Biology subjects

Kraaijeveld, K.

Publications and source records attributed to Kraaijeveld, K..

5 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↗

bioRxiv2022

Distinguishing between canonical and non-canonical tRNA genes reveals that Thermococcaceae adhere to the standard archaeal tRNA gene set

Automated genome annotation is essential for extracting biological information from sequence data. The identification and annotation of tRNA genes is frequently performed by the software package tRNAscan-SE, the output of which is listed for selected genomes in the Genomic tRNA database (GtRNAdb). Here, we highlight a pervasive error in prokaryotic tRNA gene sets on GtRNAdb: the mis-categorization of partial, non-canonical tRNA genes as standard, canonical tRNA genes. Firstly, we demonstrate the issue using the tRNA gene sets of 20 organisms from the archaeal taxon Thermococcaceae. According to GtRNAdb, these organisms collectively deviate from the expected set of tRNA genes in 15 instances, including the listing of eleven putative canonical tRNA genes. However, after detailed manual annotation, only one of these eleven remains; the others are either partial, non-canonical tRNA genes resulting from the integration of genetic elements or CRISPR-Cas activity (seven instances), or attributable to ambiguities in input sequences (three instances). Secondly, we show that similar examples of the mis-categorization of predicted tRNA sequences occur throughout the prokaryotic sections of GtRNAdb. While both canonical and non-canonical prokaryotic tRNA gene sequences identified by tRNAscan-SE are biologically interesting, the challenge of reliably distinguishing between them remains. We recommend employing a combination of (i) screening input sequences for the genetic elements typically associated with non-canonical tRNA genes, and ambiguities, (ii) activating the tRNAscan-SE automated pseudogene detection function, and (iii) scrutinizing predicted tRNA genes with low isotype scores. These measures greatly reduce manual annotation efforts, and lead to improved prokaryotic tRNA gene set predictions.

genomics↗

bioRxiv2020

Lipids as currency in ecological interactions: Competition and facilitation between two lipid scavenging parasitoids

Interspecific interactions in nature often revolve around the acquisition of nutrients. Depending on the organisms metabolic requirements, competition for specific essential nutrients may occur, which selects for increased abilities to monopolize, consume and store these nutrients. Lipid scavengers are organisms that rely on exogenous lipid acquisition as they lack the ability to synthesize fatty acids de novo or in sufficient quantity. Most parasitoid insects are lipid scavengers: they obtain all required lipids by feeding on their hosts as larvae. Here we study the nutritional ecology of competitive interactions between native Nasonia vitripennis and introduced Tachinaephagus zealandicus. While the former was already known to lack lipogenesis, we show that T. zealandicus also relies on host lipids. The interactions between the two species were studied using competition experiments, in which oviposition of T. zealandicus on a host was followed by multiparasitism by N. vitripennis. The outcome of competition was determined by the duration of the time lag between oviposition events. N. vitripennis was superior when arriving 3 days after oviposition by T. zealandicus. In contrast, 9 days after oviposition of T. zealandicus we observed complete reversal, and no N. vitripennis offspring were able to develop. Only when N. vitripennis laid eggs 15 days after T. zealandicus oviposition, both species could emerge from the same host. However, N. vitripennis realizes only 10% of its potential fitness at this time point because prior parasitization by the gregarious T. zealandicus compartmentalizes the host resources, limiting the spread of N. vitripennis venom. This study shows that successful reproduction of N. vitripennis at 15 days was achieved by hyperparasitizing, a capability that provides a fitness benefit to N. vitripennis, as it extends the time window that hosts are available for parasitization. Choice tests with hosts at different time intervals after T. zealandicus oviposition revealed a partial mismatch in N. vitripennis females between competition avoidance and offspring performance, which may be linked to the limited co-evolutionary time between native and introduced species. We discuss our results in the context of nutritional ecology and, specifically, the role of lipids in ecological interactions.

ecology↗

bioRxiv2018

Gene regulatory mechanisms underlying the evolutionary loss of a polygenic trait

Trait loss is a pervasive phenomenon in evolution, yet the underlying molecular causes have been identified in only a handful of cases. Most of these involve loss-of-function mutations in one or more trait-specific genes. Parasitoid insects are fatty acid auxotrophs: they lost the ability to convert dietary sugars into fatty acids, a trait that is ubiquitous among non-parasitoid animals and is enabled by a highly conserved set of genes. Earlier research suggests that lack of lipogenesis is caused by changes in gene regulation, rather than gene decay. We compared transcriptome-wide responses to sugar-feeding in the non-lipogenic parasitoid species Nasonia vitripennis and the lipogenic Drosophila melanogaster. Both species adjusted their metabolism within four hours after feeding, but there was little overlap at the gene level between the responses of the two species. Even at the pathway-level, there were sharp differences between the expression profiles of the two species, especially in carbohydrate and lipid metabolic pathways. Several genes coding for key enzymes in acetyl-CoA metabolism, such as malonyl-CoA decarboxylase (MCD) and HMG-CoA synthase differed in expression between the two species. Their combined action likely blocks lipogenesis in the parasitoid species. Network analysis indicates most genes involved in these pathways to be highly connected, which suggest they have pleiotropic effects and could explain the absence of gene degradation. Our results indicate that modification of expression levels of only a few non-connected genes, such as MCD, is sufficient to enable complete loss of lipogenesis in N. vitripennis.

evolutionary biology↗

bioRxiv2018

Genomic resources for Goniozus legneri, Aleochara bilineata and Paykullia maculata, representing three independent origins of the parasitoid lifestyle in insects

Parasitoid insects are important model systems for a multitude of biological research topics and widely used as biological control agents against insect pests. While the parasitoid lifestyle has evolved numerous times in different insect groups, research has focused almost exclusively on Hymenoptera from the parasitica clade. The genomes of several members of this group have been sequenced, but no genomic resources are available from any of the other, independent evolutionary origins of the parasitoid lifestyle. Our aim here was to develop genomic resources for three parasitoid insects outside the parasitica. We present draft genome assemblies for Goniozus legneri, a parasitoid Hymenopteran more closely related to the non-parasitoid wasps and bees than to the parasitica wasps, the Coleopteran parasitoid Aleochara bilineata and the Dipteran parasitoid Paykullia maculata. The genome assemblies are fragmented, but complete in terms of gene content. We also provide preliminary structural annotations. We anticipate that these genomic resources will be valuable for testing the generality of findings obtained from parasitica wasps in future comparative studies.\n\nData availabilityThe Whole Genome Shotgun projects have been deposited at DDBJ/ENA/GenBank under the accessions NCVS00000000 (G. legneri), NBZA00000000 (A. bilineata) and NDXZ00000000 (P. maculata). The versions described in this paper are versions NCVS01000000, NBZA01000000 and NDXZ01000000, respectively. Mapped reads and genome annotations are available through http://parasitoids.labs.vu.nl/parasitoids/. This website also includes genome browsers and viroblast instances for each genome.

genomics↗