Genomics Can Be Used in Agriculture to Detect Disease and More

Plant and animal domestication and cultivation have enabled humans to live and spread across the globe, reaching a current population of 8 billion people [1]. This process has been facilitated by sophisticated science and innovative biotechnology, both of which have been accelerating along with the growth of the human population.

With the population forecasted to reach 10 billion people by 2050, a question is ever-present: How can our current agricultural capacity support the additional two billion people? While seemingly dire, agriculture’s engine of innovation continues to churn, focused on a multifaceted and interconnected goal: increasing productivity, with less water and land.

In short, “doing more with less.”

The tactics that put this goal within reach are varied. One of them, precision agriculture, uses digital diagnostic tools to make plant and animal cultivation more efficient for commercial producers [2]. Another type of technology, operating at the molecular level, enable the efficient development and protection of crops, livestock, poultry, and other animals with new and desirable traits for our changing world.

Let’s look at how molecular diagnostics and genomics in agriculture expand the capabilities of our planet to support life.

Improving the productivity, nutrition, sustainability, and fitness of plants and animals help work towards the goal of “doing more with less” in agriculture. Traditionally, crop and animal improvement for any number of traits was done through selective breeding based on the identification of desirable phenotypes. But the rise of rapid and cost-effective NGS and genotyping tools has enabled the discovery and analysis of genetic markers, such as single nucleotide polymorphisms (SNPs), associated with desirable phenotypes.

This has led to the emergence of a new strategy in plant and animal selection, marker-assisted breeding, which reduces selection time (i.e., time to observe expression of a particular phenotype vs. detection of a specific genotype) and increases selection accuracy (i.e., phenotypes can be masked by environmental variation), ultimately saving plant and animal breeders time and money in their pursuit of desirable traits.

Marker-assisted breeding wouldn’t be possible without the emergence of low-cost, rapid NGS. Techniques such as whole genome, exome, or transcriptome sequencing are used for the discovery of genetic markers associated with desirable traits, at genome-scale [3]. This tactic, called genomic selection, is only recently becoming a foundational part of the plant and animal improvement workflow but has proven particularly effective at deconvoluting complex traits, such as behavior, yield, and drought tolerance, that can be controlled by hundreds of distinct genetic markers. As a result, several groups have suggested that genomic selection can improve genetic gain (i.e., improved performance) multiple times more than phenotypic selection [4].

Another more focused approach—marker-assisted selection—differs from genomic selection in that it tracks hundreds to thousands, rather than millions, of genomic markers in a cost-effective manner appropriate for the analysis of large populations of plants or animals. The technique used, GBS (like NGS), can be used for the discovery of complex traits but can also be used to inform breeding decisions, based on established genetic marker-phenotype relationships [5]. In parentage or QC applications, where larger sample sizes may need to be analyzed for tens to hundreds of validated genetic markers, several qPCR-based methods can be used for genotyping. These assays are easy to customize, and many predesigned collections of common markers for well-studied crops and animals have already been developed and validated.

Across the entire genomics continuum, from NGS to qPCR methods, DNA extraction reagents and automated instruments have been developed, enabling high-throughput sample processing, analysis, and widespread use across agricultural applications.

Another way to improve and maintain crop and animal productivity is through the effective detection and control of pathogens. On a global scale, the loss in five of the major crops—maize, rice, wheat, potatoes, and soybeans—due to pathogens has been estimated to be 17 to 30% annually [6]. Animal pathogens account for similar losses: Spread of the highly pathogenic avian influenza A (known as H5N1), accounted for 8% and 12% loss of turkey meat and table-egg laying chickens, respectively [7]. Similar mortalities have been reported for outbreaks of the Bluetongue virus, which causes severe infection in ruminants and sheep [8].

These losses due to disease outbreaks have been countered through the implementation of molecular diagnostics in agriculture, enabling the rapid and accurate detection of pathogens.

A common technique used for disease detection is ELISA, which uses a variety of experimental formats to detect pathogen-specific antigens or host antibodies. Many commercially available ELISA kits for highly contagious animal pathogens are available, including foot and mouth disease which infects cloven-hoofed animals, classical swine fever virus (CSFV) which presents a major threat to pig production, bovine tuberculosis, and for monitoring a wide range of pathogens associated with food safety such as Toxoplasma gondii, Trichinella spp., and others. Kits are also available for a wide range of plant pathogens, are exceptionally sensitive and specific, and can accommodate various sample types. To further simplify, improve sensitivity and adapt to new pathogens, scientists continue to develop modified ELISA protocols [9].

Another critical method for disease detection, considered the "gold standard" for its high sensitivity and specificity, is qPCR. This technique can be implemented in a variety of ways to detect minute amounts of pathogen-specific DNA through amplification using DNA polymerase. Variations, such as RT-PCR, can be used to detect pathogen RNA, which is reverse transcribed from RNA into DNA, before enzymatic amplification. Multiplexed PCR can also be done to detect multiple target pathogens at once. In addition, different fluorescent probes, such as TaqMan probes, molecular beacons, and more, can help ensure sensitive and specific pathogen detection. Due to the ease of custom DNA oligonucleotide design, master mix reagents, and internal positive controls, it is now easy to develop PCR diagnostic tests tailored to a labs’ capabilities or new, emerging pathogens.

NGS has also joined ELISA and qPCR methodologies as an essential technique for disease detection. Sequencing workflows can be used to track pathogen evolution and sequence unknown pathogens. NGS has been successfully implemented to sequence complete genomes of avian influenza virus, CSFV, and Bluetongue viruses [10–13].

While NGS and genomics have played a pivotal role in crop and animal improvement, health, and welfare, other “omics” technologies, including proteomics and metabolomics, are providing new insights into host-pathogen interactions, zoonosis, breed comparison, and post-harvest analysis, including infectious disease and quality [14,15]. Integration of datasets through sophisticated bioinformatics and further incorporation of innovative technologies is sure to help maximize the output of the agriculture industry, ultimately moving towards the goal of securing a sustainable and abundant food supply for future generations.

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1. Current World Population. World Population Clock. WorldOMeter. Accessed March 9, 2022. 
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