Biology subjects

Zhang, L.

Publications and source records attributed to Zhang, L..

At least 1,459 records · Page 81Linked to original sources

bioRxiv2020

Sequence and annotation of 42 cannabis genomes reveals extensive copy number variation in cannabinoid synthesis and pathogen resistance genes

Cannabis is a diverse and polymorphic species. To better understand cannabinoid synthesis inheritance and its impact on pathogen resistance, we shotgun sequenced and assembled a Cannabis trio (sibling pair and their offspring) utilizing long read single molecule sequencing. This resulted in the most contiguous Cannabis sativa assemblies to date. These reference assemblies were further annotated with full-length male and female mRNA sequencing (Iso-Seq) to help inform isoform complexity, gene model predictions and identification of the Y chromosome. To further annotate the genetic diversity in the species, 40 male, female, and monoecious cannabis and hemp varietals were evaluated for copy number variation (CNV) and RNA expression. This identified multiple CNVs governing cannabinoid expression and 82 genes associated with resistance to Golovinomyces chicoracearum, the causal agent of powdery mildew in cannabis. Results indicated that breeding for plants with low tetrahydrocannabinolic acid (THCA) concentrations may result in deletion of pathogen resistance genes. Low THCA cultivars also have a polymorphism every 51 bases while dispensary grade high THCA cannabis exhibited a variant every 73 bases. A refined genetic map of the variation in cannabis can guide more stable and directed breeding efforts for desired chemotypes and pathogen-resistant cultivars. O_FIG O_LINKSMALLFIG WIDTH=160 HEIGHT=200 SRC="FIGDIR/small/894428v1_ufig1.gif" ALT="Figure 1"> View larger version (126K): org.highwire.dtl.DTLVardef@7a1ac3org.highwire.dtl.DTLVardef@731a4dorg.highwire.dtl.DTLVardef@c3e5acorg.highwire.dtl.DTLVardef@11babb4_HPS_FORMAT_FIGEXP M_FIG Sequence and annotation of 42 cannabis genomes reveals extensive copy number variation in cannabinoid synthesis and pathogen resistance genes C_FIG

genomics↗

bioRxiv2020

Predicting long-term multicategory cause of death in patients with prostate cancer: random forest versus multinomial model

Patients with prostate cancer more likely die of non-cancer cause of death (COD) than prostate cancer. It is thus important to accurately predict multi-category COD in these patients. Random forest (RF), a popular machine learning model, has been shown useful for predicting binary cancer-specific deaths. However, its accuracy for predicting multi-category COD in cancer patients is unclear. We included patients in Surveillance, Epidemiology, and End Results-18 cancer registry-program with prostate cancer diagnosed in 2004 (followed-up through 2016). They were randomly divided into training and testing sets with equal sizes. We evaluated prediction accuracies of RF and conventional-statistical/multinomial models for 6-category COD by data-encoding types using the 2-fold cross-validation approach. Among 49,864 prostate cancer patients, 29,611 (59.4%) were alive at the end of follow-up, and 5,448 (10.9%) died of cardiovascular disease, 4,607 (9.2%) of prostate cancer, 3,681 (7.4%) of Non-Prostate cancer, 717 (1.4%) of infection, and 5,800 (11.6%) of other causes. We predicted 6-category COD among these patients with a mean accuracy of 59.1% (n=240, 95% CI, 58.7%-59.4%) in RF models with one-hot encoding, and 50.4% (95% CI, 49.7%-51.0%) in multinomial models. Tumor characteristics, prostate-specific antigen level, and diagnosis confirmation-method were important in RF and multinomial models. In RF models, no statistical differences were found between the accuracies of development versus cross validation phases, and those of categorical versus one-hot encoding. We here report a RF model that has an accuracy of 59.1% in predicting long-term 6-category COD among prostate cancer patients. It outperforms multinomial logistic models (absolute prediction-accuracy difference, 8.7%).

bioinformatics↗

bioRxiv2019

Deep6mA: a deep learning framework for exploring similar patterns in DNA N6-methyladenine sites across different species

N6-methyladenin(6mA) is an important DNA modification form associated with a wide range of biological processes. Identifying accurately 6mA sites on a genomic scale is crucial for understanding of 6mAs biological functions. In this paper, we developed, without requiring any prior knowledge of 6mA and manually crafted sequence features, a deep learning framework named Deep6mA to identify DNA 6mA sites, and its performance is superior to other DNA 6mA prediction tools. Specifically, the 5-fold cross-validation on a benchmark dataset of rice gives the sensitivity and specificity of Deep6mA as 92.96% and 95.06%, respectively, and the overall prediction accuracy is 94%. Importantly, we find that the sequences with 6mA sites share similar patterns across different species. The model trained with rice data predicts well the 6mA sites of other three species: Arabidopsis thaliana, Fragaria vesca, and Rosa chinensis, with a prediction accuracy over 90%. In addition, we find that (1) 6mA tends to occur at GAGG motifs, which means the sequence near the 6mA site may be conservative; (2) 6mA is enriched in the TATA box of the promoter, which may be the main source of its regulating downstream gene expression.

bioinformatics↗

bioRxiv2019

The mechanosensitive Piezo1 orchestrating angiogenesis is essential in bone fracture repair

Mechanical ion channel protein Piezo1 play vital roles in angiogenesis which has been proved to be high importance in varieties of biological processes. Bone formation in the fracture repair requires oxygen and nutrients from new blood vessels generated from fractured lesion. Understanding the underlying mechanisms linking angiogenesis and bone formation must be of great value for improved fracture healing. Here we employed mice with genetically modified endothelial specific depletion of Piezo1 channels to explore the hypothesis that Piezo1 is vital to the initiation of fracture healing. In this study, we demonstrated that Piezo1 expression and wide distribution along the bone and impaired endothelial Piezo1 channels result in derangements in bone fracture repair. Intriguingly, the calcium activated proteolytic caplain activity severely disrupted during vascularization, precluded osteoblast maturation and mineralization and subsequently the phosphorylated PI3K-AKT reduction. Furthermore, Piezo1 endothelial disruption impaired Notch signaling in bone union. These data collectively suggest that Piezo1 channels serve as a basis for clinical strategies to improve bone regeneration and treat delayed or nonunion in bone fracture.

systems biology↗

bioRxiv2019

Low basal expression and slow induction of IFITM3 puts immune cells at risk of influenza A infection

The interferon-induced transmembrane protein, IFITM3, has been shown to restrict influenza virus infection in murine and in vitro settings for ten years, but no explanation has been found to explain why this virus infection is so highly contagious and infects most individuals it comes in contact with. We confirm that the expression level of IFITM3 plays a role in determining the level of viral infection through manipulation of IFITM3 levels with interferon (IFN) stimulation and overexpression systems. Low basal expression may put some immune cells, including lymphocytes and lung-resident macrophages, at risk of influenza virus infection. Investigating the induction of IFITM3 by IFN, we find a strong preference for Type I IFN in IFITM3 induction in both cell lines and primary human cells. While myeloid cells can increase expression following stimulation by Type I IFN, lymphocytes show minimal induction of IFITM3 following IFN stimulation, suggesting that they are always at risk of viral infection. Surprisingly, we found that the time it takes for maximal induction of IFITM3 is relatively slow for an interferon-stimulated gene at around 36 hours. Low basal expression and slow induction of IFITM3 could increase the risk of influenza virus infection in selected immune cells. ImportanceInfluenza virus infection remains one of the top ten threats to global health, causing significant deaths and hospitalisations across the world each year. Understanding mechanisms for controlling influenza virus infection remain a priority. The interferon-induced transmembrane protein IFITM3 can restrict influenza infection by limiting replication of the virus. The precise mechanisms of how IFITM3 reduced replication of influenza are unknown, although it is predicted to prevent release of viral contents into the cytosol by preventing pore formation on the endosomal compartments where it is suggested to reside. Here we have shown that the expression level of IFITM3 is important in determining the control of influenza virus infection. We find an expression pattern for IFITM3 that varies based on cell type, tissue locality, differentiation state and cell naivety, all of which highlights cells that may be at the highest risk of influenza infection.

immunology↗

bioRxiv2019

Cryo-EM Structures and Regulation of Arabinofuranosyltransferase AftD from Mycobacteria

Mycobacterium tuberculosis causes tuberculosis, a disease that kills over one million people each year. Its cell envelope is a common antibiotic target and has a unique structure due, in part, to two lipidated polysaccharides - arabinogalactan and lipoarabinomannan. Arabinofuranosyltransferase D (AftD) is an essential enzyme involved in assembling these glycolipids. We present the 2.9 [A] resolution structure of M. abscessus AftD determined by single particle cryo-electron microscopy. AftD has a conserved GT-C glycosyltransferase fold and three carbohydrate binding modules. Glycan array analysis shows that AftD binds complex arabinose glycans. Additionally, AftD is non-covalently complexed with an acyl carrier protein (ACP). 3.4 and 3.5 [A] structures of a mutant with impaired ACP binding reveal a conformational change that suggests the ACP may regulate AftD function. Using a conditional knock-out constructed in M. smegmatis, mutagenesis experiments confirm the essentiality of the putative active site and the ACP binding for AftD function.

biochemistry↗

bioRxiv2019

The Tung Tree (Vernicia Fordii) Genome Provides A Resource for Understanding Genome Evolution and Oil Improvement

Tung tree (Vernicia fordii) is an economically important woody oil plant that produces tung oil containing a high proportion of eleostearic acid ([~]80%). Here we report a high-quality, chromosome-scale tung tree genome sequence of 1.12 Gb with 28,422 predicted genes and over 73% repeat sequences. Tung tree genome was assembled by combining Illumina short reads, PacBio single-molecule real-time long reads and Hi-C sequencing data. Insertion time analysis revealed that the repeat-driven tung tree genome expansion might be due to long standing long terminal repeat (LTR) retrotransposon bursts and lack of efficient DNA deletion mechanisms. An electronic fluorescent pictographic (eFP) browser was generated based on genomic and RNA-seq data from 17 various tissues and developmental stages. We identified 88 nucleotide-binding site (NBS)-encoding resistance genes, of which 17 genes may help the tung tree resist the Fusarium wilt shortly after infection. A total of 651 oil-related genes were identified and 88 of them were predicted to be directly involved in tung oil biosynthesis. The fewer phosphoenolpyruvate carboxykinase (PEPC) genes, and synergistic effects between transcription factors and oil biosynthesis-related genes may contribute to high oil content in tung seeds. The tung tree genome should provide valuable resources for molecular breeding and genetic improvement.

bioinformatics↗

bioRxiv2019

Visual impairment, spectacle wear and academic performance among junior high school students in western China

In September 2013, 2248 students from 36 junior high schools in Shaanxi Province underwent assessment of visual acuity (VA), completed a questionnaire about their spectacle use and were administered a standardized mathematics examination. Among 2,248 students (mean age 13.6 years, 52% male), visual impairment was present in 699 (31%, 95% Confidence Interval 29-33%). Spectacle wear was observed in 360 of 966 children needing glasses (37%). Ownership of spectacles among children needing glasses was associated with poorer uncorrected vision in the better-seeing eye (P <0.001) and paternal educational (p=0.001), but not age, sex, boarding at school, both parents having out-migrated for work or maternal education. Spectacle ownership among children with visual impairment was associated with better test performance (P=0.035). Therefore, visual impairment and non-wear of spectacle were common. Wearing spectacles was associated with better academic performance in this cross-sectional analysis, consistent with recent trial results among younger children.

scientific communication and education↗

bioRxiv2019

Dissecting molecular regulatory mechanisms underlying noncoding susceptibility SNPs associated with 19 autoimmune diseases using multi-omics integrative analysis

The genome-wide association studies (GWAS) have identified hundreds of susceptibility loci associated with autoimmune diseases. However, over 90% of risk variants are located in the noncoding regions, leading to great challenges in deciphering the underlying causal functional variants/genes and biological mechanisms. Previous studies focused on developing new scoring method to prioritize functional/disease-relevant variants. However, they principally incorporated annotation data across all cells/tissues while omitted the cell-specific or context-specific regulation. Moreover, limited analyses were performed to dissect the detailed molecular regulatory circuits linking functional GWAS variants to disease etiology. Here we devised a new analysis frame that incorporate hundreds of immune cell-specific multi-omics data to prioritize functional noncoding susceptibility SNPs with gene targets and further dissect their downstream molecular mechanisms and clinical applications for 19 autoimmune diseases. Most prioritized SNPs have genetic associations with transcription factors (TFs) binding, histone modification or chromatin accessibility, indicating their allelic regulatory roles on target genes. Their target genes were significantly enriched in immunologically related pathways and other immunologically related functions. We also detected long-range regulation on 90.7% of target genes including 132 ones exclusively regulated by distal SNPs (eg, CD28, IL2RA), which involves several potential key TFs (eg, CTCF), suggesting the important roles of long-range chromatin interaction in autoimmune diseases. Moreover, we identified hundreds of known or predicted druggable genes, and predicted some new potential drug targets for several autoimmune diseases, including two genes (NFKB1, SH2B3) with known drug indications on other diseases, highlighting their potential drug repurposing opportunities. In summary, our analyses may provide unique resource for future functional follow-up and drug application on autoimmune diseases, which are freely available at http://fngwas.online/. Author SummaryAutoimmune diseases are groups of complex immune system disorders with high prevalence rates and high heritabilities. Previous studies have unraveled thousands of SNPs associated with different autoimmune diseases. However, it remains largely unknown on the molecular mechanisms underlying these genetic associations. Striking, over 90% of risk SNPs are located in the noncoding region. By leveraging multiple immune cell-specific multi-omics data across genomic, epigenetic, transcriptomic and 3D chromatin interaction information, we systematically analyzed the functional variants/genes and biological mechanisms underlying genetic association on 19 autoimmune diseases. We found that most functional SNPs may affect target gene expression through altering transcription factors (TFs) binding, histone modification or chromatin accessibility. Most target genes had known immunological functions. We detected prevailing long-range chromatin interaction linking distal functional SNPs to target genes. We also identified many known drug targets and predicted some new drug target genes for several autoimmune diseases, suggesting their potential clinical applications. All analysis results and tools are available online, which may provide unique resource for future functional follow-up and drug application. Our study may help reduce the gap between traditional genetic findings and biological mechanistically exploration of disease etiologies as well as clinical drug development.

immunology↗

bioRxiv2019

Prolonged inflammation leads to ongoing damage after spinal cord injury.

The pathogenesis of spinal cord injury (SCI) remains poorly understood and treatment remains limited. Emerging evidence indicates the severity of post-SCI inflammation and an ongoing controversy in the roles of astrocytes with studies identifying astrocytes as associated both with ongoing inflammation and damage as well as potentially having a protective role. We have completed an extensive systematic study with MRI, histopathology, proteomics and ELISA analyses designed to further define the severe protracted and damaging inflammation after SCI in a rat model. We have identified 3 distinct phases of SCI: acute (first 2 days), inflammatory (starting day 3) and resolution (>3 months) in 16 weeks follow up. Actively phagocytizing, CD68+/CD163- macrophages infiltrate myelin-rich necrotic areas converting them into cavities of injury (COI) when deep in the spinal cord. Alternatively, superficial SCI areas are infiltrated by granulomatous tissue, or arachnoiditis where glial cells are obliterated. In the COI, CD68+/CD163- macrophage numbers reach a maximum in the first 4 weeks and then decline. Myelin phagocytosis is present at 16 weeks indicating ongoing inflammatory damage. The COI and arachnoiditis are defined by a wall of progressively hypertrophied astrocytes. MR imaging indicates persistent spinal cord edema that is linked to the severity of inflammation. Microhemorrhages in the spinal cord around the lesion are eliminated, presumably by reactive astrocytes within the first week post-injury. Acutely increased levels of TNF-, IL-1{beta}, IFN-{gamma} and other pro-inflammatory cytokines, chemokines and proteases decrease and anti-inflammatory cytokines increase in later phases. In this study we elucidated a number of fundamental mechanisms in pathogenesis of SCI and have demonstrated a close association between progressive astrogliosis and reduction in the severity of inflammation.

pathology↗

bioRxiv2019

Sub physiological temperature induces pervasive alternative splicing in Chinese hamster ovary cells

RNA sequencing (RNASeq) has been widely used to associate alterations in Chinese hamster ovary (CHO) cell gene expression with bioprocess phenotypes, however alternative mRNA splicing, has thus far, received little attention. In this study, we utilised RNASeq for transcriptomic analysis of a monoclonal antibody producing CHOK1 cell line subjected to a temperature shift. More than 2,365 instances of differential splicing were observed 24hrs after the reduction of cell culture temperature. 1,163 of these alternative splicing events were identified in genes where no changes in abundance were detected by standard differential expression analysis. Ten examples of alternative splicing were selected for independent validation using qPCR in the monoclonal antibody producing CHOK1 line used for RNASeq and a further 2 CHOK1 cell lines. This analysis provided evidence that exon skipping and mutually exclusive splicing events occur in genes linked to the cellular response to changes in temperature and mitochondrial function. While further work is required to determine the impact of changes in mRNA sequence on cellular phenotype, this study demonstrates that alternative splicing analysis can be utilised to gain a deeper understanding of post-transcriptional regulation in CHO cells during biopharmaceutical production.

cell biology↗

bioRxiv2019

Expanding the Chinese hamster ovary cell long non-coding RNA transcriptome using RNASeq

Our ability to study Chinese hamster ovary (CHO) cell biology has been revolutionised over the last decade with the development of next generation sequencing and the publication of reference DNA sequences for CHO cells and the Chinese hamster. RNA sequencing has not only enabled the association of transcript expression with bioreactor conditions and desirable bioprocess phenotypes but played a key role in the characterisation of protein coding and small non-coding RNAs. The annotation of long non-coding RNAs, and therefore our understanding of their role in CHO cell biology, has been limited to date. In this manuscript, we use high resolution RNASeq data to more than double the number of annotated lncRNA transcripts for the CHOK1 genome. In addition, the utilisation of strand specific sequencing enabled the identification of more than 1,000 new lncRNAs located antisense to protein coding genes. The utility of monitoring lncRNA expression is demonstrated through an analysis of the transcriptomic response to a reduction of cell culture temperature and identification of simultaneous sense/antisense differential expression for the first time in CHO cells. To enable further studies of lncRNAs, the transcripts annotated in this study have been made available for the CHO cell biology community.

cell biology↗

bioRxiv2019

Single-cell transcriptomics reveals diverse and complex gene expression alterations in human trisomy 18

Trisomy 18, commonly known as Edwards syndrome, is the second most common autosomal trisomy among live born neonates. Multiple tissues including cardiac, abdominal, and nervous systems are affected by an extra chromosome 18. To delineate the complexity of anomalies of trisomy 18, we analyzed amniotic fluid cells from two normal and three trisomy 18 samples using single-cell transcriptomics. We identified six cell groups, which function in major tissue development such as kidney, vasculature, and smooth muscle, and display significant alterations in gene expression detected by single-cell RNA-sequencing. Moreover, we demonstrated significant gene expression changes in previously proposed trisomy 18 critical regions, and identified three new regions such as 18p11.32, 18q11, 18q21.32, which are likely associated with trisomy 18 phenotypes. Our results indicate complexity of trisomy 18 at the gene expression level and reveal genetic reasoning of diverse phenotypes in trisomy 18 patients.

genetics↗

bioRxiv2019

Single-cell RNA-seq data reveals TNBC tumor heterogeneity through characterizing subclone compositions and proportions

Understanding subclonal architecture and their biological functions poses one of the key challenges to deeply portray and investigative the cause of triple-negative breast cancer (TNBC). Here we combine single-cell and bulk sequencing data to analyze tumor heterogeneity through characterizing subclone compositions and proportions. Based on sing-cell RNA-seq data (GSE118389) we identified five distinct cell subpopulations and characterized their biological functions based on their gene markers. According to the results of functional annotation, we found that C1 and C2 are related to immune functions, while C5 is related to programmed cell death. Then based on subclonal basis gene expression matrix, we applied deconvolution algorithm on TCGA tissue RNA-seq data and observed that microenvironment is diverse among TNBC subclones, especially C1 is closely related to T cells. Whats more, we also found that high C5 proportions would led to poor survival outcome, log-rank test p-value and HR [95%CI] for five years overall survival in GSE96058 dataset were 0.0158 and 2.557 [1.160-5.636]. Collectively, our analysis reveals both intra-tumor and inter-tumor heterogeneity and their association with subclonal microenvironment in TNBC (subclone compositions and proportions), and uncovers the organic combination of subclones dictating poor outcomes in this disease. HighlightsWe applied deconvolution algorithm on subclonal basis gene expression matrix to link single cells and bulk tissue together.

cancer biology↗

bioRxiv2019

An optimized 16S rRNA sequencing protocol for vaginal microbiome to avoid biased abundance estimation

We applied three 16S rRNA sequencing protocols on vaginal microbiome samples, to evaluate whether they produce unbiased estimation of vaginal microbiome composition. We modified the 27F primer (hereafter denoted as 27F). Using vaginal samples from 28 healthy women and 10 women with bacterial vaginosis, we sequenced three 16S rRNA sequencing protocols, i.e., 27F-338R, 27F-338R and 341F-806R protocols, naming after their PCR primer sets, to test whether the sequencing results are consistent with the clinical diagnostics, morphology and qPCR results. First, the 27F primer would not align with Gardnerlla vaginalis very well, leading to poor amplification of such species. By modifying the primer sequences, the modified 27F primer (27F) was able to amplify Gardnerlla vaginalis very well. Second, the DNA sequence of characteristic species Lactobacillus crispatus is identical with Lactobacillus garrinarum, leading to biased estimation of abundance of Lactobacillus crispatus when using V3-V4 as PCR target region; in contrast, such bias did not occur when using V1-V2 as a target region. Third, optimized 27F-338R avoided above-mentioned biases and restored the well-established community state types (CSTs) clustering. ImportanceVaginal microbiome has profound effects on the health of women and their newborns. Our study found that two well-established 16S rDNA sequencing protocols led to systementical biased estimation of characteristic species of vaginal microbiome. Subsequent analysis proved that the PCR primer fetching efficacy and target region identity were major contributor for such bias. With carefully selected target region and optimized PCR primer set, we were able to eliminate such biases and provide accurate estimation of vaginal microbiome, which showed high consistency with clinical diagnostics. We modified the 27F primer (27F). Using the optimized PCR primer set of 27F and 338R to target the V1-V2 hyper-variable region, our 16S rRNA sequencing correctly evaluate the composition of vaginal microbiome.

microbiology↗

bioRxiv2019

Bax and Bak jointly control survival and dampen the early unfolded protein response in pancreatic β-cells under glucolipotoxic stress

ER stress and apoptosis contribute to the loss of pancreatic {beta}-cells under the pro-diabetic conditions of glucolipotoxicity. Although activation of the canonical pathway of intrinsic apoptosis is known to require Bax and Bak, their individual and combined involvement in glucolipotoxic {beta}-cell death have not been demonstrated. It has also remained an open question if Bax and Bak in {beta}-cells have non-apoptotic roles in mitochondrial function and ER stress signaling, as suggested in other cell types. Using mice with individual or combined {beta}-cell deletion of Bax and Bak, we demonstrated that glucolipotoxic {beta}-cell death in vitro happens in sequential stages; first via non-apoptotic mechanisms and later by apoptosis, which Bax and Bak were redundant in triggering. In contrast, they had non-redundant roles in mediating staurosporine-induced {beta}-cell apoptosis. We further established that Bax and Bak do not affect normal glucose-stimulated {beta}-cell Ca2+ responses, insulin secretion, or in vivo glucose tolerance. Finally, our experiments revealed that Bax and Bak together dampen the unfolded protein response in {beta}-cells during the early stages of chemical- or glucolipotoxicity-induced ER stress. These findings identify novel roles of the canonical apoptosis machinery in modulating stress signals that are important for the pathobiology of {beta}-cells in diabetes.

cell biology↗

bioRxiv2019

Can computers understand word meanings like the human brain does? Comparable semantic representation in neural and computer systems

Semantic representation has been studied independently in neuroscience and computer science. A deep understanding of human neural computations and the revolution to strong artificial intelligence appeal for a joint force in the language domain. We investigated comparable representational formats of lexical semantics between these two complex systems with fine temporal resolution neural recordings. We found semantic representations generated from computational models significantly correlated with EEG responses at an early stage of a typical semantic processing time window in a two-word semantic priming paradigm. Moreover, three representative computational models differentially predicted EEG responses along the dynamics of word processing. Our study provided a finer-grained understanding of the neural dynamics underlying semantic processing and developed an objective biomarker for assessing human-like computation in computational models. Our novel framework trailblazed a promising way to bridge across disciplines in the investigation of higher-order cognitive functions in human and artificial intelligence.

neuroscience↗

bioRxiv2019

The Molecular Basis of Specific DNA Binding by the BRG1 AT-hook and Bromodomain

The ATP-dependent BAF chromatin remodeling complex plays a critical role in gene regulation by modulating chromatin architecture, and is frequently mutated in cancer. Indeed, subunits of the BAF complex are found to be mutated in >20% of human tumors. The mechanism by which BAF properly navigates chromatin is not fully understood, but is thought to involve a multivalent network of histone and DNA contacts. We previously identified a composite domain in the BRG1 ATPase subunit that is capable of associating with both histones and DNA in a multivalent manner. Mapping the DNA binding pocket revealed that it contains several cancer mutations. Here, we utilize SELEX-seq to identify the DNA specificity of this composite domain and NMR spectroscopy and molecular modelling to determine the structural basis of DNA binding. Finally, we demonstrate that cancer mutations in this domain alter the mode of DNA association.

biochemistry↗