Seven of the hottest topics at PAG 2018

Posted on Tue, May 08, 2018 @ 08:00 AM

RSVP now!Visiting PAG is exhilarating, energising and somewhat overwhelming. With over 3000 leading plant and animal genetics researchers, 150 workshops and 1100 posters it can be hard to see the forest for the trees.

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With that in mind and as we gear up for our time at PAG Asia, I’ve picked out a few topics that caught my eye at this year's past U.S. conference and have highlighted the topics below:

 

  1. CRISPR technology optimisation

CRISPR methodology has firmly moved into the verification stage of development. The issues ‘off target integration’ have been addressed, but still exist. Topics for discussion centre on the regulation and categorisation with respect to GMO status of the technology. Strategies in removal of transfer DNA used via agrobacterium – mediated transformation have been successful in producing transgene free mutant lines.

 

  1. Expression genotyping

Elucidation and association of phenotypes related to genotypes can be a long term process. Fast track expression genotyping was shown by pioneer Patrick Schnable on the RNA- seq data for identifying trait specific SNP, which could then be deployed for large scale MAS programs. The development of eQTL’s and eRD-GWAS will be a useful tool in the breeding toolbox.

 

  1. Pan – genomes

A single reference genome that encompasses available genetic diversity for any given species is now thought to be an impossibility. The reductions in costs of sequencing and specifically whole genome sequencing combined with rapid genome assembly pipelines have made possible the development of Pan-genomes. Pan-genomes will allow structural variation in defined germplasms to be assessed more rapidly.  Characterization of haplotypes for imputation could then in turn help reducing costs associated with genomic selection.

 

  1. Machine learning sequencing (Haplotype-Resolved Genomes).

The future is machine learning. Automated gene function annotation could influence pharmacogenomics to soil pathogen analysis. Data analysis through  machine learning would enable interpretation of large datasets and could be the key for simplification of bioinformatics, making the application of big complex data relevant to any agricultural scenario.

 

  1. Bioinformatics bottle neck; Big Data: Manage your data before your data kills you

Generation of ‘big data’ resulting from cost effective sequencing has led to production of a plethora of data, that is not being used for the advancement of breeding programs and development of much needed novel products from the Agbio sector. Traditional breeders require simplification of data analysis on platforms that provide user friendly interfaces that are accessible to non bioinformaticians.

Ensuring the standardisation of ontology inputs into databases was a central theme to a number of workshops. Planning for future accessibility and the ability to cross reference databases was highlighted by James Reecy and Zhiliang Hu.

 

  1. Nitrogen usage efficiency (NUE) to feed into protein cycle and provide efficient incorporation.

Deficits in food production in the next 30 years have been highlighted extensively, but the deficit in protein production through sustainable agricultural practises, is yet to be addressed. The development of specialised food production systems are needed to increase N2 sources was highlighted in Ed Bucklers amazing plenary talk.

Another outcome from improving NUE is the reduction of the application of fertilizers which has surpassed 200 million tonnes in 2018 (FAO). Contamination of oceans and impact on the environment are being addressed by application of crop rotation, intercropping with N2 fixation species and precision application through drone technology.

 

  1. Connecting Crop Phenotype and Genotype Data

Building connections between phenotype and genotype data needs to combine large scale ‘omics data’ for application in breeding programs. It could combine the development of pan-genomes machine learning and high resolution screens through the generation of ‘big data’. This connection is essential for the challenges faced in global agricultural sustainability. Pipelines such as the Seeds of Discovery initiative (SeeD) provide an accessible data management and decision making portal that can be applied globally.  

 

There's no doubt these will continue to be the topics dominating conversations this year at PAG Asia in Seoul, Korea. To discuss these and other exciting topics stop by our booth, #9, and make sure to attend our workshop, "Overcoming AgBio challenges, from SNP discovery to routine screening", Wednesday, May 30 from 2:00-3:45 PM, in Grand Ballroom 3. Hope to see you there!

Topics: Genomics, AgBio, Genotyping, CRISPR

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