Maternal effects as the cause of parent-of-origin effects that mimic genomic imprinting

Epigenetic effects are increasingly recognized as an important source of variation in complex traits and have emerged as the focus of a rapidly expanding area of research. Principle among these effects is genomic imprinting, which has generally been examined in analyses of complex traits by testing for parent-of-origin-dependent effects of alleles. However, in most of these analyses maternal effects are confounded with genomic imprinting because they can produce the same patterns of phenotypic variation expected for various forms of imprinting. Distinguishing between the two is critical for genetic and evolutionary studies because they have entirely different patterns of gene expression and evolutionary dynamics. Using a simple single-locus model, we show that maternal genetic effects can result in patterns that mimic those expected under genomic imprinting. We further demonstrate how maternal effects and imprinting effects can be distinguished using genomic data from parents and offspring. The model results are applied to a genome scan for quantitative trait loci (QTL) affecting growth- and weight-related traits in mice to illustrate how maternal effects can mimic imprinting. This genome scan revealed five separate maternal-effect loci that caused a diversity of patterns mimicking those expected under various modes of genomic imprinting. These results demonstrate that the appearance of parent-of-origin-dependent effects (POEs) of alleles at a locus cannot be taken as direct evidence that the locus is imprinted. Moreover, they show that, in gene mapping studies, genetic data from both parents and offspring are required to successfully differentiate between imprinting and maternal effects as the cause of apparent parent-of-origin effects of alleles.     

植物多倍体基因组的形成与进化

多倍化是植物进化变异的自然现象,也是促进植物发生进化改变的重要力量。在被子植物中,约 70％的种类在进化史中曾发生过一次或多次多倍化的过程。目前的研究结果表明,自然界绝大多数多倍体是通过未减数配子的融合而形成的,并且很多多倍体种是通过多次独立的多倍化过程而重复发生的。由多倍化所导致的重复基因在多倍体基因组中可能有三种不同的命运,即：保持原有的功能、基因沉默或分化并执行新的功能。多倍化以后,重复基因组的进化动态则主要表现在染色体重排和“染色体二倍化”、不同基因组之间的相互渗透、以及核-质之间的相互作用等方面。     

What can patterns of differentiation across plant genomes tell us about adaptation and speciation?

Genome scans have become a common approach to identify genomic signatures of natural selection and reproductive isolation, as well as the genomic bases of ecologically relevant phenotypes, based on patterns of polymorphism and differentiation among populations or species. Here, we review the results of studies taking genome scan approaches in plants, consider the patterns of genomic differentiation documented and their possible causes, discuss the results in light of recent models of genomic differentiation during divergent adaptation and speciation, and consider assumptions and caveats in their interpretation. We find that genomic regions of high divergence generally appear quite small in comparisons of both closely and more distantly related populations, and for the most part, these differentiated regions are spread throughout the genome rather than strongly clustered. Thus, the genome scan approach appears well-suited for identifying genomic regions or even candidate genes that underlie adaptive divergence and/or reproductive barriers. We consider other methodologies that may be used in conjunction with genome scan approaches, and suggest further developments that would be valuable. These include broader use of sequence-based markers of known genomic location, greater attention to sampling strategies to make use of parallel environmental or phenotypic transitions, more integration with approaches such as quantitative trait loci mapping and measures of gene flow across the genome, and additional theoretical and simulation work on processes related to divergent adaptation and speciation.     

Widespread yet heterogeneous genomic divergence

Genetic differentiation during adaptive divergence and speciation is heterogeneous among genomic regions. Some regions can be highly differentiated between populations, for example, because they harbour genes under divergent selection or those causing reproductive isolation and thus are resistant to gene flow. Other regions might be homogenized by gene flow and thus weakly differentiated. Debates persist about the number of differentiated regions expected under divergence with gene flow, and their causes, size, and genomic distribution. In this issue of Molecular Ecology, a study of freshwater stickleback used next-generation sequencing to shed novel insight into these issues (Roesti et al. 2012). Many genomic regions distributed across the genome were strongly differentiated, indicating divergence with gene flow can involve a greater number of loci than often thought. Nonetheless, differentiation of some regions, such as those near the centre of chromosomes where recombination is reduced, was strongly accentuated over others. Thus, divergence was widespread yet highly heterogeneous across the genome. Moreover, different population pairs varied in patterns of differentiation, illustrating how genomic divergence builds up across stages of the speciation process. The study demonstrates how variation in different evolutionary processes, such as selection and recombination rate, can combine to result in similar genomic patterns. Future work could focus on teasing apart the contributions of different processes for causing differentiation, a task facilitated by experimental manipulations.     

DNA restriction patterns and DNA-DNA solution hybridization studies of Frankia isolates from Myrica pennsylvanica (bayberry).

Sixteen Frankia strains were isolated from Myrica pennsylvanica (bayberry) root nodules collected at diverse sites in New Jersey. Restriction pattern analysis of total genomic DNA was used to group the isolates into gel groups, and the genetic relatedness among the isolates was evaluated by DNA-DNA solution hybridization studies. Restriction pattern analysis provided a distinctive reproducible fingerprint for each isolate. Isolates fell into nine separate groups (strain types). More than one strain type was isolated from most sites. Isolates from two different gel groups were found in 3 of 10 nodules examined. Of the 16 isolates, 10 contained extrachromosomal DNA. Six different extrachromosomal DNA banding patterns were found. Genomically similar isolates carried related, but different, banding patterns. DNA hybridization studies indicated that isolates from a single plant species can be minimally related as determined by total genome homology. Homology ranged from 12 to 99%. Highly divergent strains were isolated from the same plant and found to cohabit the same nodule. Thus, this study demonstrated that Frankia strains which infect the same host plant are not only phenotypically different but also genetically diverse.     

DNA restriction patterns and DNA-DNA solution hybridization studies of Frankia isolates from Myrica pennsylvanica (bayberry)

Sixteen Frankia strains were isolated from Myrica pennsylvanica (bayberry) root nodules collected at diverse sites in New Jersey. Restriction pattern analysis of total genomic DNA was used to group the isolates into gel groups, and the genetic relatedness among the isolates was evaluated by DNA-DNA solution hybridization studies. Restriction pattern analysis provided a distinctive reproducible fingerprint for each isolate. Isolates fell into nine separate groups (strain types). More than one strain type was isolated from most sites. Isolates from two different gel groups were found in 3 of 10 nodules examined. Of the 16 isolates, 10 contained extrachromosomal DNA. Six different extrachromosomal DNA banding patterns were found. Genomically similar isolates carried related, but different, banding patterns. DNA hybridization studies indicated that isolates from a single plant species can be minimally related as determined by total genome homology. Homology ranged from 12 to 99%. Highly divergent strains were isolated from the same plant and found to cohabit the same nodule. Thus, this study demonstrated that Frankia strains which infect the same host plant are not only phenotypically different but also genetically diverse.     

Structural genomics: correlation blocks, population structure, and genome architecture

An integration of the pattern of genome-wide inter-site associations with evolutionary forces is important for gaining insights into the genomic evolution in natural or artificial populations. Here, we assess the inter-site correlation blocks and their distributions along chromosomes. A correlation block is broadly termed as the DNA segment within which strong correlations exist between genetic diversities at any two sites. We bring together the population genetic structure and the genomic diversity structure that have been independently built on different scales and synthesize the existing theories and methods for characterizing genomic structure at the population level. We discuss how population structure could shape correlation blocks and their patterns within and between populations. Effects of evolutionary forces (selection, migration, genetic drift, and mutation) on the pattern of genome-wide correlation blocks are discussed. In eukaryote organisms, we briefly discuss the associations between the pattern of correlation blocks and genome assembly features in eukaryote organisms, including the impacts of multigene family, the perturbation of transposable elements, and the repetitive nongenic sequences and GC-rich isochores. Our reviews suggest that the observable pattern of correlation blocks can refine our understanding of the ecological and evolutionary processes underlying the genomic evolution at the population level.     

Correlated patterns of genetic diversity and differentiation across an avian family

Comparative studies of closely related taxa can provide insights into the evolutionary forces that shape genome evolution and the prevalence of convergent molecular evolution. We investigated patterns of genetic diversity and differentiation in stonechats (genus Saxicola), a widely distributed avian species complex with phenotypic variation in plumage, morphology and migratory behaviour, to ask whether similar genomic regions have become differentiated in independent, but closely related, taxa. We used whole‐genome pooled sequencing of 262 individuals from five taxa and found that levels of genetic diversity and divergence are strongly correlated among different stonechat taxa. We then asked whether these patterns remain correlated at deeper evolutionary scales and found that homologous genomic regions have become differentiated in stonechats and the closely related Ficedula flycatchers. Such correlation across a range of evolutionary divergence and among phylogenetically independent comparisons suggests that similar processes may be driving the differentiation of these independently evolving lineages, which in turn may be the result of intrinsic properties of particular genomic regions (e.g. areas of low recombination). Consequently, studies employing genome scans to search for areas important for reproductive isolation or adaptation should account for corresponding regions of differentiation, as these regions may not necessarily represent speciation islands or evidence of local adaptation.     

Genomic consequences of multiple speciation processes in a stick insect

Diverse geographical modes and mechanisms of speciation are known, and individual speciation genes have now been identified. Despite this progress, genome-wide outcomes of different evolutionary processes during speciation are less understood. Here, we integrate ecological and spatial information, mating trials, transplantation data and analysis of 86 130 single nucleotide polymorphisms (SNPs) in eight populations (28 pairwise comparisons) of Timema cristinae stick insects to test the effects of different factors on genomic divergence in a system undergoing ecological speciation. We find patterns consistent with effects of numerous factors, including geographical distance, gene flow, divergence in host plant use and climate, and selection against maladaptive hybridization (i.e. reinforcement). For example, the number of highly differentiated ‘outlier loci’, allele-frequency clines and the overall distribution of genomic differentiation were recognizably affected by these factors. Although host use has strong effects on phenotypic divergence and reproductive isolation, its effects on genomic divergence were subtler and other factors had pronounced effects. The results demonstrate how genomic data can provide new insights into speciation and how genomic divergence can be complex, yet predictable. Future work could adopt experimental, mapping and functional approaches to directly test which genetic regions are affected by selection and determine their physical location in the genome.     

Cancer progression by non-clonal chromosome aberrations

The establishment of the correct conceptual framework is vital to any scientific discipline including cancer research. Influenced by hematologic cancer studies, the current cancer concept focuses on the stepwise patterns of progression as defined by specific recurrent genetic aberrations. This concept has faced a tough challenge as the majority of cancer cases follow non-linear patterns and display stochastic progression. In light of the recent discovery that genomic instability is directly linked to stochastic non-clonal chromosome aberrations (NCCAs), and that cancer progression can be characterized as a dynamic relationship between NCCAs and recurrent clonal chromosome aberrations (CCAs), we propose that the dynamics of NCCAs is a key element for karyotypic evolution in solid tumors. To support this viewpoint, we briefly discuss various basic elements responsible for cancer initiation and progression within an evolutionary context. We argue that even though stochastic changes can be detected at various levels of genetic organization, such as at the gene level and epigenetic level, it is primarily detected at the chromosomal or genome level. Thus, NCCA-mediated genomic variation plays a dominant role in cancer progression. To further illustrate the involvement of NCCA/CCA cycles in the pattern of cancer evolution, four cancer evolutionary models have been proposed based on the comparative analysis of karyotype patterns of various types of cancer.     

The value-added genome: building and maintaining genomic cytosine methylation landscapes

Epigenetic marks, such as cytosine methylation and post-translational histone modifications, are important for interpreting and managing eukaryotic genomes. Recent genetic studies in plants have uncovered details on the different interwoven mechanisms that are responsible for specification of genomic cytosine methylation patterns. These mechanisms include targeting cytosine methylation using heterochromatic histone modifications and RNA guides. Genomic cytosine methylation patterns also reflect locus-specific demethylation initiated by specialized DNA glycosylases. While genetics continues to more fully define these mechanisms, genomic studies in Arabidopsis have yielded an unprecedented high-resolution view of how epigenetic marks are layered over a genome.     

USING POPULATION GENOMICS TO DETECT SELECTION IN NATURAL POPULATIONS: KEY CONCEPTS AND METHODOLOGICAL CONSIDERATIONS

Natural selection shapes patterns of genetic variation among individuals, populations, and species, and it does so differentially across genomes. The field of population genomics provides a comprehensive genome-scale view of the action of selection, even beyond traditional model organisms. However, even with nearly complete genomic sequence information, our ability to detect the signature of selection on specific genomic regions depends on choosing experimental and analytical tools appropriate to the biological situation. For example, processes that occur at different timescales, such as sorting of standing genetic variation, mutation-selection balance, or fixed interspecific divergence, have different consequences for genomic patterns of variation. Inappropriate experimental or analytical approaches may fail to detect even strong selection or falsely identify a signature of selection. Here we outline the conceptual framework of population genomics, relate genomic patterns of variation to evolutionary processes, and identify major biological factors to be considered in studies of selection. As data-gathering technology continues to advance, our ability to understand selection in natural populations will be limited more by conceptual and analytical weaknesses than by the amount of molecular data. Our aim is to bring critical biological considerations to the fore in population genomics research and to spur the development and application of analytical tools appropriate to diverse biological systems.     

Genome-wide prediction of genetic interactions in a metazoan

Genetic interactions provide information about genes and processes with overlapping functions in biological systems. For Saccharomyces cerevisiae, computational integration of multiple types of functional genomic data is used to generate genome-wide predictions of genetic interactions. However, this methodology cannot be applied to the vastly more complex genome of metazoans, and only recently has the first metazoan genome-wide prediction of genetic interactions been reported. The prediction for Caenorhabditis elegans was generated by computationally integrating functional genomic data from S. cerevisiae, C. elegans and Drosophila melanogaster. This achievement is an important step toward system-level understanding of biological systems and human diseases.     

Comparison of type A enterotoxigenic Staphylococcus aureus strains isolated from geographically far distant locations by pulsed field gel electrophoresis

Staphylococcal enterotoxin A (SEA) is one of the major staphylococcal enterotoxins which may cause food-borne outbreaks. In order to investigate the difference in genomic types and to elucidate the most disseminated strains for enterotoxin A-producing strains of Staphylococcus aureus , a total of 60 SEA Staph. aureus strains isolated from food and clinical samples in Taiwan and 30 strains of the same enterotoxigenic type of strains obtained from geographically far distant locations were compared for their pulsed field gel electrophoresis (PFGE) patterns. The rare cutting endonuclease Sma I generated 10 distinct genome patterns for the 60 local SEA isolates and 15 and eight genome patterns, respectively, for the 20 and 10 SEA strains originally isolated from the USA and other countries. The local isolates are less diverse in genome patterns as compared to the US isolates. Of all these PFGE patterns, a certain pattern, such as pattern 3, is shared by the food and clinical isolates and the local and foreign isolates. Thus, although SEA Staph. aureus strains from geographically far distant locations showed considerable genetic diversity, PFGE pattern 3 strain might be one of the most disseminated strains.     

Noninvasive genome sampling in chimpanzees

The inevitable has happened: genomic technologies have been added to our noninvasive genetic sampling repertoire. In this issue of Molecular Ecology, Perry et al. (2010) demonstrate how DNA extraction from chimpanzee faeces, followed by a series of steps to enrich for target loci, can be coupled with next-generation sequencing. These authors collected sequence and single-nucleotide polymorphism (SNP) data at more than 600 genomic loci (chromosome 21 and the X) and the complete mitochondrial DNA. By design, each locus was 'deep sequenced' to enable SNP identification. To demonstrate the reliability of their data, the work included samples from six captive chimps, which allowed for a comparison between presumably genuine SNPs obtained from blood and potentially flawed SNPs deduced from faeces. Thus, with this method, anyone with the resources, skills and ambition to do genome sequencing of wild, elusive, or protected mammals can enjoy all of the benefits of noninvasive sampling.     

Reconstructing human origins in the genomic era

Analyses of recently acquired genomic sequence data are leading to important insights into the early evolution of anatomically modern humans, as well as into the more recent demographic processes that accompanied the global radiation of Homo sapiens. Some of the new results contradict early, but still influential, conclusions that were based on analyses of gene trees from mitochondrial DNA and Y-chromosome sequences. In this review, we discuss the different genetic and statistical methods that are available for studying human population history, and identify the most plausible models of human evolution that can accommodate the contrasting patterns observed at different loci throughout the genome.     

Genotyping-by-Sequencing for Populus Population Genomics: An Assessment of Genome Sampling Patterns and Filtering Approaches

Continuing advances in nucleotide sequencing technology are inspiring a suite of genomic approaches in studies of natural populations. Researchers are faced with data management and analytical scales that are increasing by orders of magnitude. With such dramatic advances comes a need to understand biases and error rates, which can be propagated and magnified in large-scale data acquisition and processing. Here we assess genomic sampling biases and the effects of various population-level data filtering strategies in a genotyping-by-sequencing (GBS) protocol. We focus on data from two species of Populus, because this genus has a relatively small genome and is emerging as a target for population genomic studies. We estimate the proportions and patterns of genomic sampling by examining the Populus trichocarpa genome (Nisqually-1), and demonstrate a pronounced bias towards coding regions when using the methylation-sensitive ApeKI restriction enzyme in this species. Using population-level data from a closely related species (P. tremuloides), we also investigate various approaches for filtering GBS data to retain high-depth, informative SNPs that can be used for population genetic analyses. We find a data filter that includes the designation of ambiguous alleles resulted in metrics of population structure and Hardy-Weinberg equilibrium that were most consistent with previous studies of the same populations based on other genetic markers. Analyses of the filtered data (27,910 SNPs) also resulted in patterns of heterozygosity and population structure similar to a previous study using microsatellites. Our application demonstrates that technically and analytically simple approaches can readily be developed for population genomics of natural populations.     

Quantifying the relative contributions of the X chromosome,autosomes, and mitochondrial genome to local adaptation*

During local adaptation with gene flow, some regions of the genome are inherently more responsive to selection than others. Recent theory predicts that X‐linked genes should disproportionately contribute to local adaptation relative to other genomic regions, yet this prediction remains to be tested. We carried out a multigeneration crossing scheme, using two cline‐end populations of Drosophila melanogaster, to estimate the relative contributions of the X chromosome, autosomes, and mitochondrial genome to divergence in four traits involved in local adaptation (wing size, resistance to heat, desiccation, and starvation stresses). We found that the mitochondrial genome and autosomes contributed significantly to clinal divergence in three of the four traits. In contrast, the X made no significant contribution to divergence in these traits. Given the small size of the mitochondrial genome, our results indicate that it plays a surprisingly large role in clinal adaptation. In contrast, the X, which represents roughly 20% of the Drosophila genome, contributes negligibly—a pattern that conflicts with theoretical predictions. These patterns reinforce recent work implying a central role of mitochondria in climatic adaptation, and suggest that different genomic regions may play fundamentally different roles in processes of divergence with gene flow.     

When structure leads to sex: Untangling signals in population genetic data sets

A robust signal of population structure often provides the first glimpse into the evolutionary history of a species and its populations. In this issue of Molecular Ecology, new work from Louis Bernatchez's group (Benestan et al., 2017 ) starts with an investigation of apparent structure in two marine species and concludes with an identification of sex‐linked genes, and in the process provides a model for robust analysis. Structure is the genetic signal left by natural selection as well as by neutral processes like migration and gene flow. Neutral areas of the genome can reveal the geographical relationships and related gene flow between populations over time and space, while selection can resist the natural genomic turnover created by recombination and generate adaptive structure between populations that can be detected. However, artefacts in a data set can easily hide the true signal of structure; mutation, whether it is a true appearance of a recent, minor allele, or more commonly, an error in SNP calling or molecular library construction, can easily conceal patterns of population structure (e.g., geographical structure in mackerel, Rodriguez‐Ezpeleta et al. ( 2016 )). A demographic structure that results from the most “forceful” evolutionary processes can overwhelm another signal generated by other, unrelated phenotypes. For example, the structure among diverged freshwater and marine threespine stickleback populations results from such strong selection and linkage disequilibrium across the genome that it impairs the ability to disentangle the genetic basis of particular evolved morphological traits (e.g., opercle development, Alligood ( 2017 )). Finally, there might be conflicting inferences for what underlies structure patterns. Structure may be created by differential patterns of meiotic recombination, and genetic maps are a reliable means for identifying genomic regions that resist recombination. But, without additional information (Anderson et al., 2012 ), it can be difficult to distinguish the recombination‐suppressing effect of a segregating genomic inversion (Small et al., 2016 ) from that of sex‐linked selection.