London Calling Online Agenda

Fera Science Limited is the national reference laboratory for plant health in England and Wales, providing scientific advice and services to Defra, other government bodies, and commercial customers. It is responsible for providing diagnostic services to the Plant Health and Seed Inspectorate who work at UK ports and airports protecting UK agriculture and the natural environment from the introduction of invasive plant pests and diseases. For the last 10 years these services have included an increasing use of high throughput sequencing for environmental monitoring and disease diagnosis. Due to the high cost of the existing platforms, samples need to be batched (24 to over 100 samples per batch) to make the process viable leading to regular runs of particular samples types and waits of greater than a month for all but the highest priority samples. The cost and scalability of the MinION with the Flongle adapter opens up the potential to run single or small batches of samples as soon as they are requested. This concept is being tested in a number of case study trials. Much of our work involves correctly identifying insects from larvae intercepted on imported fruit. This is carried out using morphological examination and confirmed by DNA barcoding, with the sequencing being carried out by offsite commercial suppliers using capillary sequencers. In a trial with 8 samples, within an hour the Flongle had produced enough sequence to correctly and accurately identify the insect species present. A number of problematic samples with the target infected with a second insect (parasitoid or mite) were also tested. This approach has been extended and used to assess the invertebrate populations of sticky traps looking for invasive insect pests using metabarcoding. The Flongle has also been successfully used to identify novel plant viruses in import samples (direct RNA sequencing), identify the species of a disease-causing bacteria (whole genome sequencing) and confirm infections with phytoplasma, which are obligate bacterial parasites of plants (amplicon sequencing). Finally, using the Flongle we have also been able to show that we can determine the diet of spittle bugs (metabarcoding), possible vectors of Xyella fastidiosa, a bacterial pest currently causing serious damage across Europe. Knowledge of the vectors and their hosts will be important if this disease comes to the UK. The MinION with the option of the Flongle is showing great promise delivering rapid, scalable, useful data and will soon become a standard tool defending the UK from invasive plant pests and diseases.

Variation in transcript structure via RNA splicing and differences in the 5’ and 3’ untranslated regions is a key feature of gene regulation. Disruption of transcript structure is one of the primary functional changes behind a large proportion of disease variants, both common and rare. These discoveries have so far been partly based on analysis of RNA-sequencing data of 50-100 bp reads, which cannot directly measure the real biological unit of the transcriptome – transcripts. The advent of long read technologies for RNA-seq has the potential to transform transcriptome analysis, since it can directly measure full-length isoforms. In this study, we created a large long-read transcriptome sequencing data set across diverse samples of the GTEx project using Oxford Nanopore technology and developed a new computational approach for investigating the effects of genetic variants on the transcriptome. We generated cDNA sequencing data using the PCR-based protocol from 88 samples across 15 different tissues, for which we also had access to Illumina RNA-seq data and 73 had whole genome sequencing data. We identified novel transcripts and showed how transcript quantifications vary across tissues. We developed pipelines to perform allele specific expression (ASE) and allele specific transcript structure (ASTS) analyses genome wide. In ASTS analysis we test for differences in transcripts originating from each haplotype of a sample by splitting the reads according to the haplotype of a heterozygous variant and determining to which transcript that read had been assigned to – an analysis that is not informative with short-read Illumina data. In order to do that we first devised a new mapping strategy to mediate the high reference bias observed in Oxford Nanopore data. Across all the samples, 14,212 genes showed allelic expression in at least one sample, of which 1,230 fulfilled the requirements for ASTS analysis. We found 187 genes that had significant allelic differences in their transcript distributions in at least one sample, only half of which also showed ASE. ASTS events capture splicing quantitative trait loci that have been mapped as part of the GTEx consortium, verifying that it reflects true genetic effects on splicing. We also discovered rare splice-disrupting variants using ASTS data. Finally, we knocked-down PTBP1, an RNA binding protein that mediates splicing, using siRNA in fibroblast cell lines generated from five donors. We demonstrate the successful ablation of ASTS in some cases, indicating that genetic effects on splicing can be modified by the cellular state. Altogether, our results provide evidence of the widespread nature of genetically driven allelic differences in transcript structure, and the power of long-read data and careful computational approaches to study it in human population samples.

The African Orphan Crops Consortium (AOCC) is a global partnership promoting strategic, genome-enabled improvement of under-researched crops for biodiversity-based nutritious food solutions in Africa. We present current status, opportunities and examples successes of AOCC. Orphan crops like Lablab (Lablab purpureus; ~452 Mbp), African Yam bean (Sphenostylis stenocarpa; ~800 Mbp) and Moringa (Moringa oleifera; ~315 Mbp), are often of high nutritive value and are climate resilient. The Oxford Nanopore MinION was used to generate long reads of all three crops, to compliment and generate contiguous draft genome assemblies. Work is under way to improve these assemblies to chromosome-scale using Hi-C mapping.