Diversification at Transcription Factor Binding Sites within a Species and the Implications for Environmental Adaptation

PublishedEvolution of new cellular functions can be achieved both by changes in protein coding sequences and by alteration of expression patterns. Variation of expression may lead to changes in cellular function with relatively little change in genomic sequence. We therefore hypothesize that one of the first signals of functional divergence should be evolution of transcription factor–binding sites (TFBSs). This adaptation should be detectable as substantial variation in the TFBSs of alleles. New data sets allow the first analyses of intraspecies variation from large number of whole-genome sequences. Using data from the Saccharomyces Genome Resequencing Project, we have analyzed variation in TFBSs. We find a large degree of variation both between these closely related strains and between pairs of duplicated genes. There is a correlation between changes in promoter regions and changes in coding sequences, indicating a coupling of changes in expression and function. We show that 1) the types genes with diverged promoters vary between strains from different environments and 2) that patterns of divergence in promoters consistent with positive selection are detectable in alleles between strains and on duplicate promoters. This variation is likely to reflect adaptation to each strain's natural environment. We conclude that, even within a species, we detect signs of selection acting on promoter regions that may act to alter expression patterns. These changes may indicate functional innovation in multiple genes and across the whole genome. Change in function could represent adaptation to the environment and be a precursor to speciation.This work was funded by Biotechnology and Biological Sciences Research Council grant BB/F007620/1

Inferring Gene Family Histories in Yeast Identifies Lineage Specific Expansions

PublishedThe complement of genes found in the genome is a balance between gene gain and gene loss. Knowledge of the specific genes that are gained and lost over evolutionary time allows an understanding of the evolution of biological functions. Here we use new evolutionary models to infer gene family histories across complete yeast genomes; these models allow us to estimate the relative genome-wide rates of gene birth, death, innovation and extinction (loss of an entire family) for the first time. We show that the rates of gene family evolution vary both between gene families and between species. We are also able to identify those families that have experienced rapid lineage specific expansion/contraction and show that these families are enriched for specific functions. Moreover, we find that families with specific functions are repeatedly expanded in multiple species, suggesting the presence of common adaptations and that these family expansions/contractions are not random. Additionally, we identify potential specialisations, unique to specific species, in the functions of lineage specific expanded families. These results suggest that an important mechanism in the evolution of genome content is the presence of lineage-specific gene family changes.This work is funded by BBSRC grant BB/I020489/1. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Determining the evolutionary history of gene families

PublishedMotivation: Recent large-scale studies of individuals within a population have demonstrated that there is widespread variation in copy number in many gene families. In addition, there is increasing evidence that the variation in gene copy number can give rise to substantial phenotypic effects. In some cases, these variations have been shown to be adaptive. These observations show that a full understanding of the evolution of biological function requires an understanding of gene gain and gene loss. Accurate, robust evolutionary models of gain and loss events are, therefore, required. Results: We have developed weighted parsimony and maximum likelihood methods for inferring gain and loss events. To test these methods, we have used Markov models of gain and loss to simulate data with known properties. We examine three models: a simple birth–death model, a single rate model and a birth–death innovation model with parameters estimated from Drosophila genome data. We find that for all simulations maximum likelihood-based methods are very accurate for reconstructing the number of duplication events on the phylogenetic tree, and that maximum likelihood and weighted parsimony have similar accuracy for reconstructing the ancestral state. Our implementations are robust to different model parameters and provide accurate inferences of ancestral states and the number of gain and loss events. For ancestral reconstruction, we recommend weighted parsimony because it has similar accuracy to maximum likelihood, but is much faster. For inferring the number of individual gene loss or gain events, maximum likelihood is noticeably more accurate, albeit at greater computational cost.Biotechnology and Biological Sciences Research Council, UK

Modular Biological Function Is Most Effectively Captured by Combining Molecular Interaction Data Types

PublishedLarge-scale molecular interaction data sets have the potential to provide a comprehensive, system-wide understanding of biological function. Although individual molecules can be promiscuous in terms of their contribution to function, molecular functions emerge from the specific interactions of molecules giving rise to modular organisation. As functions often derive from a range of mechanisms, we demonstrate that they are best studied using networks derived from different sources. Implementing a graph partitioning algorithm we identify subnetworks in yeast protein-protein interaction (PPI), genetic interaction and gene co-regulation networks. Among these subnetworks we identify cohesive subgraphs that we expect to represent functional modules in the different data types. We demonstrate significant overlap between the subgraphs generated from the different data types and show these overlaps can represent related functions as represented by the Gene Ontology (GO). Next, we investigate the correspondence between our subgraphs and the Gene Ontology. This revealed varying degrees of coverage of the biological process, molecular function and cellular component ontologies, dependent on the data type. For example, subgraphs from the PPI show enrichment for 84%, 58% and 93% of annotated GO terms, respectively. Integrating the interaction data into a combined network increases the coverage of GO. Furthermore, the different annotation types of GO are not predominantly associated with one of the interaction data types. Collectively our results demonstrate that successful capture of functional relationships by network data depends on both the specific biological function being characterised and the type of network data being used. We identify functions that require integrated information to be accurately represented, demonstrating the limitations of individual data types. Combining interaction subnetworks across data types is therefore essential for fully understanding the complex and emergent nature of biological function.JIM was funded by a Biotechnology and Biological Sciences Research Council (BBSRC) CASE studentship with industry partner Pfizer and RMA by a BBSRC studentship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Gene Duplication and Environmental Adaptation within Yeast Populations

PublishedPopulation-level differences in the number of copies of genes resulting from gene duplication and loss have recently been recognized as an important source of variation in eukaryotes. However, except for a small number of cases, the phenotypic effects of this variation are unknown. Data from the Saccharomyces Genome Resequencing Project permit the study of duplication in genome sequences from a set of individuals within the same population. These sequences can be correlated with available information on the environments from which these yeast strains were isolated. We find that yeast show an abundance of duplicate genes that are lineage specific, leading to a large degree of variation in gene content between individual strains. There is a detectable bias for specific functions, indicating that selection is acting to preferentially retain certain duplicates. Most strikingly, we find that sets of over- and underrepresented duplicates correlate with the environment from which they were isolated. Together, these observations indicate that gene duplication can give rise to substantial phenotypic differences within populations that in turn can offer a shortcut to evolutionary adaptation.This work was funded by BBSRC grant BB/F007620/1

Binding interface change and cryptic variation in the evolution of protein-protein interactions

Background:Physical interactions between proteins are essential for almost all biological functions and systems. To understand the evolution of function it is therefore important to understand the evolution of molecular interactions. Of key importance is the evolution of binding specificity, the set of interactions made by a protein, since change in specificity can lead to “rewiring” of interaction networks. Unfortunately, the interfaces through which proteins interact are complex, typically containing many amino-acid residues that collectively must contribute to binding specificity as well as binding affinity, structural integrity of the interface and solubility in the unbound state. Results: In order to study the relationship between interface composition and binding specificity, we make use of paralogous pairs of yeast proteins. Immediately after duplication these paralogues will have identical sequences and protein products that make an identical set of interactions. As the sequences diverge, we can correlate amino-acid change in the interface with any change in the specificity of binding. We show that change in interface regions correlates only weakly with change in specificity, and many variants in interfaces are functionally equivalent. We show that many of the residue replacements within interfaces are silent with respect to their contribution to binding specificity. Conclusions: We conclude that such functionally-equivalent change has the potential to contribute to evolutionary plasticity in interfaces by creating cryptic variation, which in turn may provide the raw material for functional innovation and coevolution.BBSRCWellcome Trust Institutional Strategic Support Awar

What constitutes 'good' home care for people with dementia? An investigation of the views of home care service recipients and providers

BACKGROUND: Our objective was to explore what people receiving and providing care consider to be ‘good’ in-home care for people living with dementia. METHODS: We conducted 36 in-depth interviews and two focus groups with key stakeholders in Australia in the first quarter of 2018. Participants included those receiving care (4 people living with dementia, 15 family carers) or providing care (9 case managers, 5 service managers, 10 home care workers). Qualitative thematic analysis was guided by Braun and Clarke’s six-step approach. RESULTS: Consensus was reached across all groups on five themes considered as important for good in-home dementia care: 1) Home care workers’ understanding of dementia and its impact; 2) Home care workers’ demonstrating person-centred care and empathy in their care relationship with their client; 3) Good relationships and communication between care worker, person with dementia and family carers; 4) Home care workers’ knowing positive practical strategies for changed behaviours; 5) Effective workplace policies and workforce culture. The results contributed to the co-design of a dementia specific training program for home care workers. CONCLUSIONS: It is crucial to consider the views and opinions of each stakeholder group involved in providing/receiving dementia care from home care workers, to inform workforce training, education program design and service design. Results can be used to inform and empower home care providers, policy, and related decision makers to guide the delivery of improved home care services. TRIAL REGISTRATION: ACTRN 12619000251123

What constitutes ‘good’ home care for people with dementia? An investigation of the views of home care service recipients and providers

BACKGROUND: Our objective was to explore what people receiving and providing care consider to be 'good' in-home care for people living with dementia. METHODS: We conducted 36 in-depth interviews and two focus groups with key stakeholders in Australia in the first quarter of 2018. Participants included those receiving care (4 people living with dementia, 15 family carers) or providing care (9 case managers, 5 service managers, 10 home care workers). Qualitative thematic analysis was guided by Braun and Clarke's six-step approach. RESULTS: Consensus was reached across all groups on five themes considered as important for good in-home dementia care: 1) Home care workers' understanding of dementia and its impact; 2) Home care workers' demonstrating person-centred care and empathy in their care relationship with their client; 3) Good relationships and communication between care worker, person with dementia and family carers; 4) Home care workers' knowing positive practical strategies for changed behaviours; 5) Effective workplace policies and workforce culture. The results contributed to the co-design of a dementia specific training program for home care workers. CONCLUSIONS: It is crucial to consider the views and opinions of each stakeholder group involved in providing/receiving dementia care from home care workers, to inform workforce training, education program design and service design. Results can be used to inform and empower home care providers, policy, and related decision makers to guide the delivery of improved home care services. TRIAL REGISTRATION: ACTRN 12619000251123

Protective role of vitamin B6 (PLP) against DNA damage in Drosophila models of type 2 diabetes

Growing evidence shows that improper intake of vitamin B6 increases cancer risk and several studies indicate that diabetic patients have a higher risk of developing tumors. We previously demonstrated that in Drosophila the deficiency of Pyridoxal 5' phosphate (PLP), the active form of vitamin B6, causes chromosome aberrations (CABs), one of cancer prerequisites, and increases hemolymph glucose content. Starting from these data we asked if it was possible to provide a link between the aforementioned studies. Thus, we tested the effect of low PLP levels on DNA integrity in diabetic cells. To this aim we generated two Drosophila models of type 2 diabetes, the first by impairing insulin signaling and the second by rearing flies in high sugar diet. We showed that glucose treatment induced CABs in diabetic individuals but not in controls. More interestingly, PLP deficiency caused high frequencies of CABs in both diabetic models demonstrating that hyperglycemia, combined to reduced PLP level, impairs DNA integrity. PLP-depleted diabetic cells accumulated Advanced Glycation End products (AGEs) that largely contribute to CABs as α-lipoic acid, an AGE inhibitor, rescued not only AGEs but also CABs. These data, extrapolated to humans, indicate that low PLP levels, impacting on DNA integrity, may be considered one of the possible links between diabetes and cancer

Global and regional brain metabolic scaling and its functional consequences

Background: Information processing in the brain requires large amounts of metabolic energy, the spatial distribution of which is highly heterogeneous reflecting complex activity patterns in the mammalian brain. Results: Here, it is found based on empirical data that, despite this heterogeneity, the volume-specific cerebral glucose metabolic rate of many different brain structures scales with brain volume with almost the same exponent around -0.15. The exception is white matter, the metabolism of which seems to scale with a standard specific exponent -1/4. The scaling exponents for the total oxygen and glucose consumptions in the brain in relation to its volume are identical and equal to $0.86\pm 0.03$, which is significantly larger than the exponents 3/4 and 2/3 suggested for whole body basal metabolism on body mass. Conclusions: These findings show explicitly that in mammals (i) volume-specific scaling exponents of the cerebral energy expenditure in different brain parts are approximately constant (except brain stem structures), and (ii) the total cerebral metabolic exponent against brain volume is greater than the much-cited Kleiber's 3/4 exponent. The neurophysiological factors that might account for the regional uniformity of the exponents and for the excessive scaling of the total brain metabolism are discussed, along with the relationship between brain metabolic scaling and computation.Comment: Brain metabolism scales with its mass well above 3/4 exponen