UCL Biosciences Big Data
Lead Research Organisation:
University College London
Department Name: Genetics Evolution and Environment
Abstract
Much research in the biosciences is transitioning away from experimental work towards computational analysis. This involves a massive increase in the volume of data to be analysed and in the computational power to analyse it, and in the speed and capacity of computer networks to move data from the collection instruments to the compute clusters used to analyse it and then onto data archives.
University College London is one of the leading research-focused univsesities in the world. The UCL division of Biosciences undertakes an increasing amoutn of research involving Big Data. This includes large-scale biological and cellular imaging and DNA sequencing, much of it funded by the BBSRC and other UK research organisations.
The proposal aims to put in place a new computational infractructure within UCL Biosciences that links its data generation groups together with augemted compute and archive facilities. This involves installing a high-speed network capable of transferring up to 10 Gb/s from data collection instruments to the computer clusters and data archives managed in the UCL Depts of Computer Science and Research Computing. It also involves purchasing over 700 computers for data analysis and over two petabytes of disk storage, in a combination of high-speed disk attach to thte compute cluster and lower speed cheaper disk for archiving.
This combination of network, compute and storage will position UCL Biosciences to grow as a UK centre of research excellence over the next 4 years.
University College London is one of the leading research-focused univsesities in the world. The UCL division of Biosciences undertakes an increasing amoutn of research involving Big Data. This includes large-scale biological and cellular imaging and DNA sequencing, much of it funded by the BBSRC and other UK research organisations.
The proposal aims to put in place a new computational infractructure within UCL Biosciences that links its data generation groups together with augemted compute and archive facilities. This involves installing a high-speed network capable of transferring up to 10 Gb/s from data collection instruments to the computer clusters and data archives managed in the UCL Depts of Computer Science and Research Computing. It also involves purchasing over 700 computers for data analysis and over two petabytes of disk storage, in a combination of high-speed disk attach to thte compute cluster and lower speed cheaper disk for archiving.
This combination of network, compute and storage will position UCL Biosciences to grow as a UK centre of research excellence over the next 4 years.
Technical Summary
The proposal creates a new infrastructure for scientific computation within the UCL Division of Biosciences, to enable the growth of Big Data analysis over the next four years. This supports the work of Biosciences research groups in genetics, bioinformatics, protein structural studies, molecular biology, developmental biology, ecology, evolution, biophysics and biophotonics. Much of this research portfolio is funded by the BBSRC It comprises a fast network at 10Gb/s to connect imaging equipment in different buildings to a centralised datacentre. the data centre will comprise 3PtB RAID5 storage attached to at least 700 compute cores each with 8GB RAM arranged in groups of 24 cores, and finally a 48-core server with 1TB of shared RAM for parallel computations involving large shared memory, such as some image processing and de-novo assembly of genomes. This integrated suite of equipment will support the forseeable High-Performance Computing needs of UCL Biosciences for the next 4 years.
Planned Impact
Who might benefit from this equipment?
Researchers in UCL Biosciences funded by BBSRC will see an immediate benefit. These include all researchers using High Performance Computing, particularly in the fields of genetics, bioinformatics, protein structural studies, molecular biology, developmental biology, ecology, evolution, biophysics and biophotonics. Over 20 research groups in UCL Biosciences are likely to be immediate beneficiaries. Collaborators and other UCL scientists will also benefit. Longer term, the BBSRC and the wider community will benefit by the accelerated rate of research that will be produced. Collaborators working on crop improvement in Lower and Middle Income Countries (LMIC) will benefit.
How might they benefit from this equipment?
(i) Researchers using the BBSRC-funded imaging facilities in UCL Biosciences will be able to transfer their images over the new 10Gb/s network to be implemented as part of the equipment grant, and store them on the >2Ptb . They will then be able to process their images using the >700 compute cores and high-memory server.
(ii) Researchers using population DNA sequence data will be able to perform analyses such as mapping reads from multiple individuals to the reference geneome, and creating de-novo assemblies of large genomes. They will be able to analyse very large datasets (~50tB) which at present is very difficult due to space and compute resource limitations. These researchers include (a) Prof Richard Mott, who has BBSRC/GCRF research programmmes into crop improvement for wheat, rice and chickpea involving LMIC collaborators, analysing thousands of crop genomes. (b) Prof Chris Thompson, working on Dictylostelium genetics and evolution of social and non-social traits will be able to analyse ~1000 genomes.
(iii) Researchers using the CATH protein database developed by Prof Christine Orengo will be able to perform large-scale searches of large metagenomes providing functional characterisation of metagenomes across environments to detect novel bacterial relatives of CATH families associated with antibiotic resistance. Understanding antimicrobial resistance is a strategic priority for the BBSRC.
The Case for Support describes more research projects that will benefit directly from this equipment.
Researchers in UCL Biosciences funded by BBSRC will see an immediate benefit. These include all researchers using High Performance Computing, particularly in the fields of genetics, bioinformatics, protein structural studies, molecular biology, developmental biology, ecology, evolution, biophysics and biophotonics. Over 20 research groups in UCL Biosciences are likely to be immediate beneficiaries. Collaborators and other UCL scientists will also benefit. Longer term, the BBSRC and the wider community will benefit by the accelerated rate of research that will be produced. Collaborators working on crop improvement in Lower and Middle Income Countries (LMIC) will benefit.
How might they benefit from this equipment?
(i) Researchers using the BBSRC-funded imaging facilities in UCL Biosciences will be able to transfer their images over the new 10Gb/s network to be implemented as part of the equipment grant, and store them on the >2Ptb . They will then be able to process their images using the >700 compute cores and high-memory server.
(ii) Researchers using population DNA sequence data will be able to perform analyses such as mapping reads from multiple individuals to the reference geneome, and creating de-novo assemblies of large genomes. They will be able to analyse very large datasets (~50tB) which at present is very difficult due to space and compute resource limitations. These researchers include (a) Prof Richard Mott, who has BBSRC/GCRF research programmmes into crop improvement for wheat, rice and chickpea involving LMIC collaborators, analysing thousands of crop genomes. (b) Prof Chris Thompson, working on Dictylostelium genetics and evolution of social and non-social traits will be able to analyse ~1000 genomes.
(iii) Researchers using the CATH protein database developed by Prof Christine Orengo will be able to perform large-scale searches of large metagenomes providing functional characterisation of metagenomes across environments to detect novel bacterial relatives of CATH families associated with antibiotic resistance. Understanding antimicrobial resistance is a strategic priority for the BBSRC.
The Case for Support describes more research projects that will benefit directly from this equipment.
People |
ORCID iD |
| Richard Mott (Principal Investigator) |
Publications
Acman M
(2022)
Role of mobile genetic elements in the global dissemination of the carbapenem resistance gene blaNDM
in Nature Communications
Acman M
(2020)
Large-scale network analysis captures biological features of bacterial plasmids.
in Nature communications
Chen H
(2021)
Drivers of methicillin-resistant Staphylococcus aureus (MRSA) lineage replacement in China.
in Genome medicine
Cui L
(2020)
ADDO: a comprehensive toolkit to detect, classify and visualize additive and non-additive quantitative trait loci.
in Bioinformatics (Oxford, England)
Cui L
(2023)
Dominance is common in mammals and is associated with trans-acting gene expression and alternative splicing
in Genome Biology
Curtis D
(2021)
Analysis of 50,000 exome-sequenced UK Biobank subjects fails to identify genes influencing probability of developing a mood disorder resulting in psychiatric referral.
in Journal of affective disorders
Curtis D
(2021)
Haploinsufficiency of the HIRA gene may not always produce severe neurodevelopmental consequences
in Psychiatric Genetics
Curtis D
(2020)
Analysis of exome-sequenced UK Biobank subjects implicates genes affecting risk of hyperlipidaemia
in Molecular Genetics and Metabolism
| Description | The 17ALERT grant was awarded to UCL Division of Biosciences to purchase equipment for high-performance scientific computing, which underlies much of the research performed by the Division. This research is performed on two UCL computer clusters, managed by the Department of Computer Sciences (CS) and by Research IT Services (RITS). The final purchases made with funds from the grant were as follows: (i) With UCL Dept of Computer Science: 960 Cores with average 8GB RAM per core 2x 48core 3TB RAM high-memory servers (96 cores). 2.4 Petabytes of disk space (ii) With RITS: 6x 36cores 192GB RAM servers ie 216 cores 1x36 core 1.5TB RAM server high memory ie 36 cores Overall total number of Cores: 1308 Total disk Space: 2.4 Petabytes We have several hundred researchers who actively use high performance computing in their work. Much of this research involves running software pipelines on large datasets in parallel (for example, processing the genomes of a large population of individuals). This type of workflow requires large volumes of disk space to store the raw data and intermediate analysis files, and fast networks to be able to read and write large volumes (multi-terabyte) of data in parallel without causing bandwidth contention. For that reason we have purchased a large tranche of disk space (2.4 Petabytes) as well as over a thousand cores (roughly speaking, each compute core can run one process). UCL has invested significant money (of which this 17 ALERT award is a key component) into its high-performance computing infrastructure in order to allow our researchers to carry out data-driven biology and to enable the work required for the many BBSRC grants held at UCL. |
| Exploitation Route | Note that by careful procurement we were able to purchase almost double the number of cores originally costed on the grant. The equipment will be used by all researchers at UCL for their research, with priority given to those from the Division of Biosciences with BBSRC remit research projects. We expect the equipment to have a lifetime of approximately three years. We are planning further grant applications to replace and expand our scientific computing infrastructure. |
| Sectors | Agriculture, Food and Drink,Digital/Communication/Information Technologies (including Software),Environment,Healthcare,Pharmaceuticals and Medical Biotechnology |
| Description | What determines protein abundance in plants? |
| Amount | £3,354,456 (GBP) |
| Funding ID | BB/T002182/1 |
| Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 11/2019 |
| End | 10/2024 |
| Title | Array Genotypes for the wheat DIVERSE population and its founders |
| Description | We have made publicly available SNP genotypes for the diverse MAGIC wheat population, which has been characterised using the 35k Wheat Breeders' Array. Genotyping calls are available to download for the 16 founders and for 550 MAGIC lines. Calls were made using the Axiom Best Practices Genotyping Analysis workflow with an inbreeding penalty of 4. The released genotypes have consensus calls where multiple samples were genotyped from the same line. In addition, the genotypes at sites with no minor homozygous calls have been adjusted. The diverse MAGIC wheat population was developed at the National Institute for Applied Botany (NIAB). Genetic resources for this population were developed in collaboration between University College London (UCL) and NIAB as part of the MAGIC CARPeT project (MAGIC: Community Access to Resources, Protocols and Training), funded by the Biotechnology and Biological Sciences Research Council (BBSRC) under grants BB/M011666/1 (to NIAB) and BB/M011585/1 (to UCL) |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2019 |
| Provided To Others? | Yes |
| Impact | The data have just been made public and will be of use to breeders in the future who use the germplasm for the Diverse wheat in their own trials. |
| URL | http://mtweb.cs.ucl.ac.uk/mus/www/MAGICdiverse/index.html |
| Title | Sequence Data for a 3,000 year old emmer wheat genome |
| Description | Sequence data from an emmer wheat genome from ancient Egypt from our publication Nature Plants volume 5, p 1120-1128 (2019) are deposited in the ENA with study accession number PRJEB31103. The genotype calls are also provided as the source data for Fig. 2 on the paper web site. A database of archaeobotanical observations is provided as the source data for Extended Data Fig. 1. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2019 |
| Provided To Others? | Yes |
| Impact | The data are available for download by researchers interested in emmer wheat. It is too soon to quantify any impacts. |
| URL | https://www.ebi.ac.uk/ena/data/search?query=PRJEB31103 |
| Title | Sequence, Genotype, and Phenotype Data for wheat MAGIC diverse population and its sixteen founders |
| Description | The NIAB Diverse MAGIC (NDM) is a population of recombinant inbred lines of wheat descended from 16 diverse founders representing varieties commonly grown in the UK since about 1935. The founders were sequenced using exome/promotor capture or whole genome sequencing. Low coverage whole-genome sequence data for 555 MAGIC lines are available. Using variants called using exome data from the founders, we impute the genotype at >1m SNPs segregating among these lines. In addition genotyping array data (axiom wheat breeders' array) form the founders and MAGIC lines is available, although since this is much sparser than the imputed sequence data it is only of use for checking genotyping accuracy. 15 of the founders were sequenced after enriching for exome and promoter regions (~23x coverage of targets), one founder was sequenced using whole genome sequencing (~16x coverage of targets). 504 inbred lines were sequencing using ~0.3x whole genome sequencing. The sequencing data is available from the European Nucleotide Archive under project number PRJEB39021. VCFs of the called SNP variation are available from the European Variant Archive (EVA). SNP variants in exome/promoter regions were called from the founder data (EVA accession ERZ1643321). At these SNP sites, we then made genotype calls in the inbred lines (i) by using the alignments to make genotype calls directly (EVA accession ERZ1643320) and (ii) by imputation with STITCH software (EVA accession ERZ1643322). We provide files in PLINK format to give the genotypes of the founders and imputed genotypes of the inbred lines at ~1.1M sites. You can also download the inbred line genotypes at a tagging set of ~55k sites (LD pruned). VCFs of the called SNP variation are available from the European Variant Archive (EVA). SNP variants in exome/promoter regions were called from the founder data (EVA accession ERZ1643321). At these SNP sites, we then made genotype calls in the inbred lines (i) by using the alignments to make genotype calls directly (EVA accession ERZ1643320) and (ii) by imputation with STITCH software (EVA accession ERZ1643322). We provide files in PLINK format to give the genotypes of the founders and imputed genotypes of the inbred lines at ~1.1M sites. You can also download the inbred line genotypes at a tagging set of ~55k sites (LD pruned). Imputation using the founder genotypes as the reference panel means that the founder that contributed genetic material at each locus in each inbred line is estimated. There is some uncertainty in the reconstruction of these founder recombination mosaics, which can be accounted for by inferring the continuous 'dosage' of each founder at each locus. We provide the inferred founder haplotype contributions at all 1.1M SNP sites for download here. There is one .hap.txt file per chromosome giving the dosage at each site for each founder (column K, numbered in alphabetical order) for each inbred line. These were extracted from the VCFs outputted by STITCH using this script. Phenotypes for the founders and inbred lines are available to download from the website. Phenotype descriptions and collection methods are described in Scott, Fradgley et al. (2020). The diverse MAGIC wheat population has also been characterised using the 35k Wheat Breeders' Array. Genotyping calls are available to download for the 16 founders and for 550 MAGIC lines. Calls were made using the Axiom Best Practices Genotyping Analysis workflow with an inbreeding penalty of 4. The released genotypes have consensus calls where multiple samples were genotyped from the same line. In addition, the genotypes at sites with no minor homozygous calls have been adjusted. Scripts for alignment, variant calling, imputation, and association mapping are provided in the GitHub Repository michaelfscott/DIVERSE_MAGIC_WHEAT. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| Impact | The genotypes from the sequencing and genotyping array data has be compared, yielding information about the specificity of the widely-used array. In addition, the imputed SNP variants have been used to find QTL for traits of agronomic importance, which were phenotyped in these MAGIC lines. This establishes the MAGIC diverse wheat population as a resource for trait mapping. |
| URL | http://mtweb.cs.ucl.ac.uk/mus/www/MAGICdiverse/index.html |
| Description | Collaboration with IRRI and ICRISAT |
| Organisation | International Crops Research Institute for the Semi-Arid Tropics |
| Country | India |
| Sector | Charity/Non Profit |
| PI Contribution | We have set up formal collaborations with the International Rice Research Institute (IRRI), Philippines, and with the International Center for Crop Research in the Semi-Arid Tropics (Hyderabad, India) as part of the original. Formal collaboration agreements between UCL and IRRI and ICRISAT were signed in summer 2019. Both India and Philippines are described as LMIC in the 2020 DAC list. Richard Mott (PI of project) visited IRRI and ICRISAT in September 2017 during which time he gave seminars and held discussions and planning meetings with IRRI staff including Hei Leung, the IRRI PI, and ICRISAT staff including Rajeev Varshney, the ICRISAT PI. We have sequenced and analysed 1920 chickpea landrace genomes and 900 rice HEAT MAGIC genomes as described in the grant proposal. We have analysed several other datasets of chickpea and rice genomes shared with us by ICRISAT and IRRI. We organised, funded and held a workshop on Multiparental Crops at NIAB, Cambridge in July 2019, with over 50 attendees. 7 attendees were from LMIC and 25% were women. The project financially supported travel for 7 attendees from LMIC. Richard Mott visited ICRISAT for a workshop/progress meeting in October 2019. Attendees were from India, China, Egypt, UK. At the workshop we discussed sequencing further chickpea landraces and planned how the work would be divided.He also visited ICBA, Dubai https://www.biosaline.org for discussions about potential new collaborations around the rice HEAT MAGIC population that we sequenced as part of the project. We started collaborating in December 2019 with the Max Planck Institute of Plant Molecular Physiology who are also working with IRRI on the rice HEAT MAGIC. The MPIMP have shared phenotype data with us for analysis. |
| Collaborator Contribution | IRRI to sent us DNA from 800 samples the rice HEAT MAGIC population, and ICRISAT sent us DNA from 1920 chickpea landraces, to the Earlham Institute for sequencing. Funding was from this GCRF grant. These samples have now been sequenced as planned using low-coverage sequencing and the data have been shared with IRRI (rice) or ICRISAT (chickpea). IRRI have shared phenotype data from the HEAT MAGIC data and we have analysed these data with the genotypes we obtained from sequencing. In addition invited two researchers from IRRI to visit the UK in 2020 to attend a course on quantitative genetics and to discuss the collaboration. Unfortunately the coronavirus epidemic has prevented these visits and we now plan for them to take place at a later time. IRRI have also shared sequenced data from another rice MAGIC population with us for analysis. ICRISAT have shared phenotypes and sequence data from 1200 chickpea MAGIC lines with us, which we have imputed and analysed. |
| Impact | DNA sequence data have been generated and shared, and analyses performed as agreed. One paper has been published so far (Plant Biotechnol J. 2020 Nov 21. doi: 10.1111/pbi.13516. PMID: 33220119) Our contributions to these collaborations have been financial (paying for and organising the sequencing of rice and chickpea crop genomes) and analytical imputation of sequence variants, genome-wide assocation analysis of phenotypes collected by our collaborators. |
| Start Year | 2017 |
| Description | Collaboration with IRRI and ICRISAT |
| Organisation | International Rice Research Institute |
| Country | Philippines |
| Sector | Charity/Non Profit |
| PI Contribution | We have set up formal collaborations with the International Rice Research Institute (IRRI), Philippines, and with the International Center for Crop Research in the Semi-Arid Tropics (Hyderabad, India) as part of the original. Formal collaboration agreements between UCL and IRRI and ICRISAT were signed in summer 2019. Both India and Philippines are described as LMIC in the 2020 DAC list. Richard Mott (PI of project) visited IRRI and ICRISAT in September 2017 during which time he gave seminars and held discussions and planning meetings with IRRI staff including Hei Leung, the IRRI PI, and ICRISAT staff including Rajeev Varshney, the ICRISAT PI. We have sequenced and analysed 1920 chickpea landrace genomes and 900 rice HEAT MAGIC genomes as described in the grant proposal. We have analysed several other datasets of chickpea and rice genomes shared with us by ICRISAT and IRRI. We organised, funded and held a workshop on Multiparental Crops at NIAB, Cambridge in July 2019, with over 50 attendees. 7 attendees were from LMIC and 25% were women. The project financially supported travel for 7 attendees from LMIC. Richard Mott visited ICRISAT for a workshop/progress meeting in October 2019. Attendees were from India, China, Egypt, UK. At the workshop we discussed sequencing further chickpea landraces and planned how the work would be divided.He also visited ICBA, Dubai https://www.biosaline.org for discussions about potential new collaborations around the rice HEAT MAGIC population that we sequenced as part of the project. We started collaborating in December 2019 with the Max Planck Institute of Plant Molecular Physiology who are also working with IRRI on the rice HEAT MAGIC. The MPIMP have shared phenotype data with us for analysis. |
| Collaborator Contribution | IRRI to sent us DNA from 800 samples the rice HEAT MAGIC population, and ICRISAT sent us DNA from 1920 chickpea landraces, to the Earlham Institute for sequencing. Funding was from this GCRF grant. These samples have now been sequenced as planned using low-coverage sequencing and the data have been shared with IRRI (rice) or ICRISAT (chickpea). IRRI have shared phenotype data from the HEAT MAGIC data and we have analysed these data with the genotypes we obtained from sequencing. In addition invited two researchers from IRRI to visit the UK in 2020 to attend a course on quantitative genetics and to discuss the collaboration. Unfortunately the coronavirus epidemic has prevented these visits and we now plan for them to take place at a later time. IRRI have also shared sequenced data from another rice MAGIC population with us for analysis. ICRISAT have shared phenotypes and sequence data from 1200 chickpea MAGIC lines with us, which we have imputed and analysed. |
| Impact | DNA sequence data have been generated and shared, and analyses performed as agreed. One paper has been published so far (Plant Biotechnol J. 2020 Nov 21. doi: 10.1111/pbi.13516. PMID: 33220119) Our contributions to these collaborations have been financial (paying for and organising the sequencing of rice and chickpea crop genomes) and analytical imputation of sequence variants, genome-wide assocation analysis of phenotypes collected by our collaborators. |
| Start Year | 2017 |
| Description | Collaboration with IRRI and ICRISAT |
| Organisation | Max Planck Society |
| Department | Max Planck Institute of Molecular Plant Physiology |
| Country | Germany |
| Sector | Charity/Non Profit |
| PI Contribution | We have set up formal collaborations with the International Rice Research Institute (IRRI), Philippines, and with the International Center for Crop Research in the Semi-Arid Tropics (Hyderabad, India) as part of the original. Formal collaboration agreements between UCL and IRRI and ICRISAT were signed in summer 2019. Both India and Philippines are described as LMIC in the 2020 DAC list. Richard Mott (PI of project) visited IRRI and ICRISAT in September 2017 during which time he gave seminars and held discussions and planning meetings with IRRI staff including Hei Leung, the IRRI PI, and ICRISAT staff including Rajeev Varshney, the ICRISAT PI. We have sequenced and analysed 1920 chickpea landrace genomes and 900 rice HEAT MAGIC genomes as described in the grant proposal. We have analysed several other datasets of chickpea and rice genomes shared with us by ICRISAT and IRRI. We organised, funded and held a workshop on Multiparental Crops at NIAB, Cambridge in July 2019, with over 50 attendees. 7 attendees were from LMIC and 25% were women. The project financially supported travel for 7 attendees from LMIC. Richard Mott visited ICRISAT for a workshop/progress meeting in October 2019. Attendees were from India, China, Egypt, UK. At the workshop we discussed sequencing further chickpea landraces and planned how the work would be divided.He also visited ICBA, Dubai https://www.biosaline.org for discussions about potential new collaborations around the rice HEAT MAGIC population that we sequenced as part of the project. We started collaborating in December 2019 with the Max Planck Institute of Plant Molecular Physiology who are also working with IRRI on the rice HEAT MAGIC. The MPIMP have shared phenotype data with us for analysis. |
| Collaborator Contribution | IRRI to sent us DNA from 800 samples the rice HEAT MAGIC population, and ICRISAT sent us DNA from 1920 chickpea landraces, to the Earlham Institute for sequencing. Funding was from this GCRF grant. These samples have now been sequenced as planned using low-coverage sequencing and the data have been shared with IRRI (rice) or ICRISAT (chickpea). IRRI have shared phenotype data from the HEAT MAGIC data and we have analysed these data with the genotypes we obtained from sequencing. In addition invited two researchers from IRRI to visit the UK in 2020 to attend a course on quantitative genetics and to discuss the collaboration. Unfortunately the coronavirus epidemic has prevented these visits and we now plan for them to take place at a later time. IRRI have also shared sequenced data from another rice MAGIC population with us for analysis. ICRISAT have shared phenotypes and sequence data from 1200 chickpea MAGIC lines with us, which we have imputed and analysed. |
| Impact | DNA sequence data have been generated and shared, and analyses performed as agreed. One paper has been published so far (Plant Biotechnol J. 2020 Nov 21. doi: 10.1111/pbi.13516. PMID: 33220119) Our contributions to these collaborations have been financial (paying for and organising the sequencing of rice and chickpea crop genomes) and analytical imputation of sequence variants, genome-wide assocation analysis of phenotypes collected by our collaborators. |
| Start Year | 2017 |
| Description | Online magazine article on ancient wheat genetics for "The Conversation" website |
| Form Of Engagement Activity | A magazine, newsletter or online publication |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | Mike Scott, a PDRA funded by the BBSRC grants BB/P024726/1, BB/M011585/1 wrote a online magazine-style article entitled "What 3,000-year-old Egyptian wheat tells us about the genetics of our daily bread" for the website "The Conversation". This described in layperson's terms the findings of his Nature Plants publication https://doi.org/10.1038/s41477-019-0534-5 on the genome of an ancient wheat. |
| Year(s) Of Engagement Activity | 2019 |
| URL | https://theconversation.com/what-3-000-year-old-egyptian-wheat-tells-us-about-the-genetics-of-our-da... |
| Description | Oral and poster presentations at "Plant genomes in a Changing World" conference at the Welcome Genome Campus, Cambridge, October 2019 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Funmi Ladejobi, a PDRA employed on the BBSRC grant BB/P024726/1 gave a talk and presented a poster on the HEAT MAGIC rice population at the meeting "Plant genomes in a Changing World" in Cambridge 2019, https://coursesandconferences.wellcomegenomecampus.org/our-events/plant-genomes-2019/?utm_source=email_personal&utm_medium=banner&utm_campaign=PlantGenomes19. Her talk and poster describe analysis of the genomes of a population of rice bred by the International Rice Research Institute, Philippine |
| Year(s) Of Engagement Activity | 2019 |
| URL | https://figshare.com/s/9f6e8135dded67e7e131 |
| Description | Poster Presentation at Monogram 2019 Meeting, Nottingham UK. (Won best poster prize) |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | The Monogram meetings (http://www.monogram.ac.uk/MgNW2019.php) are the main annual meetings for the UK cereal research community, that also attract considerable international and industrial participation. Mike Scott, a PDRA funded from BBSRC grants BB/P024726/1 and BB/M011585/1 presented our poster "Genetic resources for the 16-founder NIAB MAGIC diverse wheat population" for which he won best poster prize. |
| Year(s) Of Engagement Activity | 2016,2017,2018,2019 |
| Description | Poster Presentation at the Plant and Animal Genome XXVIII conference (PAGC 2020), San Diego USA, January 2020 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Mike |Scott, a PDRA employed on the grants BB/M011585/1 and BB/P024726/1 gave a poster presentation "Imputation and QTL Mapping in Multiparental Crop Populations from Low Coverage Sequence Data" at the PAGC 2020 Meeting in San Diego. This is one of the major international meetings on plant and animal genomics. |
| Year(s) Of Engagement Activity | 2020 |
| Description | Presentation at UK Archaeological Society meeting, Manchester April 2019 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Richard Mott gave a presentation at the UKAS 2019 meeting on ancient wheat genomes. the talk was scheduled to be presented by Michael Scott who was unwell. This work later was published in Nature Plants https://doi.org/10.1038/s41477-019-0534-5 |
| Year(s) Of Engagement Activity | 2019 |
| URL | https://ukas2019.com |
| Description | Talk at "Plant Quantitative Genetics: from Theory into Practice", Birmingham 2019 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Funmi Ladejobi, a PDRA employed on the BBSRC grant BB/P024726/1, gave a talk at a meeting organised by the Genetics Society in Birmingham 2019, https://genetics.org.uk/events/plant-quantitative-genetics-from-theory-into-practice/. Her talk described the genomes of the rice HEAT MAGIC population that we have sequence as part of a collaboration with the International Rice Research Institute, Philippines. |
| Year(s) Of Engagement Activity | 2019 |
| URL | https://figshare.com/s/be252bcee91b8dfabc9b |
| Description | Webinar for UK Plant Science (Garnet): Funmi Ladejobi and Mike Scott summarise the potential for using MAGIC populations in Plant Breeding |
| Form Of Engagement Activity | Engagement focused website, blog or social media channel |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Funmi Ladejobi and Mike Scott gave a webinar to summarise the potential for using MAGIC populations in Plant Breeding |
| Year(s) Of Engagement Activity | 2020 |
| URL | https://www.youtube.com/watch?v=CNhoJ-tuao0 |