8.28.24

Guppies on the move

Guppies in the lab. Photo Credit: Eva Fischer.

The activities are as follows:

Animal parents often choose where to have their offspring in the place that will give them the best chance at success. They look for places that have plentiful food, low risk of predation, and good climate.

Even though parents pick out these spots, individuals often move away from their birthplace at some point in their lives. Why do animals move away? There are risks that come with moving from one place to another. It can be dangerous to go through unknown places – potentially stumbling into predators or being exposed to diseases. But there can also be benefits to moving, such as discovering a better spot to live as an adult, finding mates, and spreading out to reduce competition.

As someone who loves to travel and has lived in four different countries, Isabela can relate! Isabela likes to see new places, try new foods, and learn new languages. But there can be drawbacks, and occasionally she finds it hard to be in a completely new place. Sometimes people don’t understand her accent, or she can’t understand them. She also misses her family when she is away. Knowing that traveling and moving can have such highs and lows for herself, Isabela wanted to know more about what motivates animals to seek out new places.

To follow her curiosity, Isabela found a graduate advisor who was also interested in animal movement. She joined Sarah’s lab because she had already collected data on the movement of small tropical fish called guppies. Sarah is part of a large collaborative project, where researchers from all over the world come together in Trinidad to study these fish populations.

When Sarah first started collecting data in this system, she wanted to track how far guppies move from one place to the next. She used established protocols from previous work in this system to set up a study. With the help of a team, she captured every fish in two similar streams for replication. Every fish that was caught was marked with a small tattoo so the research team could recognize it if it was found again in the future. She did this same procedure every month for 14 months. Each time she sampled the fish, she recorded the individuals that she found and where they were found.

Isabela used this dataset to ask whether guppies benefit from moving from one place to another. In this study, she focused on one type of benefit: having a higher number of offspring. It is through reproduction that animals are able to pass on their genes, so the more offspring an individual fish has, the more successful it is.

First, Isabela used the existing dataset to find out how far each fish moved: if Fish 1 was captured in Portion A of a stream in February and then in Portion B of the same stream in March, Isabela knew it had to move from A to B. She could use the timepoints to estimate how far each individual had traveled that month.

Second, Isabela used genetics to find out how many offspring each fish had. She looked at genetic markers to determine familial relationships between individuals in each stream. For example, two fish that shared 50% of their genes were probably a parent and an offspring. In this case, the older individual would be marked as the parent. Isabela used the genetic information to build a pedigree, or a chart that documents each generation of a population. That way she could track how many offspring each parent had produced.

She used these data to answer her question on whether there are benefits to traveling more. Isabela also wanted to compare whether the potential benefits of dispersal differed across the sexes. Males have to compete for females in order to mate. Isabela wanted to know if males that moved more were able to mate with more females and have more offspring.

Featured scientists: Isabela Borges (she/her) and Sarah Fitzpatrick (she/her) from the Kellogg Biological Station at Michigan State University.

Flesch–Kincaid Reading Grade Level = 8.3

Additional teacher resources related to this Data Nugget include:

If you or your students are interested in accessing more of the data behind this Data Nugget, you can download the full dataset from Isabella’s research and have students create graphs in Excel, Google Sheets, or using other data visualization software.

If students would like to learn more about Isabela, check out this Exploring with Scientists video from her time at the Kellogg Biological Station.

For more on this system and the research Sarah did in this study system, check out this unit and video on Galactic Polymath:

8.2.24

A plant breeder’s quest to improve perennial grain

Hannah takes notes on the date of flowering in a Kernza® field in Southwest Minnesota.

The activities are as follows:

Kernza® is a new grain crop that is similar to wheat. It can be ground into flour and used in bread, cookies, crackers and more! Unlike wheat, the rest of the plant can be eaten by livestock such as cattle. Another difference is that Kernza® is a perennial, meaning it grows in the ground for multiple years, whereas annual wheat only grows for one year. However, the challenge is that annual wheat makes more grain and is easier to harvest and sell. This means farmers currently prefer growing annual wheat over Kernza®.

One way to address this mismatch between annual and perennial crops is through selective breeding. This is when humans select individual plants with traits that are desirable for a specific reason. This group of individuals are strategically bred together. The breeder’s goal is to shift the traits over generations. Scientists have only been working on breeding Kernza® for the past few decades; in comparison, humans started selecting annual wheat traits over 10,000 years ago! That is a lot of time to get the traits we are looking for.

Kernza® breeders are working on improving the same traits that have already been improved in annual wheat, including larger seed size. Kernza® scientists follow two main steps to breed plants 1) they select the best individuals from the population and 2) they intercross those individuals to create the next generation, or breeding cycle. With each breeding cycle, plant breeders see a slight improvement in the traits they selected.

Breeders can select plants based on phenotypes, genotypes, or both. Historically, plant breeders have selected based on desired phenotypes, or visible traits, only. Modern plant breeding can take advantage of the fact that we can now look at genotypes, or the genetic makeup, of individual plants quickly and at low costs. Scientists can use this information to make quicker breeding improvements, so we don’t have to wait another 10,000 years for high-yielding Kernza®!

A scientist pipettes DNA samples into an agarose gel to separate samples based on genotype using gel electrophoresis.

Hannah is a scientist currently working on Kernza®. Hannah’s passion for plant breeding was ignited during her high school years. She discovered the captivating world of genetics in her AP Biology class. It was then that she first realized the potential for breeding crop plants to make them more productive and viable for human consumption.

Hannah decided to join other scientists who work on Kernza® at the University of Minnesota. Here, scientists have completed four breeding cycles and are about to start the fifth. Hannah wanted to see whether different genetic makeups (genotypes) lead to differences in seed size (phenotypes). Her goal was to look at each plants’ phenotype and genotype for seed size.

To genotype a plant, scientists collect a small piece of leaf tissue, extract the DNA, and send the DNA to a lab for sequencing. This process tells scientists the genetic makeup that ultimately leads to the traits that we see. Specifically, sequencing data identifies nucleotides, or genetic building blocks of each plant’s DNA. Plants have thousands of genes, which are made up of the DNA nucleotides A, T, C, and G.

Sequencing data can be recorded in several ways. One common way is as SNP data, or Single Nucleotide Polymorphism data. You can think of SNP data as the recipe for proteins. In a SNP dataset, each SNP represents a difference in a nucleotide. Similar to using a different ingredient in a recipe, different nucleotides can result in a different phenotype.

By looking at SNP data, plant breeders can identify differences in genotypes that lead to certain phenotypes. Hannah started by evaluating 1,000 Kernza® plants from the first four breeding cycles. Data on phenotypes had already been recorded for these plants. Hannah then collected SNP data to determine their genotypes as well. She was looking for a pattern between genotypes and phenotypes. If she sees that different genotypes have different phenotypes, scientists can then rely on genotypes to select individuals to breed in future breeding cycles.

Featured scientist: Hannah Stoll (she/her) from the University of Minnesota

Flesch–Kincaid Reading Grade Level = 8.9

Additional teacher resources related to this Data Nugget include: