Protocol of a parallel, randomized controlled trial on the effects of a novel personalized nutrition approach by artificial intelligence in real world scenario.

BACKGROUND: Nutrition service needs are huge in China. Previous studies indicated that personalized nutrition (PN) interventions were effective. The aim of the present study is to identify the effectiveness and feasibility of a novel PN approach supported by artificial intelligence (AI). METHODS: This study is a two-arm parallel, randomized, controlled trial in real world scenario. The participants will be enrolled among who consume lunch at a staff canteen. In Phase I, a total of 170 eligible participants will be assigned to either intervention or control group on 1:1 ratio. The intervention group will be instructed to use the smartphone applet to record their lunches and reach the real-time AI-based information of dish nutrition evaluation and PN evaluation after meal consumption for 3 months. The control group will receive no nutrition information but be asked to record their lunches though the applet. Dietary pattern, body weight or blood pressure optimizing is expected after the intervention. In phase II, the applet will be free to all the diners (about 800) at the study canteen for another one year. Who use the applet at least 2 days per week will be regarded as the intervention group while the others will be the control group. Body metabolism normalization is expected after this period. Generalized linear mixed models will be used to identify the dietary, anthropometric and metabolic changes. DISCUSSION: This novel approach will provide real-time AI-based dish nutrition evaluation and PN evaluation after meal consumption in order to assist users with nutrition information to make wise food choice. This study is designed under a real-life scenario which facilitates translating the trial intervention into real-world practice. TRIAL REGISTRATION: This trial has been registered with the Chinese Clinical Trial Registry (ChiCTR2100051771; date registered: 03/10/2021).

Knocking out NEGATIVE REGULATOR OF PHOTOSYNTHESIS 1 increases rice leaf photosynthesis and biomass production in the field.

Improving photosynthesis is a major approach to increasing crop yield potential. Here we identify a transcription factor as a negative regulator of photosynthesis, which can be manipulated to increase rice photosynthesis and plant biomass in the field. This transcription factor, named negative regulator of photosynthesis 1 (NRP1; Os07g0471900), was identified through a co-expression analysis using rice leaf RNA sequencing data. NRP1 expression showed significantly negative correlation with the expression of many genes involved in photosynthesis. Knocking out NRP1 led to greater photosynthesis and increased biomass in the field, while overexpression of NRP1 decreased photosynthesis and biomass. Transcriptomic data analysis shows that NRP1 can negatively regulate the expression of photosynthetic genes. Protein transactivation experiments show that NRP1 is a transcription activator, implying that NRP1 may indirectly regulate photosynthetic gene expression through an unknown regulator. This study shows that combination of bioinformatics analysis with transgenic testing can be used to identify new regulators to improve photosynthetic efficiency in crops.

Distinct mRNA and long non-coding RNA expression profiles of decidual natural killer cells in patients with early missed abortion.

Early non-chromosome-related missed abortion (MA) is commonly associated with an altered immunological environment during pregnancy. Human decidual natural killer (dNK) cells, the most abundant lymphocyte population within the first-trimester maternal-fetal interface, are vital maternal regulators of immune tolerance mediating successful embryo implantation and placentation. Previous studies have shown that dNK cells may play a role in MA. However, the gene expression status and specific altered manifestations of dNK cells in patients with early MA remain largely unknown. Here, we show that MA dNK cells have distinct mRNA and lncRNA expression profiles through RNA sequencing, with a total of 276 mRNAs and 67 lncRNAs being differentially expressed compared with controls. Protein-protein interaction analysis of differentially expressed mRNAs was performed to identify hub genes and key modules. An lncRNA-mRNA regulatory network characterized by the small-world property was constructed to reveal the regulation of mRNA transcription by differential hub lncRNAs. Functional annotation of differentially expressed mRNAs and lncRNAs was performed to disclose their potential roles in MA pathogenesis. Our data highlight several enriched biological processes (immune response, inflammatory response, cell adhesion, and extracellular matrix [ECM] organization) and signaling pathways (cytokine-cytokine receptor interaction, ECM-receptor interaction, Toll-like receptor signaling pathway, and phosphatidylinositol signaling system) that may influence MA. This study is the first to demonstrate the involvement of altered mRNA and lncRNA expression profiles in the dNK cell pathogenesis of early MA, facilitating a better understanding of the underlying molecular mechanisms and the development of novel MA therapeutic strategies targeting key mRNAs and lncRNAs.

Application and prospect of cutting-edge information technology in biomedical big data.

In recent years, with the development of various high-throughput omics based biological technologies (BT), biomedical research began to enter the era of big data. In the face of high-dimensional, multi-domain and multi-modal biomedical big data, scientific research requires a new paradigm of data intensive scientific research. The vigorous development of cutting-edge information technologies (IT) such as cloud computing, blockchain and artificial intelligence provides technical means for the practice of this new research paradigm. Here,we describe the application of such cutting-edge information technologies in biomedical big data, and propose a forward-looking prospect for the construction of a new paradigm supporting environment for data intensive scientific research. We expect to establish a new research scheme and new scientific research paradigm integrating BT & IT technology, which can finally promote the great leap forward development of biomedical research.

Genome-wide association study identifies variation of glucosidase being linked to natural variation of the maximal quantum yield of photosystem II.

The maximum quantum yield of photosystem II (as reflected by variable to maximum chlorophyll a fluorescence, Fv /Fm ) is regarded as one of the most important photosynthetic parameters. The genetic basis underlying natural variation in Fv /Fm , which shows low level of variations in plants under non-stress conditions, is not easy to be exploited using the conventional gene cloning approaches. Thus, in order to answer this question, we have followed another strategy: we used genome-wide association study (GWAS) and transgenic analysis in a rice mini-core collection. We report here that four single-nucleotide polymorphisms, located in the promoter region of ß-glucosidase 5 (BGlu-5), are associated with observed variation in Fv /Fm . Indeed, our transgenic analysis showed a good correlation between BGlu-5 and Fv /Fm . Thus, our work demonstrates the feasibility of using GWAS to study natural variation in Fv /Fm , suggesting that cis-element polymorphism, affecting the BGlu-5 expression level, may, indirectly, contribute to Fv /Fm variation in rice through the gibberellin signaling pathway. Further research is needed to understand the mechanism of our novel observation.

A Barrage Jamming Strategy Based on CRB Maximization against Distributed MIMO Radar.

Distributed multiple input multiple output (MIMO) radar has attracted much attention for its improved detection and estimation performance as well as enhanced electronic counter-counter measures (ECCM) ability. To protect the target from being detected and tracked by such radar, we consider a barrage jamming strategy towards a distributed MIMO. We first derive the Cramer-Rao bound (CRB) of target parameters estimation using a distributed MIMO under barrage jamming environments. We then set maximizing the CRB as the criterion for jamming resource allocation, aiming at degrading the accuracy of target parameters estimation. Due to the non-convexity of the CRB maximizing problem, particle swarm optimization is used to solve the problem. Simulation results demonstrate the advantages of the proposed strategy over traditional jamming methods.

Leaf Photosynthetic Parameters Related to Biomass Accumulation in a Global Rice Diversity Survey.

Mining natural variations is a major approach to identify new options to improve crop light use efficiency. So far, successes in identifying photosynthetic parameters positively related to crop biomass accumulation through this approach are scarce, possibly due to the earlier emphasis on properties related to leaf instead of canopy photosynthetic efficiency. This study aims to uncover rice (Oryza sativa) natural variations to identify leaf physiological parameters that are highly correlated with biomass accumulation, a surrogate of canopy photosynthesis. To do this, we systematically investigated 14 photosynthetic parameters and four morphological traits in a rice population, which consists of 204 U.S. Department of Agriculture-curated minicore accessions collected globally and 11 elite Chinese rice cultivars in both Beijing and Shanghai. To identify key components responsible for the variance of biomass accumulation, we applied a stepwise feature-selection approach based on linear regression models. Although there are large variations in photosynthetic parameters measured in different environments, we observed that photosynthetic rate under low light (Alow) was highly related to biomass accumulation and also exhibited high genomic inheritability in both environments, suggesting its great potential to be used as a target for future rice breeding programs. Large variations in Alow among modern rice cultivars further suggest the great potential of using this parameter in contemporary rice breeding for the improvement of biomass and, hence, yield potential.

Disturbed tryptophan metabolism correlating to progression and metastasis of esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) is one of the most frequent malignancies worldwide. Lymph node metastasis is the leading cause of death in ESCC patients. To identify early diagnostic and prognostic biomarkers of ESCC and elucidate underlying pathogenesis of the disease, a targeted metabolomics strategy based on liquid chromatography combined with tandem mass spectrometry was applied to explore tryptophan metabolism between ESCC patients, metastatic ESCC patients (mESCC), and healthy controls. Statistical analysis on metabolite expression abundance and compound concentration ratio was conducted to discriminate patients from healthy controls. The concentration ratio of kynurenine, 5-hydroxytryptophan, 5-hydroxyindole-3-acetic acid, 5-hydroxytryptamine to their precursor tryptophan were identified as potential biomarkers, presenting high diagnostic capacity for distinguishing ESCC and mESCC patients from healthy controls. Moreover, a prognostic prediction model was also built on these ratios to distinguish metastasis patients from non-metastasis patients successfully. The high performance of ESCC prediction models suggest that concentration ratios of compounds may be used as biomarkers for early diagnosis and prognosis of the disease. In addition, concentration ratios of compounds show a progressively increased trend from non-metastasis to metastasis patients compared with healthy controls, which is in accordance with process of malignant transformation of ESCC. This interested finding suggests that disturbed tryptophan metabolism is correlated to progression and metastasis of ESCC since concentration ratios of compounds reflect activity of enzymes involved in tryptophan metabolism. This study reveals the impact of tryptophan metabolism to tumorigenesis and metastasis of ESCC, which help biologists investigate mechanism of the disease.

CMIP: a software package capable of reconstructing genome-wide regulatory networks using gene expression data.

BACKGROUND: A gene regulatory network (GRN) represents interactions of genes inside a cell or tissue, in which vertexes and edges stand for genes and their regulatory interactions respectively. Reconstruction of gene regulatory networks, in particular, genome-scale networks, is essential for comparative exploration of different species and mechanistic investigation of biological processes. Currently, most of network inference methods are computationally intensive, which are usually effective for small-scale tasks (e.g., networks with a few hundred genes), but are difficult to construct GRNs at genome-scale. RESULTS: Here, we present a software package for gene regulatory network reconstruction at a genomic level, in which gene interaction is measured by the conditional mutual information measurement using a parallel computing framework (so the package is named CMIP). The package is a greatly improved implementation of our previous PCA-CMI algorithm. In CMIP, we provide not only an automatic threshold determination method but also an effective parallel computing framework for network inference. Performance tests on benchmark datasets show that the accuracy of CMIP is comparable to most current network inference methods. Moreover, running tests on synthetic datasets demonstrate that CMIP can handle large datasets especially genome-wide datasets within an acceptable time period. In addition, successful application on a real genomic dataset confirms its practical applicability of the package. CONCLUSIONS: This new software package provides a powerful tool for genomic network reconstruction to biological community. The software can be accessed at http://www.picb.ac.cn/CMIP/ .

Evidence for the role of transposons in the recruitment of cis-regulatory motifs during the evolution of C4 photosynthesis.

BACKGROUND: C4 photosynthesis evolved from C3 photosynthesis and has higher light, water, and nitrogen use efficiencies. Several C4 photosynthesis genes show cell-specific expression patterns, which are required for these high resource-use efficiencies. However, the mechanisms underlying the evolution of cis-regulatory elements that control these cell-specific expression patterns remain elusive. RESULTS: In the present study, we tested the hypothesis that the cis-regulatory motifs related to C4 photosynthesis genes were recruited from non-photosynthetic genes and further examined potential mechanisms facilitating this recruitment. We examined 65 predicted bundle sheath cell-specific motifs, 17 experimentally validated cell-specific cis-regulatory elements, and 1,034 motifs derived from gene regulatory networks. Approximately 7, 5, and 1,000 of these three categories of motifs, respectively, were apparently recruited during the evolution of C4 photosynthesis. In addition, we checked 1) the distance between the acceptors and the donors of potentially recruited motifs in a chromosome, and 2) whether the potentially recruited motifs reside within the overlapping region of transposable elements and the promoter of donor genes. The results showed that 7, 4, and 658 of the potentially recruited motifs might have moved via the transposable elements. Furthermore, the potentially recruited motifs showed higher binding affinity to transcription factors compared to randomly generated sequences of the same length as the motifs. CONCLUSIONS: This study provides molecular evidence supporting the hypothesis that transposon-driven recruitment of pre-existing cis-regulatory elements from non-photosynthetic genes into photosynthetic genes plays an important role during C4 evolution. The findings of the present study coincide with the observed repetitive emergence of C4 during evolution.

Rig-I regulates NF-κB activity through binding to Nf-κb1 3'-UTR mRNA.

Retinoic acid inducible gene I (RIG-I) senses viral RNAs and triggers innate antiviral responses through induction of type I IFNs and inflammatory cytokines. However, whether RIG-I interacts with host cellular RNA remains undetermined. Here we report that Rig-I interacts with multiple cellular mRNAs, especially Nf-κb1. Rig-I is required for NF-κB activity via regulating Nf-κb1 expression at posttranscriptional levels. It interacts with the multiple binding sites within 3'-UTR of Nf-κb1 mRNA. Further analyses reveal that three distinct tandem motifs enriched in the 3'-UTR fragments can be recognized by Rig-I. The 3'-UTR binding with Rig-I plays a critical role in normal translation of Nf-κb1 by recruiting the ribosomal proteins [ribosomal protein L13 (Rpl13) and Rpl8] and rRNAs (18S and 28S). Down-regulation of Rig-I or Rpl13 significantly reduces Nf-κb1 and 3'-UTR-mediated luciferase expression levels. These findings indicate that Rig-I functions as a positive regulator for NF-κB signaling and is involved in multiple biological processes in addition to host antivirus immunity.

MOST+: A de novo motif finding approach combining genomic sequence and heterogeneous genome-wide signatures.

BACKGROUND: Motifs are regulatory elements that will activate or inhibit the expression of related genes when proteins (such as transcription factors, TFs) bind to them. Therefore, motif finding is important to understand the mechanisms of gene regulation. De novo discovery of regulatory elements, like transcription factor binding sites (TFBSs), has long been a major challenge to gain insight on mechanisms of gene regulation. Recent advances in experimental profiling of genome-wide signals such as histone modifications and DNase I hypersensitivity sites allow scientists to develop better computational methods to enhance motif discovery. However, existing methods for motif finding suffer from high false positive rates and slow speed, and it's difficult to evaluate the performance of these methods systematically. RESULT: Here we present MOST+, a motif finder integrating genomic sequences and genome-wide signals such as intensity and shape features from histone modification marks and DNase I hypersensitivity sites, to improve the prediction accuracy. MOST+ can detect motifs from a large input sequence of about 100 Mbs within a few minutes. Systematic comparison method has been established and MOST+ has been compared with existing methods. CONCLUSION: MOST+ is a fast and accurate de novo method for motif finding by integrating genomic sequence and experimental signals as clues.

Comparative transcriptome analysis of developmental stages of the Limonium bicolor leaf generates insights into salt gland differentiation.

With the expansion of saline land worldwide, it is essential to establish a model halophyte to study the salt-tolerance mechanism. The salt glands in the epidermis of Limonium bicolor (a recretohalophyte) play a pivotal role in salt tolerance by secreting excess salts from tissues. Despite the importance of salt secretion, nothing is known about the molecular mechanisms of salt gland development. In this study, we applied RNA sequencing to profile early leaf development using five distinct developmental stages, which were quantified by successive collections of the first true leaves of L. bicolor with precise spatial and temporal resolution. Specific gene expression patterns were identified for each developmental stage. In particular, we found that genes controlling salt gland differentiation in L. bicolor may evolve in a trichome formation, which was also confirmed by mutants with increased salt gland densities. Genes involved in the special ultrastructure of salt glands were also elucidated. Twenty-six genes were proposed to participate in salt gland differentiation. Our dataset sheds light on the molecular processes underpinning salt gland development and thus represents a first step towards the bioengineering of active salt-secretion capacity in crops.

Melatonin delays leaf senescence and enhances salt stress tolerance in rice.

Melatonin, an antioxidant in both animals and plants, has been reported to have beneficial effects on the aging process. It was also suggested to play a role in extending longevity and enhancing abiotic stress resistance in plant. In this study, we demonstrate that melatonin acts as a potent agent to delay leaf senescence and cell death in rice. Treatments with melatonin significantly reduced chlorophyll degradation, suppressed the transcripts of senescence-associated genes, delayed the leaf senescence, and enhanced salt stress tolerance. Genome-wide expression profiling by RNA sequencing reveals that melatonin is a potent free radical scavenger, and its exogenous application results in enhanced antioxidant protection. Leaf cell death in noe1, a mutant with over-produced H2O2, can be relieved by exogenous application of melatonin. These data demonstrate that melatonin delays the leaf senescence and cell death and also enhances abiotic stress tolerance via directly or indirectly counteracting the cellular accumulation of H2O2.

Investigating co-evolution of functionally associated phosphosites in human.

Phosphorylation is essential for protein function and signal transduction in eukaryotic cells. With the rapid development of mass spectrometry technology, a large number of phosphosites are identified. However, high-throughput methods of functional characterization for phosphosites are still scarce. In this study, we inspected if the co-evolution property can be used as an indicator to explore function of phosphosites through investigating co-evolutionary relationship between functionally associated phosphosites in human. In practice, the evolution attributes of phosphosites were represented with phylogenetic profiles, and then co-evolutionary correlations of functionally associated phosphosites were detected on three levels: (1) phosphosites within one protein; (2) phosphosites in different proteins participating in the same signal transduction pathways, and (3) general phosphosites. Results of the detection show that co-evolution is a general property of functionally associated phosphosites. This finding suggests to some degree that it is feasible to use the co-evolution property in exploring the function of phosphosites and investigating the functional association between them.

Comprehensive applications of the artificial intelligence technology in new drug research and development.

Purpose: Target-based strategy is a prevalent means of drug research and development (R&D), since targets provide effector molecules of drug action and offer the foundation of pharmacological investigation. Recently, the artificial intelligence (AI) technology has been utilized in various stages of drug R&D, where AI-assisted experimental methods show higher efficiency than sole experimental ones. It is a critical need to give a comprehensive review of AI applications in drug R &D for biopharmaceutical field. Methods: Relevant literatures about AI-assisted drug R&D were collected from the public databases (Including Google Scholar, Web of Science, PubMed, IEEE Xplore Digital Library, Springer, and ScienceDirect) through a keyword searching strategy with the following terms [("Artificial Intelligence" OR "Knowledge Graph" OR "Machine Learning") AND ("Drug Target Identification" OR "New Drug Development")]. Results: In this review, we first introduced common strategies and novel trends of drug R&D, followed by characteristic description of AI algorithms widely used in drug R&D. Subsequently, we depicted detailed applications of AI algorithms in target identification, lead compound identification and optimization, drug repurposing, and drug analytical platform construction. Finally, we discussed the challenges and prospects of AI-assisted methods for drug discovery. Conclusion: Collectively, this review provides comprehensive overview of AI applications in drug R&D and presents future perspectives for biopharmaceutical field, which may promote the development of drug industry.

Integrating single-cell and spatial analysis reveals MUC1-mediated cellular crosstalk in mucinous colorectal adenocarcinoma.

BACKGROUND: Mucinous colorectal adenocarcinoma (MCA) is a distinct subtype of colorectal cancer (CRC) with the most aggressive pattern, but effective treatment of MCA remains a challenge due to its vague pathological characteristics. An in-depth understanding of transcriptional dynamics at the cellular level is critical for developing specialised MCA treatment strategies. METHODS: We integrated single-cell RNA sequencing and spatial transcriptomics data to systematically profile the MCA tumor microenvironment (TME), particularly the interactome of stromal and immune cells. In addition, a three-dimensional bioprinting technique, canonical ex vivo co-culture system, and immunofluorescence staining were further applied to validate the cellular communication networks within the TME. RESULTS: This study identified the crucial intercellular interactions that engaged in MCA pathogenesis. We found the increased infiltration of FGF7+/THBS1+ myofibroblasts in MCA tissues with decreased expression of genes associated with leukocyte-mediated immunity and T cell activation, suggesting a crucial role of these cells in regulating the immunosuppressive TME. In addition, MS4A4A+ macrophages that exhibit M2-phenotype were enriched in the tumoral niche and high expression of MS4A4A+ was associated with poor prognosis in the cohort data. The ligand-receptor-based intercellular communication analysis revealed the tight interaction of MUC1+ malignant cells and ZEB1+ endothelial cells, providing mechanistic information for MCA angiogenesis and molecular targets for subsequent translational applications. CONCLUSIONS: Our study provides novel insights into communications among tumour cells with stromal and immune cells that are significantly enriched in the TME during MCA progression, presenting potential prognostic biomarkers and therapeutic strategies for MCA. KEY POINTS: Tumour microenvironment profiling of MCA is developed. MUC1+ tumour cells interplay with FGF7+/THBS1+ myofibroblasts to promote MCA development. MS4A4A+ macrophages exhibit M2 phenotype in MCA. ZEB1+ endotheliocytes engage in EndMT process in MCA.

Qijiao Shengbai Capsule alleviated leukopenia by interfering leukotriene pathway: Integrated network study of multi-omics.

BACKGROUND: Leukopenia could be induced by chemotherapy, which leads to bone marrow suppression and even affects the therapeutic progression of cancer. Qijiao Shengbai Capsule (QSC) has been used for the treatment of leukopenia in clinic, but its bioactive components and mechanisms have not yet been elucidated clearly. PURPOSE: This study aimed to elucidate the molecular mechanisms of QSC in treating leukopenia. STUDY DESIGN: Serum pharmacochemistry, multi-omics, network pharmacology, and validation experiment were combined to study the effect of QSC in murine leukopenia model. METHODS: First, UPLC-QTOF-MS was used to clarify the absorbed components of QSC. Then, cyclophosphamide (CTX) was used to induce mice model with leukopenia, and the therapeutic efficacy of QSC was assessed by an integrative approach of multi-omics and network pharmacology strategy. Finally, molecular mechanisms and potential therapeutic targets were identified by validated experiments. RESULTS: 121 compounds absorbed in vivo were identified. QSC significantly increase the count of white blood cells (WBCs) in peripheral blood of leukopenia mice with 15 days treatment. Multi-omics and network pharmacology revealed that leukotriene pathway and MAPK signaling pathway played crucial roles during the treatment of leukopenia with QSC. Six targets (ALOX5, LTB4R, CYSLTR1, FOS, JUN, IL-1ß) and 13 prototype compounds were supposed to be the key targets and potential active components, respectively. The validation experiment further confirmed that QSC could effectively inhibit the inflammatory response induced by leukopenia. The inhibitors of ALOX5 activity can significantly increase the number of WBCs in leukopenia mice. Molecular docking of ALOX5 suggested that calycosin, daidzein, and medicarpin were the potentially active compounds of QSC. CONCLUSION: Leukotriene pathway was found for the first time to be a key role in the development of leukopenia, and ALOX5 was conformed as the potential target. QSC may inhibit the inflammatory response and interfere the leukotriene pathway, it is able to improve hematopoiesis and achieve therapeutic effects in the mice with leukopenia.

Benzosceptrin C induces lysosomal degradation of PD-L1 and promotes antitumor immunity by targeting DHHC3.

Programmed cell death-1 (PD-1)/programmed cell death ligand-1 (PD-L1) blockade has become a mainstay of cancer immunotherapy. Targeting the PD-1/PD-L1 axis with small molecules is an attractive approach to enhance antitumor immunity. Here, we identified a natural marine product, benzosceptrin C (BC), that enhances the cytotoxicity of T cells to cancer cells by reducing the abundance of PD-L1. Furthermore, BC exerts its antitumor effect in mice bearing MC38 tumors by activating tumor-infiltrating T cell immunity. Mechanistic studies suggest that BC can prevent palmitoylation of PD-L1 by inhibiting DHHC3 enzymatic activity. Subsequently, PD-L1 is transferred from the membrane to the cytoplasm and cannot return to the membrane via recycling endosomes, triggering lysosome-mediated degradation of PD-L1. Moreover, the combination of BC and anti-CTLA4 effectively enhances antitumor T cell immunity. Our findings reveal a previously unrecognized antitumor mechanism of BC and represent an alternative immune checkpoint blockade (ICB) therapeutic strategy to enhance the efficacy of cancer immunotherapy.

Mutant DNA-binding domain of HSF4 is associated with autosomal dominant lamellar and Marner cataract.

Congenital cataracts cause 10-30% of all blindness in children, with one-third of cases estimated to have a genetic cause. Lamellar cataract is the most common type of infantile cataract. We carried out whole-genome linkage analysis of Chinese individuals with lamellar cataract, and found that the disorder is associated with inheritance of a 5.11-cM locus on chromosome 16. This locus coincides with one previously described for Marner cataract. We screened individuals of three Chinese families for mutations in HSF4 (a gene at this locus that encodes heat-shock transcription factor 4) and discovered that in each family, a distinct missense mutation, predicted to affect the DNA-binding domain of the protein, segregates with the disorder. We also discovered an association between a missense mutation and Marner cataract in an extensive Danish family. We suggest that HSF4 is critical to lens development.