Integrating multi-taxon palaeogenomes and sedimentary ancient DNA to study past ecosystem dynamics

Ancient DNA (aDNA) has played a major role in our understanding of the past. Important advances in the sequencing and analysis of aDNA from a range of organisms have enabled a detailed understanding of processes such as past demography, introgression, domestication, adaptation and speciation. However, to date and with the notable exception of microbiomes and sediments, most aDNA studies have focused on single taxa or taxonomic groups, making the study of changes at the community level challenging. This is rather surprising because current sequencing and analytical approaches allow us to obtain and analyse aDNA from multiple source materials. When combined, these data can enable the simultaneous study of multiple taxa through space and time, and could thus provide a more comprehensive understanding of ecosystem-wide changes. It is therefore timely to develop an integrative approach to aDNA studies by combining data from multiple taxa and substrates. In this review, we discuss the various applications, associated challenges and future prospects of such an approach

High resolution ancient sedimentary DNA shows that alpine plant diversity is associated with human land use and climate change.

The European Alps are highly rich in species, but their future may be threatened by ongoing changes in human land use and climate. Here, we reconstructed vegetation, temperature, human impact and livestock over the past ~12,000 years from Lake Sulsseewli, based on sedimentary ancient plant and mammal DNA, pollen, spores, chironomids, and microcharcoal. We assembled a highly-complete local DNA reference library (PhyloAlps, 3923 plant taxa), and used this to obtain an exceptionally rich sedaDNA record of 366 plant taxa. Vegetation mainly responded to climate during the early Holocene, while human activity had an additional influence on vegetation from 6 ka onwards. Land-use shifted from episodic grazing during the Neolithic and Bronze Age to agropastoralism in the Middle Ages. Associated human deforestation allowed the coexistence of plant species typically found at different elevational belts, leading to levels of plant richness that characterise the current high diversity of this region. Our findings indicate a positive association between low intensity agropastoral activities and precipitation with the maintenance of the unique subalpine and alpine plant diversity of the European Alps

Discovery and characterization of chromatin states for systematic annotation of the human genome

A plethora of epigenetic modifications have been described in the human genome and shown to play diverse roles in gene regulation, cellular differentiation and the onset of disease. Although individual modifications have been linked to the activity levels of various genetic functional elements, their combinatorial patterns are still unresolved and their potential for systematic de novo genome annotation remains untapped. Here, we use a multivariate Hidden Markov Model to reveal 'chromatin states' in human T cells, based on recurrent and spatially coherent combinations of chromatin marks. We define 51 distinct chromatin states, including promoter-associated, transcription-associated, active intergenic, large-scale repressed and repeat-associated states. Each chromatin state shows specific enrichments in functional annotations, sequence motifs and specific experimentally observed characteristics, suggesting distinct biological roles. This approach provides a complementary functional annotation of the human genome that reveals the genome-wide locations of diverse classes of epigenetic function.National Science Foundation (U.S.). (Award 0905968)National Human Genome Research Institute (U.S.) (Award U54-HG004570)National Human Genome Research Institute (U.S.) (Award RC1-HG005334

Modulation of enhancer looping and differential gene targeting by Epstein-Barr virus transcription factors directs cellular reprogramming

Epstein-Barr virus (EBV) epigenetically reprogrammes B-lymphocytes to drive immortalization and facilitate viral persistence. Host-cell transcription is perturbed principally through the actions of EBV EBNA 2, 3A, 3B and 3C, with cellular genes deregulated by specific combinations of these EBNAs through unknown mechanisms. Comparing human genome binding by these viral transcription factors, we discovered that 25% of binding sites were shared by EBNA 2 and the EBNA 3s and were located predominantly in enhancers. Moreover, 80% of potential EBNA 3A, 3B or 3C target genes were also targeted by EBNA 2, implicating extensive interplay between EBNA 2 and 3 proteins in cellular reprogramming. Investigating shared enhancer sites neighbouring two new targets (WEE1 and CTBP2) we discovered that EBNA 3 proteins repress transcription by modulating enhancer-promoter loop formation to establish repressive chromatin hubs or prevent assembly of active hubs. Re-ChIP analysis revealed that EBNA 2 and 3 proteins do not bind simultaneously at shared sites but compete for binding thereby modulating enhancer-promoter interactions. At an EBNA 3-only intergenic enhancer site between ADAM28 and ADAMDEC1 EBNA 3C was also able to independently direct epigenetic repression of both genes through enhancer-promoter looping. Significantly, studying shared or unique EBNA 3 binding sites at WEE1, CTBP2, ITGAL (LFA-1 alpha chain), BCL2L11 (Bim) and the ADAMs, we also discovered that different sets of EBNA 3 proteins bind regulatory elements in a gene and cell-type specific manner. Binding profiles correlated with the effects of individual EBNA 3 proteins on the expression of these genes, providing a molecular basis for the targeting of different sets of cellular genes by the EBNA 3s. Our results therefore highlight the influence of the genomic and cellular context in determining the specificity of gene deregulation by EBV and provide a paradigm for host-cell reprogramming through modulation of enhancer-promoter interactions by viral transcription factors

DNA fragments binding CTCF in vitro and in vivo are capable of blocking enhancer activity

<p>Abstract</p> <p>Background</p> <p>Earlier we identified ten 100-300-bp long CTCF-binding DNA fragments selected earlier from a 1-Mb human chromosome 19 region. Here the positive-negative selection technique was used to check the ability of CTCF-binding human genomic fragments to block enhancer-promoter interaction when inserted into the genome.</p> <p>Results</p> <p>Ten CTCF-binding DNA fragments were inserted between the CMV enhancer and CMV minimal promoter driving the herpes simplex virus thymidine kinase (HSV<it>-tk</it>) gene in a vector expressing also the <it>neo</it>^Rgene under a separate promoter. The constructs were then integrated into the genome of CHO cells, and the cells resistant to neomycin and ganciclovir (positive-negative selection) were picked up, and their DNAs were PCR analyzed to confirm the presence of the fragments between the enhancer and promoter in both orientations.</p> <p>Conclusions</p> <p>We demonstrated that all sequences identified by their CTCF binding both <it>in vitro </it>and <it>in vivo </it>had enhancer-blocking activity when inserted between the CMV minimal promoter and enhancer in stably transfected CHO cells.</p

The feasibility of using pattern recognition software to measure the influence of computer use on the consultation

BACKGROUND: A key feature of a good general practice consultation is that it is patient-centred. A number of verbal and non-verbal behaviours have been identified as important to establish a good relationship with the patient. However, the use of the computer detracts the doctor's attention away from the patient, compromising these essential elements of the consultation. Current methods to assess the consultation and the influence of the computer on them are time consuming and subjective. If it were possible to measure these quantitatively, it could provide the basis for the first truly objective way of studying the influence of the computer on the consultation. The aim was to assess whether pattern recognition software could be used to measure the influence and pattern of computer use in the consultation. If this proved possible it would provide, for the first time, an objective quantitative measure of computer use and a measure of the attention and responsiveness of the general practitioner towards the patient. METHODS: A feasibility study using pattern recognition software to analyse a consultation was conducted. A web camera, linked to a data-gathering node was used to film a simulated consultation in a standard office. Members of the research team enacted the role of the doctor and the patient, using pattern recognition software to try and capture patient-centred, non-verbal behaviour. As this was a feasibility study detailed results of the analysis are not presented. RESULTS: It was revealed that pattern recognition software could be used to analyse certain aspects of a simulated consultation. For example, trigger lines enabled the number of times the clinician's hand covered the keyboard to be counted and wrapping recorded the number of times the clinician nodded his head. It was also possible to measure time sequences and whether the movement was brief or lingering. CONCLUSION: Pattern recognition software enables movements associated with patient-centredness to be recorded. Pattern recognition software has the potential to provide an objective, quantitative measure of the influence of the computer on the consultation

NOF1 Encodes an Arabidopsis Protein Involved in the Control of rRNA Expression

The control of ribosomal RNA biogenesis is essential for the regulation of protein synthesis in eukaryotic cells. Here, we report the characterization of NOF1 that encodes a putative nucleolar protein involved in the control of rRNA expression in Arabidopsis. The gene has been isolated by T-DNA tagging and its function verified by the characterization of a second allele and genetic complementation of the mutants. The nof1 mutants are affected in female gametogenesis and embryo development. This result is consistent with the detection of NOF1 mRNA in all tissues throughout plant life's cycle, and preferentially in differentiating cells. Interestingly, the closely related proteins from zebra fish and yeast are also necessary for cell division and differentiation. We showed that the nof1-1 mutant displays higher rRNA expression and hypomethylation of rRNA promoter. Taken together, the results presented here demonstrated that NOF1 is an Arabidopsis gene involved in the control of rRNA expression, and suggested that it encodes a putative nucleolar protein, the function of which may be conserved in eukaryotes

Common variation near ROBO2 is associated with expressive vocabulary in infancy

Twin studies suggest that expressive vocabulary at ~24 months is modestly heritable. However, the genes influencing this early linguistic phenotype are unknown. Here we conduct a genome-wide screen and follow-up study of expressive vocabulary in toddlers of European descent from up to four studies of the EArly Genetics and Lifecourse Epidemiology consortium, analysing an early (15–18 months, ‘one-word stage’, NTotal=8,889) and a later (24–30 months, ‘two-word stage’, NTotal=10,819) phase of language acquisition. For the early phase, one single-nucleotide polymorphism (rs7642482) at 3p12.3 near ​ROBO2, encoding a conserved axon-binding receptor, reaches the genome-wide significance level (P=1.3 × 10−8) in the combined sample. This association links language-related common genetic variation in the general population to a potential autism susceptibility locus and a linkage region for dyslexia, speech-sound disorder and reading. The contribution of common genetic influences is, although modest, supported by genome-wide complex trait analysis (meta-GCTA h215–18-months=0.13, meta-GCTA h224–30-months=0.14) and in concordance with additional twin analysis (5,733 pairs of European descent, h224-months=0.20)

Assessing Computational Methods of Cis-Regulatory Module Prediction

Computational methods attempting to identify instances of cis-regulatory modules (CRMs) in the genome face a challenging problem of searching for potentially interacting transcription factor binding sites while knowledge of the specific interactions involved remains limited. Without a comprehensive comparison of their performance, the reliability and accuracy of these tools remains unclear. Faced with a large number of different tools that address this problem, we summarized and categorized them based on search strategy and input data requirements. Twelve representative methods were chosen and applied to predict CRMs from the Drosophila CRM database REDfly, and across the human ENCODE regions. Our results show that the optimal choice of method varies depending on species and composition of the sequences in question. When discriminating CRMs from non-coding regions, those methods considering evolutionary conservation have a stronger predictive power than methods designed to be run on a single genome. Different CRM representations and search strategies rely on different CRM properties, and different methods can complement one another. For example, some favour homotypical clusters of binding sites, while others perform best on short CRMs. Furthermore, most methods appear to be sensitive to the composition and structure of the genome to which they are applied. We analyze the principal features that distinguish the methods that performed well, identify weaknesses leading to poor performance, and provide a guide for users. We also propose key considerations for the development and evaluation of future CRM-prediction methods

High-throughput mapping of regulatory DNA

Quantifying the effects of cis-regulatory DNA on gene expression is a major challenge. Here, we present the multiplexed editing regulatory assay (MERA), a high-throughput CRISPR-Cas9–based approach that analyzes the functional impact of the regulatory genome in its native context. MERA tiles thousands of mutations across ~40 kb of cis-regulatory genomic space and uses knock-in green fluorescent protein (GFP) reporters to read out gene activity. Using this approach, we obtain quantitative information on the contribution of cis-regulatory regions to gene expression. We identify proximal and distal regulatory elements necessary for expression of four embryonic stem cell–specific genes. We show a consistent contribution of neighboring gene promoters to gene expression and identify unmarked regulatory elements (UREs) that control gene expression but do not have typical enhancer epigenetic or chromatin features. We compare thousands of functional and nonfunctional genotypes at a genomic location and identify the base pair–resolution functional motifs of regulatory elements.National Institutes of Health (U.S.) (1U01HG007037