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Background: Breeding of lettuce (Lactuca sativa L.), the most important leafy vegetable worldwide, for enhanced disease resistance and resilience relies on multiple wild relatives to provide the necessary genetic diversity. In this study, we constructed a super-pangenome based on four Lactuca species (representing the primary, secondary and tertiary gene pools) and comprising 474 accessions. We include 68 newly sequenced accessions to improve cultivar coverage and add important foundational breeding lines. Results: With the super-pangenome we find substantial presence/absence variation (PAV) and copy-number variation (CNV). Functional enrichment analyses of core and variable genes show that transcriptional regulators are conserved whereas disease resistance genes are variable. PAV-genome-wide association studies (GWAS) and CNV-GWAS are largely congruent with single-nucleotide polymorphism (SNP)-GWAS. Importantly, they also identify several major novel quantitative trait loci (QTL) for resistance against Bremia lactucae in variable regions not present in the reference lettuce genome. The usability of the super-pangenome is demonstrated by identifying the likely origin of non-reference resistance loci from the wild relatives Lactuca serriola, Lactuca saligna and Lactuca virosa. Conclusions: The super-pangenome offers a broader view on the gene repertoire of lettuce, revealing relevant loci that are not in the reference genome(s). The provided methodology and data provide a strong basis for research into PAVs, CNVs and other variation underlying important biological traits of lettuce and other crops.

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.

Plant organs move throughout the diurnal cycle, changing leaf and petiole positions to balance light capture, leaf temperature, and water loss under dynamic environmental conditions. Upward movement of the petiole, called hyponasty, is one of several traits of the shade avoidance syndrome (SAS). SAS traits are elicited upon perception of vegetation shade signals such as far-red light (FR) and improve light capture in dense vegetation. Monitoring plant movement at a high temporal resolution allows studying functionality and molecular regulation of hyponasty. However, high temporal resolution imaging solutions are often very expensive, making this unavailable to many researchers. Here, we present a modular and low-cost imaging set-up, based on small Raspberry Pi computers, that can track leaf movements and elongation growth with high temporal resolution. We also developed an open-source, semi-automated image analysis pipeline. Using this setup we followed responses to FR enrichment, light intensity, and their interactions. Tracking both elongation and the angle of the petiole, lamina, and entire leaf in Arabidopsis (Arabidopsis thaliana) revealed insight into R:FR sensitivities of leaf growth and movement dynamics and the interactions of R:FR with background light intensity. The detailed imaging options of this system allowed us to identify spatially separate bending points for petiole and lamina positioning of the leaf.

Genetic perturbation in different genetic backgrounds can cause a range of phenotypes within a species. These phenotypic differences can be the result of the interaction between the genetic background and the perturbation. Previously, we reported that perturbation of gld-1, an important player in the developmental control of Caenorhabditis elegans, released cryptic genetic variation (CGV) affecting fitness in different genetic backgrounds. Here, we investigated the change in transcriptional architecture. We found 414 genes with a cis-expression quantitative trait locus (eQTL) and 991 genes with a trans-eQTL that were specifically found in the gld-1 RNAi treatment. In total, we detected 16 eQTL hotspots, of which 7 were only found in the gld-1 RNAi treatment. Enrichment analysis of those 7 hotspots showed that the regulated genes were associated with neurons and the pharynx. Furthermore, we found evidence of accelerated transcriptional aging in the gld-1 RNAi-treated nematodes. Overall, our results illustrate that studying CGV leads to the discovery of hidden polymorphic regulators.

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.

Illumina reads from aquifer / groundwater for drinking water production from the Netherlands. 18 Samples from 3 different monitoring wells. Every well was sampled 6 times at different depths between 12-65m below the surface., Illumina reads from aquifer / groundwater for drinking water production from the Netherlands. 18 Samples from 3 different monitoring wells. Every well was sampled 6 times at different depths between 12-65m below the surface.

Genetic perturbation in different genetic backgrounds can cause a range of phenotypes within a species. These phenotypic differences can be the result of the interaction between the genetic background and the perturbation. Previously, we reported that perturbation of gld-1, an important player in the developmental control of Caenorhabditis elegans, released cryptic genetic variation (CGV) affecting fitness in different genetic backgrounds. Here, we investigated the change in transcriptional architecture. We found 414 genes with a cis-expression quantitative trait locus (eQTL) and 991 genes with a trans-eQTL that were specifically found in the gld-1 RNAi treatment. In total, we detected 16 eQTL hotspots, of which 7 were only found in the gld-1 RNAi treatment. Enrichment analysis of those 7 hotspots showed that the regulated genes were associated with neurons and the pharynx. Furthermore, we found evidence of accelerated transcriptional aging in the gld-1 RNAi–treated nematodes. Overall, our results illustrate that studying CGV leads to the discovery of hidden polymorphic regulators.

Information processing is an essential part of biology, enabling coordination of intra-organismal processes such as development, environmental adaptation and inter-organismal communication. Whilst in animals with specialised brain tissue a substantial amount of information processing occurs in a centralised manner, most biological computing is distributed across multiple entities, such as cells in a tissue, roots in a root system or ants in a colony. Physical context, called embodiment, also affects the nature of biological computing. While plants and ant colonies both perform distributed computing, in plants the units occupy fixed positions while individual ants move around. This distinction, solid versus liquid brain computing, shapes the nature of computations. Here we compare information processing in plants and ant colonies, highlighting how similarities and differences originate in, as well as make use of, the differences in embodiment. We end with a discussion on how this embodiment perspective may inform the debate on plant cognition.

Microbiomes play a pivotal role in plant growth and health, but the genetic factors involved in microbiome assembly remain largely elusive. Here, we map the molecular features of the rhizosphere microbiome as quantitative traits of a diverse hybrid population of wild and domesticated tomato. Gene content analysis of prioritized tomato quantitative trait loci suggests a genetic basis for differential recruitment of various rhizobacterial lineages, including a Streptomyces-associated 6.31 Mbp region harboring tomato domestication sweeps and encoding, among others, the iron regulator FIT and the water channel aquaporin SlTIP2.3. Within metagenome-assembled genomes of root-associated Streptomyces and Cellvibrio, we identify bacterial genes involved in metabolism of plant polysaccharides, iron, sulfur, trehalose, and vitamins, whose genetic variation associates with specific tomato QTLs. By integrating 'microbiomics' and quantitative plant genetics, we pinpoint putative plant and reciprocal rhizobacterial traits underlying microbiome assembly, thereby providing a first step towards plant-microbiome breeding programs.

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.

The original version of this article unfortunately contained a mistake. The Tables 1 and 2 were published erroneously. The corrected Tables 1 and 2 were shown in the next page. The publisher sincerely apologizes for this error and any inconvenience caused to the authors and readers of the journal. The original article has been corrected.