Understanding Crop Plant Genetics
The MAAM Lab, led by Dr. Mark Allan Alexander Minow in the Department of Agronomy at Iowa State University, tries to improve our understanding of plant genetics so that we can harness that knowledge to fuel crop improvement.
Through years of recurrent artificial selection, humans have modified agricultural plants to better suit their needs. However, historical crop breeding often improved traits without knowing the mechanisms through which natural genetic variation ultimately influences a plant trait. If we can better understand the genetic control of crop traits we can design, induce and test novel genetic changes to further improve crop performance. With the regulatory space softening, this crop engineering strategy can complement traditional breeding well, potentially widening the narrow genetic pool used to produce elite cultivars and enable us to push the genetic boundaries of the bioeconomy.
Although exciting, this crop genetic engineering requires improved understanding of how plant genetics influence crop traits. My lab aims to work with the scientific community to answer fundamental questions surrounding how crop genetics influence traits. We hope to use translational genomics to bridge the separate silos of foundational genetics research and applied crop improvement to help advance real-world cropping systems in a meaningful way. By providing improved crop genetic knowledge we aim to fuel crop engineering, ultimately empowering 21st century agriculture to produce more food, energy and farm profits – both in Iowa, the USA, and globally.
Individual Gene Control of Crop Traits
One major genetic goal is to understand how actions of each individual gene, and how they influence organismal traits. This 'reductionist' approach is helpful, as it allows the isolated study of how one gene interfaces with the genome to control a part of the plant's physiology. My lab combines individual genetic alterations, like natural mutations and CRISPR/Cas9 edits, with functional genomic approaches to disentangle how individual genes influence complex plant traits.
Genetic Control of Corn Flowering
The lab is interested in many traits, including the developmental control of Zea mays (maize, corn) flowering. Flowering is a critical decision for plants as reproductive growth is energetically costly, and often very sensitive to environmental stresses. Moreover, flowering represents a transition away from vegetative growth, which ultimately limits the plant's photosynthetic capacity. As such, cultivar flowering time, or days-to-maturity, is a major yield determinant. Days-to-maturity can be broken down into two genetically determined components: the rate of development and the developmental body plan. The lab focuses on what genes control this developmental body plan, which equates to the number of leaves that a plant produces.
Curiously, there is little trait variation in maize leaf number in commercial temperate corn varieties, with days-to-maturity being controlled by the rate of development. The developmental rate that controls maturity represents complex genetic control of plant growth and metabolism that is tuned to a specific latitude. The complex, or polygenic, nature of developmental rate further complicates cultivar improvement, often limiting breeding crosses to plants within a similar maturity group. Engineered control of maize leaf number is attractive for two reasons:
I) it may hasten movement of alleles between breeding groups
II) it may loosen maturity-based metabolism breeding constraints, enabling the optimization of growth and metabolism for yield potential alone
Although relatively invariant in temperate commercial corn varieties, there are many mutants that can dramatically alter maize leaf number. The lab is especially interested in understanding how Indeterminate1, a transcription factor gene, promotes flowering through the self-sensing 'autonomous' flowering pathway. Although we do not understand how Indeterminate1 works, we know it has a pronounced importance in controlling maize flowering, as mutations in this gene cause a dramatic increase in the number of leaves produced and thus delays flowering. We also know related, or orthologous, genes are found in other grains where they likewise control flowering. This similarity indicates that this poorly characterized pathway is shared, or conserved, in other grasses. Therefore, by understanding how this pathway works in corn, we might also learn something about flowering in other grain crops too.
Altering Gene Expression to Tune Crop Traits
Individual gene expression is controlled by DNA-binding proteins known as transcription factors, which bind nearby DNA and recruit RNA POLYMERASE II to transcribe the gene into mRNA, ultimately starting the actions of that gene. These transcription factors each bind a slightly different DNA sequence, or transcription factor binding motif, which allows different transcription factors to have different gene targets. These transcription factors often serve as cellular 'control switches,' turning on or off a specific plant process. Each individual gene is regulated by many transcription factors binding many local DNA sequences, which finely coordinate gene expression in response to internal and environmental signals. The availability of these transcription factor binding motifs is also dictated by chromatin accessibility, an important epigenetic mark that can be measured through cell-type resolved epigenomics.
DNA alterations, or mutations, within genes themselves often have dramatic effects (see photo to the right), as they can alter the function of that gene across all of its use contexts. In this way, genic changes often have pleiotropic consequences, which means that they affect many different traits all at once, and this pleiotropy is often not beneficial towards crop improvement. In contrast, we aim to edit the DNA sequences of the transcription factor binding motifs linked to an important gene. This will alter just the expression of that gene, effectively changing one context of that gene's function, allowing us to tune its activity to try and improve crop traits. In this way, editing these transcription factor binding sites appears to be an attractive way to improve crop traits.
The good news is that we know many genes that are critical to diverse components of plant growth. However, we do not yet have a good understanding about how the local DNA sequences, and underlying transcription factor binding motifs, exactly control nearby gene expression. Our lab will alter these transcription factor binding sites to learn which are good editing targets to improve plant performance in commercial crop varieties. In particular, we will focus on tuning maize (corn) traits like flowering time, and metabolism. We will pair these transcription factor binding site edits with functional genomics to measure how variants manifest a trait change, and also how the plant's gene network responds to these expression changes. Again, due to relatively high conservation of transcription factor target genes, what we learn will be readily transferred to other grain crop traits, informing future improvement of a variety of crops.
Gene-to-Gene Relationships and Complex Traits
Another classical genetic goal has been to disentangle gene-to-gene regulatory relationships into pathways; scientists want to understand how sequential gene actions form the pathways that ultimately drive organismal function and control complex traits like stress tolerance or seed size. By doing so, we can learn mechanisms behind how plant traits arise and better design genetic edits to mold these processes, and traits, to human needs. As discussed above, transcription factors are a great example of how one gene product affects other genes: the transcription factor directly controls the expression of other genes, placing the transcription factor upstream along a genetic pathway. However, gene-to-gene relationships extend far beyond that explained by transcription factors. Genes can alter hormone levels, cellular protein states and metabolism, all of which will have consequences on the actions of genes downstream. Further complicating the dissection of complex gene regulatory networks (GRNs), gene-to-gene relationships are multifaceted, with the actions of one gene affecting many others in the genome.
Unveiling Gene-to-Gene Relationships Via Repeat Discovery
However, the multifaceted reality of gene-to-gene relationships is a blessing in disguise, as it gives us a pattern to look for in gene expression data. During my postdoctoral work, I pioneered the use of a new approach to study these gene-to-gene relationships: Multiple Discovery Filtering, or MDF for short—a computational approach that exploits the multifaceted nature of gene-to-gene relationships to find gene variation that repeatedly associates with the expression changes of many other genes. In a way, MDF functions similarly to medium density fiberboard, which is strong only because glue holds many weaker wood fibers together; MDF uses repeated discovery of the same gene to 'glue' together many weaker associations to find important regulatory genes with large genomic impacts. The lab will be using MDF to find and better understand the important gene regulators found in agronomically valuable grain crops. Ultimately, better understanding the genetic pathways behind plant traits will highlight regions of the genome that could be altered to improve crop resilience and yield.
One area of particular interest is understanding how hybrid gene-to-gene relationships cause maize hybrid vigor, or heterosis. In commercial field corn, yield improvements have largely coincided with the growth of F1 hybrids, which are produced by the crossing of two divergent inbred lines. These F1 hybrids exhibit so-called heterosis, where they exceed their parents for many agronomic traits, including yield. This F1 heterosis is ultimately driven by gene-to-gene regulation that was not present in either parental state; that is, it is driven by combined actions of different gene variants, alleles, in the F1 plant.
The F1 allelic interactions are thought to either be dominant or overdominant. In dominant cases, it is thought that one allele often rescues a deficiency from the other parent. In overdominant cases, it is thought that the heterozygous combination of alleles somehow performs better than either allele on its own. Using MDF, we can now uncover the alleles that underpin F1 heterosis. We hope to use this new approach to not only discover which genes and alleles contribute to heterosis, but also which alleles do so through dominant or overdominant interactions. These overdominant alleles are of special interest, as we may be able to stack or pyramid them into new varieties to improve heterosis, further improving hybrid field performance.
Single-Cell Genetic Study of Essential Genes
Our ability to understand gene function is predicated upon functional variation of that gene, which often involves natural genetic variants. However, natural variation only encompasses a fraction of the genetic potential within a species, with many gene functions being effectively invariant in natural populations. Beyond that, some genes are too critical to life to accommodate meaningful variation, meaning individuals with these variants die at some point in development. However, the invariant genes are still important, potentially even essential, to crop growth and life in general. This genetic invariance requires new approaches to understand how these invariant genes impact the broader gene-to-gene genetic network.
One approach to understand these naturally invariant genes is to study genetically variable cell populations instead of genetically variable individuals, as cells can tolerate some mutations incapable of producing an entire organism. In fact, plant cells are the best system for this sort of approach because they are very good at sharing; unlike most cells, plant cells exist in a shared cytoplasm, or symplasm, that is connected by pore-structures known as plasmodesmata. These plasmodesmata allow for unparalleled sharing of metabolites between cells with differing genetics. This metabolite sharing allows plant cells to be extra tolerant of genetic variation near essential-to-life genes. Importantly, this means that we can use chemicals to induce mutations in plant cells that cannot be tolerated in other species or models by creating maize single-cell mutant populations. Studying these plant single-cell mutant populations may allow us to understand the control of metabolism genes, which are critical to both crop growth, and also all life on Earth.
However, in order to study the genetics of maize single-cell mutant populations, we need to be able to measure both a trait and the underlying genetics of these cells. This is only made possible by emerging single-cell technologies, especially single-cell multi-omics, which allow us to measure a cell's genetics and a molecular trait, like gene transcription. With these measurements we will, in theory, be able to determine the gene-to-gene regulatory genetic relationships for nearly all genes in the plant genome, not just those that vary in natural plant populations. Importantly, all plant traits have an underlying molecular mechanism that involves the genetic networks that control gene expression. In this way, our study of how gene-to-gene relationships regulate transcription will provide a roadmap for scientists and breeders to understand the genetic control of all plant traits. This will help inform future gene editing to allow crop genetics to move beyond the constraints of existing variation to improve crop growth, resilience and yield.
Join Our Team!
We are always seeking out new talented and motivated lab members who want to join our mission of understanding the genetics behind crop production.
We welcome:
- Innovative approaches to studying plant growth
- Scientists with broad plant science interests
- A passion for bridging foundational genetics and agriculture
Please do not hesitate to reach out via email if you think the MAAM lab might be for you!