Thomas Hurd
Associate Editor, Molecular Genetics of Development

Thomas Hurd is an Associate Professor in the Department of Molecular Genetics at the University of Toronto. He earned his undergraduate degree in biochemistry from the University of Toronto and his PhD in mitochondrial biology at Cambridge University, where he studied under Michael Murphy. During his postdoctoral fellowship with Ruth Lehmann at NYU, he used Drosophila to uncover mechanisms of mitochondrial inheritance through the female germline. His current research continues to investigate this topic through genetic, molecular, and cytological approaches.

Why Publish in GENETICS?

Researchers at the Big Data Institute and colleagues have developed a new method for understanding the relationships between different DNA sequences and where they come from.

This information has widespread applications, from understanding the development of viruses, such as SARS-CoV-2, the strain of coronavirus that causes COVID-19, to precision medicine, an approach to disease treatment and prevention that takes into account individual genetic information. The study is published in GENETICS and is the featured paper in the September 2024 edition.  

Genetics is rapidly becoming part of our everyday lives. Nearly every week sees another newspaper headline about genetics and human ancestry, with huge datasets of DNA sequences routinely generated and used for medical study.

We can make sense of this genomic big data by working out the historical process that created it ‒ in other words, where the DNA sequences came from. If we take a small section of someone’s DNA we know it must have come from one of their two parents in the last generation, and previously from one of their four grandparents in the generation before that, and so on. This means we can represent the history of different sections of DNA by tracing them backwards through time.

If we do this for a large set of DNA sequences from different people, we can build up a set of genetic “family trees,” a genealogy of DNA sequences. This grand network of inheritance is sometimes called an ancestral recombination graph (ARG). Previous work by the same research group has shown that such networks can be used not only to illuminate the history of our genome, but also to compress DNA data and speed up genetic analyses.

Lead author and evolutionary geneticist at the Big Data Institute, Dr Yan Wong said, “There has been surprisingly little consensus on exactly how to represent such an ancestral recombination graph on a computer. In this study, we outline a simple and efficient encoding of genetic genealogies in which each ancestor can be thought of as a fragmentary length of DNA, or ‘ancestral genome’ at some point in the past. The history of today’s genetic sequences is traced back through those ancestral genomes, keeping track of which chunks of DNA were inherited from which ancestors.”

By using this simple scheme, recording genome-to-genome transmission of information, the study shows that the same genetic ancestry can be stored to different degrees of precision. This means relationships between different DNA sequences can be represented without having to know or guess the precise timing of joins and splits that underlie the true history of inheritance. The researchers also show that their description of genetic inheritance is flexible enough to deal with the wide variety of different methods that researchers currently use to reconstruct genetic history.

The approach allows scientists to store and analyze large amounts of genetic data on a standard laptop, and it generalizes to any species of life on earth. For example, it forms the basis of a “unified genealogy” of over 7,000 publicly available whole human genome sequences that the researchers released previously. They are currently creating a genetic genealogy of millions of SARS-CoV-2 genomes, collected over the span of the coronavirus pandemic, which will allow analysis of the recent history of the virus, pinpointing the emergence of novel mixed (or “recombinant”) strains. Dr Wong added, “We hope that this formal standard for how to represent genetic genealogies can help to unify the field of genetic history and make it easier for scientists to analyze, share and compare results. This will be crucial as we move into an era of genomic medicine, where genetic data will be used to diagnose and treat diseases, and where understanding the history of our genomes will be key to understanding our health and ancestry.”

As part of its scope, G3 Genes|Genomes|Genetics is dedicated to reporting new methods and technologies of significant benefit to the genetics community. Here, we highlight a selection of new analysis pipelines and software developments from the August 2024 issue that promise to improve research and practical applications in their respective subfields. These advances include easy and ready-to-use genomics tools that improve data management and analysis and overcome long-time challenges, emphasizing the ongoing progress and innovation happening in genomics.

An easy-to-use phylogenetic analysis pipeline

A new turn-key pipeline called OrthoPhyl has answered the call to improve the phylogenetic analysis of bacterial genomes. Developed by Middlebrook et al., OrthoPhyl can analyze up to 1,200 input genomes and reconstruct high-resolution phylogenetic trees based on whole genome codon alignments from diverse bacterial clades.

The beauty of OrthoPhyl is that it streamlines a usually complex, multi-step process requiring extensive bioinformatics expertise and computing resources into a multi-threaded tool that runs from a single command.

With more than 2 million publicly available bacterial genomes in NCBI’s GenBank database, OrthoPhyl can help research groups in the fields of bacterial phylogenetics and taxonomy take advantage of existing datasets to inform their ongoing analyses amid the ever-expanding sea of bacterial diversity.

Accurate genotype phasing and inference of grandparental haplotypes

To improve the analysis of complex plant genomes, Montero-Tena et al. have developed a new computational pipeline called haploMAGIC, which lets researchers identify locations of recombination known as genome-wide crossovers (COs) in multi-parent populations. haploMAGIC uses single-nucleotide polymorphism (SNP) data and known pedigree information to accurately phase genotypes, i.e., determine which alleles were inherited from each parent, and to reconstruct grandparental haplotypes, i.e., determine which alleles were inherited from each grandparent.

When tested on real-world data, haploMAGIC improved upon existing methods by using different levels of haploblock filtering to prevent false-positive COs—a common limitation—even as rates of genotyping errors increased. haploMAGIC can also distinguish between COs and gene conversions. By learning more about the position and frequency of genetic recombination events in complex plant genomes, breeders can better manage and expand genetic variation in their breeding programs.

A complete HiC/HiFi assembly pipeline

The USDA-ARS AgPest100 Initiative aims to create high-quality genome assemblies of pest insects that threaten agricultural production. However, the high cost and time currently needed to produce and manage these assemblies often hinders progress.

Molik et al. set out to address this challenge by developing a new Hi-C/high-fidelity (HiFi) sequencing genomic assembly pipeline called only the best (otb) using the Nextflow programming language. They then used otb to create a HiC/HiFi genome of the two-lined spittlebug, a significant agricultural pest that is not well understood. Overall, otb was able to streamline the process and reduce manual input and analysis time—including time spent organizing data and installing and calibrating bioinformatic tools.

By saving time, otb can significantly reduce costs for large genomic projects like AgPest100 and pave the way for new discoveries. Indeed, the HiC/HiFi assembly of the spittlebug genome represents a first step toward better understanding this plant-eating pest, which may lead to new, sustainable ways to manage it.

Assigning triploids to their diploid parents

Roche et al. have developed the first publicly-available, ready-to-use software for assigning triploid fish to their diploid parents. Triploidy means that an organism has three sets of chromosomes instead of two, and sterile triploids are commonly used in aquaculture breeding programs for their better yield and growth and to prevent genetic contamination of wild fish populations. The authors improve upon existing frameworks by updating the parentage assignment R package APIS to support triploids with diploid parentage.

When assessed with simulated and real datasets, APIS accurately assigned triploid offspring to their diploid parents using both likelihood and exclusion methods. The new software represents a key tool for establishing pedigrees in fish farming.

Eugenics is a stain on the founding of the field of genetics, one that modern geneticists must still reckon with. The Allied Genetics Conference 2024 featured a thought-provoking panel discussion on this subject, moderated by past GSA Presidents Denise Montell and Tracy Johnson. Panelists Katrina Claw, Nathaniel Comfort, Steven Farber, Daniel HoSang, and Jazlyn Mooney shared their expertise on the history of eugenics and the ways its ideas persist in both science and society even today. Their keen insights shed light on the interdisciplinary nature of science, highlighting that anthropology, philosophy, and the humanities are all key in the study of science. 

This event marks the start of important conversations for GSA and the larger genetics and genomics community about the field’s history. GSA understands that scientific research takes place in the context of society, and we strive to build an environment in which all researchers from all backgrounds feel welcome and can thrive. For that, we must look critically at the space in which we conduct research, including reflecting on and learning from the past. Even today, bad actors twist the findings of genetics research to support racist ideology, giving this conversation and reflection notable immediacy. 

While acknowledging that this topic can be uncomfortable, GSA will not oversimplify these discussions; our goal is to face this history directly, even as it may require re-contextualizing luminaries in the field. Only through honest reckoning can we move forward toward an anti-racist scientific enterprise.

GSA fully rejects eugenics ideology, and we commit to understanding how it has lived within and outside our institutions and society at large so we can do better as a field and a scientific community. We will continue to address this topic at GSA, creating space for our community to share their thoughts and experiences and to learn together.

Watch the recording of the panel on our YouTube channel.

Yaniv Brandvain
Associate Editor, Empirical Population Genetics section

Yaniv Brandvain is an Associate Professor of Plant and Microbial Biology at the University of Minnesota working in theoretical and empirical population genomics. He received a BA in Human Ecology from the College of the Atlantic and a PhD in Biology from Indiana University, working on the robe of conflict, cooperation, and co-adaptation in plant evolution and speciation. During his postdoc at the University of California, Davis, he developed evolutionary theory concerning meiotic drive, and he developed population genomic approaches to study the evolutionary origins of self-fertilizing plant species. He is interested in understanding how new plant species arise with a particular interest in how mating systems and genomic conflicts shape plant diversity. His lab combines empirical and theoretical population genomic analyses with collaborative work in empirical systems to study the evolutionary forces shaping flowering plant diversity. He was also named McKnight Land-Grant Professor from the University of Minnesota (2017-2019) for his research efforts and received the Stanley Dagley-Samuel Kirkwood Undergraduate Education Award for his efforts in undergraduate instruction in biostatistics. 

We’ve all suffered a cut from a blade, some broken glass, or even a sheet of paper. The smallest of wounds can cause infections and become detrimental if they don’t heal, so luckily for most of us, our immune system steps in to do the job. Just as the immune system kicks off a cascade of events to heal a cut, an individual cell kicks off a cascade of signals to manage disruption to its cell membrane. However, the molecular mechanisms that underlie cellular wound healing are quite complex, and we don’t have a complete picture of the phenomenon. In a recent study published in the August issue of GENETICS, Mitsutoshi Nakamura and Susan M. Parkhurst flesh out additional details of the process.

In eukaryotic cells, a structural protein called actin forms the cytoskeleton that underlies the cell membrane. When the cell cortex (cytoskeleton and membrane) is wounded, vesicles are recruited to temporarily plug the opening, and a ring of actin filaments and myosin fibers assembles around the site to rapidly close the wound. After the wound closes, the patch job is removed, and the cytoskeleton and cell membrane are remodeled to their normal states. Actin remodeling requires the activity of the Rho family of small guanosine triphosphatases (GTPases), including the guanine nucleotide exchange factors RhoGEF2 and RhoGEF3.

One of the earliest events after a cell is wounded is a swift influx of calcium from the extracellular space into the cell. The uniform inflow of calcium across the wound site recruits specific factors to precise locations—but how this occurs is still an open question. We do know, however, that a group of proteins called annexins bind specific phospholipids in a calcium-dependent manner and play a conserved role in wound healing. The authors previously showed that annexin AnxB9 is rapidly recruited to wounds and plays a vital role in actin stabilization in the Drosophila cell wound model by recruiting RhoGEF2 to the site. Interestingly, they found that AnxB9 is not required for RhoGEF3 recruitment.

In the current study, Nakamura and Parkhurst show that two additional Drosophila annexins, AnxB10 and AnxB11, are also rapidly recruited to distinct sites around the wound within seconds of injury and that they, in turn, recruit RhoGEF2 and RhoGEF3. The three annexins at the center of their work must find their way to specific locations, and they have non-redundant functions in stabilizing the formation of the actomyosin ring around the wound, which sets the stage for RhoGTPase-mediated repair. The authors show that, while the repair process can begin under reduced-calcium conditions, it is inefficient and ultimately unsuccessful.

Calcium signals are widely known as a second messenger and are crucial for many processes. In addition to its impacts on wound healing, an imbalance in calcium homeostasis is found in cancer, muscular dystrophy, and diabetes. Understanding the dynamics of calcium-mediated annexin recruitment may inform the development of therapeutic strategies to enhance cellular repair mechanisms. For instance, targeting annexin functions or modulating calcium signaling pathways could offer new avenues for treating injuries and diseases characterized by impaired wound repair. Continued research in this area promises to unveil further nuances of this vital cellular process—with potential applications in regenerative medicine and beyond.

Christos Palaiokostas
Associate Editor, Fish and Complex Traits section

Christos Palaiokostas is an Associate Professor in the Department of Animal Biosciences at the Swedish University of Agricultural Sciences. He is working in the field of aquaculture genetics and breeding. He received his PhD from the Institute of Aquaculture at Stirling University in Scotland, while studying the sex determining system of fish with sexual dimorphism. During his postdoc at the Roslin Institute of Edinburgh University he worked on improving disease resistance in farmed fish using genomics. His research is focused in the application of high-throughput sequencing and genotyping technologies for studying complex traits in aquatic organisms.

Why Publish in G3?

Biodegradation is currently the most eco-friendly approach to breaking down complex plastic into less harmful products. Luckily, a number of insects and microorganisms have the capability to digest plastic polymers, and several studies have shown that insect guts can biodegrade plastics faster than environmental microbes. To tackle the global—and mounting—plastic waste problem, researchers look to these critters in hopes of adapting their enzymatic capabilities into efficient systems that can degrade plastic waste at scale.

In a recent study published in the June issue of G3: Genes, Genomes, Genetics, Young et al. report an improved reference genome for the greater wax moth Galleria mellonella as a tool to identify enzymatic pathways with plastic biodegradation properties.

Well-known as a honeybee pest, greater wax moth larvae feed on beeswax, which contains long-chain hydrocarbons. Since long-chain hydrocarbons are also the major constituent in polyethylene (PE), researchers are quite interested in the enzymes responsible for beeswax degradation; in fact, the hexamerin and arylphorin proteins, found in larval saliva, have demonstrated PE-degrading abilities. Evidence suggesting wax moth larvae can degrade other plastics like polystyrene and polypropylene makes them attractive for plastic biodegradation research. The extent to which moth larvae possess plastic catabolizing enzymes is unclear; however, since both the larvae themselves and their gut microbiota have been implicated in PE biodegradation.

Since the existing reference genome for G. mellonella was fragmented, Young et al. combined short- and long-read sequencing approaches to generate a new assembly with improved continuity, identifying an additional 3,000 mRNA sequences. This new reference genome also supported phylogenetic comparisons with other Lepidoptera members such as moths, butterflies, and silkworms, allowing the authors to begin constructing an understanding of the evolutionary history of PE-degrading enzymes in winged insects.

Secreted proteins have a much better chance of playing a role in long-chain hydrocarbon degradation than intracellular proteins, so the authors investigated 3,865 proteins identified as secreted in their assembly, finding numerous hydrolases, transferases, oxidoreductases, ligases, lyases, and isomerases. They propose that these secretory enzymes, which may have evolved to catabolize a variety of exogenous and insoluble polymers, must also be capable of processing long-chain polymers like polyethylene. Several of the identified hydrolases and oxidoreductases are members of enzyme classes known to degrade plastic. They also found 135 hydrolases and 10 oxidoreductases that are predicted to act on ester bonds and peroxide, which may make them capable of breaking polyethylene. This genome is one of many sequenced by the Applied Genomics Initiative at the Commonwealth Scientific and Industrial Research Organisation in Australia. The initiative aims to sequence the genomes of a variety of organisms of interest to enable translational research in areas such as conservation, biosecurity, and health. The improved reference genome for the greater wax moth will continue to aid researchers in uncovering the molecular mechanisms behind its ability to degrade long-chain hydrocarbons; hopefully, these larvae can become a powerhouse for developing industrial and bioremediation applications in reducing plastic waste.

Epigenetics has the potential to help us understand key differences in how divergent species control gene expression. Recent work published by Brown et al. in GENETICS delves into the epigenetic mechanisms of Pristionchus pacificus, providing significant insights into the evolutionary dynamics of epigenetic regulation.

Many developmental traits are sensitive to environmental factors, and the differences in how close evolutionary relatives respond to their environments can help demystify development. The nematode Pristionchus pacificus has been established as a comparative system to the well-studied Caenorhabditis elegans, but a thorough exploration of the conservation of epigenetic pathways between the two species has not been conducted—until now.

P. pacificus is known for its remarkable morphological plasticity, especially in its feeding structures. It appears to be a perfect model to study the epigenetic regulation of these adaptive changes; however, its relative newness as a model system means its epigenetic “toolkit” isn’t well-defined. To manipulate the proteins and modifications involved in the epigenetics of plasticity, they first must be identified.

To address this gap, Brown et al. began with an in-silico approach to identify potential epigenetic genes, followed by biochemical analysis to identify histone posttranslational modifications. By orthology, they then predicted which proteins might be responsible for adding or removing these marks. Their work provides a comprehensive “epigenetic toolkit” for P. pacificus and reveals significant differences in epigenetic machinery between P. pacificus and C. elegans, highlighting the evolutionary flexibility of epigenetic regulation and underscoring the importance of understanding species-specific epigenetic landscapes.

One of the authors’ most striking findings is that P. pacificus lacks the repressive PRC2 complex, which is usually crucial for histone methylation. Surprisingly, the enzymatic product H3K27me3 is still present, suggesting an unknown methyltransferase is responsible for this modification. The revelation that P. pacificus can maintain a critical histone modification while missing its canonical enzyme opens the door to myriad new paths of investigation.

This work serves as a foundational resource for future studies on developmental plasticity and epigenetic regulation in P. pacificus. It also provides a comparative framework for studying similar mechanisms in other species, offering new avenues for research in evolutionary biology and epigenetics.

Advances in technology have allowed geneticists to sequence a slew of unique animal, plant, and fungi to species over the past thirty years. Public databases currently house tens of thousands of eukaryotic genome assemblies, but a relative few include an estimate of the total genome size for their respective species. Genome size (or C-value) varies widely, even at the species level, largely due to noncoding DNA, which is often dismissed as “junk” DNA. The standard metrics used to characterize assemblies don’t get at size and chromosome number—the fundamental structure of genomes. Without this foundational information, a new study in GENETICS asks: “Are our genome assemblies good enough?”

To determine whether existing assemblies match the estimated genome size for their corresponding species, author Carl Hjelmen designed an R script to pull information from four NCBI databases: Assembly, BioSample, Sequence Read Archive (SRA), and Taxonomy. Starting from the >40,000 available eukaryotic genome assemblies, he analyzed the ~15,000 animal, plant, and fungi genomes that had existing size estimates. He also used karyotype databases to determine the haploid chromosome number for mammals, dipterans, coleopterans, amphibians, polyneopterans.

Taking into account Kingdom, the sequencing platform used, and common assembly statistics, Hjelmen devised a metric called “Proportional difference from genome size” to determine how closely a given assembly length came to matching the estimated genome size. If the assembly was within 10% of the estimate, he considered it “good.” 

He found that almost half of the assemblies analyzed were outside of 10% of the genome size estimate for their species. Most were smaller than the estimates, suggesting that some assemblies are missing information. The larger the genome size, the more dramatic the deviation tended to be—which wasn’t surprising considering that larger eukaryotic genomes often carry more of that so-called “junk” DNA. (Nongenic DNA—a friendlier way to describe the regions of the genome that don’t code for proteins—might turn out to be more informative than its reputation would suggest, points out Hjelmen.)

Hjelmen also discovered a positive relationship between late-replicating heterochromatin and assembly/genome size deviation. When genomes contained more heterochromatin, the assembly was more likely to be missing DNA; he argues that this “lost information” should be highly sought after when studying populations and their health. And though the results were modest, long-read technologies appeared more likely to assemble genomes near that 10% cutoff.

This study points out the limitations of widely used genome metrics like N50 (which narrowly measures contiguity) and BUSCO value (which describes completeness of core sets of genes). To shrink this analytic gap, Hjelmen proposes a new structural unit: “PN50,” or proportional N50 value, which contextualizes N50 values by relating them to estimated genome size and haploid chromosome number. Adding PN50 to the current mix of metrics could increase the rigor of genome research, offering insight into the less-studied structural components of assemblies and supporting universal assembly comparison.