Biology subjects

De Graeve, F.

Publications and source records attributed to De Graeve, F..

4 recordsLinked to original sources

bioRxiv2026

Multiparental RNA-seq driven eQTL screening identifies loci underlying host plant fitness in a generalist herbivore

The two-spotted spider mite (Tetranychus urticae) is an extremely polyphagous pest, yet the genetic basis of this adaptive potential remains to be fully elucidated. Since expression quantitative trait loci (eQTLs) provide the genetic basis of numerous phenotypes, we aimed to identify trans-eQTL hotspots underlying T. urticae fitness upon transfer from a common (bean) to a challenging (tomato) host plant. Nonetheless, the identification of trans-eQTLs is complex and often constrained by methodological challenges and high costs. Therefore, we employed a multiparental mapping strategy driven by RNA-seq, enabling us to leverage extensive genetic variation in a cost-efficient manner. A randomly mating population was generated on bean from a small number of genetically diverse, often heterozygous parents, and subsequently transferred to tomato prior to RNA-seq. Upon whole genome sequencing of the parents, RNA-seq of the mapping population individuals was sufficient to reconstruct their genomes as a combination of parental haploblocks. Subsequent eQTL mapping identified 23 distinct trans-eQTL hotspot regions associated with the expression of numerous target genes. The most prominent hotspot on chromosome 3 was associated with approximately 900 genes and showed enrichment for functions related to detoxification and digestion. Furthermore, 4 of these trans-eQTL hotspot genotypes explained significant variation in mite fitness on the challenging host plant. This contrasted a traditional QTL mapping approach, where these genotypes could not be detected due to multiple testing correction. Our study hence offers a powerful strategy for trans-eQTL hotspot screening and the discovery of trait-associated loci in complex, multiparental genetic backgrounds.

bioinformatics↗

bioRxiv2026

Genome sequence and efficient CRISPR/Cas9 gene editing in the solanacea specialist pest Tetranychus evansi

Tetranychus evansi is an invasive spider mite pest of solanaceous crops worldwide. Its global expansion and ability to rapidly develop acaricide resistance highlight the need for robust genomic resources and functional genetic tools to design custom control strategies. Here, we deliver a high-quality genome assembly and establish efficient CRISPR/Cas9 editing in T. evansi to enable mechanistic studies of host adaptation and pesticide resistance. Using an inbred line and Oxford Nanopore Technologies (ONT) long-read sequencing ([~]36x), we assembled an 89 Mb genome into 13 contigs (N50 = 18.6 Mb) with high completeness and annotated 14,246 protein-coding genes. We manually curated the principal detoxification gene families (P450s, CCEs, GSTs, UGTs, ABC transporters and DOGs), revealing consistently smaller repertoires than in the highly polyphagous relative Tetranychus urticae. To enable reverse genetics, we adapted SYNCAS (saponin + branched amphiphilic peptide capsules) for maternal delivery of CRISPR/Cas9 in T. evansi. Targeting the phytoene desaturase (PD) pigmentation marker produced reliable knockouts with visible albinism and mean editing efficiencies of [~]9.6-14.7%, allowing establishment of stable mutant lines. We further applied precision gene editing to knock-in (KI) the M918T and M918L substitutions into the voltage-gated sodium channel (VGSC). While M918L was lethal in T. evansi, we generated multiple homozygous lines for M918T (mean KI [~]4.4%). Bioassays demonstrated that while the mutation caused extremely high levels of bifenthrin resistance (RR>1000), this was less so for cyfluthrin (RR=164), revealing the independent and specific role of M918T in pyrethroid resistance. Collectively, these resources establish T. evansi as a tractable system for reverse genetic analysis and provide a reference for future comparative and population genomics.

genetics↗

bioRxiv2024

Independent genetic mapping experiments identify diverse molecular determinants of host adaptation in a generalist herbivore

Interactions between plants and herbivores promote evolutionary change. Studying the evolution of herbivore mechanisms aimed to cope with diUerent host plant species is a critical intersection between evolutionary biology and sustainable pest management. Generalist herbivores are of particular interest, as hybridization between genetically distinct populations can increase the standing genetic variation and therefore the adaptive potential of the species. Tetranychus urticae is a generalist arthropod known for its adaptive potential, evidenced in its immense host range and ability to develop metabolic resistance to xenobiotics. However, the molecular underpinnings associated with the potential of host adaptation and the consequences of host adaptation in this and many other pests remain elusive. Here, we use two independent, empirical approaches to identify and map the genetic basis of host plant performance and adaptation in genetically distinct populations of T. urticae. In the first approach, we subject a genetically diverse mite population to tomato selection and map genomic regions linked to the phenotypic evolution of increased reproductive performance. In the second approach, we map genomic regions responsible for performance on tomato by comparing the genomes of pooled individuals from a F2 backcross between populations with high and low reproductive performance. Both approaches revealed specific and shared genomic regions associated with host plant performance and adaptation and key candidate genes were identified. Our findings highlight the power of spider mite genetic approaches to identify the complex genetic basis of host adaptation in a generalist herbivore.

evolutionary biology↗

bioRxiv2022

MAGE enables population level RNAseq driven genotyping and (differential) allelic divergence detection in healthy kidney and carcinoma

Decreasing sequencing costs have instigated large-scale RNAseq experiments, yet genetic polymorphisms in such data remain poorly exploited. Currently, allele-specific expression (ASE) studies focus almost exclusively on genetic variants explaining expression differences (cis-eQTLs), largely ignoring other ASE effects. The latter are typically associated with higher variance in expression of both copies of a gene, here called Allelic Divergence (AD). We therefore developed an RNAseq-driven population-level beta-binomial mixture model for (differential) AD detection. The model simultaneously enables RNAseq-driven genotyping, which outperforms alternative RNA genotyping methods when applied on healthy kidney data from The Cancer Genome Atlas. Moreover, we identify well-known non-cis-eQTL ASE, e.g. random monoallelic expression of HLA and immunoglobulin genes in healthy kidney, as well as allele-specific aberrations in clear cell kidney carcinoma, including long-range epigenetic silencing of protocadherins, copy-number alterations, and loss of imprinting. These methods are available as the Modeller of Allelic Gene Expression (MAGE) tool suite: https://biobix.github.io/MAGE/.

bioinformatics↗