A radio-detected type Ia supernova with helium-rich circumstellar material.

Type Ia supernovae (SNe Ia) are thermonuclear explosions of degenerate white dwarf stars destabilized by mass accretion from a companion star1, but the nature of their progenitors remains poorly understood. A way to discriminate between progenitor systems is through radio observations; a non-degenerate companion star is expected to lose material through winds2 or binary interaction3 before explosion, and the supernova ejecta crashing into this nearby circumstellar material should result in radio synchrotron emission. However, despite extensive efforts, no type Ia supernova (SN Ia) has ever been detected at radio wavelengths, which suggests a clean environment and a companion star that is itself a degenerate white dwarf star4,5. Here we report on the study of SN 2020eyj, a SN Ia showing helium-rich circumstellar material, as demonstrated by its spectral features, infrared emission and, for the first time in a SN Ia to our knowledge, a radio counterpart. On the basis of our modelling, we conclude that the circumstellar material probably originates from a single-degenerate binary system in which a white dwarf accretes material from a helium donor star, an often proposed formation channel for SNe Ia (refs. 6,7). We describe how comprehensive radio follow-up of SN 2020eyj-like SNe Ia can improve the constraints on their progenitor systems.

Island-specific evolution of a sex-primed autosome in a sexual planarian.

The sexual strain of the planarian Schmidtea mediterranea, indigenous to Tunisia and several Mediterranean islands, is a hermaphrodite1,2. Here we isolate individual chromosomes and use sequencing, Hi-C3,4 and linkage mapping to assemble a chromosome-scale genome reference. The linkage map reveals an extremely low rate of recombination on chromosome 1. We confirm suppression of recombination on chromosome 1 by genotyping individual sperm cells and oocytes. We show that previously identified genomic regions that maintain heterozygosity even after prolonged inbreeding make up essentially all of chromosome 1. Genome sequencing of individuals isolated in the wild indicates that this phenomenon has evolved specifically in populations from Sardinia and Corsica. We find that most known master regulators5-13 of the reproductive system are located on chromosome 1. We used RNA interference14,15 to knock down a gene with haplotype-biased expression, which led to the formation of a more pronounced female mating organ. On the basis of these observations, we propose that chromosome 1 is a sex-primed autosome primed for evolution into a sex chromosome.

A very luminous jet from the disruption of a star by a massive black hole.

Tidal disruption events (TDEs) are bursts of electromagnetic energy that are released when supermassive black holes at the centres of galaxies violently disrupt a star that passes too close1. TDEs provide a window through which to study accretion onto supermassive black holes; in some rare cases, this accretion leads to launching of a relativistic jet2-9, but the necessary conditions are not fully understood. The best-studied jetted TDE so far is Swift J1644+57, which was discovered in γ-rays, but was too obscured by dust to be seen at optical wavelengths. Here we report the optical detection of AT2022cmc, a rapidly fading source at cosmological distance (redshift z = 1.19325) the unique light curve of which transitioned into a luminous plateau within days. Observations of a bright counterpart at other wavelengths, including X-ray, submillimetre and radio, supports the interpretation of AT2022cmc as a jetted TDE containing a synchrotron 'afterglow', probably launched by a supermassive black hole with spin greater than approximately 0.3. Using four years of Zwicky Transient Facility10 survey data, we calculate a rate of [Formula: see text] per gigapascals cubed per year for on-axis jetted TDEs on the basis of the luminous, fast-fading red component, thus providing a measurement complementary to the rates derived from X-ray and radio observations11. Correcting for the beaming angle effects, this rate confirms that approximately 1 per cent of TDEs have relativistic jets. Optical surveys can use AT2022cmc as a prototype to unveil a population of jetted TDEs.

Highly complete long-read genomes reveal pangenomic variation underlying yeast phenotypic diversity.

Understanding the genetic causes of trait variation is a primary goal of genetic research. One way that individuals can vary genetically is through variable pangenomic genes: genes that are only present in some individuals in a population. The presence or absence of entire genes could have large effects on trait variation. However, variable pangenomic genes can be missed in standard genotyping workflows, owing to reliance on aligning short-read sequencing to reference genomes. A popular method for studying the genetic basis of trait variation is linkage mapping, which identifies quantitative trait loci (QTLs), regions of the genome that harbor causative genetic variants. Large-scale linkage mapping in the budding yeast Saccharomyces cerevisiae has found thousands of QTLs affecting myriad yeast phenotypes. To enable the resolution of QTLs caused by variable pangenomic genes, we used long-read sequencing to generate highly complete de novo genome assemblies of 16 diverse yeast isolates. With these assemblies, we resolved QTLs for growth on maltose, sucrose, raffinose, and oxidative stress to specific genes that are absent from the reference genome but present in the broader yeast population at appreciable frequency. Copies of genes also duplicate onto chromosomes where they are absent in the reference genome, and we found that these copies generate additional QTLs whose resolution requires pangenome characterization. Our findings show the need for highly complete genome assemblies to identify the genetic basis of trait variation.

Discovery of a rapidly evolving yeast defense factor, KTD1, against the secreted killer toxin K28.

Secreted protein toxins are widely used weapons in conflicts between organisms. Elucidating how organisms genetically adapt to defend themselves against these toxins is fundamental to understanding the coevolutionary dynamics of competing organisms. Within yeast communities, "killer" toxins are secreted to kill nearby sensitive yeast, providing a fitness advantage in competitive growth environments. Natural yeast isolates vary in their sensitivity to these toxins, but to date, no polymorphic genetic factors contributing to defense have been identified. We investigated the variation in resistance to the killer toxin K28 across diverse natural isolates of the Saccharomyces cerevisiae population. Using large-scale linkage mapping, we discovered a novel defense factor, which we named KTD1. We identified many KTD1 alleles, which provided different levels of K28 resistance. KTD1 is a member of the DUP240 gene family of unknown function, which is rapidly evolving in a region spanning its two encoded transmembrane helices. We found that this domain is critical to KTD1's protective ability. Our findings implicate KTD1 as a key polymorphic factor in the defense against K28 toxin.

Exploring the genetic architecture of protein secretion in Komagataella phaffii (Pichia pastoris) for biotechnology applications.

Improvements to the production of proteins in industrial yeast species have largely relied on generating variation in a single genetic background. A new study in PLOS Biology leverages natural genetic variation to identify genes and variants with the potential to improve protein yield.

Pooled analysis of radiation hybrids identifies loci for growth and drug action in mammalian cells.

Genetic screens in mammalian cells commonly focus on loss-of-function approaches. To evaluate the phenotypic consequences of extra gene copies, we used bulk segregant analysis (BSA) of radiation hybrid (RH) cells. We constructed six pools of RH cells, each consisting of ∼2500 independent clones, and placed the pools under selection in media with or without paclitaxel. Low pass sequencing identified 859 growth loci, 38 paclitaxel loci, 62 interaction loci, and three loci for mitochondrial abundance at genome-wide significance. Resolution was measured as ∼30 kb, close to single-gene. Divergent properties were displayed by the RH-BSA growth genes compared to those from loss-of-function screens, refuting the balance hypothesis. In addition, enhanced retention of human centromeres in the RH pools suggests a new approach to functional dissection of these chromosomal elements. Pooled analysis of RH cells showed high power and resolution and should be a useful addition to the mammalian genetic toolkit.

Modeling epistasis in mice and yeast using the proportion of two or more distinct genetic backgrounds: Evidence for "polygenic epistasis".

BACKGROUND: The majority of quantitative genetic models used to map complex traits assume that alleles have similar effects across all individuals. Significant evidence suggests, however, that epistatic interactions modulate the impact of many alleles. Nevertheless, identifying epistatic interactions remains computationally and statistically challenging. In this work, we address some of these challenges by developing a statistical test for polygenic epistasis that determines whether the effect of an allele is altered by the global genetic ancestry proportion from distinct progenitors. RESULTS: We applied our method to data from mice and yeast. For the mice, we observed 49 significant genotype-by-ancestry interaction associations across 14 phenotypes as well as over 1,400 Bonferroni-corrected genotype-by-ancestry interaction associations for mouse gene expression data. For the yeast, we observed 92 significant genotype-by-ancestry interactions across 38 phenotypes. Given this evidence of epistasis, we test for and observe evidence of rapid selection pressure on ancestry specific polymorphisms within one of the cohorts, consistent with epistatic selection. CONCLUSIONS: Unlike our prior work in human populations, we observe widespread evidence of ancestry-modified SNP effects, perhaps reflecting the greater divergence present in crosses using mice and yeast.

Retrospective Detection of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in Symptomatic Patients Prior to Widespread Diagnostic Testing in Southern California.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused one of the worst pandemics in recent history. Few reports have revealed that SARS-CoV-2 was spreading in the United States as early as the end of January. In this study, we aimed to determine if SARS-CoV-2 had been circulating in the Los Angeles (LA) area at a time when access to diagnostic testing for coronavirus disease 2019 (COVID-19) was severely limited. METHODS: We used a pooling strategy to look for SARS-CoV-2 in remnant respiratory samples submitted for regular respiratory pathogen testing from symptomatic patients from November 2019 to early March 2020. We then performed sequencing on the positive samples. RESULTS: We detected SARS-CoV-2 in 7 specimens from 6 patients, dating back to mid-January. The earliest positive patient, with a sample collected on January 13, 2020 had no relevant travel history but did have a sibling with similar symptoms. Sequencing of these SARS-CoV-2 genomes revealed that the virus was introduced into the LA area from both domestic and international sources as early as January. CONCLUSIONS: We present strong evidence of community spread of SARS-CoV-2 in the LA area well before widespread diagnostic testing was being performed in early 2020. These genomic data demonstrate that SARS-CoV-2 was being introduced into Los Angeles County from both international and domestic sources in January 2020.

Genomic epidemiology of the Los Angeles COVID-19 outbreak and the early history of the B.1.43 strain in the USA.

BACKGROUND: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused global disruption of human health and activity. Being able to trace the early outbreak of SARS-CoV-2 within a locality can inform public health measures and provide insights to contain or prevent viral transmission. Investigation of the transmission history requires efficient sequencing methods and analytic strategies, which can be generally useful in the study of viral outbreaks. METHODS: The County of Los Angeles (hereafter, LA County) sustained a large outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To learn about the transmission history, we carried out surveillance viral genome sequencing to determine 142 viral genomes from unique patients seeking care at the University of California, Los Angeles (UCLA) Health System. 86 of these genomes were from samples collected before April 19, 2020. RESULTS: We found that the early outbreak in LA County, as in other international air travel hubs, was seeded by multiple introductions of strains from Asia and Europe. We identified a USA-specific strain, B.1.43, which was found predominantly in California and Washington State. While samples from LA County carried the ancestral B.1.43 genome, viral genomes from neighboring counties in California and from counties in Washington State carried additional mutations, suggesting a potential origin of B.1.43 in Southern California. We quantified the transmission rate of SARS-CoV-2 over time, and found evidence that the public health measures put in place in LA County to control the virus were effective at preventing transmission, but might have been undermined by the many introductions of SARS-CoV-2 into the region. CONCLUSION: Our work demonstrates that genome sequencing can be a powerful tool for investigating outbreaks and informing the public health response. Our results reinforce the critical need for the USA to have coordinated inter-state responses to the pandemic.

Analysis of the genetic basis of height in large Jewish nuclear families.

Despite intensive study, most of the specific genetic factors that contribute to variation in human height remain undiscovered. We conducted a family-based linkage study of height in a unique cohort of very large nuclear families from a founder (Jewish) population. This design allowed for increased power to detect linkage, compared to previous family-based studies. Loci we identified in discovery families could explain an estimated lower bound of 6% of the variance in height in validation families. We showed that these loci are not tagging known common variants associated with height. Rather, we suggest that the observed signals arise from variants with large effects that are rare globally but elevated in frequency in the Jewish population.

Genetics of single-cell protein abundance variation in large yeast populations.

Variation among individuals arises in part from differences in DNA sequences, but the genetic basis for variation in most traits, including common diseases, remains only partly understood. Many DNA variants influence phenotypes by altering the expression level of one or several genes. The effects of such variants can be detected as expression quantitative trait loci (eQTL). Traditional eQTL mapping requires large-scale genotype and gene expression data for each individual in the study sample, which limits sample sizes to hundreds of individuals in both humans and model organisms and reduces statistical power. Consequently, many eQTL are probably missed, especially those with smaller effects. Furthermore, most studies use messenger RNA rather than protein abundance as the measure of gene expression. Studies that have used mass-spectrometry proteomics reported unexpected differences between eQTL and protein QTL (pQTL) for the same genes, but these studies have been even more limited in scope. Here we introduce a powerful method for identifying genetic loci that influence protein expression in the yeast Saccharomyces cerevisiae. We measure single-cell protein abundance through the use of green fluorescent protein tags in very large populations of genetically variable cells, and use pooled sequencing to compare allele frequencies across the genome in thousands of individuals with high versus low protein abundance. We applied this method to 160 genes and detected many more loci per gene than previous studies. We also observed closer correspondence between loci that influence protein abundance and loci that influence mRNA abundance of a given gene. Most loci that we detected were clustered in 'hotspots' that influence multiple proteins, and some hotspots were found to influence more than half of the proteins that we examined. The variants that underlie these hotspots have profound effects on the gene regulatory network and provide insights into genetic variation in cell physiology between yeast strains.

Finding the sources of missing heritability in a yeast cross.

For many traits, including susceptibility to common diseases in humans, causal loci uncovered by genetic-mapping studies explain only a minority of the heritable contribution to trait variation. Multiple explanations for this 'missing heritability' have been proposed. Here we use a large cross between two yeast strains to accurately estimate different sources of heritable variation for 46 quantitative traits, and to detect underlying loci with high statistical power. We find that the detected loci explain nearly the entire additive contribution to heritable variation for the traits studied. We also show that the contribution to heritability of gene-gene interactions varies among traits, from near zero to approximately 50 per cent. Detected two-locus interactions explain only a minority of this contribution. These results substantially advance our understanding of the missing heritability problem and have important implications for future studies of complex and quantitative traits.

Genetic mapping of MAPK-mediated complex traits Across S. cerevisiae.

Signaling pathways enable cells to sense and respond to their environment. Many cellular signaling strategies are conserved from fungi to humans, yet their activity and phenotypic consequences can vary extensively among individuals within a species. A systematic assessment of the impact of naturally occurring genetic variation on signaling pathways remains to be conducted. In S. cerevisiae, both response and resistance to stressors that activate signaling pathways differ between diverse isolates. Here, we present a quantitative trait locus (QTL) mapping approach that enables us to identify genetic variants underlying such phenotypic differences across the genetic and phenotypic diversity of S. cerevisiae. Using a Round-robin cross between twelve diverse strains, we identified QTL that influence phenotypes critically dependent on MAPK signaling cascades. Genetic variants under these QTL fall within MAPK signaling networks themselves as well as other interconnected signaling pathways. Finally, we demonstrate how the mapping results from multiple strain background can be leveraged to narrow the search space of causal genetic variants.

Exclusion of a luminous red giant as a companion star to the progenitor of supernova SN 2011fe.

Type Ia supernovae are thought to result from a thermonuclear explosion of an accreting white dwarf in a binary system, but little is known of the precise nature of the companion star and the physical properties of the progenitor system. There are two classes of models: double-degenerate (involving two white dwarfs in a close binary system) and single-degenerate models. In the latter, the primary white dwarf accretes material from a secondary companion until conditions are such that carbon ignites, at a mass of 1.38 times the mass of the Sun. The type Ia supernova SN 2011fe was recently detected in a nearby galaxy. Here we report an analysis of archival images of the location of SN 2011fe. The luminosity of the progenitor system (especially the companion star) is 10-100 times fainter than previous limits on other type Ia supernova progenitor systems, allowing us to rule out luminous red giants and almost all helium stars as the mass-donating companion to the exploding white dwarf.

Supernova SN 2011fe from an exploding carbon-oxygen white dwarf star.

Type Ia supernovae have been used empirically as 'standard candles' to demonstrate the acceleration of the expansion of the Universe even though fundamental details, such as the nature of their progenitor systems and how the stars explode, remain a mystery. There is consensus that a white dwarf star explodes after accreting matter in a binary system, but the secondary body could be anything from a main-sequence star to a red giant, or even another white dwarf. This uncertainty stems from the fact that no recent type Ia supernova has been discovered close enough to Earth to detect the stars before explosion. Here we report early observations of supernova SN 2011fe in the galaxy M101 at a distance from Earth of 6.4 megaparsecs. We find that the exploding star was probably a carbon-oxygen white dwarf, and from the lack of an early shock we conclude that the companion was probably a main-sequence star. Early spectroscopy shows high-velocity oxygen that slows rapidly, on a timescale of hours, and extensive mixing of newly synthesized intermediate-mass elements in the outermost layers of the supernova. A companion paper uses pre-explosion images to rule out luminous red giants and most helium stars as companions to the progenitor.

A variant in the neuropeptide receptor npr-1 is a major determinant of Caenorhabditis elegans growth and physiology.

The mechanistic basis for how genetic variants cause differences in phenotypic traits is often elusive. We identified a quantitative trait locus in Caenorhabditis elegans that affects three seemingly unrelated phenotypic traits: lifetime fecundity, adult body size, and susceptibility to the human pathogen Staphyloccus aureus. We found a QTL for all three traits arises from variation in the neuropeptide receptor gene npr-1. Moreover, we found that variation in npr-1 is also responsible for differences in 247 gene expression traits. Variation in npr-1 is known to determine whether animals disperse throughout a bacterial lawn or aggregate at the edges of the lawn. We found that the allele that leads to aggregation is associated with reduced growth and reproductive output. The altered gene expression pattern caused by this allele suggests that the aggregation behavior might cause a weak starvation state, which is known to reduce growth rate and fecundity. Importantly, we show that variation in npr-1 causes each of these phenotypic differences through behavioral avoidance of ambient oxygen concentrations. These results suggest that variation in npr-1 has broad pleiotropic effects mediated by altered exposure to bacterial food.

Single-cell eQTL mapping in yeast reveals a tradeoff between growth and reproduction.

Expression quantitative trait loci (eQTLs) provide a key bridge between noncoding DNA sequence variants and organismal traits. The effects of eQTLs can differ among tissues, cell types, and cellular states, but these differences are obscured by gene expression measurements in bulk populations. We developed a one-pot approach to map eQTLs in Saccharomyces cerevisiae by single-cell RNA sequencing (scRNA-seq) and applied it to over 100,000 single cells from three crosses. We used scRNA-seq data to genotype each cell, measure gene expression, and classify the cells by cell-cycle stage. We mapped thousands of local and distant eQTLs and identified interactions between eQTL effects and cell-cycle stages. We took advantage of single-cell expression information to identify hundreds of genes with allele-specific effects on expression noise. We used cell-cycle stage classification to map 20 loci that influence cell-cycle progression. One of these loci influenced the expression of genes involved in the mating response. We showed that the effects of this locus arise from a common variant (W82R) in the gene GPA1, which encodes a signaling protein that negatively regulates the mating pathway. The 82R allele increases mating efficiency at the cost of slower cell-cycle progression and is associated with a higher rate of outcrossing in nature. Our results provide a more granular picture of the effects of genetic variants on gene expression and downstream traits.