Biology subjects

Kammenga, J.

Publications and source records attributed to Kammenga, J..

10 recordsLinked to original sources

bioRxiv2025

Additive effects of environmental and demographic variation shape the repeatability of evolution across replicated experiments

The repeatability of evolution is fundamentally important for understanding the origin and diversification of life as well as for developing evolutionary forecasting tools. Repeatability is limited by stochasticity, here defined as changes that are independent of genotypic fitness effects. Over short timescales, the two main sources of stochasticity of evolutionary change are environmental stochasticity and demographic (life-history) stochasticity. Quantifying the relative importance of these two sources of stochasticity in driving fitness outcomes is crucially important for predicting evolutionary responses. To gain insights in the effects of stochasticity, five institutes replicated an evolutionary experiment exposing Caenorhabditis elegans to novel rearing conditions. Replication across the institutes led to variation in selective environments, e.g. through divergent microbiomes among institutes. Replication within institutes was done across demographic treatments that influence the potential for population-size dependent fluctuations in allele frequencies (drift) and genetic hitchhiking (draft). We found high among-institute variation in fitness outcomes, which was partially explained by variation in microbiota. Whereas lab-specific effects explained most of the variance in mean fitness, the repeatability of fitness outcomes depended more on demographic heterogeneity. Specifically, population bottlenecks resulted in high among-replicate variation in fitness. When combined, environmental and demographic stochasticity additively reduced repeatability, underlining their additive importance in developing evolutionary forecasting tools. These results further highlight the importance of statistically integrating heterogeneity in experimental evolution to identify factors constraining outcome repeatability and study replicability.

evolutionary biology↗

bioRxiv2024

Uncovering large effect loci and epistasis for lifespan in standing genetic variation in the fruit fly Drosophila melanogaster

Lifespan is a heritable trait with a polygenic architecture. Experimental evolution in combination with re-sequencing has often been used to identify candidate loci for lifespan in Drosophila melanogaster. Previous experiments showed that Drosophila populations experimentally evolved to increase late-life reproduction showed a correlated responses in development time, body size, but also lifespan. Subsequent whole genome sequencing allowed for the identification of candidate loci that correlated to lifespan differentiation. However, it remains difficult to assess whether candidate loci affect lifespan and to what extent such loci pleiotropically underpin multiple traits. Furthermore, recent studies indicate that lifespan effects of loci are often context dependent, but genotype-by-genotype interactions remain understudied. Therefore, here, we report on a study where we genotyped 3210 individuals for 32 candidate loci that emerged from our evolve and re-sequence experiment and tested, (1) whether these loci significantly affected lifespan, (2) the effect size of each locus, and, (3) how these loci mutually interact, i.e. determine the level of epistasis in moulding lifespan. Of the 32 loci, six showed significant main effect associations, of which three loci showed effects of 6.6 days difference in lifespan or larger, while the overall average lifespan was 41.7 days. Eight additional significant pairwise interactions between loci were found, of which four (single) main effects and one three-way interaction was significant. Lastly, we found that alleles that increased lifespan did not necessarily have higher frequencies in populations that showed increased lifespan, indicating that lifespan itself had not been the major target of selection. Our study indicates that individual genotyping following an evolve and re-sequencing study is essential to understand the mechanistic basis of polygenetic adaptation.

evolutionary biology↗

bioRxiv2023

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

Regulation of gene expression plays a crucial role in the development and adaptation of organisms to changing environments. A population-based procedure used to investigate the genetic regulation of gene expression is eQTL mapping. Typically, the age of the population used for eQTL mapping at the time of sampling is strictly controlled. This is necessary because the developmental process causes changes in gene expression, complicating the interpretation of eQTL mapping experiments. However, organisms can differ in their "developmental age", even if they are of the same chronological age. As a result, eQTL patterns are affected by uncontrolled developmental variation in gene expression. The model organism C. 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 four 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 an available normalization procedure. We used dynamical eQTL mapping, which includes 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 recombinant inbred lines of C. elegans. The results show that many eQTLs are actually caused by developmental variation, that most trans-bands are associated with developmental age and that dynamical eQTL mapping detects additional eQTLs not found with classical eQTL mapping.

genetics↗

bioRxiv2021

The genetics of gene expression in a C. elegans multi parental recombinant inbred line population.

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.

genetics↗

bioRxiv2020

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 x 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 contributes to the difference in OrV susceptibility between N2 and CB4856. An allele swap experiment showed the strain CB4856 became more susceptible by having an N2 cul-6 allele, although having the CB4856 cul-6 allele did not increase resistance in N2. Additionally, we found that multiple strains with non-overlapping 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.

genetics↗

bioRxiv2019

Transcriptome dynamics predict thermotolerance in Caenorhabditis elegans

BackgroundThe 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.\n\nResultsHere, we use the nematode Caenorhabditis elegans to measure transcriptional resilience to heat stress and predict thermotolerance. Using high dimensionality reduction techniques 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.\n\nConclusionOur 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.

genomics↗

bioRxiv2018

C. elegans genetic background modifies the core transcriptional response in an α-synuclein model of Parkinson’s disease

Accumulation of protein aggregates is a major cause of Parkinsons disease (PD), a progressive neurodegenerative condition that is one of the most common causes of dementia. Transgenic Caenorhabditis elegans worms expressing the human synaptic protein -synuclein show inclusions of aggregated protein and replicate the defining pathological hallmarks of PD. It is however not known how PD progression and pathology differs among individual genetic backgrounds. Here, we compared gene expression patterns, and investigated the phenotypic consequences of transgenic -synuclein expression in five different C. elegans genetic backgrounds. Transcriptome analysis indicates that the effects of -synuclein expression on pathways associated with nutrient storage, lipid transportation and ion exchange depend on the genetic background. The gene expression changes we observe suggest that a range of phenotypes will be affected by -synuclein expression. We experimentally confirm this, showing that the transgenic lines generally show delayed development, reduced lifespan, and an increased rate of matricidal hatching. These phenotypic effects coincide with the core changes in gene expression, linking developmental arrest, mobility, metabolic and cellular repair mechanisms to -synuclein expression. Together, our results show both genotype-specific effects and core alterations in global gene expression and in phenotype in response to -synuclein. We conclude that the PD effects are substantially modified by the genetic background, illustrating that genetic background mechanisms should be elucidated to understand individual variation in PD.

genomics↗

bioRxiv2017

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

Metabolic homeostasis is sustained by complex biological networks responding to nutrient availability. Disruption of this equilibrium involving intricate interactions between genetic and environmental factors can lead to metabolic disorders, including obesity and type 2 diabetes. To identify the genetic factors controlling metabolism, we applied a quantitative genetic strategy using a Caenorhabditis elegans population consisting of 199 recombinant inbred lines (RILs) originally derived from crossing parental strains Bristol N2 and Hawaii CB4856. We focused on the genetic factors that control metabolite levels and measured fatty acid (FA) and amino acid (AA) composition in the 199 RILs using targeted metabolomics. For both FA and AA profiles, we observed large variation in metabolite levels with 32-82% heritability between the RILs. We performed metabolite-metabolite correlation analysis and detected strongly co-correlated metabolite clusters. To identify natural genetic variants responsible for the observed metabolite variations, we performed QTL mapping and detected 36 significant metabolite QTL (mQTL). We focused on the mQTL that displayed high 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. Overall, this systems approach provides us with a powerful platform to study the genetic basis of C. elegans metabolism. It also allows us to investigate additional interventions, such as nutrients and stresses that maintain or disturb the regulatory network controlling metabolic homeostasis, and identify gene-by-environment interactions.

genomics↗

bioRxiv2017

Rictor/TORC2 mediates gut-to-brain signaling in the regulation of phenotypic plasticity in C. elegans

Animals integrate external cues with information about internal conditions such as metabolic state to execute the appropriate behavioral and developmental decisions. Information about food quality and quantity is assessed by the intestine and transmitted to modulate neuronal functions via mechanisms that are not fully understood. The conserved Target of Rapamycin complex 2 (TORC2) controls multiple processes in response to cellular stressors and growth factors. Here we show that TORC2 coordinates larval development and adult behaviors in response to environmental cues and feeding state in the bacterivorous nematode C. elegans. During development, pheromone, bacterial food, and temperature regulate expression of the daf-7 TGF-{beta} and daf-28 insulin-like peptide in sensory neurons to promote a binary decision between reproductive growth and entry into the alternate dauer larval stage. We find that TORC2 acts in the intestine to regulate neuronal expression of both daf-7 and daf-28, which together reflect bacterial-diet dependent feeding status, thus providing a mechanism for integration of food signals with external cues in the regulation of neuroendocrine gene expression. In the adult, TORC2 similarly acts in the intestine to modulate food-regulated foraging behaviors via the PDFR-1 neuropeptide receptor. We also demonstrate that genetic variation affects food-dependent larval and adult phenotypes, and identify quantitative trait loci (QTL) associated with these traits.Together, these results suggest that TORC2 acts as a hub for communication of feeding state information from the gut to the brain, thereby contributing to modulation of neuronal function by internal state.\n\nAUTHOR SUMMARYDecision-making in all animals, including humans, involves weighing available information about the external environment as well as the animals internal conditions. Information about the environment is obtained via the sensory nervous system, whereas internal state can be assessed via cues such as levels of hormones or nutrients. How multiple external and internal inputs are processed in the nervous system to drive behavior or development is not fully understood. In this study, we examine how the nematode C. elegans integrates dietary information received by the gut with environmental signals to alter nervous system function. We have found that a signaling complex, called TORC2, acts in the gut to relay nutrition signals to alter hormonal signaling by the nervous system in C. elegans. Altered neuronal signaling in turn affects a food-dependent binary developmental decision in larvae, as well as food-dependent foraging behaviors in adults. Our results provide a mechanism by which animals prioritize specific signals such as feeding status to appropriately alter their development and/or behavior.

neuroscience↗

bioRxiv2017

Contribution Of Trans Regulatory eQTL To Cryptic Genetic Variation In C. elegans

BackgroundCryptic genetic variation (CGV) is the hidden genetic variation that can be unlocked by perturbing normal conditions. CGV can drive the emergence of novel complex phenotypes through changes in gene expression. Although our theoretical understanding of CGV has thoroughly increased over the past decade, insight into polymorphic gene expression regulation underlying CGV is scarce. Here we investigated the transcriptional architecture of CGV in response to rapid temperature changes in the nematode Caenorhabditis elegans. We analyzed regulatory variation in gene expression (and mapped eQTL) across the course of a heat stress and recovery response in a recombinant inbred population.\n\nResultsWe measured gene expression over three temperature treatments: i) control, ii) heat stress, and iii) recovery from heat stress. Compared to control, exposure to heat stress affected the transcription of 3305 genes, whereas 942 were affected in recovering worms. These affected genes were mainly involved in metabolism and reproduction. The gene expression pattern in recovering worms resembled both the control and the heat stress treatment. We mapped eQTL using the genetic variation of the recombinant inbred population and detected 2626 genes with an eQTL in the heat stress treatment, 1797 in the control, and 1880 in the recovery. The cis-eQTL were highly conserved across treatments. A considerable fraction of the trans-eQTL (40-57%) mapped to 19 treatment specific trans-bands. In contrast to cis-eQTL, trans-eQTL were highly environment specific and thus cryptic. Approximately 67% of the trans-eQTL were only induced in a single treatment, with heat-stress showing the most unique trans-eQTL.\n\nConclusionsThese results illustrate the highly dynamic pattern of CGV across three different environmental conditions that can be evoked by a stress response over a relatively short time-span (2 hours) and that CGV is mainly determined by response related trans regulatory eQTL.

genetics↗