CONDOR: a database resource of developmentally associated conserved non-coding elements

<p>Abstract</p> <p>Background</p> <p>Comparative genomics is currently one of the most popular approaches to study the regulatory architecture of vertebrate genomes. Fish-mammal genomic comparisons have proved powerful in identifying conserved non-coding elements likely to be distal <it>cis-</it>regulatory modules such as enhancers, silencers or insulators that control the expression of genes involved in the regulation of early development. The scientific community is showing increasing interest in characterizing the function, evolution and language of these sequences. Despite this, there remains little in the way of user-friendly access to a large dataset of such elements in conjunction with the analysis and the visualization tools needed to study them.</p> <p>Description</p> <p>Here we present CONDOR (COnserved Non-coDing Orthologous Regions) available at: <url>http://condor.fugu.biology.qmul.ac.uk</url>. In an interactive and intuitive way the website displays data on > 6800 non-coding elements associated with over 120 early developmental genes and conserved across vertebrates. The database regularly incorporates results of ongoing <it>in vivo </it>zebrafish enhancer assays of the CNEs carried out in-house, which currently number ~100. Included and highlighted within this set are elements derived from duplication events both at the origin of vertebrates and more recently in the teleost lineage, thus providing valuable data for studying the divergence of regulatory roles between paralogs. CONDOR therefore provides a number of tools and facilities to allow scientists to progress in their own studies on the function and evolution of developmental <it>cis</it>-regulation.</p> <p>Conclusion</p> <p>By providing access to data with an approachable graphics interface, the CONDOR database presents a rich resource for further studies into the regulation and evolution of genes involved in early development.</p

MICA: a multi-omics method to predict gene regulatory networks in early human embryos

Recent advances in single-cell omics have transformed characterisation of cell types in challenging-to-study biological contexts. In contexts with limited single-cell samples, such as the early human embryo inference of transcription factor-gene regulatory network (GRN) interactions is especially difficult. Here, we assessed application of different linear or non-linear GRN predictions to single-cell simulated and human embryo transcriptome datasets. We also compared how expression normalisation impacts on GRN predictions, finding that transcripts per million reads outperformed alternative methods. GRN inferences were more reproducible using a non-linear method based on mutual information (MI) applied to single-cell transcriptome datasets refined with chromatin accessibility (CA) (called MICA), compared with alternative network prediction methods tested. MICA captures complex non-monotonic dependencies and feedback loops. Using MICA, we generated the first GRN inferences in early human development. MICA predicted co-localisation of the AP-1 transcription factor subunit proto-oncogene JUND and the TFAP2C transcription factor AP-2γ in early human embryos. Overall, our comparative analysis of GRN prediction methods defines a pipeline that can be applied to single-cell multi-omics datasets in especially challenging contexts to infer interactions between transcription factor expression and target gene regulation

Testing of the Lunar Reconnaissance Orbiter Attitude Control System Re-Design Without a Gyro

The Lunar Reconnaissance Orbiter (LRO) was launched in 2009 and, with itsseven science instruments, has made numerous contributions to our understandingof the moon. LRO is in an elliptical, polar lunar orbit and nominally maintainsa nadir orientation. There are frequent slews off nadir to observe various sciencetargets. LRO attitude control system (ACS) has two star trackers and a gyro forattitude estimation in an extended Kalman filter (EKF) and four reaction wheelsused in a proportional-integral-derivative (PID) controller. LRO is equipped withthrusters for orbit adjustments and momentum management. In early 2018, thegyro was powered off following a fairly rapid decline in the laser intensity on theX axis. Without the gyro, the EKF has been disabled. Attitude is provided by asingle star tracker and a coarse rate estimate is computed by a back differencingof the star tracker quaternions. Slews have also been disabled. A new rate estimationapproach makes use of a complementary filter, combining the quaterniondifferentiated rates and the integrated PID limited control torque (with reactionwheel drag and feedforward torque removed). The filtered rate estimate replacesthe MIMU rate in the EKF, resulting in minimal flight software changes. The paperwill cover the preparation and testing of the new gyroless algorithm, both inground simulations and inflight

Post-consumer plastic packaging waste in England: Assessing the yield of multiple collection-recycling schemes

The European Commission (EC) recently introduced a ‘Circular Economy Package’, setting ambitious recycling targets and identifying waste plastics as a priority sector where major improvements are necessary. Here, the authors explain how different collection modalities affect the quantity and quality of recycling, using recent empirical data on household (HH) post-consumer plastic packaging waste (PCPP) collected for recycling in the devolved administration of England over the quarterly period July-September 2014. Three main collection schemes, as currently implemented in England, were taken into account: (i) kerbside collection (KS), (ii) household waste recycling centres (HWRCs) (also known as ‘civic amenity sites’), and (iii) bring sites/banks (BSs). The results indicated that: (a) the contribution of KS collection scheme in recovering packaging plastics is higher than HWRCs and BBs, with respective percentages by weight (wt%) 90%, 9% and 1%; (b) alternate weekly collection (AWC) of plastic recyclables in wheeled bins, when collected commingled, demonstrated higher yield in KS collection; (c) only a small percentage (16%) of the total amount of post-consumer plastics collected in the examined period (141 kt) was finally sent to reprocessors (22 kt); (c) nearly a third of Local Authorities (LAs) reported insufficient or poor data; and (d) the most abundant fractions of plastics that finally reached the reprocessors were mixed plastic bottles and mixed plastics

Biological Earth observation with animal sensors

Space-based tracking technology using low-cost miniature tags is now delivering data on fine-scale animal movement at near-global scale. Linked with remotely sensed environmental data, this offers a biological lens on habitat integrity and connectivity for conservation and human health; a global network of animal sentinels of environmen-tal change

Genomic epidemiology of SARS-CoV-2 in a UK university identifies dynamics of transmission

AbstractUnderstanding SARS-CoV-2 transmission in higher education settings is important to limit spread between students, and into at-risk populations. In this study, we sequenced 482 SARS-CoV-2 isolates from the University of Cambridge from 5 October to 6 December 2020. We perform a detailed phylogenetic comparison with 972 isolates from the surrounding community, complemented with epidemiological and contact tracing data, to determine transmission dynamics. We observe limited viral introductions into the university; the majority of student cases were linked to a single genetic cluster, likely following social gatherings at a venue outside the university. We identify considerable onward transmission associated with student accommodation and courses; this was effectively contained using local infection control measures and following a national lockdown. Transmission clusters were largely segregated within the university or the community. Our study highlights key determinants of SARS-CoV-2 transmission and effective interventions in a higher education setting that will inform public health policy during pandemics.</jats:p

Monitoring Wild Coffee Using Ground Survey and Satellite Observation in Community-Managed Forest in Sheko, South-West Ethiopia

Preserving wild coffee in the natural forest, especially in southwest Ethiopia, is important for maintaining the genetic diversity of Arabica coffee and sustaining coffee production. To monitor the changes in wild coffee in the natural forest, we conducted an in situ baseline survey in 2015, and 30 of those survey sites were re-visited in 2019. Those surveys involved counting the number of mature mother trees, saplings and seedlings, as well as recording details of the sites, including disturbance, accessibility and forest conditions. Satellite imagery was combined with the site-specific in situ survey data to provide evidence of the forest condition around the study sites and therefore help more fully explore the causes for the changes in the wild coffee stock. The results show that, overall, the population of mother coffee trees was maintained during the 4-year period, and a slight increase in saplings occurred. Closer examination reveals considerable variations between sites, with some equally accessible sites showing a sharp decline in the number of mother trees while others show consistent increases. This study demonstrates the importance of systematic surveys, especially for the areas where forest cover and wild coffee plants are highly variable, and this may help explore community-specific approaches in managing wild coffee in the forest

Reviews

The following publications have been reviewed by the mentioned authors;Exploring Primary Design and Technology - reviewed by Alan CrossCreative Computing - reviewed by Alan CrossAll About Food - reviewed by Jonty KinsellaProducts and Packages for Key Stage 4 - reviewed by Chris SnellExamining Textiles Technology - reviewed by Glen Reeve-FowkesPCB Wizard V2.0 - reviewed by Rowland Dye and Phil NormanSkills in Textiles Technology - reviewed by Christine TwisletonGraphic Products to GCSE - reviewed by George AsquithCollins Real World Technology Series: Food Technology - reviewed by Roy BallamPackaging - reviewed by Melanie FasciatoThe Cutting Edge of Manufacturing - reviewed by Alan TruemanUnderstanding Ingredients - reviewed by Jonty KinsellaJapanese Art and Design - reviewed by Christine TwisletonTextiles: A Handbook for Teachers - reviewed by Christine TwisletonPICtutor - reviewed by David FosterDesign and Make It! Systems and Control Technology - reviewed by Trevor Taylo

MICA: a multi-omics method to predict gene regulatory networks in early human embryos.

Recent advances in single-cell omics have transformed characterisation of cell types in challenging-to-study biological contexts. In contexts with limited single-cell samples, such as the early human embryo inference of transcription factor-gene regulatory network (GRN) interactions is especially difficult. Here, we assessed application of different linear or non-linear GRN predictions to single-cell simulated and human embryo transcriptome datasets. We also compared how expression normalisation impacts on GRN predictions, finding that transcripts per million reads outperformed alternative methods. GRN inferences were more reproducible using a non-linear method based on mutual information (MI) applied to single-cell transcriptome datasets refined with chromatin accessibility (CA) (called MICA), compared with alternative network prediction methods tested. MICA captures complex non-monotonic dependencies and feedback loops. Using MICA, we generated the first GRN inferences in early human development. MICA predicted co-localisation of the AP-1 transcription factor subunit proto-oncogene JUND and the TFAP2C transcription factor AP-2γ in early human embryos. Overall, our comparative analysis of GRN prediction methods defines a pipeline that can be applied to single-cell multi-omics datasets in especially challenging contexts to infer interactions between transcription factor expression and target gene regulation