A new associate editor is joining GENETICS. We’re excited to welcome Chun-Liang Pan to the editorial team.

Chun-Liang Pan
Associate Editor

Chun-Liang Pan is a Distinguished Professor at the Institute of Molecular Medicine, National Taiwan University (NTU), in Taipei, Taiwan. He received an MD and completed residency in clinical neurology at NTU, and then obtained a PhD in neuroscience at the University of California, Berkeley, under the mentorship of Gian Garriga. After postdoc training with Steve McIntire at the University of California, San Francisco, he established his own lab at NTU in 2010. Using C. elegans as a model, his lab studies the genetic and circuit basis of learning, memory, and other behaviors. He is particularly interested in understanding how the nervous system integrates internal states of the animal to enable behavioral plasticity and regulate physiological homeostasis.

A new associate editor is joining G3: Genes|Genomes|Genetics. We’re excited to welcome Emily Clark to the editorial team.

Emily Clark
Associate Editor

Emily Clark is a research group leader at the Roslin Institute, University of Edinburgh, in Scotland. Her research group provides highly annotated genomes for farmed animals as resources to inform genome editing, genomic selection, and fundamental biology. She has a particular interest in how the genome is expressed and regulated across tissues and developmental stages and in different populations of sheep and goats. Using this information she is working towards improving the link between genotype and phenotype in these species, in both tropical and temperate regions of the globe. Recently, she led a white paper describing the next decade of research priorities for the global Functional Annotation of Animal Genomes Consortium (FAANG). She is also co-coordinator of the EuroFAANG Research Infrastructure project which aims to provide access to sustainable genomic resources for farmed animal genotype and phenotype research across Europe.

A new associate editor is joining G3: Genes|Genomes|Genetics. We’re excited to welcome Steven Munger to the editorial team.

Steven Munger
Associate Editor

Steven Munger, PhD, is an Associate Professor at The Jackson Laboratory in Bar Harbor, Maine, where he applies a systems genetics approach that integrates multi-scale genomics and genetic data from genetically diverse mice and embryonic stem cells to define the genetic and molecular bases of pluripotency and cell fate decisions. Munger received his BS in Biology from the University of Michigan and his PhD in Genetics from Duke University. As a first-generation college graduate from a small town in rural Michigan, he is acutely sensitive to the systemic barriers and personal obstacles that make it difficult for students from economically disadvantaged and underrepresented communities to enter and succeed in STEM fields. In his own lab and through his service to GSA, Steve is committed to finding solutions to lower these barriers and actively support and promote the next generation of talented young researchers from diverse backgrounds. Outside of the lab, Steve enjoys traveling, cooking, playing with his golden retriever Higgins, and starting and almost finishing DIY house projects.

A new associate editor is joining GENETICS. We’re excited to welcome Bo Zhang to the editorial team.

Bo Zhang
Associate Editor

Bo Zhang is a Professor in Developmental Biology and Genetics at Peking University in China. She received her BS and PhD degrees in Cell Biology from Peking University in 1989 and 1995, respectively, and pursued her post-doctoral training in the Institute of Molecular Biology at University of Zürich, Switzerland. She has been a visiting scholar at University of Wisconsin, Madison, as well as University of California, Los Angeles. Her group is interested in dissecting molecular and cellular mechanisms of vertebrate development through genetic approaches, using zebrafish as the major model with a focus on heart development and regeneration, as well as on developing genome editing techniques in zebrafish based on engineered endonucleases, including TALEN and CRISPR/Cas9.

A new associate editor is joining GENETICS in statistical genetics and genomics. We’re excited to welcome Lei Sun to the editorial team.

Lei Sun
Associate Editor
Lei Sun is a Professor in Statistics and Biostatistics at the University of Toronto. She studied mathematics at Fudan University and obtained her PhD in statistics from the University of Chicago in 2001. Her research area is in statistical genetics and genomics, with a focus on robust association methods, multiple hypothesis testing, selective inference, and more recently methods for the X chromosome. In 2017, she received the prestigious Centre de recherches mathématiques-Statistical Society of Canada Prize in Statistics, and in 2020, she served as the President of the Biostatistics Section of the Statistical Society of Canada.

A new associate editor is joining GENETICS in population and evolutionary genetics. We’re excited to welcome Konrad Lohse to the editorial team.

Konrad Lohse
Associate Editor

Konrad Lohse is a population geneticist interested in learning about evolution in natural populations from genomic data. After a BSc at the University of St Andrews, he obtained a PhD at Edinburgh University under the mentorship of Nick Barton and Graham Stone working on inference of population history. Konrad is currently a Senior Lecturer at Edinburgh University, and he leads a research group that combines theoretical work on the coalescent with genomic studies of adaptation, chromosome evolution and speciation in insects (including various species of butterflies and Drosophila). His group has developed a coalescent-based method to scan genomes of recently diverged taxa for barriers to gene-flow.

A new associate editor is joining GENETICS in the population and evolutionary genetics section. We’re excited to welcome Thomas Lenormand to the editorial team.

Thomas Lenormand

Associate Editor

Thomas Lenormand is Centre National de la Recherche Scientifique research director at the CEFE laboratory. He is an evolutionary geneticist, combining mathematical theory, statistical developments, laboratory experiments, and field work. His work covers a wide range of issues at the intersection of evolution, genetics, and ecology. He is mainly interested in adaptation, the evolution of genetic systems (sex, asex, meiosis, recombination, sex chromosomes) and the effect of mutations. He was an editor and an associate editor of several evolutionary biology journals, twice an European Research Council laureate, and a Harvard Radcliffe fellow. He has received several awards, including the Dobzhansky Prize from the Society for the Study of Evolution.

Three new editors are joining GSA journals, GENETICS and G3: Genes|Genomes|Genetics. We’re excited to welcome Arash Bashirullah, Noah Whiteman, and Yun Li to their roles as Senior Advisory Editor for GENETICS, Genome Report Senior Editor for G3, and Associate Editor for GENETICS, respectively.

Arash Bashirullah

Senior Advisory Editor, GENETICS

Dr. Arash Bashirullah is a Professor of Pharmaceutical Sciences in the School of Pharmacy at the University of Wisconsin, Madison where he is also the Associate Dean for Research & Graduate Education. He was an Associate Editor for G3 from 2016-2022; chaired GSA’s International Strategic Planning Group in 2018; and served as an advisor on the GSA’s Early Career Scientist Communication Subcommittee from 2017 to 2019.

Bashirullah’s lab uses genetic, cellular, and molecular approaches to study the hormonal control of animal development with Drosophila as the model organism. The goal of their research is to identify novel genetic and cellular drivers of development and disease.

Bashirullah is responsible for the instruction or coordination of several classes taken by PharmD, BS, and PhD students in the School of Pharmacy. He is also a Faculty Trainer in the Genetics and the Cellular & Molecular Biology Programs at the University of Wisconsin, Madison. As the Associate Dean for Research and Graduate Education, Bashirullah is responsible for the oversight of facilities and processes that support academic research and graduate education in the school. He recently participated in the Academic Leadership Program of the Big Ten Academic Alliance.

Noah Whiteman

Genome Report Editor, G3: Genes|Genomes|Genetics

Noah Whiteman’s research focuses on unraveling the evolutionary histories of interacting species and the genetic basis of adaptations arising from those interactions. They focus on how toxins are a fulcrum around which these species interactions revolve.

Although the systems his lab have studied are diverse, the questions are all about the evolution of species interactions. A strength of their lab is pursuing studies that bridge between model organisms and those organisms that are difficult to study but remarkable in terms of their natural history.

Yun Li

Associate Editor, GENETICS

Yun Li is a statistical geneticist with extensive experiences in method development and application on genotype imputation (developer of MaCH and MaCH-admix), genetic studies of recently admixed population, design and analysis of sequencing-based studies, analyses of multi-omics data including mRNA expression, DNA methylation, chromatin 3D organization, and imaging genetics. She has played an active role in genetic studies of complex human traits resulting in many GWAS and meta-analysis publications, including more than 30 articles in Nature, Science, Cell, and Nature Genetics. Li is leading multiple NIH projects on statistical method development for complex trait genetics. Li has received many awards and was granted the Thomson Reuters Highly Cited Researcher award due to her high impact scientific work. 

Multiple divergent retrocopies of the well-characterized Ku70 gene were identified in humans and other primates.

The last 63 million years of primate evolution have been strongly shaped by genetic retrotransposition; thousands of genes and proteins with new functions have evolved from retrocopies scattered throughout the genome. These retrocopies arise when retrotransposons reverse transcribe a cellular mRNA and insert the resulting cDNA copy back into the genome.

A recent study published in G3: Genes|Genomes|Genetics characterized a new family of five retrocopies in the human genome. These retrocopies—which researchers named NUKUs—are derived from KU70, a highly conserved gene that encodes a ubiquitous protein involved in DNA double-strand break repair.

“Many people think retrocopies are junk DNA, but there are many examples where they have functional relevance in humans and other organisms,” says lead author Paul Rowley of the University of Idaho. Rowley and his collaborators found that NUKUs are among those retrocopies that may have a function that differs from that of the original parent gene.

The long journey to identifying and characterizing NUKUs

More than 10 years ago, scientists studying Ku70 performed a BLAST search for the gene in the human genome. They noticed that additional genes came up in the search results, often truncated or missing introns.

“It raised some eyebrows, because very few other genes in the DNA double-strand break repair pathway have this many retrocopies,” says Rowley. Since that initial observation, numerous scientists have contributed to the ongoing process of characterizing these NUKU retrocopies.

Through experiments, the researchers demonstrated that NUKUs are transcribed in human tissue. To determine whether these retrogene transcripts were capable of producing proteins, they mined existing Ribo-seq (ribosome profiling) datasets to look for unique NUKU transcripts that were easily distinguishable from Ku70 and other transcripts.

“The day when we confirmed the ribosome association of the transcripts—that was a good day,” says Rowley. “We had already spent a lot of time showing that NUKUs are transcribed, but without ribosome association, any case for full protein translation is pretty much dead in the water.”

Rowley emphasizes the collaborative nature of this work. “Being supported through the Institute for Modeling Collaboration and Innovation enabled me as an empiricist to bring expertise in molecular and computational modeling on board, which really strengthened the paper and laid better groundwork for future studies,” he says.

Hypothesizing functionality

The researchers have not yet determined the functionality of NUKU genes, but they know enough to conclude that they aren’t exact functional duplicates of Ku70.

“You would imagine that a retrocopy would function as a bona fide copy of its parental gene, but if these proteins are doing something in the cell, they certainly seem to have lost their canonical function through truncation and specific mutations,” says Rowley.

The Ku70p protein interacts with Ku80p, the other half of the eukaryotic Ku heterodimer. Through computational modeling, collaborator Jagdish Patel demonstrated that the mutations in the NUKU retrogenes would disrupt the NUKU proteins’ ability to bind Ku80p. Without the ability to form a heterodimer, it is unlikely that NUKUs are involved in DNA double-strand break repair. Their expression patterns suggest divergence too: while Ku70 is expressed fairly ubiquitously, NUKU transcripts show greater tissue specificity. Together, the study’s results suggest that NUKUs evolved rapidly during primate speciation and that the genes developed novel functions separate from Ku70.

Future studies will aim to identify possible functions of this familiar-yet-distinct gene family. These studies might also provide broader evolutionary insights by revealing factors driving the selection of specific mutations in NUKUs, such as regulation or interactions with pathogens or other host proteins.

CITATION

NUKU, a family of primate retrocopies derived from KU70

Paul A Rowley, Aisha Ellahi, Kyudong Han, Jagdish Suresh Patel, James T Van Leuven, Sara L Sawyer

G3 Genes|Genomes|Genetics 2021; jkab163

https://doi.org/10.1093/g3journal/jkab163

New Bolotie method can handle the barrage of sequencing data that posed a problem for conventional recombination algorithms.

Humanity has faced many pandemics throughout history, but never before have we tackled an active pandemic while so well equipped with genetic technology. In fact, when SARS-CoV-2 struck, the genetics community produced so much sequencing data so quickly that existing software couldn’t handle it all. To study how the viral genome was changing, researchers at Johns Hopkins University created new software capable of processing tens of thousands of individual genome sequences. Their results, published in GENETICS, identified 225 likely instances of recombination, a type of genetic swapping between different variants.

“This pandemic has shown us that genomics and genetics can play a very deciding role in how quickly we can understand a problem that’s been unknown to us,” says Ales Varabyou, an author on the study.

As COVID-19 spread, researchers around the world sought to understand the evolution of the SARS-CoV-2 virus as it spread through the population. Documenting how the virus evolved over time could not only shed light on where it might have come from, but also how best to stop it.

“People were searching to see if new variants emerged that would have an effect on susceptibility or vaccine efficacy,” says Christopher Pockrandt, another author on the study.

How variants arise

Viruses reproduce inside the cells of an infected individual before being transmitted to a new host. As the cell makes new copies of the viral genome, errors regularly creep in. Most of these changes don’t make much difference in the ability of the virus to infect people, so they don’t attract our attention. Some changes make the virus less efficient at spreading, and those variants tend to die out. Other changes catch on, however, and these may soon become a significant fraction of the samples taken from patients. This is where new named variants come from.

Even within a single named variant, like “beta” or “delta”, there’s a considerable amount of variation. “Pick two random people on the street that are infected with SARS-CoV-2,” says Pockrandt. “Even if they have the same variant, they most likely will not have exactly the same genomic sequence.” If an unlucky person happens to get infected by two different versions of SARS-CoV-2 at the same time, the cellular machinery that’s cranking out copies of the virus can mix up the two viruses and create an entirely new viral sequence containing sections from each of the two originals. This type of change is called recombination, and that’s what the Johns Hopkins team were searching for.

So many genomes, so little time

Existing software can scan viral genome sequences looking for the telltale signs of a recombination event. But in the past, the genome sequences being scanned had major differences. Often the viral samples were collected months or years apart, allowing more changes to accumulate. In the case of SARS-CoV-2, the genetics community swung into action immediately, and the widespread availability of inexpensive, rapid sequencing meant that new genomes were being produced daily.

“We had so many SARS-CoV-2 genomes sequenced in such a short time that when we wrote up the paper [in October 2020], there were already 300,000 genomes sequenced and assembled,” says Pockrandt. Besides the sheer volume of data to be processed, the researchers faced the problem that many of these sequences were very similar to one another. “Let’s say you sample all the positive people in a region and sequence the SARS-CoV-2 samples. If you do that again two weeks later, there will be very little change,” Pockrandt says. “A lot of the software relies on much higher sequence divergence to be able to detect those recombination events.”

That’s why the researchers decided to write their own software.

Creating Bolotie

A recombination event involves two “parent” viruses that get remixed into a third, “offspring” virus. The purpose of the software is to compare all the existing sequences and establish relationships between them—like a family tree. Previous approaches analyzed triads, comparing sequences to see whether two variants could be the “parents” of the third.

“If you have 100,000 sequences, there’s no way you will ever be able to process all this data,” says Pockrandt. “It works out to something like a quadrillion instances you’d have to check. So that was the challenge.”

Bolotie takes a different approach. A genome consists of a string of nucleotide bases, and each location can be one of four possible bases. The genomes can be grouped into four “clades” based on which nucleotide base is present at certain positions in the genome. Members of a given clade are all slightly different, but the differences within a clade are smaller than the differences between clades. Instead of analyzing all the possible sets of three, Bolotie searches for recombination events between clades rather than between individual genomes.

“We simplify the problem a little bit,” Varabyou says. “We look for interclade recombinations. We never say that a recombination happened specifically between this genome and that genome, but that it happened between some two genomes of these two clades.”

Tracking the current pandemic, and future ones

After analyzing the 300,000 viral genomes, the team identified 225 potential recombination events,  suggesting that recombination in SARS-CoV-2 is more common than previously reported. Still, most of the recombinant viruses did not establish a strong presence in the population. “One of the important findings is that recombination is not a very widespread event,” says Varabyou. “Over time, the number of recombinations did not start suddenly increasing exponentially, but stayed pretty constant at a low level.”

The new software will help detect future recombination events and could be a valuable tool for tracking the spread of different variants. It could also improve tracking of other disease-causing viruses, such as HIV or influenza.

“I hope this phenomenon of mass sequencing and data availability will only grow with time,” Varabyou says. He points out that although the HIV pandemic has been ongoing for 40 years, nowhere near as many HIV genomes have been sequenced as for SARS-CoV-2. “This tool was designed to answer this one specific question early on, but it’s a very interesting direction to take once things settle down and we start thinking about the future.”

CITATION

Rapid detection of inter-clade recombination in SARS-CoV-2 with Bolotie

Ales Varabyou, Christopher Pockrandt, Steven L Salzberg, Mihaela Pertea

GENETICS, Volume 218, Issue 3, July 2021, iyab074

https://doi.org/10.1093/genetics/iyab074