Bioinformatics Education Dissemination: Reaching Out, Connecting and Knitting-together

Desiccation Tolerance Problem Space
Curricular Resources


Some suggested starting points for exploring desiccation tolerance are hot linked below:


Exploring the Physiology of Desiccation Tolerance

There are a number of physiological problems faced by desiccating cells. A visual demonstration of the problem can be observed in a common aquarium plant, Elodea. Under a light microscope, students can see the movement of chloroplasts around the edge of the turgid vacuole. When a drop of salt water is added, the vacuole collapses (video of this phenomenon is listed below).

Students may explore the challenges presented by desiccation using the following prompts:

Plasmolysis in Elodea (Video and class exercise)

These materials were developed by Kristin Jenkins, National Evolutionary Synthesis Center, at the 2009 BioQUEST summer workshop.



Phylogenetics and Desiccation Tolerance

Research in desiccation tolerance has potential applications in agriculture. Humans have been changing the characteristics of crop plants continuously since domesticating wild ancestors. Crops have been bred for higher yield, shorter or longer generation time, disease resistance, and other traits humans have found desirable in different environments around the globe. Biotechnology has allowed us to increase the speed and specificity of these modifications. By focusing on key genes and genetic control elements crops with novel features can be generated rapidly. Golden rice is an example of adding a novel and useful trait to a common crop plant.

An important source for candidate genes is evolutionary relatives or ancestors of crop plants. Because gene expression and protein production varies between cell types, bioengineering is more likely to be successful when genes are moved between more closely related species. In addition, wild relatives of crop plants often have adaptations to protect them from disease and environmental pressures. Identifying these hardy relatives provides a pool of candidate genes for further improvement of staple crops. An example of successful identification of related species, and subsequent bioengineering of an important staple crop is recent work in cassava:

Many of our most common crop plants including wheat, millet, rice, corn, and sorghum are members of the Family Poaceae -- the grasses. Desiccation tolerance is found in a few species in the Poaceae such as Sporobulus stapfiansus and Eragostis nindensis (http://www.kew.org/data/grasses-db/www/imp03928.htm). Other species within these genera are drought resistant, but not desiccation tolerant. By studying the biogeography of closely related species, researchers can learn more about the environmental pressures driving the evolution of drought resistance and desiccation tolerance. Information about these plants, combined with data about the molecular and cellular processes of desiccation tolerance, may inform agricultural research in crop plants.

Students can explore the phylogeny of Poaceae or the relationships of the gene families involved in desiccation tolerance.

Poaceae

Use phylogenetic trees from the following sources to explore the phylogeny of the Poaceae:

Gene families involved in desiccation tolerance

The evolution of desiccation tolerance is complicated. When plants invaded the land, desiccation tolerance was probably a common trait. In modern plants, many ferns and mosses have either retained or re-evolved desiccation tolerance. All seed and pollen tissues are desiccation tolerant, so seed plants have also either retained or re-evolved this ability. A few vascular species, scattered throughout the gymnosperms and angiosperms, are desiccation tolerant. Researchers are comparing the genes present in desiccation tolerant and sensitive plants, and the expression patterns of those genes to learn more about their evolutionary relationships and the mechanism of desiccation tolerance.

Data sets are provided to allow students to do a multiple alignment and generate phylogenies based on the alignment using the tools available in Swami. Data is provided for Arabidopsis (sensitive vascular plant), Xerophyta (tolerant vascular plant), and Tortula (resistant moss). Data sets include protein sequences, aligned sequences, gene trees generated from the alignments, and gene expression patterns.

Reading phylogenies can be tricky for a number of reasons. Phylogenies may represent relationships between species or genes. They may include information about time or genetic relationships. As a result, phylogenies can differ based on the data used to develop them. However, although the location of individual branches may shift between phylogenies, the main branches remain stable. This fluctuation reflects the nature of science -- as more data is collected and analyzed, the deeper and more complete our understanding becomes. In this case, details of relationships may be disputed based on analytical approaches or which data sets are used, but with the continued addition of more information the relationships become clearer. More information about reading trees is available at these sites:

These materials were developed by Shaily Menon, Associate Professor of Biology, Grand Valley State University, Gabriella Pinter, Associate Professor of Mathematical Sciences, University of Wisconsin- Milwaukee, and Kristin Jenkins, National Evolutionary Synthesis Center at the 2009 BioQUEST Summer Workshop.



Making Tougher Tef

This case study is a more specific application of the ideas in the previous section on Phylogenetics and Desiccation Tolerance. "Making Tougher Tef" explores the issue of reduced tef crop yield due to climate change. Tef is a primary food crop in Ethiopia, where it is used to make injera, the fermented flatbread that serves as plate and utensil, as well as a fodder crop. Tef is highly nutritious and the fodder is excellent and this crop is beginning to be grown in non-traditional areas. It grows best at higher altitudes with moderately high rainfall. A comprehensive overview of tef is available in this very accessible paper which can be downloaded as a pdf (search for the author) or read online:

Tef belongs to the genus Eragrostis ("love grass"), which is found around the world. Eragrostis are often drought tolerant, and Eragrostis nindensis is actually desiccation tolerant. Genes involved in drought tolerance and desiccation tolerance in other Eragrostis are likely candidates for increasing drought tolerance in tef by genetic engineering. Understanding the phylogenetic relationships between Eragrostis species, and exploring the biogeography of these species, can help identify the best species to explore. Information about the known phylogenetic relationships of Eragrostis species is available in Ingram, A.L. and Doyle, J.J. 2003. The Origin and Evolution of Eragrostis tef (Poaceae) and Related Polyploids: Evidence from Nuclear Waxy and Plastid rps16. American Journal of Botany. 90(1):116-122.

The case study "Making Tougher Tef" is available here. This case study is presented in such a way that it can be tailored to provide learners with different levels of assistance as they think through the case study. If only the background and case-study set-up are desired, the case-study can be truncated at the first set of italicized questions. One or both of the paragraphs subsequent to the first set of italicized questions may be included to provide increasing levels of guidance through the problem presented in the case-study.

Molecular data from genes upregulated under drought stress in a desiccation tolerant species, Sporobulus staphianus, are available in the data section. (Molecular data for this closely related desiccation tolerant species, Sporobulus staphianus, are provided in the data section for analysis in this activity, since there are little molecular data for E. nindensis.) Use this data to search for potentially homologous genes in Eragrostis species. A guide for using the BLAST algorithm to recover these sequences from the NCBI database is available here.

Use data and tools from the Global Biodiversity Information Facility (GBIF in the Tools Section) to explore known distributions and generate niche models to study potential distribution of tef and drought tolerant Eragrostis species. A guide to using GBIF is available here.

These materials were developed by Kirsten Fisher, Assistant Professor of Biology, California State University, Los Angeles, and Kristin Jenkins, National Evolutionary Synthesis Center.



Spatial Exploration of Biodiversity Data with Arc Explorer

Download ArcExplorer (Geographic Information System - GIS) software and install

Figure 1. ArcExplorer layout of world countries and occurrence points for Sporobolus stapfianus, a desiccation tolerant species. Figure 2. ArcExplorer layout of global vegetation types.

Download species occurrence data (Biodiversity databases)

These materials were developed by Shaily Menon, Associate Professor of Biology, Grand Valley State University at the 2009 BioQUEST Summer Workshop.



Modeling Spatial Distribution with OpenModeller

On the www.gbif.org Data Portal, search for occurrences of Sporobolus stapfianus, a desiccation tolerant species.

Figure 3. A representation of the niche model generated by openModeller for Sporobolus stapfianus, a desiccation tolerant species. The probability scale indicates dark reds as areas predicted to be high probability areas for species occurrence and dark blues to be low probability areas for species occurrence. Environmental variables used to create this model were Annual mean temperature, Mean diurnal range, Isothermality, Temperature annual range, Annual precipitation, Precipitation of driest month, Precipitation seasonality, and Precipitation of driest quarter.

The example below is of a niche model output from Maxent, which uses maximum entropy approach to species distribution modeling. How does the the Maxent model compare with that generated by openModeller?

Figure 4. A representation of the Maxent model for Sporobolus stapfianus, a desiccation tolerant species. Warmer colors show areas with better predicted conditions. White dots show the presence locations used for training.
The follow settings were used during the run: 5 presence records used for training. 10005 points used to determine the Maxent distribution (background points and presence points). Environmental layers used (all continuous): frs6190_ann h_aspect h_dem h_flowacc h_flowdir h_slope h_topoind pre6190_ann rad6190_ann tmn6190_ann tmp6190_ann tmx6190_ann vap6190_ann wet6190_ann

Analysis of environmental variable contributions to the Maxent model for Sporobolus stapfianus, a desiccation tolerant species.

The following table gives a heuristic estimate of relative contributions of the environmental variables to the Maxent model.

VariablePercent Contribution
frs6190_ann 52.5
h_dem 33
h_slope 5.4
pre6190_ann 3.2
tmx6190_ann 3.1
wet6190_ann 2.6
tmp6190_ann 0.1
h_flowacc 0.1
vap6190_ann 0
tmn6190_ann 0
h_flowdir 0
rad6190_ann 0
h_aspect 0
h_topoind 0

These materials were developed by Shaily Menon, Associate Professor of Biology, Grand Valley State University at the 2009 BioQUEST Summer Workshop.



Introduction to Information Entropy

To download this unit go to: http://bioquest.org/workshops/summer2009/projectfiles/inf_entropy_unit6.pdf

These materials were developed by Gabriella Pinter, Associate Professor of Mathematical Sciences, University of Wisconsin- Milwaukee at the 2009 BioQUEST summer workshop.

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