bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2024.06.14.599000

Cryptic Variation in Adaptive Phenotypes Revealed by Panspecific flc Mutants

Lutz, U.·Bezrukov, I.·Schwab, R.·Yuan, W.·Kollmar, M.·Weigel, D.
View original source ↗Export metadata ↓

Abstract

The study of mutants is one of the best tools for understanding the genetic basis of phenotypes that contribute to adaptation. Oddly, mutant analyses are almost always restricted to single genetic backgrounds and findings therefore can not be easily generalized. A case in point is the key regulator of flowering, FLOWERING LOCUS C (FLC), which has been inferred to explain much of the flowering time variation in Arabidopsis thaliana, yet mutants have been examined in very few backgrounds. We have previously established a set of panspecific flc mutants in 62 accessions of A. thaliana (Ruffley et al. 2024). Here, we investigate how genetic background modulates mutant effects on flowering and vegetative traits, as well as on physiology and transcriptomes. Time to onset of flowering in the genome-edited flc lines was reduced by up to 83%, but considerable variation remained. Genetic mapping showed that extremely early flowering in the absence of FLC was mostly explained by natural variation at the known FLC target FT, with additional contribution from loci colocalizing with FLC. Prognostic sequence analyses of accessions did not suggest that extremely-early combinations of engineered flc and natural FT alleles would be deleterious, yet extremely early flowering accessions are not represented in the commonly used collections of A. thaliana accessions. To test whether this discrepancy could be due to sampling bias, we undertook a focused collection effort of wild populations in Southern Italy, which confirmed that extremely early flowering accessions exist in natural populations. Apart from its specific role in flowering time regulation, FLC has pleiotropic effects on other ecophysiological traits such as growth, and these were also dependent on the genetic background, which was further supported by transcriptomic comparisons. Together we conclude that the various roles of FLC have greatly diversified in different genetic backgrounds. Our study provides a proof-of-concept on how analysis of panspecific mutants can reveal the true extent of genetic networks in which a focal gene participates in.

Explore related subjects

plant biologyPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Lutz, U., Bezrukov, I., Schwab, R., Yuan, W., Kollmar, M., Weigel, D.. 2024-06-17. Cryptic Variation in Adaptive Phenotypes Revealed by Panspecific flc Mutants. https://doi.org/10.1101/2024.06.14.599000

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

AtNHR2A and AtNHR2B participate in unconventional protein secretion in response to environmental stress

The Arabidopsis thaliana nonhost resistance proteins 2A (AtNHR2A) and 2B (AtNHR2B) play crucial roles in plant immunity as the single mutants Atnhr2a and Atnhr2b and the double mutant Atnhr2bAtnhr2a are susceptible to the non-adapted pathogen Pseudomonas syringae pv. tabaci that is unable to infect wild-type Col-0 plants. The localization of fluorescent versions of AtNHR2A and AtNHR2B to compartments of the endomembrane system together with their interaction with secreted proteins suggested a function in endomembrane-mediated secretory processes participating in plant immunity. Comparative apoplastic proteomics analysis between wild type Col-0 and the double mutant Atnhr2bAtnhr2a after treatment P. syringae pv. tabaci, revealed that AtNHR2A and AtNHR2B are indeed required for the secretion of proteins containing N-terminal signal peptides that occurs through the conventional protein secretion pathway. In this work, we leveraged these apoplastic proteomics datasets to identify proteins lacking N-terminal signal peptide and expected to be secreted through unconventional secretion pathway(s). We discovered that AtNHR2A and AtNHR2B are also required for the secretion of proteins through an unconventional secretion pathway that, intriguingly, included proteins previously associated with abiotic stress. These findings led us to define the subcellular dynamics of AtNHR2A and AtNHR2B, and through co-localization analyses and the use of vesicle trafficking inhibitors, we uncovered their trafficking pathways transitioning through Golgi-dependent and Golgi-independent pathways to ultimately reach the central vacuole. Our findings suggest that AtNHR2A and AtNHR2B participate in a multivesicular bodies-vacuole-mediated unconventional secretion pathway that results in the release of proteins involved in plant responses to environmental stresses.

plant biology↗
bioRxiv2026

Low-cost rhizotron imaging and zero-shot deep-learning resolve temporal, spatial, and genetic variation in grapevine rootstock root systems

Root system architecture shapes how grapevine rootstocks take up water and nutrients, yet roots remain the least phenotyped grapevine organ because they are hidden and hard to image. We present a low-cost phenotyping pipeline that pairs custom acrylic rhizotrons (about US$30 each) with a consumer flatbed scanner and BiRefNet, a general-purpose deep-learning model used without training on root images, followed by automated mask cleaning, skeleton-based trait extraction, and soil moisture mapping. We tested it on nine commercial rootstocks scanned 16 times over 42 days after transplanting (DAT), with half under a ten-day water deficit. From 1,108 images we extracted 21 whole-root, depth-resolved, and topological traits. Genotypes differed in nearly every trait and in how they changed over time. Heritability of size and branching traits peaked at 0.92-0.93 between 21 and 31 DAT and fell for width, depth, and convex hull once roots reached the rhizotron walls, defining the best measurement window. The image-derived soil moisture map accurately tracked the deficit and its recovery. Deficit plants shifted new root growth to deeper soil without growing less overall, and the substrate dried fastest around older and denser roots. Root brightness decreased with root age and local moisture, and transport segments (axes serving several tips) were brighter than terminal laterals in every genotype. Root system size was associated with stomatal conductance in well-watered plants, and stomatal recovery after re-watering correlated with new root growth. The pipeline turns simple hardware into a quantitative, time-resolved root phenotyping platform suitable for breeding.

plant biology↗
bioRxiv2026

Engineering chromatin to encode transcriptional immune memory in Arabidopsis

Transcriptional memory enables organisms to respond more rapidly to recurrent stress, yet the underlying features of chromatin that contribute to this transcriptional recalibration remain poorly defined. Here we identify the genes displaying transcriptional memory in response to the bacterial immune elicitor, flg22, in Arabidopsis thaliana. In comparison to non-memory response genes, these memory genes show a preference for tissue-specific over uniform spatial expression patterning. The chromatin architecture of these genes in the resting state displays depletion of H3K4me3, elevation H3K27me3 and a subset are marked by H3K27me3-H3K4me3 bivalency. The H3K4me3 demethylase, JMJ14, is required for transcriptional memory, with JMJ14 occupancy enriched over memory gene loci. Upon priming, chromatin is reconfigured, with H3K4me3 levels increasing in a sustained manner at memory gene loci. To assess the function of this H3K4me3 accrual, we employ epigenome-engineering, observing that its targeted deposition at memory gene loci, including the WRKY29 locus, is sufficient to drive transcriptional memory and can endow plants with enhanced resistance to the bacterial pathogen, Pseudomonas syringae. Together, the findings demonstrate a causal role for H3K4me3 in transcriptional memory, under the regulation of JMJ14, and open the door for rational rewriting of chromatin to enhance organismal resilience.

plant biology↗