Genomic gigantism: DNA loss is slow in mountain grasshoppers

Several studies have shown DNA loss to be inversely correlated with genome size in animals. These studies include a comparison between Drosophila and the cricket, Laupala, but there has been no assessment of DNA loss in insects with very large genomes. Podisma pedestris, the brown mountain grasshopper, has a genome over 100 times as large as that of Drosophila and 10 times as large as that of Laupala. We used 58 paralogous nuclear pseudogenes of mitochondrial origin to study the characteristics of insertion, deletion, and point substitution in P. pedestris and Italopodisma. In animals, these pseudogenes are "dead on arrival"; they are abundant in many different eukaryotes, and their mitochondrial origin simplifies the identification of point substitutions accumulated in nuclear pseudogene lineages. There appears to be a mononucleotide repeat within the 643-bp pseudogene sequence studied that acts as a strong hot spot for insertions or deletions (indels). Because the data for other insect species did not contain such an unusual region, hot spots were excluded from species comparisons. The rate of DNA loss relative to point substitution appears to be considerably and significantly lower in the grasshoppers studied than in Drosophila or Laupala. This suggests that the inverse correlation between genome size and the rate of DNA loss can be extended to comparisons between insects with large or gigantic genomes (i.e., Laupala and Podisma). The low rate of DNA loss implies that in grasshoppers, the accumulation of point mutations is a more potent force for obscuring ancient pseudogenes than their loss through indel accumulation, whereas the reverse is true for Drosophila. The main factor contributing to the difference in the rates of DNA loss estimated for grasshoppers, crickets, and Drosophila appears to be deletion size. Large deletions are relatively rare in Podisma and Italopodisma.     

Genetic drift and mutational hazard in the evolution of salamander genomic gigantism

Salamanders have the largest nuclear genomes among tetrapods and, excepting lungfishes, among vertebrates as a whole. Lynch and Conery (2003) have proposed the mutational‐hazard hypothesis to explain variation in genome size and complexity. Under this hypothesis, noncoding DNA imposes a selective cost by increasing the target for degenerative mutations (i.e., the mutational hazard). Expansion of noncoding DNA, and thus genome size, is driven by increased levels of genetic drift and/or decreased mutation rates; the former determines the efficiency with which purifying selection can remove excess DNA, whereas the latter determines the level of mutational hazard. Here, we test the hypothesis that salamanders have experienced stronger long‐term, persistent genetic drift than frogs, a related clade with more typically sized vertebrate genomes. To test this hypothesis, we compared dN/dS and Kr/Kc values of protein‐coding genes between these clades. Our results do not support this hypothesis; we find that salamanders have not experienced stronger genetic drift than frogs. Additionally, we find evidence consistent with a lower nucleotide substitution rate in salamanders. This result, along with previous work showing lower rates of small deletion and ectopic recombination in salamanders, suggests that a lower mutational hazard may contribute to genomic gigantism in this clade.     

Integrating the ‘genomic mosaic’ view of species into studies of biotic interactions: a comment on Bernhardsson et al. ()

The co‐occurrence of geographical structure in herbivore communities, metabolomes and defence genes in forest trees has been analysed in the context of ‘geographical mosaics’ of coevolution. A deeper understanding of these important issues will require full integration of a ‘genomic mosaic’ view of species into community ecology.     

Triggers for genomic rearrangements: insights into genomic, cellular and environmental influences

Genomic rearrangements are associated with many human genomic disorders, including cancers. It was previously thought that most genomic rearrangements formed randomly but emerging data suggest that many are nonrandom, cell type-, cell stage- and locus-specific events. Recent studies have revealed novel cellular mechanisms and environmental cues that influence genomic rearrangements. In this Review, we consider the multitude of influences on genomic rearrangements by grouping these influences into four categories: proximity of chromosomal regions in the nucleus, cellular stress, inappropriate DNA repair or recombination, and DNA sequence and chromatin features. The synergy of these triggers can poise a cell for rearrangements and here we aim to provide a conceptual framework for understanding the genesis of genomic rearrangements.     

Nutrigenomics: integrating genomic approaches into nutrition research

It has been suggested that the supermarket of today will be the pharmacy of tomorrow. Such statements have been derived from recognition of our increasing ability to optimize nutrition, and maintain a state of good health through longer periods of life. The new field of nutrigenomics, which focuses on the interaction between bioactive dietary components and the genome, recognizes that current nutritional guidelines may be ideal for only a relatively small proportion of the population. There is good evidence that nutrition has significant influences on the expression of genes, and, likewise, genetic variation can have a significant effect on food intake, metabolic response to food, individual nutrient requirements, food safety, and the efficacy of disease-protective dietary factors. For example, a significant number of human studies in various areas are increasing the evidence for interactions between single nucleotide polymorphisms (SNPs) in various genes and the metabolic response to diet, including the risk of obesity. Many of the same genetic polymorphisms and dietary patterns that influence obesity or cardiovascular disease also affect cancer, since overweight individuals are at increased risk of cancer development. The control of food intake is profoundly affected by polymorphisms either in genes encoding taste receptors or in genes encoding a number of peripheral signaling peptides such as insulin, leptin, ghrelin, cholecystokinin, and corresponding receptors. Total dietary intake, and the satiety value of various foods, will profoundly influence the effects of these genes. Identifying key SNPs that are likely to influence the health of an individual provides an approach to understanding and, ultimately, to optimizing nutrition at the population or individual level. Traditional methods for identification of SNPs may involve consideration of individual variants, using methodologies such as restriction fragment length polymorphisms or quantitative real-time PCR assays. New developments allow identification of up to 500,000 SNPs in an individual, and with increasingly lowered pricings these developments may explode the population-level potential for dietary optimization based on nutrigenomic approaches.     

Marine Bacterial Sulfated Fucoglucuronomannan (SFGM) Lyase Digests Brown Algal SFGM into Trisaccharides

Abstract Three kinds of trisaccharides were prepared by digesting fucoidan from the brown alga Kjellmaniella crassifolia, with the extracellular enzymes of the marine bacterium Fucobacter marina. Their structures were determined as Δ^4,5GlcpUA1-2(L-Fucp(3-O-sulfate)α1-3)D-Manp, Δ^4,5GlcpUA1-2(L-Fucp(3-O-sulfate)α1-3)D-Manp(6-O-sulfate), and Δ^4,5GlcpUA1-2(L-Fucp(2,4-O-disulfate)α1-3)D-Manp(6-O-sulfate), which indicated the existence of a novel polysaccharide in the fucoidan and a novel glycosidase in the extracellular enzymes. In order to determine the complete structure of the polysaccharide and the reaction mechanism of the glycosidase, the fucoidan was partially hydrolyzed to obtain glucuronomannan, which is the putative backbone of the polysaccharide, and its sugar sequence was determined as (-4-D-GlcpUAβ1-2D-Manpα1-)_n, which disclosed that the main structure of the polysaccharide is (-4-D-GlcpUAβ1-2(L-Fucp(3-O-sulfate)α1-3)D-Manpα1-)_n. Consequently, the glycosidase was deduced to be an endo-α-D-mannosidase that eliminatively cleaves the α-D-mannosyl linkage between D-Manp and D-GlcpUA residues in the polysaccharide and produces the above trisaccharides. The novel polysaccharide and glycosidase were tentatively named as sulfated fucoglucuronomannan (SFGM) and SFGM lyase, respectively.     

Deeper into the maize: new insights into genomic imprinting in plants

Current models for regulation of parent-specific gene expression in plants have been based on a small number of imprinted genes in Arabidopsis. These present repression as the default state, with expression requiring targeted activation. In general, repression is associated with maintenance methylation of cytosines, while no role has been found in Arabidopsis imprinting for de novo methylation--unlike the case in mammals. A recent paper both reinforces and challenges the model drawn from Arabidopsis. Methylation patterns of two imprinted loci in maize were tracked from gametes to offspring, enabling an exploration of the timing of imprinting. For one gene, fie1, the results were as expected: parent-specific methylation patterns were inherited from the three types of gamete: egg, central cell and sperm. The behaviour of fie2, however, was a surprise: no alleles were methylated in the gametes, although paternally contributed fie2 is methylated and silent in the endosperm, indicating that, in some cases, plant imprinting requires de novo DNA methylation. This work significantly broadens our understanding of plant imprinting and points to a greater diversity in imprinting mechanisms than has previously been appreciated.     

Positional orthology: putting genomic evolutionary relationships into context

Orthology is a powerful refinement of homology that allows us to describe more precisely the evolution of genomes and understand the function of the genes they contain. However, because orthology is not concerned with genomic position, it is limited in its ability to describe genes that are likely to have equivalent roles in different genomes. Because of this limitation, the concept of 'positional orthology' has emerged, which describes the relation between orthologous genes that retain their ancestral genomic positions. In this review, we formally define this concept, for which we introduce the shorter term 'toporthology', with respect to the evolutionary events experienced by a gene's ancestors. Through a discussion of recent studies on the role of genomic context in gene evolution, we show that the distinction between orthology and toporthology is biologically significant. We then review a number of orthology prediction methods that take genomic context into account and thus that may be used to infer the important relation of toporthology.     

‘It is an entrustment’: Broad consent for genomic research and biobanks in sub‐Saharan Africa

In recent years, there has been an increase in the establishment of biobanks for genetic and genomic studies around the globe. One example of this is the Human Heredity and Health in Africa Initiative (H3Africa), which has established biobanks in the sub‐region to facilitate future indigenous genomic studies. The concept of ‘broad consent’ has been proposed as a mechanism to enable potential research participants in biobanks to give permission for their samples to be used in future research studies. However, questions remain about the acceptability of this model of consent. Drawing on findings from empirical research about the role of trust in decision‐making, we argue that an account of entrustment may be an appropriate way of addressing current challenges of seeking consent for biobank research in Africa. We propose a set of key points to consider that can support the proposed entrustment framework.     

Elastase Digests: New Ammunition for Shotgun Membrane Proteomics

Despite many advances in membrane proteomics during the last decade the fundamental problem of accessing the transmembrane regions itself has only been addressed to some extent. The present study establishes a method for the nano-LC-based analysis of complex membrane proteomes on the basis of a methanolic porcine pancreatic elastase digest to increase transmembrane coverage. Halobacterium salinarium purple and Corynebacterium glutamicum membranes were successfully analyzed by using the new protocol. We demonstrated that elastase digests yield a large proportion of transmembrane peptides, facilitating membrane protein identification. The potential for characterization of a membrane protein through full sequence coverage using elastase is there but is restricted to the higher abundance protein components. Compatibility of the work flow with the two most common mass spectrometric ionization techniques, ESI and MALDI, was shown. Currently better results are obtained using ESI mainly because of the low response of MALDI for strictly neutral peptides. New findings concerning elastase specificity in complex protein mixtures reveal a new prospect beyond the application in shotgun experiments. Furthermore peptide mass fingerprinting with less specific enzymes might be done in the near future but requires an adaptation of current search algorithms to the new proteases.Upon the introduction of modern mass spectrometric ionization techniques, such as MALDI (1) and ESI (2), extremely powerful and valuable tools were given to researchers for the identification and characterization of proteins. Nevertheless the intricate analysis of membrane subproteomes still represents one of the major challenges despite the amount of “success” reported in the literature. Until now, there was no general protocol available to address membrane proteomes as a whole, demonstrating their degree of difficulty and complexity.During the past years, two different strategies in proteome analysis have evolved: the more widespread bottom-up and top-down proteomics. The latter approach has been shown to provide access to the transmembranal regions of membrane proteins and has the power to characterize complete protein primary structures including labile covalent modifications (3, 4). Nevertheless there are limitations due to sample complexity, emphasizing the need for a liquid chromatographic separation on the protein level, which is comparable to LC peptide separation. Therefore, the bottom-up variant is the most commonly used method for the proteomics analysis of complex membrane samples. Improvements in the bottom-up work flow were achieved by adapting sample cleanup and prefractionation processes (5–10) and subsequently by the development of modified and optimized separation techniques. The two main work flows, the gel-based approach mainly carried out with 2D¹ SDS-PAGE (11, 12) and the shotgun identification of proteolytically digested protein mixtures and their multidimensional separation via liquid chromatography (13), had to be adapted. The separation of proteins via classical 2D SDS-PAGE is only possible up to a GRAVY score of ∼0.4 (14, 15). Despite lacking the separation power of the IEF-SDS-PAGE system, derived techniques like the doubled SDS- (16) and 16-benzyldimethyl-n-hexadecylammonium chloride/SDS-PAGE (17) represent an improvement for hydrophobic proteins. Advances in the nLC separation of hydrophobic peptides, e.g. the separation at elevated temperatures (18) and the use of LC-compatible detergents (19), yielded significant success. When combining both prominent separation techniques, the one-dimensional SDS-LC analysis proved to be more effective than 2D PAGE as well (20, 21).One of the remaining steps still offering room for improvements is the proteolytic procedure. The original multidimensional protein identification technique using trypsin has been successfully improved by the application of proteinase K under high pH conditions, yielding an increased number of membrane protein identifications (22). Further modification of this method by recleaving the isolated membranous parts with cyanogen bromide increased the accessibility to membrane-spanning peptides (18).Despite the suitability of proteinase K for the shotgun analysis of membrane proteomes, trypsin is the prevalent enzyme choice in most current proteomics approaches because of its very specific cleavage behavior. Calculations have implied that alternative proteases are preferentially suited for the analysis of membrane proteomes (23). Proteases other than trypsin have been utilized only to a small degree and mostly for the targeted analysis of protein complexes. Pepsin, for example, was used for the characterization of an aquaporin (24), and elastase and subtilisin were used as proteases in a triple digest approach of protein complexes and lens tissue (25). Further improvements in the accessibility of the membrane proteome have been shown for tryptic (26, 27) and tryptic/chymotryptic (28) digests by performing the proteolytic treatment in the presence of methanol.During membrane proteomics method development, purple membranes from Halobacterium sp. NRC-1, consisting to a large extent of the H⁺-ATPase bacteriorhodopsin, have widely been used as reference in a variety of cases. Full BR sequence coverage has been reported by several publications using different techniques (27, 29). Such exorbitant sequence coverage amounts are only achievable for the most abundant proteins within a complex mixture. The identification of less expressed proteins, which certainly are more in the researcher''s interest, occurs via lower peptide numbers (27).Generally the basic tryptic cleavage sites are predominantly located in the loops facing the cytoplasm and to a lesser extent in the extracellular or periplasmic loops but are very scarce within the transmembrane helix stretches. This mostly limits the potential tryptic fragments to loop components and larger peptides containing at least one TM helix. The use of another protease, preferentially cleaving after neutral aliphatic residues, should not succumb to this lack of cleavage sites.One of the previously mentioned proteases, porcine pancreatic elastase, was reported to possess potential cleavage specificity at the carboxyl-terminal side of small neutral amino acids (30). It has been used previously for the examination of single protein phosphorylations (31) but was described not to be suited for the cleavage of complex membrane-containing samples because of a supposedly limited activity when applied to them (22). Despite this finding, elastase has been successfully utilized in a mass spectrometric analysis as early as 1974 when it was regarded as an ideal protease for future mass spectrometric studies (32). At the same time, most of the experiments to characterize elastase by analyzing its S₁ pocket (for nomenclature, see Ref. 33) binding capabilities (34) as well as cleavage preferences of ester and protein substrates (35–39) were performed.Based on previous research concerning elastase, we set up an nLC-based membrane proteomics analysis. This large data set was used to characterize the protease behavior of elastase and the physicochemical properties of the detected peptides. The PM model was used to establish a method to analyze more complex Corynebacterium glutamicum membranes, which have been analyzed previously using different 2D techniques (7, 28). We demonstrated that a combination of elastase and methanol is particularly suitable for an nLC-based membrane proteome analysis and results in a significantly increased number of TM peptides. Additionally the promising PMF application of elastase digests is discussed.     

High-resolution genomic analysis: the tumor-immune interface comes into focus

A genomic analysis of heterogeneous colorectal tumor samples has uncovered interactions between immunophenotype and various aspects of tumor biology, with implications for informing the choice of immunotherapies for specific patients and guiding the design of personalized neoantigen-based vaccines.Please see related article: http://dx.doi.org/10.1186/s13059-015-0620-6Immunotherapy is a promising new approach for treating human malignancies. Approximately 20% of melanoma and lung cancer patients receiving immune checkpoint inhibitors show responses [1,2]. Current major challenges include identification of patients most likely to respond to specific therapies and elucidation of novel targets to treat those who do not. To address these problems, a detailed understanding of the dynamic interactions between tumors and the immune system is required. In a new study, Zlatko Trajanoski and colleagues [3] describe a powerful approach to dissecting these issues through high-resolution analysis of patient genomic data. This study represents a significant advance over previous work from this group, which defined 28 immune-cell-type gene expression signatures and identified specific cell types as prognostic indicators in colorectal cancer (CRC) patients [4]. Here, the authors [3] integrate genomic analyses of CRC tumor molecular phenotypes, predicted antigenicity (called the ‘antigenome’), and immune-cell infiltration derived from multiple independent cohorts to gain refined insights into tumor-immune system interactions.     

Risk factors for autism: translating genomic discoveries into diagnostics

Autism spectrum disorders (ASDs) are a group of conditions characterized by impairments in communication and reciprocal social interaction, and the presence of restricted and repetitive behaviors. The spectrum of autistic features is variable, with severity of symptoms ranging from mild to severe, sometimes with poor clinical outcomes. Twin and family studies indicate a strong genetic basis for ASD susceptibility. Recent progress in defining rare highly penetrant mutations and copy number variations as ASD risk factors has prompted early uptake of these research findings into clinical diagnostics, with microarrays becoming a ‘standard of care’ test for any ASD diagnostic work-up. The ever-changing landscape of the generation of genomic data coupled with the vast heterogeneity in cause and expression of ASDs (further influenced by issues of penetrance, variable expressivity, multigenic inheritance and ascertainment) creates complexity that demands careful consideration of how to apply this knowledge. Here, we discuss the scientific, ethical, policy and communication aspects of translating the new discoveries into clinical and diagnostic tools for promoting the well-being of individuals and families with ASDs.