Contribution of trans regulatory eQTL to cryptic genetic variation in C. elegans

Lifespan analysis of repeat expression reveals age-dependent upregulation of HERV-K in the neurotypical human brain

DNA repetitive sequences (or repeats) comprise over 50% of the human genome and have a crucial regulatory role, specifically regulating transcription machinery. The human brain is the tissue with the highest detectable repeat expression and dysregulations on the repeat activity are related to several neurological and neurodegenerative disorders, as repeat-derived products can stimulate a pro-inflammatory response. Even so, it is unclear how repeat expression acts on the aging neurotypical brain. Here, we leverage a large postmortem transcriptome cohort spanning the human lifespan to assess global repeat expression in the neurotypical brain. We identified 21,696 differentially expressed repeats (DERs) that varied across seven age bins (Prenatal; 0-15; 16-29; 30-39; 40-49; 50-59; 60+) across the caudate nucleus (n=271), dorsolateral prefrontal cortex (n=304), and hippocampus (n=310). Interestingly, we found that long interspersed nuclear elements and long terminal repeats (LTRs) DERs were the most abundant repeat families when comparing infants to early adolescence (0-15) with older adults (60+). Of these differentially regulated LTRs, we identified 17 shared across all brain regions, including increased expression of HERV-K-int in older adult brains (60+). Co-expression analysis from each of the three brain regions also showed repeats from the HERV subfamily were intramodular hubs in its subnetworks. While we do not observe a strong global relationship between repeat expression and age, we identified HERV-K as a repeat signature associated with the aging neurotypical brain. Our study is the first global assessment of repeat expression in the neurotypical brain.

Mondrian Map: Piet Mondrian's Abstraction for Differential Pathway Analysis

Motivation

Visualizing complex biological networks is a significant challenge, as traditional tools often struggle to represent data clearly and intuitively. Drawing inspiration from Piet Mondrian's abstract art style, we introduce Mondrian Map, a novel visualization tool that transforms the complexity of biological networks into a more organized, meaningful, and aesthetically appealing form.

Results

In our case study of glioma progression, Mondrian Map reveals distinct pathway patterns across multiple patient profiles at different time points. Afterwards, the significance of these distinctive pathways in glioblastoma multiforme development is validated by recent literature. Mondrian Map's visually intuitive representation of complex biological networks enables researchers to easily identify crucial pathways and potential therapeutic targets. Moreover, The potential applications of Mondrian Map extend beyond biology, making it a versatile tool across domains.

Availability and Implementation

The code was implemented in Python version 3.10 and is available through GitHub (github.com/fuad021/mondrian-map). The datasets used in this paper were retrieved from Glioma Longitudinal AnalySiS (GLASS) consortium.

Single Cell RNA Sequencing Provides Clues for the Developmental Genetic Basis of Syngnathidae's Evolutionary Adaptations

Seahorses, pipefishes, and seadragons are fishes from the family Syngnathidae that have evolved extraordinary traits including male pregnancy, elongated snouts, loss of teeth, and dermal bony armor. The developmental genetic and cellular changes that led to the evolution of these traits are largely unknown. Recent syngnathid genomes revealed suggestive gene content differences and provide the opportunity for detailed genetic analyses. We created a single cell RNA sequencing atlas of Gulf pipefish embryos to understand the developmental basis of four traits: derived head shape, toothlessness, dermal armor, and male pregnancy. We completed marker gene analyses, built genetic networks, and examined spatial expression of select genes. We identified osteochondrogenic mesenchymal cells in the elongating face that express regulatory genes bmp4, sfrp1a, and prdm16. We found no evidence for tooth primordia cells, and we observed re-deployment of osteoblast genetic networks in developing dermal armor. Finally, we found that epidermal cells expressed nutrient processing and environmental sensing genes, potentially relevant for the brooding environment. The examined pipefish evolutionary innovations are composed of recognizable cell types, suggesting derived features originate from changes within existing gene networks. Future work addressing syngnathid gene networks across multiple stages and species is essential for understanding how their novelties evolved.

Explorative Discovery of Gene Signatures and Clinotypes in Glioblastoma Cancer Through GeneTerrain Knowledge Map Representation

This study introduces the GeneTerrain Knowledge Map Representation (GTKM), a novel method for visualizing gene expression data in cancer research. GTKM leverages protein-protein interactions to graphically display differentially expressed genes (DEGs) on a 2-dimensional contour plot, offering a more nuanced understanding of gene interactions and expression patterns compared to traditional heatmap methods. The research demonstrates GTKM's utility through four case studies on glioblastoma (GBM) datasets, focusing on survival analysis, subtype identification, IDH1 mutation analysis, and drug sensitivities of different tumor cell lines. Additionally, a prototype website has been developed to showcase these findings, indicating the method's adaptability for various cancer types. The study reveals that GTKM effectively identifies gene patterns associated with different clinical outcomes in GBM, and its profiles enable the identification of sub-gene signature patterns crucial for predicting survival. The methodology promises significant advancements in precision medicine, providing a powerful tool for understanding complex gene interactions and identifying potential therapeutic targets in cancer treatment.

A deep profile of gene expression across 18 human cancers

Clinically and biologically valuable information may reside untapped in large cancer gene expression data sets. Deep unsupervised learning has the potential to extract this information with unprecedented efficacy but has thus far been hampered by a lack of biological interpretability and robustness. Here, we present DeepProfile, a comprehensive framework that addresses current challenges in applying unsupervised deep learning to gene expression profiles. We use DeepProfile to learn low-dimensional latent spaces for 18 human cancers from 50,211 transcriptomes. DeepProfile outperforms existing dimensionality reduction methods with respect to biological interpretability. Using DeepProfile interpretability methods, we show that genes that are universally important in defining the latent spaces across all cancer types control immune cell activation, while cancer type-specific genes and pathways define molecular disease subtypes. By linking DeepProfile latent variables to secondary tumor characteristics, we discover that tumor mutation burden is closely associated with the expression of cell cycle-related genes. DNA mismatch repair and MHC class II antigen presentation pathway expression, on the other hand, are consistently associated with patient survival. We validate these results through Kaplan-Meier analyses and nominate tumor-associated macrophages as an important source of survival-correlated MHC class II transcripts. Our results illustrate the power of unsupervised deep learning for discovery of novel cancer biology from existing gene expression data.

Gene expression variation underlying tissue-specific responses to copper stress in Drosophila melanogaster

Copper is one of a handful of biologically necessary heavy metals that is also a common environmental pollutant. Under normal conditions, copper ions are required for many key physiological processes. However, in excess, copper results in cell and tissue damage ranging in severity from temporary injury to permanent neurological damage. Because of its biological relevance, and because many conserved copper-responsive genes respond to nonessential heavy metal pollutants, copper resistance in Drosophila melanogaster is a useful model system with which to investigate the genetic control of the heavy metal stress response. Because heavy metal toxicity has the potential to differently impact specific tissues, we genetically characterized the control of the gene expression response to copper stress in a tissue-specific manner in this study. We assessed the copper stress response in head and gut tissue of 96 inbred strains from the Drosophila Synthetic Population Resource using a combination of differential expression analysis and expression quantitative trait locus mapping. Differential expression analysis revealed clear patterns of tissue-specific expression. Tissue and treatment specific responses to copper stress were also detected using expression quantitative trait locus mapping. Expression quantitative trait locus associated with MtnA, Mdr49, Mdr50, and Sod3 exhibited both genotype-by-tissue and genotype-by-treatment effects on gene expression under copper stress, illuminating tissue- and treatment-specific patterns of gene expression control. Together, our data build a nuanced description of the roles and interactions between allelic and expression variation in copper-responsive genes, provide valuable insight into the genomic architecture of susceptibility to metal toxicity, and highlight candidate genes for future functional characterization.

The effect of developmental variation on expression QTLs in a multi parental Caenorhabditis elegans population

Regulation of gene expression plays a crucial role in developmental processes and adaptation to changing environments. expression quantitative trait locus (eQTL) mapping is a technique used to study the genetic regulation of gene expression using the transcriptomes of recombinant inbred lines (RILs). Typically, the age of the inbred lines at the time of RNA sampling is carefully controlled. This is necessary because the developmental process causes changes in gene expression, complicating the interpretation of eQTL mapping experiments. However, due to genetics and variation in ambient micro-environments, organisms can differ in their "developmental age," even if they are of the same chronological age. As a result, eQTL patterns are affected by developmental variation in gene expression. The model organism Caenorhabditis elegans is particularly suited for studying the effect of developmental variation on eQTL mapping patterns. In a span of days, C. elegans transitions from embryo through 4 larval stages to adult while undergoing massive changes to its transcriptome. Here, we use C. elegans to investigate the effect of developmental age variation on eQTL patterns and present a normalization procedure. We used dynamical eQTL mapping, which includes the developmental age as a cofactor, to separate the variation in development from genotypic variation and explain variation in gene expression levels. We compare classical single marker eQTL mapping and dynamical eQTL mapping using RNA-seq data of ∼200 multi-parental RILs of C. elegans. The results show that (1) many eQTLs are caused by developmental variation, (2) most trans-bands are developmental QTLs, and (3) dynamical eQTL mapping detects additional eQTLs not found with classical eQTL mapping. We recommend that correction for variation in developmental age should be strongly considered in eQTL mapping studies given the large impact of processes like development on the transcriptome.

Genome-wide expression QTL mapping reveals the highly dynamic regulatory landscape of a major wheat pathogen

BACKGROUND

In agricultural ecosystems, outbreaks of diseases are frequent and pose a significant threat to food security. A successful pathogen undergoes a complex and well-timed sequence of regulatory changes to avoid detection by the host immune system; hence, well-tuned gene regulation is essential for survival. However, the extent to which the regulatory polymorphisms in a pathogen population provide an adaptive advantage is poorly understood.

RESULTS

We used Zymoseptoria tritici, one of the most important pathogens of wheat, to generate a genome-wide map of regulatory polymorphism governing gene expression. We investigated genome-wide transcription levels of 146 strains grown under nutrient starvation and performed expression quantitative trait loci (eQTL) mapping. We identified cis-eQTLs for 65.3% of all genes and the majority of all eQTL loci are within 2kb upstream and downstream of the transcription start site (TSS). We also show that polymorphism in different gene elements contributes disproportionally to gene expression variation. Investigating regulatory polymorphism in gene categories, we found an enrichment of regulatory variants for genes predicted to be important for fungal pathogenesis but with comparatively low effect size, suggesting a separate layer of gene regulation involving epigenetics. We also show that previously reported trait-associated SNPs in pathogen populations are frequently cis-regulatory variants of neighboring genes with implications for the trait architecture.

CONCLUSIONS

Overall, our study provides extensive evidence that single populations segregate large-scale regulatory variation and are likely to fuel rapid adaptation to resistant hosts and environmental change.

Genome-wide mapping of regulatory variants for temperature- and salinity-adaptive genes reveals genetic basis of genotype-by-environment interaction in Crassostrea ariakensis

Regulatory variants in gene expression serve as bridges linking genetic variation and phenotypic plasticity. Environmental conditions typically influence the effects of regulatory variants on phenotypic plasticity; however, such genotype-by-environment interactions (G × E) are poorly understood. This study aimed to investigate the genetic basis of G × E in estuarine oyster (Crassostrea ariakensis), which is an important model animal for studying environmental adaption owing to its high plasticity and large intraspecific divergence. Genome-wide mapping of expression quantitative trait loci (eQTLs) for 23 environmental adaptive genes was performed for 256 estuarine oysters. We identified 1194 eQTL single nucleotide polymorphisms (eSNPs), including 433 cis-eSNPs in four genes and 722 trans-eSNPs in eight genes. The expression variation explanation of cis-eSNPs (9.95%) was significantly higher than that of trans-eSNPs (9.15%). We specifically showed cis- and trans-eSNPs with high linkage disequilibrium (LD) for Traf7, Slc6a5, Ggt, and Dap3. For example, we identified a cis-regulatory LD block containing 68 cis-eSNP and a trans-regulatory LD block, including 20 trans-eSNPs in Traf7. A high proportion (85%) of 40 vital eSNPs exhibited significant G × E effects. We identified crossing and nonparallel interactions of G × E, with the tag cis-eSNPs of Baat and Slc6a5 as representatives. Our results indicated that cis-eQTLs are highly conserved. This study provides insights into the understanding of adaptive evolutionary mechanisms and phenotypic response prediction to variable environments, as well as the genetic improvement for superior adaptive traits for genetic resource conservation and aquaculture.

Whole blood mitochondrial copy number in clinical populations with mood disorders: a meta-analysis

Background

Major depressive disorder (MDD) and bipolar disorder (BD), are globally prevalent, contributing to significant disease burden and adverse health outcomes. These mood disorders are associated with changes in many aspects of brain reward pathways, yet cellular and molecular changes in the brain are not readily available in clinical populations. Therefore, the use of biomarkers as proxies for changes in the brain are necessary. The proliferation of mitochondria in blood has emerged as a potentially useful biomarker, yet a clear consensus on how these mood disorders impact mitochondrial DNA copy number (mtDNAcn) has not been reached.

Methods

Following PRISMA guidelines for a systematic search, 22 papers met inclusion criteria for meta-analysis (10 MDD, 10 BD, 2 both MDD and BD). We extracted demographic, disorder, and methodological information with mtDNAcn. Using the metafor package for R, calculated effect sizes were used in random effects or meta regression models for MDD and BD.

Results

Our results show a trending increase in mtDNAcn in patients with MDD, which reaches significance when one study with outlying demographic characteristics is excluded. Overall, there was no effect of BD on mtDNAcn, however, further subgroup and meta-regression analysis indicated the effects on mtDNAcn are dependent on BD type.

Conclusions

Together our data suggest whole blood/leukocyte mtDNAcn may be a useful biomarker for mood disorders, with MDD and BD Type II associated with higher mtDNAcn, and BD Type I associated with lower mtDNAcn. Further study of blood mtDNAcn could predict downstream health outcomes or treatment responsivity in individuals with mood disorders.

A novel endoplasmic reticulum adaptation is critical for the long-lived Caenorhabditis elegans rpn-10 proteasomal mutant

The loss of proteostasis due to reduced efficiency of protein degradation pathways plays a key role in multiple age-related diseases and is a hallmark of the aging process. Paradoxically, we have previously reported that the Caenorhabditis elegans rpn-10(ok1865) mutant, which lacks the RPN-10/RPN10/PSMD4 subunit of the 19S regulatory particle of the 26S proteasome, exhibits enhanced cytosolic proteostasis, elevated stress resistance and extended lifespan, despite possessing reduced proteasome function. However, the response of this mutant against threats to endoplasmic reticulum (ER) homeostasis and proteostasis was unknown. Here, we find that the rpn-10 mutant is highly ER stress resistant compared to the wildtype. Under unstressed conditions, the ER unfolded protein response (UPR) is activated in the rpn-10 mutant as signified by increased xbp-1 splicing. This primed response appears to alter ER homeostasis through the upregulated expression of genes involved in ER protein quality control (ERQC), including those in the ER-associated protein degradation (ERAD) pathway. Pertinently, we find that ERQC is critical for the rpn-10 mutant longevity. These changes also alter ER proteostasis, as studied using the C. elegans alpha-1 antitrypsin (AAT) deficiency model, which comprises an intestinal ER-localised transgenic reporter of an aggregation-prone form of AAT called ATZ. The rpn-10 mutant shows a significant reduction in the accumulation of the ATZ reporter, thus indicating that its ER proteostasis is augmented. Via a genetic screen for suppressors of decreased ATZ aggregation in the rpn-10 mutant, we then identified ecps-2/H04D03.3, a novel ortholog of the proteasome-associated adaptor and scaffold protein ECM29/ECPAS. We further show that ecps-2 is required for improved ER proteostasis as well as lifespan extension of the rpn-10 mutant. Thus, we propose that ECPS-2-proteasome functional interactions, alongside additional putative molecular processes, contribute to a novel ERQC adaptation which underlies the superior proteostasis and longevity of the rpn-10 mutant.

Common as well as unique methylation-sensitive DNA regulatory elements in three mammalian SLC9C1 genes

The SLC9C1 gene (which encodes the NHE10 protein) is essential for male fertility in both mice and humans, however the epigenetic mechanisms regulating its testis/sperm-specific gene expression have yet to be studied. Here we identify and characterize DNA regulatory elements of the SLC9C1 gene across three mammalian species: mouse, rat, and human. First, in silico analysis of these mammalian SLC9C1 genes identified a CpG island located upstream of the transcription start site in the same relative position in all three genes. Further analysis reveals that this CpG island behaves differently, with respect to gene regulatory activity, in the mouse SLC9C1 gene than it does in the rat and human SLC9C1 gene. The mouse SLC9C1 CpG island displays strong promoter activity by itself and seems to have a stronger gene regulatory effect than either the rat or human SLC9C1 CpG islands. While the function of the upstream SLC9C1 CpG island may be divergent across the three studied species, it appears that the promoters of these three mammalian SLC9C1 genes share similar DNA methylation-sensitive regulatory mechanisms. All three SLC9C1 promoter regions are differentially methylated in lung and testis, being more hypermethylated in lung relative to the testis, and DNA sequence alignments provide strong evidence of primary sequence conservation. Luciferase assays reveal that in vitro methylation of constructs containing different elements of the three SLC9C1 genes largely exhibit methylation-sensitive promoter activity (reduced promoter activity when methylated) in both HEK 293 and GC-1spg cells. In total, our data suggest that the DNA methylation-sensitive elements of the mouse, rat, and human SLC9C1 promoters are largely conserved, while the upstream SLC9C1 CpG island common to all three species seems to perform a different function in mouse than it does in rat and human. This work provides evidence that while homologous genes can all be regulated by DNA methylation-dependent epigenetic mechanisms, the location of the specific cis-regulatory elements responsible for this regulation can differ across species.

Measuring changes in Plasmodium falciparum census population size in response to sequential malaria control interventions

Here we introduce a new endpoint "census population size" to evaluate the epidemiology and control of Plasmodium falciparum infections, where the parasite, rather than the infected human host, is the unit of measurement. To calculate census population size, we rely on a definition of parasite variation known as multiplicity of infection (M O I v a r ), based on the hyper-diversity of the v a r multigene family. We present a Bayesian approach to estimate M O I v a r from sequencing and counting the number of unique DBLα tags (or DBLα types) of v a r genes, and derive from it census population size by summation of M O I v a r in the human population. We track changes in this parasite population size and structure through sequential malaria interventions by indoor residual spraying (IRS) and seasonal malaria chemoprevention (SMC) from 2012 to 2017 in an area of high-seasonal malaria transmission in northern Ghana. Following IRS, which reduced transmission intensity by > 90% and decreased parasite prevalence by ~40-50%, significant reductions in v a r diversity, M O I v a r , and population size were observed in ~2,000 humans across all ages. These changes, consistent with the loss of diverse parasite genomes, were short lived and 32-months after IRS was discontinued and SMC was introduced, v a r diversity and population size rebounded in all age groups except for the younger children (1-5 years) targeted by SMC. Despite major perturbations from IRS and SMC interventions, the parasite population remained very large and retained the v a r population genetic characteristics of a high-transmission system (high v a r diversity; low v a r repertoire similarity) demonstrating the resilience of P. falciparum to short-term interventions in high-burden countries of sub-Saharan Africa.

Gene expression variation underlying tissue-specific responses to copper stress in Drosophila melanogaster

Copper is one of a handful of biologically necessary heavy metals that is also a common environmental pollutant. Under normal conditions, copper ions are required for many key physiological processes. However, in excess, copper quickly results in cell and tissue damage that can range in severity from temporary injury to permanent neurological damage. Because of its biological relevance, and because many conserved copper-responsive genes also respond to other non-essential heavy metal pollutants, copper resistance in Drosophila melanogaster is a useful model system with which to investigate the genetic control of the response to heavy metal stress. Because heavy metal toxicity has the potential to differently impact specific tissues, we genetically characterized the control of the gene expression response to copper stress in a tissue-specific manner in this study. We assessed the copper stress response in head and gut tissue of 96 inbred strains from the Drosophila Synthetic Population Resource (DSPR) using a combination of differential expression analysis and expression quantitative trait locus (eQTL) mapping. Differential expression analysis revealed clear patterns of tissue-specific expression, primarily driven by a more pronounced gene expression response in gut tissue. eQTL mapping of gene expression under control and copper conditions as well as for the change in gene expression following copper exposure (copper response eQTL) revealed hundreds of genes with tissue-specific local cis-eQTL and many distant trans-eQTL. eQTL associated with MtnA, Mdr49, Mdr50, and Sod3 exhibited genotype by environment effects on gene expression under copper stress, illuminating several tissue- and treatment-specific patterns of gene expression control. Together, our data build a nuanced description of the roles and interactions between allelic and expression variation in copper-responsive genes, provide valuable insight into the genomic architecture of susceptibility to metal toxicity, and highlight many candidate genes for future functional characterization.

Gene editing without ex vivo culture evades genotoxicity in human hematopoietic stem cells

Gene editing the BCL11A erythroid enhancer is a validated approach to fetal hemoglobin (HbF) induction for β-hemoglobinopathy therapy, though heterogeneity in edit allele distribution and HbF response may impact its safety and efficacy. Here we compared combined CRISPR-Cas9 endonuclease editing of the BCL11A +58 and +55 enhancers with leading gene modification approaches under clinical investigation. We found that combined targeting of the BCL11A +58 and +55 enhancers with 3xNLS-SpCas9 and two sgRNAs resulted in superior HbF induction, including in engrafting erythroid cells from sickle cell disease (SCD) patient xenografts, attributable to simultaneous disruption of core half E-box/GATA motifs at both enhancers. We corroborated prior observations that double strand breaks (DSBs) could produce unintended on- target outcomes in hematopoietic stem and progenitor cells (HSPCs) such as long deletions and centromere-distal chromosome fragment loss. We show these unintended outcomes are a byproduct of cellular proliferation stimulated by ex vivo culture. Editing HSPCs without cytokine culture bypassed long deletion and micronuclei formation while preserving efficient on-target editing and engraftment function. These results indicate that nuclease editing of quiescent hematopoietic stem cells (HSCs) limits DSB genotoxicity while maintaining therapeutic potency and encourages efforts for in vivo delivery of nucleases to HSCs.

Decoupling of evolutionary changes in mRNA and protein levels

Variation in gene expression across lineages is thought to explain much of the observed phenotypic variation and adaptation. The protein is closer to the target of natural selection but gene expression is typically measured as the amount of mRNA. The broad assumption that mRNA levels are good proxies for protein levels has been undermined by a number of studies reporting moderate or weak correlations between the two measures across species. One biological explanation for this discrepancy is that there has been compensatory evolution between the mRNA level and regulation of translation. However, we do not understand the evolutionary conditions necessary for this to occur nor the expected strength of the correlation between mRNA and protein levels. Here we develop a theoretical model for the coevolution of mRNA and protein levels and investigate the dynamics of the model over time. We find that compensatory evolution is widespread when there is stabilizing selection on the protein level, which is true across a variety of regulatory pathways. When the protein level is under directional selection, the mRNA level of a gene and its translation rate of the same gene were negatively correlated across lineages but positively correlated across genes. These findings help explain results from comparative studies of gene expression and potentially enable researchers to disentangle biological and statistical hypotheses for the mismatch between transcriptomic and proteomic studies.

Plasticity of maternal environment-dependent expression-QTLs of tomato seeds

Seeds are essential for plant reproduction, survival, and dispersal. Germination ability and successful establishment of young seedlings strongly depend on seed quality and on environmental factors such as nutrient availability. In tomato (Solanum lycopersicum) and many other species, seed quality and seedling establishment characteristics are determined by genetic variation, as well as the maternal environment in which the seeds develop and mature. The genetic contribution to variation in seed and seedling quality traits and environmental responsiveness can be estimated at transcriptome level in the dry seed by mapping genomic loci that affect gene expression (expression QTLs) in contrasting maternal environments. In this study, we applied RNA-sequencing to construct a linkage map and measure gene expression of seeds of a tomato recombinant inbred line (RIL) population derived from a cross between S. lycopersicum (cv. Moneymaker) and S. pimpinellifolium (G1.1554). The seeds matured on plants cultivated under different nutritional environments, i.e., on high phosphorus or low nitrogen. The obtained single-nucleotide polymorphisms (SNPs) were subsequently used to construct a genetic map. We show how the genetic landscape of plasticity in gene regulation in dry seeds is affected by the maternal nutrient environment. The combined information on natural genetic variation mediating (variation in) responsiveness to the environment may contribute to knowledge-based breeding programs aiming to develop crop cultivars that are resilient to stressful environments.

PolyAMiner-Bulk: A Machine Learning Based Bioinformatics Algorithm to Infer and Decode Alternative Polyadenylation Dynamics from bulk RNA-seq data

More than half of human genes exercise alternative polyadenylation (APA) and generate mRNA transcripts with varying 3' untranslated regions (UTR). However, current computational approaches for identifying cleavage and polyadenylation sites (C/PASs) and quantifying 3'UTR length changes from bulk RNA-seq data fail to unravel tissue- and disease-specific APA dynamics. Here, we developed a next-generation bioinformatics algorithm and application, PolyAMiner-Bulk, that utilizes an attention-based machine learning architecture and an improved vector projection-based engine to infer differential APA dynamics accurately. When applied to earlier studies, PolyAMiner-Bulk accurately identified more than twice the number of APA changes in an RBM17 knockdown bulk RNA-seq dataset compared to current generation tools. Moreover, on a separate dataset, PolyAMiner-Bulk revealed novel APA dynamics and pathways in scleroderma pathology and identified differential APA in a gene that was identified as being involved in scleroderma pathogenesis in an independent study. Lastly, we used PolyAMiner-Bulk to analyze the RNA-seq data of post-mortem prefrontal cortexes from the ROSMAP data consortium and unraveled novel APA dynamics in Alzheimer's Disease. Our method, PolyAMiner-Bulk, creates a paradigm for future alternative polyadenylation analysis from bulk RNA-seq data.

A hepatitis B virus (HBV) sequence variation graph improves sequence alignment and sample-specific consensus sequence construction for genetic analysis of HBV

Hepatitis B virus (HBV) remains a global public health concern, with over 250 million individuals living with chronic HBV infection (CHB) and no curative therapy currently available. Viral diversity is associated with CHB pathogenesis and immunological control of infection. Improved methods to characterize the viral genome at both the population and intra-host level could aid drug development efforts. Conventionally, HBV sequencing data are aligned to a linear reference genome and only sequences capable of aligning to the reference are captured for analysis. Reference selection has additional consequences, including sample-specific 'consensus' sequence construction. It remains unclear how to select a reference from available sequences and whether a single reference is sufficient for genetic analyses. Using simulated short-read sequencing data generated from full-length publicly available HBV genome sequences and HBV sequencing data from a longitudinally sampled individual with CHB, we investigate alternative graph-based alignment approaches. We demonstrate that using a phylogenetically representative 'genome graph' for alignment, rather than linear reference sequences, avoids issues of reference ambiguity, improves alignment, and facilitates the construction of sample-specific consensus sequences genetically similar to an individual's infection. Graph-based methods can therefore improve efforts to characterize the genetics of viral pathogens, including HBV, and may have broad implications in host pathogen research.

Trans-regulatory changes underpin the evolution of the Drosophila immune response

When an animal is infected, the expression of a large suite of genes is changed, resulting in an immune response that can defend the host. Despite much evidence that the sequence of proteins in the immune system can evolve rapidly, the evolution of gene expression is comparatively poorly understood. We therefore investigated the transcriptional response to parasitoid wasp infection in Drosophila simulans and D. sechellia. Although these species are closely related, there has been a large scale divergence in the expression of immune-responsive genes in their two main immune tissues, the fat body and hemocytes. Many genes, including those encoding molecules that directly kill pathogens, have cis regulatory changes, frequently resulting in large differences in their expression in the two species. However, these changes in cis regulation overwhelmingly affected gene expression in immune-challenged and uninfected animals alike. Divergence in the response to infection was controlled in trans. We argue that altering trans-regulatory factors, such as signalling pathways or immune modulators, may allow natural selection to alter the expression of large numbers of immune-responsive genes in a coordinated fashion.

A fundamental question in biology is the nature of the genetic changes underlying evolutionary change, and immune systems provide an ideal system to examine this as they tend to evolve fast as animals adapt to an ever-changing array of parasites and pathogens. Comparing two species of the fruit fly Drosophila, we found that the transcriptional response to infection evolves extremely fast. However, changes in cis (where the genetic change is on the same DNA molecule as the gene in question) and trans (where the genetic change can be elsewhere in the genome) are playing different roles. Changes in cis frequently caused large differences in immune gene expression between species, but these differences were seen regardless of whether the animal was infected. In contrast, changes in trans were responsible for altering how gene expression changes in response to infection. Immune responses are complex and multifaceted, requiring the expression of many genes to be altered in a tightly regulated manner when the animal is infected. Natural selection acting on trans regulatory factors may allow the expression of many downstream genes to be altered in a coordinated fashion.

Deleterious mutations and the rare allele burden on rice gene expression

Deleterious genetic variation is maintained in populations at low frequencies. Under a model of stabilizing selection, rare (and presumably deleterious) genetic variants are associated with increase or decrease in gene expression from some intermediate optimum. We investigate this phenomenon in a population of largely Oryza sativa ssp. indica rice landraces under normal unstressed wet and stressful drought field conditions. We include single nucleotide polymorphisms, insertion/deletion mutations, and structural variants in our analysis and find a stronger association between rare variants and gene expression outliers under the stress condition. We also show an association of the strength of this rare variant effect with linkage, gene expression levels, network connectivity, local recombination rate, and fitness consequence scores, consistent with the stabilizing selection model of gene expression.

Maternal obesity, pregnancy weight gain, and birth weight and risk of colorectal cancer

OBJECTIVE

Colorectal cancer (CRC) is a leading cause of cancer-related death worldwide. Obesity is a well-established risk factor for CRC, and fetal or developmental origins of obesity may underlie its effect on cancer in adulthood. We examined associations of maternal obesity, pregnancy weight gain, and birth weight and CRC in adult offspring.

DESIGN

The Child Health and Development Studies is a prospective cohort of women receiving prenatal care between 1959 and 1966 in Oakland, California (N=18 751 live births among 14 507 mothers). Clinical information was abstracted from mothers' medical records 6 months prior to pregnancy through delivery. Diagnoses of CRC in adult (age ≥18 years) offspring were ascertained through 2019 by linkage with the California Cancer Registry. We used Cox proportional hazards models to estimate adjusted HR (aHR); we examined effect measure modification using single-referent models to estimate the relative excess risk due to interaction (RERI).

RESULTS

68 offspring were diagnosed with CRC over 738 048 person-years of follow-up, and half (48.5%) were diagnosed younger than age 50 years. Maternal obesity (≥30 kg/m²) increased the risk of CRC in offspring (aHR 2.51, 95% CI 1.05 to 6.02). Total weight gain modified the association of rate of early weight gain (RERI -4.37, 95% CI -9.49 to 0.76), suggesting discordant growth from early to late pregnancy increases risk. There was an elevated association with birth weight (≥4000 g: aHR 1.95, 95% CI 0.8 to 4.38).

CONCLUSION

Our results suggest that in utero events are important risk factors for CRC and may contribute to increasing incidence rates in younger adults.

The impact of species-wide gene expression variation on Caenorhabditis elegans complex traits

Phenotypic variation in organism-level traits has been studied in Caenorhabditis elegans wild strains, but the impacts of differences in gene expression and the underlying regulatory mechanisms are largely unknown. Here, we use natural variation in gene expression to connect genetic variants to differences in organismal-level traits, including drug and toxicant responses. We perform transcriptomic analyses on 207 genetically distinct C. elegans wild strains to study natural regulatory variation of gene expression. Using this massive dataset, we perform genome-wide association mappings to investigate the genetic basis underlying gene expression variation and reveal complex genetic architectures. We find a large collection of hotspots enriched for expression quantitative trait loci across the genome. We further use mediation analysis to understand how gene expression variation could underlie organism-level phenotypic variation for a variety of complex traits. These results reveal the natural diversity in gene expression and possible regulatory mechanisms in this keystone model organism, highlighting the promise of using gene expression variation to understand how phenotypic diversity is generated.

The genetic architecture underlying body-size traits plasticity over different temperatures and developmental stages in Caenorhabditis elegans

Most ectotherms obey the temperature-size rule, meaning they grow larger in a colder environment. This raises the question of how the interplay between genes and temperature affects the body size of ectotherms. Despite the growing body of literature on the physiological life-history and molecular genetic mechanism underlying the temperature-size rule, the overall genetic architecture orchestrating this complex phenotype is not yet fully understood. One approach to identify genetic regulators of complex phenotypes is quantitative trait locus (QTL) mapping. Here, we explore the genetic architecture of body-size phenotypes, and plasticity of body-size phenotypes at different temperatures using Caenorhabditis elegans as a model ectotherm. We used 40 recombinant inbred lines (RILs) derived from N2 and CB4856, which were reared at four different temperatures (16, 20, 24, and 26 °C) and measured at two developmental stages (L4 and adult). The animals were measured for body length, width at vulva, body volume, length/width ratio, and seven other body-size traits. The genetically diverse RILs varied in their body-size phenotypes with heritabilities ranging from 0.0 to 0.99. We detected 18 QTL underlying the body-size traits across all treatment combinations, with the majority clustering on Chromosome X. We hypothesize that the Chromosome X QTL could result from a known pleiotropic regulator-npr-1-known to affect the body size of C. elegans through behavioral changes. We also found five plasticity QTL of body-size traits where three colocalized with body-size QTL. In conclusion, our findings shed more light on multiple loci affecting body-size plasticity and the possibility of co-regulation of traits and traits plasticity by the same loci under different environments.

Neuronal GPCR NMUR-1 regulates distinct immune responses to different pathogens

A key question in current immunology is how the innate immune system generates high levels of specificity. Using the Caenorhabditis elegans model system, we demonstrate that functional loss of NMUR-1, a neuronal G-protein-coupled receptor homologous to mammalian receptors for the neuropeptide neuromedin U, has diverse effects on C. elegans innate immunity against various bacterial pathogens. Transcriptomic analyses and functional assays reveal that NMUR-1 modulates C. elegans transcription activity by regulating the expression of transcription factors involved in binding to RNA polymerase II regulatory regions, which, in turn, controls the expression of distinct immune genes in response to different pathogens. These results uncover a molecular basis for the specificity of C. elegans innate immunity. Given the evolutionary conservation of NMUR-1 signaling in immune regulation across multicellular organisms, our study could provide mechanistic insights into understanding the specificity of innate immunity in other animals, including mammals.

Balancing Selection of the Intracellular Pathogen Response in Natural Caenorhabditis elegans Populations

Genetic variation in host populations may lead to differential viral susceptibilities. Here, we investigate the role of natural genetic variation in the Intracellular Pathogen Response (IPR), an important antiviral pathway in the model organism Caenorhabditis elegans against Orsay virus (OrV). The IPR involves transcriptional activity of 80 genes including the pals-genes. We examine the genetic variation in the pals-family for traces of selection and explore the molecular and phenotypic effects of having distinct pals-gene alleles. Genetic analysis of 330 global C. elegans strains reveals that genetic diversity within the IPR-related pals-genes can be categorized in a few haplotypes worldwide. Importantly, two key IPR regulators, pals-22 and pals-25, are in a genomic region carrying signatures of balancing selection, suggesting that different evolutionary strategies exist in IPR regulation. We infected eleven C. elegans strains that represent three distinct pals-22 pals-25 haplotypes with Orsay virus to determine their susceptibility. For two of these strains, N2 and CB4856, the transcriptional response to infection was also measured. The results indicate that pals-22 pals-25 haplotype shapes the defense against OrV and host genetic variation can result in constitutive activation of IPR genes. Our work presents evidence for balancing genetic selection of immunity genes in C. elegans and provides a novel perspective on the functional diversity that can develop within a main antiviral response in natural host populations.

A large chromosomal inversion shapes gene expression in seaweed flies (Coelopa frigida)

Inversions often underlie complex adaptive traits, but the genic targets inside them are largely unknown. Gene expression profiling provides a powerful way to link inversions with their phenotypic consequences. We examined the effects of the Cf-Inv(1) inversion in the seaweed fly Coelopa frigida on gene expression variation across sexes and life stages. Our analyses revealed that Cf-Inv(1) shapes global expression patterns, most likely via linked variation, but the extent of this effect is variable, with much stronger effects in adults than larvae. Furthermore, within adults, both common as well as sex-specific patterns were found. The vast majority of these differentially expressed genes mapped to Cf-Inv(1). However, genes that were differentially expressed in a single context (i.e., in males, females, or larvae) were more likely to be located outside of Cf-Inv(1). By combining our findings with genomic scans for environmentally associated SNPs, we were able to pinpoint candidate variants in the inversion that may underlie mechanistic pathways that determine phenotypes. Together the results of this study, combined with previous findings, support the notion that the polymorphic Cf-Inv(1) inversion in this species is a major factor shaping both coding and regulatory variation resulting in highly complex adaptive effects.

Single-nucleus RNA sequencing of plant tissues using a nanowell-based system

Single-cell genomics provides unprecedented potential for research on plant development and environmental responses. Here, we introduce a generic procedure for plant nucleus isolation combined with nanowell-based library preparation. Our method enables the transcriptome analysis of thousands of individual plant nuclei. It serves as an alternative to the use of protoplast isolation, which is currently a standard methodology for plant single-cell genomics, although it can be challenging for some plant tissues. We show the applicability of our nucleus isolation method by using different plant materials from different species. The potential of our single-nucleus RNA sequencing method is shown through the characterization of transcriptomes of seedlings and developing flowers from Arabidopsis thaliana. We evaluated the transcriptome dynamics during the early stages of anther development, identified stage-specific activities of transcription factors regulating this process, and predicted potential target genes of these transcription factors. Our nucleus isolation procedure can be applied in different plant species and tissues, thus expanding the toolkit for plant single-cell genomics experiments.

The genetics of gene expression in a Caenorhabditis elegans multiparental recombinant inbred line population

Studying genetic variation of gene expression provides a powerful way to unravel the molecular components underlying complex traits. Expression quantitative trait locus (eQTL) studies have been performed in several different model species, yet most of these linkage studies have been based on the genetic segregation of two parental alleles. Recently, we developed a multiparental 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 1789 genes differentially expressed between the parental lines. Transgression, expression beyond any of the parental lines in the mpRILs, was found for 7896 genes. For expression QTL mapping almost 9000 SNPs were available. By combining these SNPs and the RNA-seq profiles of the mpRILs, we detected almost 6800 eQTLs. Most trans-eQTLs (63%) co-locate in six newly identified trans-bands. The trans-eQTLs found in previous two-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 multiallelic eQTLs and systems genetics studying the genotype–phenotype relationship.

Heat Stress Reduces the Susceptibility of Caenorhabditis elegans to Orsay Virus Infection

The nematode Caenorhabditis elegans has been a versatile model for understanding the molecular responses to abiotic stress and pathogens. In particular, the response to heat stress and virus infection has been studied in detail. The Orsay virus (OrV) is a natural virus of C. elegans and infection leads to intracellular infection and proteostatic stress, which activates the intracellular pathogen response (IPR). IPR related gene expression is regulated by the genes pals-22 and pals-25, which also control thermotolerance and immunity against other natural pathogens. So far, we have a limited understanding of the molecular responses upon the combined exposure to heat stress and virus infection. We test the hypothesis that the response of C. elegans to OrV infection and heat stress are co-regulated and may affect each other. We conducted a combined heat-stress-virus infection assay and found that after applying heat stress, the susceptibility of C. elegans to OrV was decreased. This difference was found across different wild types of C. elegans. Transcriptome analysis revealed a list of potential candidate genes associated with heat stress and OrV infection. Subsequent mutant screens suggest that pals-22 provides a link between viral response and heat stress, leading to enhanced OrV tolerance of C. elegans after heat stress.

From QTL to gene: C. elegans facilitates discoveries of the genetic mechanisms underlying natural variation

Although many studies have examined quantitative trait variation across many species, only a small number of genes and thereby molecular mechanisms have been discovered. Without these data, we can only speculate about evolutionary processes that underlie trait variation. Here, we review how quantitative and molecular genetics in the nematode Caenorhabditis elegans led to the discovery and validation of 37 quantitative trait genes over the past 15 years. Using these data, we can start to make inferences about evolution from these quantitative trait genes, including the roles that coding versus noncoding variation, gene family expansion, common versus rare variants, pleiotropy, and epistasis play in trait variation across this species.

Cryptic genetic variation in a heat shock protein modifies the outcome of a mutation affecting epidermal stem cell development in C. elegans

A fundamental question in medical genetics is how the genetic background modifies the phenotypic outcome of mutations. We address this question by focusing on the seam cells, which display stem cell properties in the epidermis of Caenorhabditis elegans. We demonstrate that a putative null mutation in the GATA transcription factor egl-18, which is involved in seam cell fate maintenance, is more tolerated in the CB4856 isolate from Hawaii than the lab reference strain N2 from Bristol. We identify multiple quantitative trait loci (QTLs) underlying the difference in phenotype expressivity between the two isolates. These QTLs reveal cryptic genetic variation that reinforces seam cell fate through potentiating Wnt signalling. Within one QTL region, a single amino acid deletion in the heat shock protein HSP-110 in CB4856 is sufficient to modify Wnt signalling and seam cell development, highlighting that natural variation in conserved heat shock proteins can shape phenotype expressivity.

How the genetic background modifies the expression of mutations is a key question that is addressed in this study in the context of seam cell development in Caenorhabditis elegans isolates. One amino acid deletion in a conserved heat shock protein is sufficient to shape phenotype expressivity upon mutation of a GATA transcription factor.

Punctuated Loci on Chromosome IV Determine Natural Variation in Orsay Virus Susceptibility of Caenorhabditis elegans Strains Bristol N2 and Hawaiian CB4856

Host-pathogen interactions play a major role in evolutionary selection and shape natural genetic variation. The genetically distinct Caenorhabditis elegans strains, Bristol N2 and Hawaiian CB4856, are differentially susceptible to the Orsay virus (OrV). Here, we report the dissection of the genetic architecture of susceptibility to OrV infection. We compare OrV infection in the relatively resistant wild-type CB4856 strain to the more susceptible canonical N2 strain. To gain insight into the genetic architecture of viral susceptibility, 52 fully sequenced recombinant inbred lines (CB4856 × N2 RILs) were exposed to OrV. This led to the identification of two loci on chromosome IV associated with OrV resistance. To verify the two loci and gain additional insight into the genetic architecture controlling virus infection, introgression lines (ILs) that together cover chromosome IV, were exposed to OrV. Of the 27 ILs used, 17 had an CB4856 introgression in an N2 background, and 10 had an N2 introgression in a CB4856 background. Infection of the ILs confirmed and fine-mapped the locus underlying variation in OrV susceptibility, and we found that a single nucleotide polymorphism in cul-6 may contribute to the difference in OrV susceptibility between N2 and CB4856. An allele swap experiment showed the strain CB4856 became as susceptible as the N2 strain by having an N2 cul-6 allele, although having the CB4856 cul-6 allele did not increase resistance in N2. In addition, we found that multiple strains with nonoverlapping introgressions showed a distinct infection phenotype from the parental strain, indicating that there are punctuated locations on chromosome IV determining OrV susceptibility. Thus, our findings reveal the genetic complexity of OrV susceptibility in C. elegans and suggest that viral susceptibility is governed by multiple genes.IMPORTANCE Genetic variation determines the viral susceptibility of hosts. Yet, pinpointing which genetic variants determine viral susceptibility remains challenging. Here, we have exploited the genetic tractability of the model organism Caenorhabditis elegans to dissect the genetic architecture of Orsay virus infection. Our results provide novel insight into natural determinants of Orsay virus infection.

The GASA Gene Family in Theobroma cacao: Genome wide Identification and Expression Analysis.. [DOI: 10.1101/2021.01.27.425041]

The gibberellic acid-stimulated Arabidopsis (GASA/GAST) gene family is widely distributed in plants. The role of the GASA gene family has been reported previously in various physiological and biological processes, such as cell division, root and seed development, stem growth, and fruit ripening. These genes also provide resistance to abiotic and biotic stresses including antimicrobial, antiviral, and antifungal. Here, we report 17 tcGASA genes in Theobroma cacao L. distributed on six chromosomes. The gene structure, promoter-region sequences, protein structure, and biochemical properties, expression, and phylogenetics of all tcGASAs were analyzed. Phylogenetic analyses divided tcGASA proteins into five groups. The nine segmentally duplicating genes form four pairs and cluster together in phylogenetic tree. Purifying selection pressure was recorded on tcGASA, including duplicated genes. Several stress/hormone-responsive cis-regulatory elements were also recognized in the promoter region of tcGASAs. Differential expression analyses revealed that most of the tcGASA genes showed elevated expression in the seeds (cacao food), implying their role in seed development. The black rod disease of genus Phytophthora caused up to 20–25% loss (700,000 metric tons) in world cacao production. The role of tcGASA genes in conferring fungal resistance was also explored based on RNAseq data against Phytophthora megakarya. The differential expression of tcGASA genes was recorded between the tolerant and susceptible cultivars of cacao plants, which were inoculated with the fungus for 24h and 72h. This differential expression indicating possible role of tcGASA genes to fungal resistant in cacao. Our findings provide new insight into the function, evolution, and regulatory system of the GASA family genes in T. cacao and provide new target genes for development of fungi-resistant cacao varieties in breeding programs.

Simultaneous quantification of mRNA and protein in single cells reveals post-transcriptional effects of genetic variation

Trans-acting DNA variants may specifically affect mRNA or protein levels of genes located throughout the genome. However, prior work compared trans-acting loci mapped in separate studies, many of which had limited statistical power. Here, we developed a CRISPR-based system for simultaneous quantification of mRNA and protein of a given gene via dual fluorescent reporters in single, live cells of the yeast Saccharomyces cerevisiae. In large populations of recombinant cells from a cross between two genetically divergent strains, we mapped 86 trans-acting loci affecting the expression of ten genes. Less than 20% of these loci had concordant effects on mRNA and protein of the same gene. Most loci influenced protein but not mRNA of a given gene. One locus harbored a premature stop variant in the YAK1 kinase gene that had specific effects on protein or mRNA of dozens of genes. These results demonstrate complex, post-transcriptional genetic effects on gene expression.

Network Analysis Prioritizes DEWAX and ICE1 as the Candidate Genes for Major eQTL Hotspots in Seed Germination of Arabidopsis thaliana

Seed germination is characterized by a constant change of gene expression across different time points. These changes are related to specific processes, which eventually determine the onset of seed germination. To get a better understanding on the regulation of gene expression during seed germination, we performed a quantitative trait locus mapping of gene expression (eQTL) at four important seed germination stages (primary dormant, after-ripened, six-hour after imbibition, and radicle protrusion stage) using Arabidopsis thaliana Bay x Sha recombinant inbred lines (RILs). The mapping displayed the distinctness of the eQTL landscape for each stage. We found several eQTL hotspots across stages associated with the regulation of expression of a large number of genes. Interestingly, an eQTL hotspot on chromosome five collocates with hotspots for phenotypic and metabolic QTL in the same population. Finally, we constructed a gene co-expression network to prioritize the regulatory genes for two major eQTL hotspots. The network analysis prioritizes transcription factors DEWAX and ICE1 as the most likely regulatory genes for the hotspot. Together, we have revealed that the genetic regulation of gene expression is dynamic along the course of seed germination.

Dissecting the eQTL Micro-Architecture in Caenorhabditis elegans

The study of expression quantitative trait loci (eQTL) using natural variation in inbred populations has yielded detailed information about the transcriptional regulation of complex traits. Studies on eQTL using recombinant inbred lines (RILs) led to insights on cis and trans regulatory loci of transcript abundance. However, determining the underlying causal polymorphic genes or variants is difficult, but ultimately essential for the understanding of regulatory networks of complex traits. This requires insight into whether associated loci are single eQTL or a combination of closely linked eQTL, and how this QTL micro-architecture depends on the environment. We addressed these questions by testing for independent replication of previously mapped eQTL in Caenorhabditis elegans using new data from introgression lines (ILs). Both populations indicate that the overall heritability of gene expression, number, and position of eQTL differed among environments. Across environments we were able to replicate 70% of the cis- and 40% of the trans-eQTL using the ILs. Testing eight different simulation models, we suggest that additive effects explain up to 60-93% of RIL/IL heritability for all three environments. Closely linked eQTL explained up to 40% of RIL/IL heritability in the control environment whereas only 7% in the heat-stress and recovery environments. In conclusion, we show that reproducibility of eQTL was higher for cis vs. trans eQTL and that the environment affects the eQTL micro-architecture.

Identification of miRNA-eQTLs in maize mature leaf by GWAS

Background

MiRNAs play essential roles in plant development and response to biotic and abiotic stresses through interaction with their target genes. The expression level of miRNAs shows great variations among different plant accessions, developmental stages, and tissues. Little is known about the content within the plant genome contributing to the variations in plants. This study aims to identify miRNA expression-related quantitative trait loci (miR-QTLs) in the maize genome.

Results

The miRNA expression level from next generation sequencing (NGS) small RNA libraries derived from mature leaf samples of the maize panel (200 maize lines) was estimated as phenotypes, and maize Hapmap v3.2.1 was chosen as the genotype for the genome-wide association study (GWAS). A total of four significant miR-eQTLs were identified contributing to miR156k-5p, miR159a-3p, miR390a-5p and miR396e-5p, and all of them are trans-eQTLs. In addition, a strong positive coexpression of miRNA was found among five miRNA families. Investigation of the effects of these miRNAs on the expression levels and target genes provided evidence that miRNAs control the expression of their targets by suppression and enhancement.

Conclusions

These identified significant miR-eQTLs contribute to the diversity of miRNA expression in the maize penal at the developmental stages of mature leaves in maize, and the positive and negative regulation between miRNA and its target genes has also been uncovered.

Detecting selection with a genetic cross

Distinguishing which traits have evolved under natural selection, as opposed to neutral evolution, is a major goal of evolutionary biology. Several tests have been proposed to accomplish this, but these either rely on false assumptions or suffer from low power. Here, I introduce an approach to detecting selection that makes minimal assumptions and only requires phenotypic data from ∼10 individuals. The test compares the phenotypic difference between two populations to what would be expected by chance under neutral evolution, which can be estimated from the phenotypic distribution of an F2 cross between those populations. Simulations show that the test is robust to variation in the number of loci affecting the trait, the distribution of locus effect sizes, heritability, dominance, and epistasis. Comparing its performance to the QTL sign test-an existing test of selection that requires both genotype and phenotype data-the new test achieves comparable power with 50- to 100-fold fewer individuals (and no genotype data). Applying the test to empirical data spanning over a century shows strong directional selection in many crops, as well as on naturally selected traits such as head shape in Hawaiian Drosophila and skin color in humans. Applied to gene expression data, the test reveals that the strength of stabilizing selection acting on mRNA levels in a species is strongly associated with that species' effective population size. In sum, this test is applicable to phenotypic data from almost any genetic cross, allowing selection to be detected more easily and powerfully than previously possible.

Genetic Variation in Complex Traits in Transgenic α-Synuclein Strains of Caenorhabditis elegans

Different genetic backgrounds can modify the effect of mutated genes. Human α-synuclein (SNCA) gene encodes α-synuclein, and its oligomeric complexes accumulate with age and mediate the disruption of cellular homeostasis, resulting in the neuronal death that is characteristic of Parkinson’s Disease. Polymorphic variants modulate this complex pathologic mechanism. Previously, we constructed five transgenic introgression lines of a Caenorhabditis elegans model of α-synuclein using genetic backgrounds that are genetically diverse from the canonical wild-type Bristol N2. A gene expression analysis revealed that the α-synuclein transgene differentially affects genome-wide transcription due to background modifiers. To further investigate how complex traits are affected in these transgenic lines, we measured the α-synuclein transgene expression, the overall accumulation of the fusion protein of α-synuclein and yellow fluorescent protein (YFP), the lysosome-related organelles, and the body size. By using quantitative PCR (qPCR), we demonstrated stable and similar expression levels of the α-synuclein transgene in different genetic backgrounds. Strikingly, we observed that the levels of the a-synuclein:YFP fusion protein vary in different genetic backgrounds by using the COPAS™ biosorter. The quantification of the Nile Red staining assay demonstrates that α-synuclein also affects lysosome-related organelles and body size. Our results show that the same α-synuclein introgression in different C. elegans backgrounds can produces differing effects on complex traits due to background modifiers.

A Cell Fate Switch in the Caenorhabditis elegans Seam Cell Lineage Occurs Through Modulation of the Wnt Asymmetry Pathway in Response to Temperature Increase

Populations often display consistent developmental phenotypes across individuals despite inevitable biological stochasticity. Nevertheless, developmental robustness has limits, and systems can fail upon change in the environment or the genetic background. We use here the seam cells, a population of epidermal stem cells in Caenorhabditis elegans, to study the influence of temperature change and genetic variation on cell fate. Seam cell development has mostly been studied so far in the laboratory reference strain (N2), grown at 20° temperature. We demonstrate that an increase in culture temperature to 25° introduces variability in the wild-type seam cell lineage, with a proportion of animals showing an increase in seam cell number. We map this increase to lineage-specific symmetrization events of normally asymmetric cell divisions at the fourth larval stage, leading to the retention of seam cell fate in both daughter cells. Using genetics and single-molecule imaging, we demonstrate that this symmetrization occurs via changes in the Wnt asymmetry pathway, leading to aberrant Wnt target activation in anterior cell daughters. We find that intrinsic differences in the Wnt asymmetry pathway already exist between seam cells at 20° and this may sensitize cells toward a cell fate switch at increased temperature. Finally, we demonstrate that wild isolates of C. elegans display variation in seam cell sensitivity to increased culture temperature, although their average seam cell number is comparable at 20°. Our results highlight how temperature can modulate cell fate decisions in an invertebrate model of stem cell patterning.

Tensor decomposition of stimulated monocyte and macrophage gene expression profiles identifies neurodegenerative disease-specific trans-eQTLs

Recent human genetic studies suggest that cells of the innate immune system have a primary role in the pathogenesis of neurodegenerative diseases. However, the results from these studies often do not elucidate how the genetic variants affect the biology of these cells to modulate disease risk. Here, we applied a tensor decomposition method to uncover disease associated gene networks linked to distal genetic variation in stimulated human monocyte and macrophage gene expression profiles. We report robust evidence that some disease associated genetic variants affect the expression of multiple genes in trans. These include a Parkinson's disease locus influencing the expression of genes mediated by a protease that controls lysosomal function, and Alzheimer's disease loci influencing the expression of genes involved in type 1 interferon signaling, myeloid phagocytosis, and complement cascade pathways. Overall, we uncover gene networks in induced innate immune cells linked to disease associated genetic variants, which may help elucidate the underlying biology of disease.

WormQTL2: an interactive platform for systems genetics in Caenorhabditis elegans

Quantitative genetics provides the tools for linking polymorphic loci to trait variation. Linkage analysis of gene expression is an established and widely applied method, leading to the identification of expression quantitative trait loci (eQTLs). (e)QTL detection facilitates the identification and understanding of the underlying molecular components and pathways, yet (e)QTL data access and mining often is a bottleneck. Here, we present WormQTL2, a database and platform for comparative investigations and meta-analyses of published (e)QTL data sets in the model nematode worm C. elegans. WormQTL2 integrates six eQTL studies spanning 11 conditions as well as over 1000 traits from 32 studies and allows experimental results to be compared, reused and extended upon to guide further experiments and conduct systems-genetic analyses. For example, one can easily screen a locus for specific cis-eQTLs that could be linked to variation in other traits, detect gene-by-environment interactions by comparing eQTLs under different conditions, or find correlations between QTL profiles of classical traits and gene expression. WormQTL2 makes data on natural variation in C. elegans and the identified QTLs interactively accessible, allowing studies beyond the original publications. Database URL: www.bioinformatics.nl/WormQTL2/.

Transcriptome resilience predicts thermotolerance in Caenorhabditis elegans

BACKGROUND

The detrimental effects of a short bout of stress can persist and potentially turn lethal, long after the return to normal conditions. Thermotolerance, which is the capacity of an organism to withstand relatively extreme temperatures, is influenced by the response during stress exposure, as well as the recovery process afterwards. While heat-shock response mechanisms have been studied intensively, predicting thermal tolerance remains a challenge.

RESULTS

Here, we use the nematode Caenorhabditis elegans to measure transcriptional resilience to heat stress and predict thermotolerance. Using principal component analysis in combination with genome-wide gene expression profiles collected in three high-resolution time series during control, heat stress, and recovery conditions, we infer a quantitative scale capturing the extent of stress-induced transcriptome dynamics in a single value. This scale provides a basis for evaluating transcriptome resilience, defined here as the ability to depart from stress-expression dynamics during recovery. Independent replication across multiple highly divergent genotypes reveals that the transcriptional resilience parameter measured after a spike in temperature is quantitatively linked to long-term survival after heat stress.

CONCLUSION

Our findings imply that thermotolerance is an intrinsic property that pre-determines long-term outcome of stress and can be predicted by the transcriptional resilience parameter. Inferring the transcriptional resilience parameters of higher organisms could aid in evaluating rehabilitation strategies after stresses such as disease and trauma.

Aedes aegypti (Aag2)-derived clonal mosquito cell lines reveal the effects of pre-existing persistent infection with the insect-specific bunyavirus Phasi Charoen-like virus on arbovirus replication

BACKGROUND

Aedes aegypti is a vector mosquito of major public health importance, transmitting arthropod-borne viruses (arboviruses) such as chikungunya, dengue, yellow fever and Zika viruses. Wild mosquito populations are persistently infected at high prevalence with insect-specific viruses that do not replicate in vertebrate hosts. In experimental settings, acute infections with insect-specific viruses have been shown to modulate arbovirus infection and transmission in Ae. aegypti and other vector mosquitoes. However, the impact of persistent insect-specific virus infections, which arboviruses encounter more commonly in nature, has not been investigated extensively. Cell lines are useful models for studying virus-host interactions, however the available Ae. aegypti cell lines are poorly defined and heterogenous cultures.

METHODOLOGY/PRINCIPLE FINDINGS

We generated single cell-derived clonal cell lines from the commonly used Ae. aegypti cell line Aag2. Two of the fourteen Aag2-derived clonal cell lines generated harboured markedly and consistently reduced levels of the insect-specific bunyavirus Phasi Charoen-like virus (PCLV) known to persistently infect Aag2 cells. In contrast to studies with acute insect-specific virus infections in cell culture and in vivo, we found that pre-existing persistent PCLV infection had no major impact on the replication of the flaviviruses dengue virus and Zika virus, the alphavirus Sindbis virus, or the rhabdovirus vesicular stomatitis virus. We also performed a detailed characterisation of the morphology, transfection efficiency and immune status of our Aag2-derived clonal cell lines, and have made a clone that we term Aag2-AF5 available to the research community as a well-defined cell culture model for arbovirus-vector interaction studies.

CONCLUSIONS/SIGNIFICANCE

Our findings highlight the need for further in vivo studies that more closely recapitulate natural arbovirus transmission settings in which arboviruses encounter mosquitoes harbouring persistent rather than acute insect-specific virus infections. Furthermore, we provide the well-characterised Aag2-derived clonal cell line as a valuable resource to the arbovirus research community.

Tightly linked antagonistic-effect loci underlie polygenic phenotypic variation in C. elegans

Recent work has provided strong empirical support for the classic polygenic model for trait variation. Population-based findings suggest that most regions of genome harbor variation affecting most traits. Here, we use the approach of experimental genetics to show that, indeed, most genomic regions carry variants with detectable effects on growth and reproduction in Caenorhabditis elegans populations sensitized by nickel stress. Nine of 15 adjacent intervals on the X chromosome, each encompassing ∼0.001 of the genome, have significant effects when tested individually in near-isogenic lines (NILs). These intervals have effects that are similar in magnitude to those of genome-wide significant loci that we mapped in a panel of recombinant inbred advanced intercross lines (RIAILs). If NIL-like effects were randomly distributed across the genome, the RIAILs would exhibit phenotypic variance that far exceeds the observed variance. However, the NIL intervals are arranged in a pattern that significantly reduces phenotypic variance relative to a random arrangement; adjacent intervals antagonize one another, cancelling each other's effects. Contrary to the expectation of small additive effects, our findings point to large-effect variants whose effects are masked by epistasis or linkage disequilibrium between alleles of opposing effect.

Genome structure predicts modular transcriptome responses to genetic and environmental conditions

Understanding the plasticity, robustness and modularity of transcriptome expression to genetic and environmental conditions is crucial to deciphering how organisms adapt in nature. To test how genome architecture influences transcriptome profiles, we quantified expression responses for distinct temperature-adapted genotypes of the nematode Caenorhabditis briggsae when exposed to chronic temperature stresses throughout development. We found that 56% of the 8,795 differentially expressed genes show genotype-specific changes in expression in response to temperature (genotype-by-environment interactions, GxE). Most genotype-specific responses occur under heat stress, indicating that cold vs. heat stress responses involve distinct genomic architectures. The 22 co-expression modules that we identified differ in their enrichment of genes with genetic vs. environmental vs. interaction effects, as well as their genomic spatial distributions, functional attributes and rates of molecular evolution at the sequence level. Genes in modules enriched for simple effects of either genotype or temperature alone tend to evolve especially rapidly, consistent with disproportionate influence of adaptation or weaker constraint on these subsets of loci. Chromosome-scale heterogeneity in nucleotide polymorphism, however, rather than the scale of individual genes predominates as the source of genetic differences among expression profiles, and natural selection regimes are largely decoupled between coding sequences and noncoding flanking sequences that contain cis-regulatory elements. These results illustrate how the form of transcriptome modularity and genome structure contribute to predictable profiles of evolutionary change.

Genetic background modifies phenotypic and transcriptional responses in a C. elegans model of α-synuclein toxicity

Background

Accumulation of protein aggregates are a major hallmark of progressive neurodegenerative disorders such as Parkinson’s disease and Alzheimer’s disease. Transgenic Caenorhabditis elegans nematodes expressing the human synaptic protein α-synuclein in body wall muscle show inclusions of aggregated protein, which affects similar genetic pathways as in humans. It is not however known how the effects of α-synuclein expression in C. elegans differs among genetic backgrounds. Here, we compared gene expression patterns and investigated the phenotypic consequences of transgenic α-synuclein expression in five different C. elegans genetic backgrounds.

Results

Transcriptome analysis indicates that α-synuclein expression effects pathways associated with nutrient storage, lipid transportation and ion exchange and that effects vary depending on the genetic background. These gene expression changes predict that a range of phenotypes will be affected by α-synuclein expression. We confirm this, showing that α-synuclein expression delayed development, reduced lifespan, increased rate of matricidal hatching, and slows pharyngeal pumping. Critically, these phenotypic effects depend on the genetic background and coincide with the core changes in gene expression.

Conclusions

Together, our results show genotype-specific effects and core alterations in both gene expression and in phenotype in response to α-synuclein expression. We conclude that the effects of α-synuclein expression are substantially modified by the genetic background, illustrating that genetic background needs to be considered in C. elegans models of neurodegenerative disease.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5597-1) contains supplementary material, which is available to authorized users.

A multi-parent recombinant inbred line population of C. elegans allows identification of novel QTLs for complex life history traits

BACKGROUND

The nematode Caenorhabditis elegans has been extensively used to explore the relationships between complex traits, genotypes, and environments. Complex traits can vary across different genotypes of a species, and the genetic regulators of trait variation can be mapped on the genome using quantitative trait locus (QTL) analysis of recombinant inbred lines (RILs) derived from genetically and phenotypically divergent parents. Most RILs have been derived from crossing two parents from globally distant locations. However, the genetic diversity between local C. elegans populations can be as diverse as between global populations and could thus provide means of identifying genetic variation associated with complex traits relevant on a broader scale.

RESULTS

To investigate the effect of local genetic variation on heritable traits, we developed a new RIL population derived from 4 parental wild isolates collected from 2 closely located sites in France: Orsay and Santeuil. We crossed these 4 genetically diverse parental isolates to generate a population of 200 multi-parental RILs and used RNA-seq to obtain sequence polymorphisms identifying almost 9000 SNPs variable between the 4 genotypes with an average spacing of 11 kb, doubling the mapping resolution relative to currently available RIL panels for many loci. The SNPs were used to construct a genetic map to facilitate QTL analysis. We measured life history traits such as lifespan, stress resistance, developmental speed, and population growth in different environments, and found substantial variation for most traits. We detected multiple QTLs for most traits, including novel QTLs not found in previous QTL analysis, including those for lifespan and pathogen responses. This shows that recombining genetic variation across C. elegans populations that are in geographical close proximity provides ample variation for QTL mapping.

CONCLUSION

Taken together, we show that using more parents than the classical two parental genotypes to construct a RIL population facilitates the detection of QTLs and that the use of wild isolates facilitates the detection of QTLs. The use of multi-parent RIL populations can further enhance our understanding of local adaptation and life history trade-offs.

Natural genetic variation in C. elegans identified genomic loci controlling metabolite levels

Metabolic homeostasis is sustained by complex biological networks that respond to nutrient availability. Genetic and environmental factors may disrupt this equilibrium, leading to metabolic disorders, including obesity and type 2 diabetes. To identify the genetic factors controlling metabolism, we performed quantitative genetic analysis using a population of 199 recombinant inbred lines (RILs) in the nematode Caenorhabditis elegans We focused on the genomic regions that control metabolite levels by measuring fatty acid (FA) and amino acid (AA) composition in the RILs using targeted metabolomics. The genetically diverse RILs showed a large variation in their FA and AA levels with a heritability ranging from 32% to 82%. We detected strongly co-correlated metabolite clusters and 36 significant metabolite quantitative trait loci (mQTL). We focused on mQTL displaying highly significant linkage and heritability, including an mQTL for the FA C14:1 on Chromosome I, and another mQTL for the FA C18:2 on Chromosome IV. Using introgression lines (ILs), we were able to narrow down both mQTL to a 1.4-Mbp and a 3.6-Mbp region, respectively. RNAi-based screening focusing on the Chromosome I mQTL identified several candidate genes for the C14:1 mQTL, including lagr-1, Y87G2A.2, nhr-265, nhr-276, and nhr-81 Overall, this systems approach provides us with a powerful platform to study the genetic basis of C. elegans metabolism. Furthermore, it allows us to investigate interventions such as nutrients and stresses that maintain or disturb the regulatory network controlling metabolic homeostasis, and identify gene-by-environment interactions.