Biology subjects

Cui, Y.

Publications and source records attributed to Cui, Y..

At least 19 recordsLinked to original sources

bioRxiv2026

BioIMA: a one-click desktop tool for standardized extraction of phenotypic traits from biological images

Standardized extraction of quantitative phenotypes from images is increasingly important across plant biology, from ecological and evolutionary studies to genetics, breeding, and functional genomics. However, as large image datasets are increasingly used for trait analysis, many biologically relevant traits, including size, shape, color, and spatial patterning, are still measured manually or using fragmented semi-automated workflows. These limitations reduce throughput, reproducibility, and accessibility, especially for researchers without computational expertise. Here, we present BioIMA, an open-source desktop tool for rapid and standardized phenotyping from biological images. BioIMA integrates foundation model-based segmentation with automated trait computation, allowing users to extract quantitative measurements from images through an intuitive graphical interface and without model training. To validate its performance, we quantified a set of knot morphological traits in two Populus species, as these measurements are typically time-consuming to perform manually. Automatic measurements showed strong agreement with manual ImageJ-based measurements (R2 > 0.95), while reducing per-image processing time by approximately 75% (from ~15 s to ~4 s). BioIMA was further applied to diverse plant datasets, including Helianthus and Rhododendron images with varying morphologies and background conditions. Although developed for plant phenotyping, BioIMA may also be extended to other biological samples where region-based size, shape, or color traits are of interest. By combining accessibility and standardization in a lightweight local application, BioIMA provides a practical community resource for image-based phenotyping in ecological and evolutionary studies.

bioinformatics↗

bioRxiv2018

The genome of the plague-resistant great gerbil reveals species-specific duplication of an MHCII gene

The great gerbil (Rhombomys opimus) is a social rodent living in permanent, complex burrow systems distributed throughout Central Asia, where it serves as the main host of several important vector-borne infectious diseases and is defined as a key reservoir species for plague (Yersinia pestis). Studies from the wild have shown that the great gerbil is largely resistant to plague but the genetic basis for resistance is yet to be determined. Here, we present a highly contiguous annotated genome assembly of great gerbil, covering over 96 % of the estimated 2.47 Gb genome. Comparative genomic analyses focusing on the immune gene repertoire, reveal shared gene losses within TLR gene families (i.e. TLR8, TLR10 and all members of TLR11-subfamily) for the Gerbillinae lineage, accompanied with signs of diversifying selection of TLR7 and TLR9. Most notably, we find a great gerbil-specific duplication of the MHCII DRB locus. In silico analyses suggest that the duplicated gene provides high peptide binding affinity for Yersiniae epitopes. The great gerbil genome provides new insights into the genomic landscape that confers immunological resistance towards plague. The high affinity for Yersinia epitopes could be key in our understanding of the high resistance in great gerbils, putatively conferring a faster initiation of the adaptive immune response leading to survival of the infection. Our study demonstrates the power of studying zoonosis in natural hosts through the generation of a genome resource for further comparative and experimental work on plague survival and evolution of host-pathogen interactions.

genomics↗

bioRxiv2018

Actomyosin-mediated nanostructural remodeling of the presynaptic vesicle pool by cannabinoids induces long-term depression

Endo- and exocannabinoids, such as the psychoactive component of marijuana, exert their effects on brain function by inducing several forms of synaptic plasticity through the modulation of presynaptic vesicle release. However, the molecular mechanisms underlying the widely expressed endocannabinoid-mediated long-term depression (eCB-LTD), are poorly understood. Here, we reveal that eCB-LTD depends on the contractile properties of the pre-synaptic actomyosin cytoskeleton. Preventing this contractility, both directly by inhibiting non-muscle myosin II NMII ATPase and indirectly by inhibiting the upstream Rho-associated kinase ROCK, abolished long-term, but not short-term forms of cannabinoid-induced functional plasticity in both inhibitory hippocampal and excitatory cortico-striatal synapses. Furthermore, using 3D superresolution microscopy, we find an actomyosin contractility-dependent redistribution of synaptic vesicle pools within the presynaptic compartment following cannabinoid receptor activation, leading to vesicle clustering and depletion from the pre-synaptic active zone. These results suggest that cannabinoid-induced functional plasticity is mediated by a nanoscale structural reorganization of the presynaptic compartment produced by actomyosin contraction. By introducing the contractile NMII as an important actin binding/structuring protein in the dynamic regulation of synaptic function, our results open new perspectives in the understanding of mechanisms of synaptic and cognitive function, marijuana intoxication and psychiatric pathogenesis.

neuroscience↗

bioRxiv2018

Modeling Sensory-Motor Decisions in Natural Behavior

Although a standard reinforcement learning model can capture many aspects of reward-seeking behaviors, it may not be practical for modeling human natural behaviors because of the richness of dynamic environments and limitations in cognitive resources. We propose a modular reinforcement learning model that addresses these factors. Based on this model, a modular inverse reinforcement learning algorithm is developed to estimate both the rewards and discount factors from human behavioral data, which allows predictions of human navigation behaviors in virtual reality with high accuracy across different subjects and with different tasks. Complex human navigation trajectories in novel environments can be reproduced by an artificial agent that is based on the modular model. This model provides a strategy for estimating the subjective value of actions and how they influence sensory-motor decisions in natural behavior.\n\nAuthor summaryIt is generally agreed that human actions can be formalized within the framework of statistical decision theory, which specifies a cost function for actions choices, and that the intrinsic value of actions is controlled by the brains dopaminergic reward machinery. Given behavioral data, the underlying subjective reward value for an action can be estimated through a machine learning technique called inverse reinforcement learning. Hence it is an attractive method for studying human reward-seeking behaviors. Standard reinforcement learning methods were developed for artificial intelligence agents, and incur too much computation to be a viable model for real-time human decision making. We propose an approach called modular reinforcement learning that decomposes a complex task into independent decision modules. This model includes a frequently overlooked variable called the discount factor, which controls the degree of impulsiveness in seeking future reward. We develop an algorithm called modular inverse reinforcement learning that estimates both the reward and the discount factor. We show that modular reinforcement learning may be a useful model for natural navigation behaviors. The estimated rewards and discount factors explain human walking direction decisions in a virtual-reality environment, and can be used to train an artificial agent that can accurately reproduce human navigation trajectories.

neuroscience↗

bioRxiv2018

Regulation by HSP70/90 in the different tissues and testis development of male cattle (Cattle-yak and Yak)

HSP70/90 play important role in testis develop and spermatozoa regulation, but the contact of HSP70/90 with infertility in cattle is unclear. Here, we focus on male cattle-yak and yak, which to investigate the expression and localization of HSP70/90 in different tissues, and explore the influence of HSP70/90 to infertility. In our study, a total of 54 cattle (24 cattle-yak and 30 yak) were examined. The HSP90 mRNA of cattle-yak was cloned first and found amino acid variation in HSP90, which led to difference at protein spatial structure compare with yak. To investigate whether the expression of HSP70/90 mRNA and protein are different in cattle-yak and yak, we used real-time quantitative PCR (qRT-PCR) and Western blot (WB) to examine them. We found that the expression level of HSP70/90 mRNA and protein are disparity in different tissues and testis development stages, and obviously high expression was observed in testicle during juvenile and adult, Moreover, it s interestingly in which the HSP70 expression is significant high in yak whereas HSP90 in cattle-yak (P<0.01). On this bases, we detect the location of HSP70/90 in testis by immunohistochemical (IHC) and immunofluorescence (IF), the results demonstrate that HSP70/90 were located in the epithelial cells, spermatogenic cells and mesenchymal cells. In summary, our study proved the expression of HSP70/90 are different in tissues, and the expression of HSP90 is obviously high in testis of cattle-yak, which propose that the infertility of cattle-yak may cause from up-regulating of HSP90.

biochemistry↗

bioRxiv2018

Artificial Selection on Storage Protein 1 Contributes to Increase of Hatchability during Silkworm Domestication

Like other domesticates, efficient utilization of nitrogen resource is also important for the domestic insect, the silkworm. Deciphering how artificial selection act on silkworm genome for improved utilization of nitrogen resource and further human-favored domestication traits will provide unique cues from the insect scenario for understanding general rules of Darwins evolutionary theory on domestication. Storage proteins (SP), which belong to a hemocyanin superfamily, basically serve as a source of amino acids and nitrogen during metamorphosis and reproduction in insects. Here through genomic search and further screening of artificial selection signature on silkworm SPs, we discovered a candidate domestication gene, i.e. the methionine-rich storage protein1 (SP1), which is uniquely diverged from the others and showed increased expression in the ova of domestic silkworms. Knockout of SP1 via CRISPR/Cas9 approach resulted in dramatic decrease in egg hatchability, without obvious impact on egg production, which was similar to the case in the wild silkworm compared with domestic one. Larval development or metamorphosis were not affected by SP1 knockout. Comprehensive ova comparative transcriptomes indicated a general repression of gene expression, specifically vitellogenin, chorion proteins and structural component proteins in the extracellular matrix (ECM)-interaction pathway, as well as enzymes in folate biosynthesis, in both the mutant and the wild silkworm with the mutated allele, compared to the wild type domestic silkworm. Wild silkworms with the wild allele also showed generally down-regulated expression of genes enriched in structural constituent of ribosome and amide and peptide biosynthesis. This study exemplified a novel case that artificial selection could directly act on nitrogen resource protein to affect egg nutrient and eggshell formation, and activate ribosome for improved biosynthesis and increased hatchability during domestication. The findings shed new light on both understanding of artificial selection and silkworm breeding from the angle of nitrogen and amino acid resource.\n\nAuthor summaryLike other domesticates, nitrogen resource is also important for the domestic insect, the silkworm. Deciphering how artificial selection act on silkworm genome for improved utilization of nitrogen resource and further human-favored domestication traits, will provide unique cues from insect scenario, for understanding general rules of Darwins evolutionary theory. However, mechanism of domestication in the silkworm is largely unknown to date. Here we focused on one important nitrogen resource, i.e, the storage proteins (SP). We discovered that the methionine-rich storage protein1 (SP1) which is divergent from the other SPs are the only target of the artificial selection. We proposed based on functional evidence together with the key findings of comprehensive comparative transcriptome, that artificial selection, on one hand favored higher expression of SP1 in the domestic silkworm, which would subsequently up-regulate the genes or pathways vital for egg development and eggshell formation. On the other hand, artificial selection consistently favored activated ribosome activities and improved amide and peptide biosynthesis and in the ova, as it might act in the silk gland for increased silk-cocoon yield. We here exemplified a novel case that artificial selection could directly act on nitrogen resource protein for human desired domestication trait.

evolutionary biology↗

bioRxiv2018

Why panmictic bacteria are rare

BackgroundBacteria typically have more structured populations than higher eukaryotes, but this difference is surprising given high recombination rates, enormous population sizes and effective geographical dispersal in many bacterial species.\n\nResultsWe estimated the recombination scaled effective population size Ner in 21 bacterial species and find that it does not correlate with synonymous nucleotide diversity as would be expected under neutral models of evolution. Only two species have estimates substantially over 100, consistent with approximate panmixia, namely Helicobacter pylori and Vibrio parahaemolyticus. Both species are far from demographic equilibrium, with diversity predicted to increase more than 30 fold in V. parahaemolyticus if the current value of Ner were maintained, to values much higher than found in any species. We propose that panmixia is unstable in bacteria, and that persistent environmental species are likely to evolve barriers to genetic exchange, which act to prevent a continuous increase in diversity by enhancing genetic drift.\n\nConclusionsOur results highlight the dynamic nature of bacterial population structures and imply that overall diversity levels found within a species are poor indicators of its size.

microbiology↗

bioRxiv2018

DeepSeqPan, a novel deep convolutional neural network model for pan-specific class I HLA-peptide binding affinity prediction

Interactions between human leukocyte antigens (HLAs) and peptides play a critical role in the human immune system. Accurate computational prediction of HLA-binding peptides can be used for peptide drug discovery. Currently, the best prediction algorithms are neural network based pan-specific models, which take advantage of the large amount of data across HLA alleles. However, current pan-specific models are all based on the pseudo sequence encoding for modeling the binding context and depend on the available HLA protein-peptide bound structures. In this work, we proposed a novel deep convolutional neural network model (DCNN) for HLA-peptide binding prediction, in which the encoding of the HLA sequence and the binding context are both learned by the network itself without requiring the HLA-peptide bound structure information. Our DCNN model is also characterized by its binding context extraction layer and dual outputs with both binding affinity output and binding probability outputs. Evaluation on public benchmark datasets shows that our DeepSeqPan model without HLA structural information in training achieves state-of-the-art performance on a large number of HLA alleles with good generalization capability. Since our model only needs raw sequences from the HLA-peptide binding pairs, it can be applied to binding predictions of HLAs without structure information and can also be applied to other protein binding problems such as protein-DNA and protein-RNA bindings. The implementation code and trained models are freely available at https://github.com/pcpLiu/DeepSeqPan.

bioinformatics↗

bioRxiv2018

The landscape of coadaptation in Vibrio parahaemolyticus

Investigating fitness interactions in natural populations remains a considerable challenge. We take advantage of the unique population structure of Vibrio parahaemolyticus, a bacterial pathogen of humans and shrimp, to perform a genome-wide screen for coadapted genetic elements. We identified 90 interaction groups involving 1,560 coding genes. 82 of these interaction groups are between accessory genes, many of which have functions related to carbohydrate transport and metabolism. Only 8 interaction groups involve both core and accessory genomes. The largest includes 1,540 SNPs in 82 genes and 338 accessory genome elements, many involved in lateral flagella and cell wall biogenesis. The interactions have a complex hierarchical structure encoding at least four distinct ecological strategies. Preliminary experiments imply that the strategies influence biofilm formation and bacterial growth rate in vitro. One strategy involves a divergent profile in multiple genome regions, implying that strains have irreversibly specialized, while the others involve fewer genes and are more plastic. Our results imply that most genetic alliances are ephemeral but that increasingly complex strategies can evolve and eventually cause speciation.

microbiology↗

bioRxiv2018

Recent mixing of Vibrio parahaemolyticus populations

BackgroundHumans have profoundly affected the ocean environment but little is known about anthropogenic effects on the distribution of microbes. Vibrio parahaemolyticus is found in warm coastal waters and causes gastroenteritis in humans and economically significant disease in shrimps.\n\nResultsBased on data from 1,103 genomes, we show that V. parahaemolyticus is divided into four diverse populations, VppUS1, VppUS2, VppX and VppAsia. The first two are largely restricted to the US and Northern Europe, while the others are found worldwide, with VppAsia making up the great majority of isolates in the seas around Asia. Patterns of diversity within and between the populations are consistent with them having arisen by progressive divergence via genetic drift during geographical isolation. However, we find that there is substantial overlap in their current distribution. These observations can be reconciled without requiring genetic barriers to exchange between populations if dispersal between oceans has increased dramatically in the recent past. We found that VppAsia isolates from the US have an average of 1.01% more shared ancestry with VppUS1 and VppUS2 isolates than VppAsia isolates from Asia itself. Based on time calibrated trees of divergence within epidemic lineages, we estimate that recombination affects about 0.017% of the genome per year, implying that the genetic mixture has taken place within the last few decades.\n\nConclusionsThese results suggest that human activity, such as shipping and aquatic products trade, are responsible for the change of distribution pattern of this marine species.

microbiology↗

bioRxiv2018

The Mechanical of Organic Acids Secreted by Roots of Tartary Buckwheat under the Effects of Low Nitrogen Stress

A pot experiment was conducted to study the effects of two different low nitrogen tolerant tartary buckwheat varieties (Diqing buckwheat (DQ, low nitrogen resistance) and Heifeng 1 (HF, low nitrogen sensitive) response mechanism of organic acids to low nitrogen stress. The results showed that the soil moisture of HF and DQ under low nitrogen treatment decreased 24.2% and 14.32%, respectively when compared with normal nitrogen treatment, and the water consumption of DQ was significantly higher than that of HF at seedling stage. Under low nitrogen treatment, the soil pH value of DQ was 1.44% and 8.44% lower than that of HF at seedling and flowering stages, respectively, the content of NH4+ in DQ soil was 8.2% lower than that of HF at maturity stage, the content of NO3- was significantly higher than that HF 49.2%, 12.9%, and 16.6% in each growth period, respectively. Split plot analysis showed that nitrogen treatment significantly affected the organic acids content in the soil of the buckwheat. The secretion content of organic acids are different among buckwheat cultivars under low nitrogen stress. In the soil of DQ, the content of malonic acid was higher than that of HF by 34.39% at maturity stage; the content of oxalic acid was respectively higher than that of HF by 24.86% and 24.52% at seedling and flowering stages; the content of propionic acid was significantly higher than that of HF by 7.36%, 9.44% and23.47% in each growth period, respectively; and tartaric acid acetic acid also showed the same trend at flowering and maturity stages. In summary, tartary buckwheat may regulate the nutrient availability of rhizosphere soil through the secretion of organic acids in the root system to cope with the low nitrogen stress environment. For the cultivation of tartary buckwheat on poor soil should consider the differences cultivaring barren resistance varieties to increase efficiency in the future.

plant biology↗

bioRxiv2018

An optimal kernel-based method for gene set association analysis

Single-variant based genome-wide association studies have successfully detected many genetic variants that are associated with many complex traits. However, their power is limited due to weak marginal signals and ignoring potential complex interactions among genetic variants. Set-based strategy was proposed to provide a remedy where multiple genetic variants in a given set (e.g., gene or pathway) are jointly evaluated, so that the systematic effect of the set is considered. Among many, the kernel-based testing (KBT) framework is one of the most popular and powerful methods in set-based association studies. Given a set of candidate kernels, method has been proposed to choose the one with the smallest p-value. Such a method, however, can yield inflated type I error, especially when the number of variants in a set is large. Alternatively one can get p-values by permutations which, however, could be very time consuming. In this work, we proposed an efficient testing procedure that can not only control type I error rate but also generate power close to the one obtained under the optimal kernel. Our method is built upon the KBT framework and is based on asymptotic results under a high-dimensional setting. Hence it can efficiently deal with the case where the number of variants in a set is much larger than the sample size. Both simulation and real data analysis demonstrate the advantages of the method compared with its counterparts.

genetics↗

bioRxiv2018

Time-dependent mnemonic vulnerability induced by new-learning

Reactivation renders consolidated memory labile again, and the ensuing temporary reconsolidation process is highly susceptible to mnemonic modification. Here, we show that memories in such an unstable state could be reprogrammed by sheer behavioral means, bypassing the need for pharmacological intervention. In two experiments using a \"face-location associationc\" paradigm in which participants experienced a \"Learning - New-learning - Final-test\" programme, we demonstrate that reactivated memory traces were robustly hampered when the new learning was strategically administered within a critical 20-minute time window. Using fMRI, we further advance our theoretical understanding that this lability can be mechanistically explained by the differential activation in the hippocampal-amygdala memory system implicated by the new-learning whereas the mnemonic intrusion caused by newly learned memories is efficaciously reconciled by the left inferior frontal gyrus. Our findings provide important implications for educational and clinical practices in devising effective strategies for memory integration.

neuroscience↗

bioRxiv2018

Robustness of STDP to spike timing jitter

In Hebbian plasticity, neural circuits adjust their synaptic weights depending on patterned firing of action potential on either side of the synapse. Spike-timing-dependent plasticity (STDP) is an experimental implementation of Hebbs postulate that relies on the precise order and the millisecond timing of the paired activities in pre- and postsynaptic neurons. In recent years, STDP has attracted considerable attention in computational and experimental neurosciences. However, canonical STDP is assessed with deterministic (constant) spike timings and time intervals between successive pairings, thus exhibiting a regularity that strongly differs from the biological variability. Hence, the emergence of STDP from noisy neural activity patterns as expected in in vivo-like firing remains unresolved. Here, we used noisy STDP stimulations where the spike timing and/or the interval between successive pairings were jittered. We explored with a combination of experimental neurophysiology and mathematical modeling, the impact of jittering on three distinct forms of STDP at corticostriatal synapses: NMDAR-mediated tLTP, endocannabinoid-mediated tLTD and endocannabinoid-mediated tLTP. As the main result, we found a differential sensitivity to jittered spike timing: NMDAR-tLTP was highly fragile whereas endocannabinoid-plasticity (tLTD and tLTP) appeared more resistant. Moreover, when the frequency or the number of pairings was increased, NMDAR-tLTP became more robust and could be expressed despite strong jittering of the spike timing. Taken together, our results identify endocannabinoid-mediated plasticity as a robust form of STDP while the sensitivity to jitter of NMDAR-tLTP varies with activity frequency. This provides new insights into the mechanisms at play during the different phases of learning and memory and the emergence of Hebbian plasticity in in vivo-like firing.

neuroscience↗

bioRxiv2018

Taxonomic Profiling and Populational Patterns of Bacterial Bile Salt Hydrolase (BSH) Genes on Worldwide Human Gut Microbiome

Bile salt hydrolase (BSH) in gut bacteria can hydrolyze conjugated bile salts to unconjugated bile acids and amino acids. Thereby play a crucially important role in host health by reducing serum cholesterol levels, preserving bile acids balance and regulating various metabolism as signaling molecules. Here we present the taxonomic identification of BSHs in human microbiota and elucidate the abundance and activity differences of various bacterial BSHs among 11 different populations. For the first time, we have revealed BSH are distributed in 154 intestinal bacterial strains within 33 genera in human microbiota. However, these BSHs present obviously differentiation for the sequence identity being from 28.6% to 100%, and the 32.7% bacteria strains having more than one paralogs of BSHs with dissimilarity. Therefore, we reclassified the BSHs from the different genera into 6 phylotypes basing on their phylogenetic tree, and demonstrate the significant abundance patterns of BSH phylotypes among different populations. From the enzyme activity comparison, the representative sequence of BSH-T3 was shown highest enzyme activity in 6 phylotypes. Meanwhile, BSH-T3 sequences which all distributed in Lactobacillus show highest abundance in Chinese and Austrian. The information illustrated by this study is useful for investigating the population differences of bile acid metabolism related diseases, and further giving a new suggestion on selection of probiotics or development of pharmaceutical proteins based upon the activity of BSH phylotypes to regulate host metabolism and maintain fitness.

genomics↗

bioRxiv2018

Electron transfer dictates metabolic reprogramming in proliferating cells under hypoxia

Metabolic reprogramming extensively occurs in proliferating cancer cells. This phenomenon occurs highly heterogeneously, but its origin has remained unclear. Here we use a physicochemical concept of free electron potential (FEP) and its equation of state to profile metabolites. We demonstrate that FEP change between substrates and products exactly reflects electrons dissipated in a metabolic transformation. Based on the law of conservation of electron in chemical reactions, a function of FEP change for central metabolism in proliferating cells are further derived, and it can accurately predict metabolic behaviors under hypoxia by maximizing the cellular FEP change to consume electrons. Therefore, enabling electron transfer dictates metabolic reprogramming in hypoxic cells, which underlies the major findings in cancer metabolism and is supported by our experiments. Importantly, our model established on FEP helps to reveal a combination of promising targets to inhibit tumor growth under hypoxia by blocking electron consumption, and could also guide future studies on cancer metabolism under hypoxia.

biochemistry↗

bioRxiv2017

VlbZIP30 of grapevine functions in drought tolerance via the abscisic acid core signaling pathway

Drought stress limits the growth and development of grapevines, thereby reducing productivity, but the mechanisms by which grapevines respond to drought stress remain largely uncharacterized. Here, we characterized a group A bZIP gene from Kyoho grapevine, VlbZIP30, which was shown to be induced by abscisic acid (ABA) and dehydration stress. Overexpression of VlbZIP30 in transgenic Arabidopsis enhanced dehydration tolerance during seed germination, and in the seedling and adult stages. Transcriptome analysis revealed that a major proportion of ABA- and/or drought-responsive genes are transcriptionally regulated by VlbZIP30 during ABA or mannitol treatment at the cotyledon greening stage. We identified an A. thaliana G-box motif (CACGTG) and a potential grapevine G-box motif (MCACGTGK) in the promoters of the 39 selected A. thaliana genes up-regulated in the transgenic plants and in the 35 grapevine homologs, respectively. Subsequently, using two grapevine-related databases, we found that 74% and 84% (a total of 27 genes) of the detected grapevine genes were significantly up-regulated by ABA and drought stress, respectively, suggesting that these 27 genes involve in ABA or dehydration stress and may be regulated by VlbZIP30 in grapevine. We propose that VlbZIP30 functions as a positive regulator of drought-responsive signaling in the ABA core signaling pathway.\n\nHighlightVlbZIP30 positively regulate plant drought tolerance through regulated the expression of 27 grapevine candidate genes via G-box cis-element (MCACGTGK) in ABA signaling pathway.

plant biology↗

bioRxiv2017

BRUTUS-LIKE proteins moderate the transcriptional response to iron deficiency in roots

Iron is an essential micronutrient but in excess is toxic inside cells. Under iron deficiency, the expression of iron uptake genes is increased, but it is not known how the transcriptional response is controlled to avoid uptake of too much iron. The hemerythrin E3 ligases BRUTUS (BTS) and BTS-LIKE (BTSL) have previously been identified as negative regulators of the iron deficiency response. Our phylogenetic analysis indicated that BTSL proteins are present in dicotyledonous plants only and form a separate clade from BTS homologs. BTSL1 and BTSL2 in Arabidopsis thaliana are in a network with nearly all iron uptake genes, whereas BTS is in a shoot-specific network. BTSL1 and BTSL2 are expressed predominantly in the root epidermis and cortex, separate from BTS in the root stele, shoot and embryos. Mutant analysis identified BTSL2 as the dominant paralog of the otherwise redundant BTSL genes. The btsl double mutant had increased protein levels of FIT, the FER-like Iron deficiency-induced Transcription factor, and failed to switch off the transcriptional response upon iron resupply, leading to dramatic iron accumulation in roots and shoots. Protein interaction between the C-terminus of BTSL proteins and FIT indicate that FIT is a direct target for degradation. Taken together, our studies show that BTSL1 and BTSL2 control iron uptake in the epidermis and cortex, upstream of BTS in the vasculature and leaves.

plant biology↗