Peter Piper picked a peck of Pickled Peppers- An introduction to High Throughput Phenotyping.

Learning Objectives

  1. Describe high-throughput phenotyping
  2. List the 4 parts of high-throughput phenotyping for crops
  3. Evaluate the importance of high-throughput phenotyping in medicine

Graphical Abstract

Legend.

High-throughput phenotyping uses sensors to gather vast amounts of data on the physical appearance of plants (for crop breeding) and cells (for immunophenotyping). This data is used to fill the gaps in knowledge left by high-throughput genotyping. As well studied as the genome is, environmental factors play a key role in gene expression and can affect an organism’s phenotype, resulting in a need to better understand the relationship between genes and phenotype.

Summary

High-throughput phenotyping (HTP) uses a variety of methods to evaluate the physical properties of plants, particularly crops, to understand their growth capabilities, photosynthetic productivity, and response to environmental changes.1 This information helps farmers and crop breeders better select plants based on traits such as disease resistance, nutrition content, and overall yield.2 Even though the genetics of these plants are well understood and have been analyzed through HT genotyping, there is a great need to match this knowledge with the phenotypic knowledge of the same plants.1 The reason for this is that while plant strains may carry the same or similar genetic markers, the expression of these genes can vary and result in different physical appearances. Knowing the combination of genetic and phenotypic data about their crops allows for a better selection of desirable and more productive crops.

As the world’s population continues to grow and changes to the climate affect both growing regions and growing seasons, some fear the ability to produce enough staple crops to feed everyone.3 Selecting plants at early stages, before they reach maturity, allows breeders to optimize their crops.2 This would also reduce the need for additives such as fertilizers and pesticides.3 Decreased use of pesticides would be beneficial to the honey bee population and other pollinators that are vital to grain and fruit production. 

Current low-throughput methods of phenotyping include manually evaluating the size, appearance, and taste of crops. HTP methods need to be as accurate as manual methods while being more efficient. This is done by combining four components: a sensor, platform, analysis, and data (SPAD).3 The sensor could be a camera (standard visible light, near-infrared, or fluorescence), IR thermometer, spectral sensor, or positron sensor.2,3 It is used to measure plant height, growth rate, leaf area, canopy temperature, among other factors. Sensors are used with one of three platforms: ground, aerial, or satellite.3 Ground platforms were most commonly used but there has been a recent shift to aerial platforms, particularly using drones. The increased mobility of drones allows them to cover more of the crops over less time and can also carry more than one sensor at a time. Analysis of this data includes image analysis, calibration, and machine learning.2 Storing the data collected by the sensors requires cloud storage such that analytics can be performed and the user can understand the output data.3 Improvements to each part of SPAD would increase the accuracy of HTP and could also decrease the cost, making it more accessible to farmers and crop breeders around the world. 

Another application of HTP is to analyze immune variation within a species. Immunophenotypic variation is not always clearly tied to genetic variation, resulting in a need to better understand their relationship.4 Abeler-Dörner et al used a 3i (infection and immunity immunophenotyping) platform to study gene-knockout mice to determine which genes may be related to the organism’s immune response. They studied 530 genes and found that some immunophenotypes are sex-linked. Only 140 of the total genes examined were found to affect the immune system, though more research is needed to confirm these genes and their exact effects.4 This deep dive into which genes exhibit a clear immune response serves as a starting point for further research into how these genes affect the immune system. This could be powerful information for drug development and cell therapy methods to target these genes and repair the patient’s phenotype.

While HTP varies greatly from HT genotyping, there are some similarities. Methods of data collection must be optimized for accuracy and efficiency, which entails significant quality assurance and quality controls. The large amount of data gathered from these methods need to be processed and analyzed, often using platforms such as Python or ImageJ for data analysis. Machine learning can also be used to accelerate data analysis, particularly non-image data. HTP can also be used as a way to understand what parts of the genotype are not as well understood as they need to be, and together, can provide a greater understanding of how genes are expressed and altered with different environmental stressors, both for plants and animals.

Audio Recordings

HTD Portfolio Audio Part 1

HTD Portfolio Audio Part 2

HTD Portfolio Audio Part 3

Questions

  1. What is high-throughput phenotyping? 
    1. High-throughput phenotyping analyzes the physical characteristics of organisms to better understand the effects that environmental stressors have on gene expression
  2. Why is HTP important? 
    1. HTP is important for two main reasons; it can be used to produce better crops with higher yield and nutritional value, and it can be used to better understand the body’s immune system to create more functional drugs
  3. List the 4 parts of high-throughput phenotyping for crops
    1. sensor, platform, analysis, and data
  4. Reflect on the importance of high-throughput phenotyping in medicine
    1. HTP provides a better understanding of how phenotypic variation may arise, even with a lack of genetic variation. This allows researchers to investigate what other factors resulted in phenotypic variation; environmental factors such as location, water source, diet, and lifestyle, for example. Some of these factors, such as location and water source, cannot be controlled by the patient and can have significant effects on their health. Understanding what factors affect disease phenotype can help with creating better drugs or even understanding what genes are resulting in these phenotypes and how to target these genes.

References:

Reyazul Rouf Mir, Mathew Reynolds, Francisco Pinto, Mohd Anwar Khan, Mohd Ashraf Bhat, High-throughput phenotyping for crop improvement in the genomics era, Plant Science, Volume 282, 2019, Pages 60-72, ISSN 0168-9452 https://doi.org/10.1016/j.plantsci.2019.01.007.

Jangra, S., Chaudhary, V., Yadav, R. C., & Yadav, N. R.. (2021). High-Throughput Phenotyping: A Platform to Accelerate Crop Improvement. Phenomics, 1(2), 31–53. https://doi.org/10.1007/s43657-020-00007-6

Kim, J. Y.. (2020). Roadmap to High Throughput Phenotyping for Plant Breeding. Journal of Biosystems Engineering, 45(1), 43–55. https://doi.org/10.1007/s42853-020-00043-0

Abeler-Dörner, L., Laing, A.G., Lorenc, A. et al. High-throughput phenotyping reveals expansive genetic and structural underpinnings of immune variation. Nat Immunol 21, 86–100 (2020). https://doi.org/10.1038/s41590-019-0549-0