic evolutionary experiment of adaptation and speciation, generating incipient species. Wheat is one of the most important grain crops in the world, and consists mainly of two types: the hexaploid bread wheat (Triticum aestivum) accounting for about 95% of world wheat production, and the tetraploid durum wheat (T. durum) accounting for the other 5%. In this review, we summarize and discuss research on wheat domestication, mainly focusing on recent findings in genetics and genomics studies. T. aestivum originated from a cross between domesticated emmer wheat T. dicoccum and the goat grass Aegilops tauschii, most probably in the south and west of the Caspian Sea about 9,000 years ago. Wild emmer wheat has the same genome formula as durum wheat and has contributed two genomes to bread wheat, and is central to wheat domestication. Domestication has genetically not only transformed the brittle rachis, tenacious glume and non-free threshability, but also modified yield and yield components in wheat. Wheat domestication involves a limited number of chromosome regions, or domestication syndrome factors, though many relevant quantitative trait loci have been detected. On completion of the genome sequencing of diploid wild wheat (T. urartu or Ae. tauschii), domestication syndrome factors and other relevant genes could be isolated, and effects of wheat domestication could be determined. The achievements of domestication genetics and robust research programs in Triticeae genomics are of greatly help in conservation and exploitation of wheat germplasm and genetic improvement of wheat cultivars.     

At the interfaces of epidemiology, genetics and genomics

You come onto the court prepared for tennis but your partner seems to be ready for rugby. Neither of you is at all sure what it is that your opponent wants to play. The only recourse is to teach each other the rules of your own game and then decide whether you can collectively invent a new sport. Welcome to the dialogue at the intersections of epidemiology with genetics and genomics.     

Adaptive gene expression divergence inferred from population genomics

Detailed studies of individual genes have shown that gene expression divergence often results from adaptive evolution of regulatory sequence. Genome-wide analyses, however, have yet to unite patterns of gene expression with polymorphism and divergence to infer population genetic mechanisms underlying expression evolution. Here, we combined genomic expression data—analyzed in a phylogenetic context—with whole genome light-shotgun sequence data from six Drosophila simulans lines and reference sequences from D. melanogaster and D. yakuba. These data allowed us to use molecular population genetics to test for neutral versus adaptive gene expression divergence on a genomic scale. We identified recent and recurrent adaptive evolution along the D. simulans lineage by contrasting sequence polymorphism within D. simulans to divergence from D. melanogaster and D. yakuba. Genes that evolved higher levels of expression in D. simulans have experienced adaptive evolution of the associated 3′ flanking and amino acid sequence. Concomitantly, these genes are also decelerating in their rates of protein evolution, which is in agreement with the finding that highly expressed genes evolve slowly. Interestingly, adaptive evolution in 5′ cis-regulatory regions did not correspond strongly with expression evolution. Our results provide a genomic view of the intimate link between selection acting on a phenotype and associated genic evolution.     

PGDSpider: an automated data conversion tool for connecting population genetics and genomics programs

The analysis of genetic data often requires a combination of several approaches using different and sometimes incompatible programs. In order to facilitate data exchange and file conversions between population genetics programs, we introduce PGDSpider, a Java program that can read 27 different file formats and export data into 29, partially overlapping, other file formats. The PGDSpider package includes both an intuitive graphical user interface and a command-line version allowing its integration in complex data analysis pipelines. AVAILABILITY: PGDSpider is freely available under the BSD 3-Clause license on http://cmpg.unibe.ch/software/PGDSpider/.     

Molecular genetics and structural genomics of the human protein kinase C gene module

Background  

Protein kinase C (PKC) has become a major focus among cell biologists interested in second-messenger signal transduction and much has been learned about differences in the cellular localization and function of its different isotypes. In this study we systematically address the genomic locations and gene structures of the human PKC gene module.     

Exploiting genomics,genetics and chemistry to combat antibiotic resistance

To address the worsening problem of antibiotic-resistant bacteria there is an urgent need to develop new antibiotics. Comparative genomics and molecular genetics are being applied to produce lists of essential new targets for compound screening programmes. Combinatorial chemistry and structural biology are being applied to rapidly explore and optimize the interactions between lead compounds and their biological targets. Several compounds that have been identified from target-based screens are now in development, but technical and economic constraints might result in a trickle, rather than a flood, of new antibiotics onto the market in the near future.     

Proteomics: a link between genomics,genetics and physiology

Thanks to spectacular advances in the techniques for identifying proteins separated by two-dimensional electrophoresis and in methods for large-scale analysis of proteome variations, proteomics is becoming an essential methodology in various fields of plant biology. In the study of pleiotropic effects of mutants and in the analysis of responses to hormones and to environmental changes, the identification of involved metabolic pathways can be deduced from the function of affected proteins. In molecular quantitative genetics, proteomics can be used to map translated genes and loci controlling their expression, which can be used to identify proteins accounting for the variation of complex phenotypic traits. Linking gene expression to cell metabolism on the one hand and to genetic maps on the other, proteomics is a central tool for functional genomics.