G3 Genes|Genomes|Genetics

Germ cell development and gamete production in animals require small RNA pathways. While studies indicate that microRNAs (miRNAs) are necessary for normal sperm production and function, the specific roles for individual miRNAs are largely unknown. Here, we use small RNA sequencing of dissected gonads and functional analysis of new loss of function alleles to identify functions for miRNAs in the control of fecundity and sperm production in Caenorhabditis elegans males and hermaphrodites. We describe a set of 29 male gonad-enriched miRNAs and identify a set of 3 individual miRNAs (mir-58.1, mir-83, and mir-235) and a miRNA cluster (mir-4807-4810.1) that are required for optimal sperm production at 20{degrees}C and 5 additional miRNAs (mir-49, mir-57, mir-261, and mir-357/358) that are required for sperm production at 25{degrees}C. We observed defects in meiotic progression in mir-58.1, mir-83, mir-235, and mir-4807-4810.1 mutants that may contribute to the reduced number of sperm. Further, analysis of multiple mutants of these miRNAs suggested complex genetic interactions between these miRNAs for sperm production. This study provides insights on the regulatory roles of miRNAs that promote optimal sperm production and fecundity in males and hermaphrodites. Article SummaryMicroRNAs are small non-coding RNAs that are required for the normal production of sperm but the roles of individual microRNAs in the process of spermatogenesis are not well understood. Here, we use the nematode Caenorhabditis elegans to identify microRNAs that are enriched in the male gonad to identify specific microRNAs that regulate male fertility. We generated new loss of function mutants for functional analysis to identify a set of microRNAs that are necessary for optimal fertility and fecundity in males.

Growth rate and body size are complex traits that contribute to the fitness of organisms. The identification of loci that underlie differences in these traits provides insights into the genetic contributions to development. Leveraging Caenorhabditis elegans as a tractable metazoan model for quantitative genetics, we can identify genomic regions that underlie differences in growth. We measured post-embryonic growth of the laboratory-adapted wild-type strain (N2) and a wild strain from Hawaii (CB4856), and found differences in body size. Using linkage mapping, we identified three distinct quantitative trait loci (QTL) on chromosomes IV, V, and X that are associated with variation in body size. We further examined these size-associated QTL using chromosome substitution strains and near-isogenic lines, and validated the chromosome X QTL. Additionally, we generated a list of candidate genes for the chromosome X QTL. These genes could potentially contribute to differences in animal growth and should be evaluated in subsequent studies. Our work reveals the genetic architecture underlying animal growth variation and highlights the genetic complexity of body size in C. elegans natural populations.

Studying genetic variation of gene expression provides a powerful way to unravel the molecular components underlying complex traits. Expression QTL studies have been performed in several different model species, yet most of these linkage studies have been based on genetic segregation of two parental alleles. Recently we developed a multi-parental segregating population of 200 recombinant inbred lines (mpRILs) derived from four wild isolates (JU1511, JU1926, JU1931 and JU1941) in the nematode Caenorhabditis elegans. We used RNA-seq to investigate how multiple alleles affect gene expression in these mpRILs. We found 1,789 genes differentially expressed between the parental lines. Transgression, expression beyond any of the parental lines in the mpRILs, was found for 7,896 genes. For expression QTL mapping almost 9,000 SNPs were available. By combining these SNPs and the RNA-seq profiles of the mpRILs, we detected almost 6,800 eQTLs. Most trans-eQTLs (63%) co-locate in six newly identified trans-bands. The trans-eQTLs found in previous 2-parental allele eQTL experiments and this study showed some overlap (17.5%- 46.8%), highlighting on the one hand that a large group of genes is affected by polymorphic regulators across populations and conditions, on the other hand it shows that the mpRIL population allows identification of novel gene expression regulatory loci. Taken together, the analysis of our mpRIL population provides a more refined insight into C. elegans complex trait genetics and eQTLs in general, as well as a starting point to further test and develop advanced statistical models for detection of multi-allelic eQTLs and systems genetics studying the genotype-phenotype relationship.

I outline a streamlined method to create single copy large genomic insert transgenes using Recombination-Mediated Cassette Exchange (RMCE) that relies solely on drug selection yielding a homozygous fluorescent protein (FP) marked transgene in 3 generations (8 days) at high efficiency (>1 insertion per 2 injected P0 animals). Landing sites for this approach are available on four chromosomes in several configurations which yield lines marked in distinct cell types. An array of vectors permit creating transgenes using a variety of selection methods (HygR, NeoR, PuroR, unc-119(+)) that yield lines expressing different colored FP tagged lines (BFP, GFP, mNG, and Scarlet). Although these transgenes retain a plasmid backbone and a selection marker, the inclusion of these sequences typically does not alter the expression of several cell specific promoters tested. However, in certain orientations promoters exhibits crosstalk with adjacent transcription units. In cases where crosstalk is problematic, the loxP-flanked fluorescent marker, plasmid backbone and hygR gene can be excised by crossing through germline Cre expressing lines also created using this technique. Finally, genetic and molecular reagents designed to facilitate customization of both targeting vectors and landing sites are also described. Together, the rRMCE toolbox provides a platform for developing further innovative uses of RMCE to create complex genetically engineered tools.

The Ets domain transcription factors direct diverse biological processes throughout all metazoans and are implicated in development as well as in tumor initiation, progression and metastasis. The Drosophila Ets transcription factor Pointed (Pnt) is required for several aspects of eye development and regulates cell cycle progression, specification, and differentiation. Despite its critical role in development, very few targets of Pnt have been reported previously. Here, we used chromatin immunoprecipitation with high-throughput sequencing (ChIP-seq) to determine the genome-wide occupancy of Pnt in late larval eye discs. We identified enriched regions that mapped to an average of 6,941 genes, the vast majority of which are novel putative Pnt targets. Integrating ChIP-seq data with two other larval eye single cell genomics datasets (scRNA-seq and snATAC-seq) reveals genes that may be putative cell type-specific genes regulated by Pnt. Finally, our ChIP-seq data predict cell type-specific functional enhancers that were not reported previously. Our study provides a greatly expanded list of putative Pnt targets in the eye and is a resource for future studies that will allow mechanistic insights into complex developmental processes regulated by Pnt.

Drosophila pseudoobscura is a long-standing model organism in evolutionary genetics because natural populations segregate for an inversion polymorphism on the third chromosome. In addition, D. pseudoobscura has a neo-X chromosome that was formed by an X-autosome fusion, which segregates for a sex-ratio drive allele. Previous genome-wide studies of DNA sequence variation in D. pseudoobscura have focused on individual chromosomes or did not use chromosome-scale reference genomes. To address these shortcomings, we generated a new D. pseudoobscura population genetic resource by sequencing the genomes of over 60 inbred lines sampled across the species geographic range in North America. Using these data, we examined patterns of nucleotide diversity and population structure across the entire genome. Tajimas D was negative across most of the genome, consistent with a recent population expansion. However, there was substantial heterogeneity of D across chromosomes, suggesting distinct evolutionary dynamics across the genome. We found no strong evidence of population structure across most chromosomes, consistent with a near panmictic population. In contrast, we identified population structure on the third chromosome, which we attributed to the inversion polymorphism and used to infer the arrangements carried by the strains we sampled. Our analysis therefore demonstrates that tests for population structure can identify polymorphic chromosomal rearrangements. The population genomic data we have collected is publicly available and will support future research on genome evolution, local adaptation, and sex chromosome evolution in D. pseudoobscura.

The distribution of allelic effects on traits, along with their gene-by-gene and gene-by-environment interactions, contributes to the phenotypes available for selection and the trajectories of adaptive variants. Nonetheless, uncertainty persists regarding the effect sizes underlying adaptations and the importance of genetic interactions. Herein, we aimed to investigate the genetic architecture and the epistatic and environmental interactions involving loci that contribute to multiple adaptive traits using two new panels of Drosophila melanogaster recombinant inbred lines (RILs). To better fit our data, we re-implemented functions from R/qtl (Broman et al. 2003) using additive genetic models. We found 14 quantitative trait loci (QTL) underlying melanism, wing size, song pattern, and ethanol resistance. By combining our mapping results with population genetic statistics, we identified potential new genes related to these traits. None of the detected QTLs showed clear evidence of epistasis, and our power analysis indicated that we should have seen at least one significant interaction if sign epistasis or strong positive epistasis played a pervasive role in trait evolution. In contrast, we did find roles for gene-by-environment interactions involving pigmentation traits. Overall, our data suggest that the genetic architecture of adaptive traits often involves alleles of detectable effect, that strong epistasis does not always play a role in adaptation, and that environmental interactions can modulate the effect size of adaptive alleles.

Phenotypic development is regulated by multiple mechanisms that ensure tight control of gene expression. Post-transcriptional regulation, including the silencing or degradation of messenger RNAs by microRNAs (miRNAs), is an important component of this process. Here, we use gain-of-function and loss-of-function screens to examine the effects of miRNAs on cuticular pigmentation in adult Drosophila melanogaster. We found that 48 of 166 miRNAs ectopically expressed in a stripe along the dorsal side of developing flies were each sufficient to affect pigmentation. We also found that 22 of 41 miRNAs competitively inhibited in the same tissue visibly altered pigmentation, showing that they were necessary for adult pigmentation development. For each of the 15 miRNAs with opposing effects in the gain- and loss-of-function screens, computational tools identified possible targets among 93 genes previously reported to affect adult pigmentation. Using cell culture, we found that one of these miRNAs (miR-8) was able to regulate gene expression through 3 UTR sequences from at least three pigmentation genes: ebony, bric-a-brac 1, and bric-a-brac 2. All three of these genes reduce development of black pigments, suggesting that miR-8 coordinately regulates expression of multiple genes with similar effects on pigmentation. These data show that miRNAs are important developmental regulators of body pigmentation, which could also allow them to contribute to pigmentation divergence, as has been shown for miR-193 in butterflies.

Most gene functions were detected by screens in very few model organisms but it has remained unclear how comprehensive these data are. Here, we expanded our RNAi screen in the red flour beetle Tribolium castaneum to cover more than half of the protein-coding genes and we compared the gene sets involved in several processes between beetle and fly. We find that around 50 % of the gene functions are detected in both species while the rest was found only in fly (~10%) or beetle (~40%) reflecting both technical and biological differences. We conclude that work in complementary model systems is required to gain a comprehensive picture on gene functions documented by the annotation of novel GO terms for 96 genes studied here. The RNAi screening resources developed in this project, the expanding transgenic tool-kit and our large-scale functional data make T. castaneum an excellent model system in that endeavor.

Here we localize a genetic suppressor that enhances the reduced locomotor activity phenotype of flies lacking brain dopamine. We utilized a non-bulked segregant analysis using whole genome sequencing (WGS), mapping the trait to a roughly 3.5 mega-base (Mb) region of the X-chromosome. However, this mapping yielded [~]5-fold lower resolution than anticipated, due to an uneven distribution of Single Nucleotide Polymorphisms (SNPs) between the X-chromosomes of the two recombining lines. This uneven SNP distribution was associated with recombination events biased towards regions of low SNP density, and away from the more SNP dense regions associating with the activity phenotype. We find that nearly perfect mapping of X-chromosome visible markers occurs only in historical data from a time before the establishment of discrete genetic background strains. This suggests that genetic uniformity in early Drosophila studies may have contributed to more consistent recombination frequencies, whereas modern mapping efforts are complicated by variability in SNP distribution across recombining strains. These findings highlight challenges in Drosophila genetic mapping in situations where altered SNP density can skew recombination, complicating trait localization. Article SummaryGenetic mapping studies generally assume uniform crossover distribution across chromosomes. However, this study demonstrates that an uneven density of single nucleotide polymorphism (SNP) is associated with biased sites of meiotic recombination. Using brain dopamine-deficient Drosophila, SNP dense regions show reduced crossover frequency, which reduced the mapping resolution, complicating genetic trait localization. These findings highlight the need to consider parental chromosome SNP distribution and its impact on recombination when designing genetic mapping studies. Future studies should consider chromosome structure, parental haplotype, and sequence heterogeneity to enhance mapping accuracy and resolution.

Neuron-specific morphology and function are fundamentally tied to differences in gene expression across the nervous system. We previously generated a single cell RNA-seq (scRNA-Seq) dataset for every anatomical neuron class in the C. elegans hermaphrodite. Here we present a complementary set of bulk RNA-seq samples for 52 of the 118 canonical neuron classes in C. elegans. We show that the bulk RNA-seq dataset captures both lowly expressed and noncoding RNAs that are not detected in the scRNA-Seq profile, but also includes false positives due to contamination by other cell types. We present an analytical strategy that integrates the two datasets, preserving both the specificity of scRNA-Seq data and the sensitivity of bulk RNA-Seq. We show that this integrated dataset enhances the sensitivity and accuracy of transcript detection and differential gene analysis. In addition, we show that the bulk RNA-Seq data set detects differentially expressed non-coding RNAs across neuron types, including multiple families of non-polyadenylated transcripts. We propose that our approach provides a new strategy for interrogating gene expression by bridging the gap between bulk and single cell methodologies for transcriptomic studies. We suggest that these datasets advance the goal of delineating the mechanisms that define morphology and connectivity in the nervous system.

A central goal of evolutionary genetics in Caenorhabditis elegans is to understand the genetic basis of traits that contribute to adaptation and fitness. Genome-wide association (GWA) mappings scan the genome for individual genetic variants that are significantly correlated with phenotypic variation in a population, or quantitative trait loci (QTL). GWA mappings are a popular choice for quantitative genetic analyses because the QTL that are discovered segregate in natural populations. Despite numerous successful mapping experiments, the empirical performance of GWA mappings has not, to date, been formally evaluated for this species. We developed an open-source GWA mapping pipeline called NemaScan and used a simulation-based approach to provide benchmarks of mapping performance among wild C. elegans strains. Simulated trait heritability and complexity determined the spectrum of QTL detected by GWA mappings. Power to detect smaller-effect QTL increased with the number of strains sampled from the C. elegans Natural Diversity Resource (CeNDR). Population structure was a major driver of variation in GWA mapping performance, with populations shaped by recent selection exhibiting significantly lower false discovery rates than populations composed of more divergent strains. We also recapitulated previous GWA mappings of experimentally validated quantitative trait variants. Our simulation-based evaluation of GWA performance provides the community with critical context for pursuing quantitative genetic studies using CeNDR to elucidate the genetic basis of complex traits in C. elegans natural populations.

Intracellular pathogen infection leads to proteotoxic stress in host organisms. Previously we described a physiological program in the nematode C. elegans called the Intracellular Pathogen Response (IPR), which promotes resistance to proteotoxic stress and appears to be distinct from canonical proteostasis pathways. The IPR is controlled by PALS-22 and PALS-25, proteins of unknown biochemical function, which regulate expression of genes induced by natural intracellular pathogens. We previously showed that PALS-22 and PALS-25 regulate the mRNA expression of the predicted ubiquitin ligase component cullin cul-6, which promotes thermotolerance in pals-22 mutants. However, it was unclear whether CUL-6 acted alone, or together with other ubiquitin ligase components. Here we use co-immunoprecipitation studies paired with genetic analysis to define the cullin-RING ligase components that act together with CUL-6 to promote thermotolerance. First, we identify a previously uncharacterized RING domain protein in the TRIM family we named RCS-1, which acts as a core component with CUL-6 to promote thermotolerance. Next, we show that the Skp-related proteins SKR-3, SKR-4 and SKR-5 act redundantly to promote thermotolerance with CUL-6. Finally, we screened F-box proteins that co-immunoprecipitate with CUL-6 and find that FBXA-158 promotes thermotolerance. In summary, we have defined the three core components and an F-box adaptor of a cullin-RING ligase complex that promotes thermotolerance as part of the IPR in C. elegans, which adds to our understanding of how organisms cope with proteotoxic stress.\n\nSignificance StatementIntracellular pathogen infection in the nematode Caenorhabditis elegans induces a robust transcriptional response as the host copes with infection. This response program includes several ubiquitin ligase components that are predicted to function in protein quality control. In this study, we show that these infection-induced ubiquitin ligase components form a protein complex that promotes increased tolerance of acute heat stress, an indicator of improved protein homeostasis capacity. These findings show that maintaining protein homeostasis may be a critical component of a multifaceted approach allowing the host to deal with stress caused by intracellular infection.

CRISPR/Cas technology allows the creation of double strand breaks and hence loss of function mutations at any location in the genome. This technology is now routine for many organisms and cell lines. Here we describe how CRISPR/Cas can be combined with other DNA manipulation techniques (e.g. homology-based repair, site-specific integration and Cre or FLP-mediated recombination) to create sophisticated tools to measure and manipulate gene activity. In one class of applications, a single site-specific insertion generates a transcriptional reporter, a loss-of function allele, and a tagged allele. In a second class of modifications, essential sequences are deleted and replaced with an integrase site, which serves as a platform for the creation of custom reporters, transcriptional drivers, conditional alleles and regulatory mutations. We describe how these tools and protocols can be implemented easily and efficiently. Importantly, we also highlight unanticipated failures, which serve as cautionary tales, and suggest mitigating measures. Our tools are designed for use in Drosophila but the lessons we draw are likely to be widely relevant.\n\nAUTHOR SUMMARYThe genome contains all the information that an organism needs to develop and function throughout its life. One of the goal of genetics is to decipher the role of all the genes (typically several thousands for an animal) present in the genome. One approach is to delete each gene and assay the consequences. Deletion of individual genes is now readily achieved with a technique called CRISPR/Cas9. However, simple genetic deletion provides limited information. Here we describe strains and DNA vectors that streamline the generation of more sophisticated genetic tools. We describe general means of creating alleles (genetic variants) that enable gene activity to be measured and experimentally modulated in space and time. Although the tools we describe are universally applicable, each gene requires special consideration. Based on our experience of successes and failures, we suggest measures to maximise the chances that engineered alleles serve their intended purpose. Although our methods are designed for use in Drosophila, they could be adapted to any organism that is amenable to CRISPR/Cas9 genome modification.

Flow cytometry estimates of genome sizes among species of Drosophila show a 3-fold variation, ranging from [~]127 Mb in Drosophila mercatorum to [~]400 Mb in Drosophila cyrtoloma. However, the assembled portion of the Muller F Element (orthologous to the fourth chromosome in Drosophila melanogaster) shows a nearly 14-fold variation in size, ranging from [~]1.3 Mb to > 18 Mb. Here, we present chromosome-level long read genome assemblies for four Drosophila species with expanded F Elements ranging in size from 2.3 Mb to 20.5 Mb. Each Muller Element is present as a single scaffold in each assembly. These assemblies will enable new insights into the evolutionary causes and consequences of chromosome size expansion.

The availabilty of reference genomes is accelerating rapidly, making their use in a wide variety of biological research programmes more feasible than ever. However, current Next-Generation Sequencing platforms are limited in the length of reads they are able to produce; requiring the correct order to be determined algorithmically. While there is a potential for errors in assembly algorithims, genetic pedigree data can be used to identify recombination events and, as recombination events are rare locally, test the order of sequences within a genome assembly. We use high-resolution population genomic data to test and compare the assembly quality of the three most recent reference genome assemblies for the western honey bee (Apis mellifera). As a model organism, there are several reference genomes available for A. mellifera with estimated recombination rates ranging from 19 cM/Mb to 37 cM/Mb. We identify a large degree of variation between assemblies and find that at least 20% of the most recent A. mellifera reference genome is mis-assembled. Providing an explanation for the degree of variation in estimated recombination rates and potentially influencing results downstream.

While post-transcriptional control is thought to be required at the periphery of neurons and glia, its extent is unclear. Here, we investigate systematically the spatial distribution and expression of mRNA at single molecule sensitivity and their corresponding proteins of 200 YFP trap protein trap lines across the intact Drosophila nervous system. 98% of the genes studied showed discordance between the distribution of mRNA and the proteins they encode in at least one region of the nervous system. These data suggest that post-transcriptional regulation is very common, helping to explain the complexity of the nervous system. We also discovered that 68.5% of these genes have transcripts present at the periphery of neurons, with 9.5% at the glial periphery. Peripheral transcripts include many potential new regulators of neurons, glia and their interactions. Our approach is applicable to most genes and tissues and includes powerful novel data annotation and visualisation tools for post-transcriptional regulation. Brief outlineA novel high resolution and sensitive approach to systematically co-visualise the distribution of mRNAs and proteins in the intact nervous system reveals that post-transcriptional regulation of gene expression is very common. The rich data landscape is provided as a browsable resource (link), using Zegami, a cloud-based data exploration platform (link). Our solution provides a paradigm for the characterisation of post-transcriptional regulation of most genes and model systems. HighlightsO_LI196/200 (98%) Drosophila genes show discordant RNA and protein expression in at least one nervous system region C_LIO_LI137/200 (68.5%) mRNAs are present in at least one synaptic compartment C_LIO_LINovel localised mRNA and protein discovered in periphery of glial processes C_LIO_LINew paradigm for analysis of post-transcriptional regulation and data exploration C_LI

Neuron-specific morphology and function are fundamentally tied to differences in gene expression across the nervous system. We previously generated a single cell RNA-seq (scRNA-Seq) dataset for every anatomical neuron class in the C. elegans hermaphrodite. Here we present a complementary set of bulk RNA-seq samples for 52 of the 118 canonical neuron classes in C. elegans. We show that the bulk RNA-seq dataset captures both lowly expressed and noncoding RNAs that are not detected in the scRNA-Seq profile, but also includes false positives due to contamination by other cell types. We present an analytical strategy that integrates the two datasets, preserving both the specificity of scRNA-Seq data and the sensitivity of bulk RNA-Seq. We show that this integrated dataset enhances the sensitivity and accuracy of transcript detection and differential gene analysis. In addition, we show that the bulk RNA-Seq data set detects differentially expressed non-coding RNAs across neuron types, including multiple families of non-polyadenylated transcripts. We propose that our approach provides a new strategy for interrogating gene expression by bridging the gap between bulk and single cell methodologies for transcriptomic studies. We suggest that these datasets advance the goal of delineating the mechanisms that define morphology and connectivity in the nervous system.

While Bacterial Artificial Chromosomes were once a key resource for the genomic community, they have been obviated, for sequencing purposes, by long-read technologies. Such libraries may now serve as a valuable resource for manipulating and assembling large genomic constructs. To enhance accessibility and comparison, we have developed a BAC restriction map database.

A central challenge of quantitative genetics is partitioning phenotypic variation into genetic and non-genetic components. These non-genetic components are usually interpreted as environmental effects; however, variation between genetically identical individuals in a common environment can still exhibit phenotypic variation. A traits resistance to variation is called robustness, though the genetics underlying it are poorly understood. Accordingly, we performed an association study on a previously studied, whole organism trait: robustness for flight performance. Using 197 of the Drosophila Genetic Reference Panel (DGRP) lines, we surveyed variation across single nucleotide polymorphisms, whole genes, and epistatic interactions to find genetic modifiers robustness for flight performance. There was an abundance of genes involved in the development of sensory organs and processing of external stimuli, supporting previous work that processing proprioceptive cues is important for affecting variation in flight performance. Additionally, we tested insertional mutants for their effect on robustness using candidate genes found to modify flight performance. These results suggest several genes involved in modulating a trait mean are also important for affecting trait variance, or robustness, as well. Article SummaryWe sought to understand the genetic architecture of robustness (variation in a trait caused by non-genetic factors) for flight performance. We used 197 Drosophila Genetic Reference Panel (DGRP) lines to find significant individual variants and pairs of epistatic interactions, many of which were involved in proprioception. Additionally, we validated significant genes identified from a prior study for the mean of flight performance, showing genes affecting trait means may also affect trait robustness.