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Song, L.

Publications and source records attributed to Song, L..

At least 91 records · Page 5Linked to original sources
bioRxiv2024

Rapid production of modified cattle and sheep from spermatid-like stem cells

Genome-modified ruminants, such as cattle and sheep, are important germplasm for agricultural applications. Haploid androgenetic stem cells (haSCs) can support the full-term development of embryos upon intracytoplasmic haSCs injection (iCHI) into intact oocytes. Thus, haSCs are invaluable resources for studying economic traits and significantly impact livestock breeding; however, ruminant haSCs have yet to be obtained. Here, we report the derivation of cattle and sheep haSCs using a recombinant FACE medium. These cells display characteristics of formative-state pluripotency and can differentiate into three germ layers, both in vitro and in vivo. Interestingly, the ectopic expression of protamine in haSCs converts their nuclei into a spermatid-like structure and synergistic enhancement of full-term development of iCHI embryos, named as Pro-iCHI approach. Furthermore, gene-modified cattle and sheep can be efficiently produced through the combinatorial use of the CRISPR and Pro-iCHI approach. Overall, Pro-iCHI provides an easy-to-manipulate agrobiotechnology tool for rapidly producing genetically modified livestock.

bioengineering↗
bioRxiv2024

Identification of Proteins Influencing CRISPR-Associated Transposases for Enhanced Genome Editing

CRISPR-Associated Transposases (CASTs) hold tremendous potential for microbial genome editing due to their ability to integrate large DNA cargos in a programmable and site-specific manner. However, the widespread application of CASTs has been hindered by their low efficiency in diverse, non-model bacteria. In an effort to address this shortcoming, we conducted the first genome-wide screen for host factors impacting Vibrio cholerae CAST (VchCAST) activity and used the findings to increase VchCAST editing efficiency. A genome-wide loss-of-function mutant library in E. coli was screened to identify 15 genes that impact type VchCAST transposition. Of these, seven factors were validated to improve VchCAST activity and two were found to be inhibitory. Informed by homologous recombination involved effectors, RecD and RecA, we tested the {lambda}-Red recombineering system in our VchCAST editing vectors, which increased its insertion meditated-editing efficiency by 25.7-fold in E. coli while maintaining high target specificity and similar insertion arrangements. Furthermore, {lambda}-Red-enhanced VchCAST achieved increased editing efficiency in the industrially important bacteria Pseudomonas putida and the emerging pathogen Klebsiella michiganensis. This study improves understanding of factors impacting VchCAST activity and enhances its efficiency as a bacterial genome editor. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/612086v2_ufig1.gif" ALT="Figure 1"> View larger version (13K): org.highwire.dtl.DTLVardef@12609e5org.highwire.dtl.DTLVardef@53a128org.highwire.dtl.DTLVardef@794e63org.highwire.dtl.DTLVardef@9835f_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗
bioRxiv2024

Early steps of the biosynthesis of the anticancer antibiotic pleurotin

Pleurotin is a meroterpenoid specialised metabolite made by the fungus Hohenbuehelia grisea, and it is a lead anticancer molecule due to its irreversible inhibition of the thioredoxin-thioredoxin reductase system. Total synthesis of pleurotin has previously been achieved, including through a stereoselective route, however its biosynthesis has not been characterised. In this study, we used isotope-labelled precursor feeding to show that the non-terpenoid quinone ring of pleurotin and its congeners is derived from phenylalanine. We sequenced the genome of the pleurotin-producing fungus and used comparative transcriptomics to identify putative genes involved in pleurotin biosynthesis. Additionally, the heterologous expression of a UbiA-like prenyltransferase from H. grisea resulted in the isolation and characterisation of the first predicted pleurotin biosynthetic intermediate, 3-farnesyl-4-hydroxybenzoic acid. This work sets the foundation to fully elucidate the biosynthesis of pleurotin and its congeners, with long-term potential to optimise their production for therapeutic use and engineer the pathway towards the biosynthesis of valuable analogues.

microbiology↗
bioRxiv2024

Multi-Modal Large Language Model Enables Protein Function Prediction

Predicting the functions of proteins can greatly accelerate biological discovery and applications, where deep learning methods have recently shown great potential. However, these methods predominantly predict protein functions as discrete categories, which fails to capture the nuanced and complex nature of protein functions. Furthermore, existing methods require the development of separate models for each prediction task, a process that can be both resource-heavy and time-consuming. Here, we present ProteinChat, a versatile, multi-modal large language model that takes a proteins amino acid sequence as input and generates comprehensive narratives describing its function. ProteinChat is trained using over 1,500,000 (protein, prompt, answer) triplets curated from the Swiss-Prot dataset, covering diverse functions. This novel model can universally predict a wide range of protein functions, all within a single, unified framework. Furthermore, ProteinChat supports interactive dialogues with human users, allowing for iterative refinement of predictions and deeper exploration of protein functions. Our experimental results, evaluated through both human expert assessment and automated metrics, demonstrate that ProteinChat outperforms general-purpose LLMs like GPT-4, one of the flagship LLMs, by over ten-fold. In addition, ProteinChat exceeds or matches the performance of task-specific prediction models.

bioinformatics↗
bioRxiv2024

An intrinsic hierarchical, retinotopic organization of pulvinar connectivity in the human neonate

Thalamic connectivity is crucial for the development of the neocortex. The pulvinar nuclei are thought to be particularly important for visual development due to their involvement in various functions that emerge early in infancy. The development of these connections constrains the role the pulvinar plays in infant visual processing and the maturation of associated cortical networks. However, the extent to which pulvino-cortical pathways found in adults are established at birth remains largely unknown, limiting our understanding of how these thalamic connections may support infant vision. To address this gap, we examined the organization of pulvino-cortical connections in human neonates using probabilistic tractography analyses on diffusion imaging data. Our findings revealed the presence of white matter pathways between the pulvinar and each individual visual area at birth. These pathways exhibited specificity in their connectivity within the pulvinar, reflecting both intraareal retinotopic organization and the hierarchical organization across ventral, lateral, and dorsal visual cortical pathways. These connections could enable detailed processing of information across sensory space and communication along distinct processing pathways. Comparative analyses revealed that the large-scale organization of pulvino-cortical connectivity in neonates mirrored that of adults. However, connectivity with ventral visual cortex was less adult-like than the other cortical pathways, aligning with prior findings of protracted development associated with the visual recognition pathway. These results deepen our understanding of the developmental trajectory of thalamocortical connections and provide a framework for how subcortical structures may support early perceptual abilities and scaffold the development of cortex.

neuroscience↗
bioRxiv2024

A pan-cancer gamma delta T cell repertoire

This report presents the largest collection of gamma-delta T cell receptor ({gamma}{delta} TCR) reads in human cancer to date, analyzing about 11,000 patient tumor samples across 33 cancer types using the TRUST4 algorithm. Despite {gamma}{delta} T cells being a small fraction of the T cell population, they play a key role in both innate and adaptive immunity. Our comprehensive analysis reveals their significant presence across all cancer types, specifically highlighting the diverse spectrum and clonality patterns of their {gamma}{delta} receptors. This research highlights the complex roles of {gamma}{delta} T cells in tumor tissues and their potential as prognostic biomarkers. We also demonstrate the utility of T cell receptor gamma (TRG) and delta (TRD) gene expression values from standard RNA-seq data. Ultimately, our work establishes a fundamental resource for future tumor-infiltrating {gamma}{delta} T cell research and may facilitate the development of novel {gamma}{delta}-T-cell-based therapeutic strategies. Together, we demonstrate the strong diversity and prognostic potential of {gamma}{delta} T cells in multiple cancer types. HighlightsComprehensive analysis of {gamma}{delta} TCRs from 11,473 tumor samples Significant variability and overall consistency in {gamma}{delta} gene expression and clonotype {gamma}{delta}TCR expression and diversity as prognostic biomarkers across multiple cancers Centralized {gamma}{delta} TCR repertoire database for future therapeutic discovery

genomics↗
bioRxiv2024

TIM-3 blockade enhances ex vivo stimulated allogeneic NK cell therapy for relapsed murine neuroblastoma after hematopoietic cell transplant

BackgroundHigh-risk neuroblastoma (HR-NBL) is an aggressive tumor of the sympathetic nervous system with high risk of relapse and poor overall survival. Allogeneic hematopoietic cell transplant (allo-HCT) has been used previously in HR-NBL patients; however, graft-versus-host-disease (GVHD) and disease progression have limited clinical application. Ex-vivo stimulated allogeneic natural killer (NK) cells represent a potential approach to enhance the graft-versus-tumor (GVT) effect without exacerbation of GVHD but have not shown efficacy in NBL. MethodsEx-vivo stimulated NK cells from C57BL/6NCr (B6) mice were expanded with soluble IL-15/IL-15R alone or with irradiated CD137L/CD54+ AgN2a-4P (15-4P) at a 1:1 ratio for 10-12 days. Allogeneic NK cells were then analyzed for activation, proliferation, cytokine production, and cytotoxicity against two murine NBL cell lines, Neuro2a and NXS2, in the absence or presence of anti-TIM-3. Lethally irradiated B6AJF1 Mice received allo-HCT from B6 donors followed by NBL challenge after 7 days to mimic tumor relapse. Select groups received anti-TIM-3 starting on day 9 for every 4 days with/without infusions of 15-4P B6 NK cells on days 14, 21, and 28. In select experiments, T cell and NK cells were selectively depleted to establish their contribution to the GVT effect. All groups were analyzed for tumor growth, GVHD and overall survival. ResultsCo-culturing NK cells with 15-4P results in 78-fold expansion with increased expression of Ki-67 and NKG2D, NKp46, TRAIL and TIM-3. 15-4P stimulated allogeneic NK cells showed enhanced cytotoxicity against NBL compared to IL-15 NK cells alone but was limited in part due to high expression of TIM-3 ligands on Neuro-2a compared to NXS2. The addition of TIM-3 blockade further enhanced NK cytotoxicity versus Neuro-2a, with enhanced 15-4P NK cell degranulation, Eomes, TRAIL and FasL expression observed. Analysis of RNA from 15-4P NK cells exposed to TIM-3 blockade showed gene expression of chemokines, NKG2D/DAP12 signaling, non-canonical NF-{kappa}b pathway and TRAIL signaling. Blockade of NKG2D, TRAIL or FasL on 15-4P NK cells abrogated cytotoxicity. In vivo, the combination of 15-4P stimulated allogeneic NK cells and TIM-3 blockade after allo-HCT resulted in prolonged survival against NBL with decreased tumor burden compared to NK cells or anti-TIM-3 alone, without inducing GVHD. Depletion of NK cells, but not T cells, abrogated the GVT effect. ConclusionAllo-HCT can be a platform for treating NBL using combination ex-vivo stimulated allogeneic NK cell therapy with TIM-3 blockade to enhance the GVT effect without inducing GVHD. Ethics StatementThe animal study M005915 was reviewed and approved by University of Wisconsin-Madison IACUC. WHAT IS ALREADY KNOWN ON THIS TOPICO_LIT cell depleted (TCD) allogeneic hematopoietic cells transplant (allo-HCT) has potential to be a salvage therapy for relapsed/refractory neuroblastoma (NBL) through the graft-versus-tumor (GVT) effect, however, the high incidence of graft-vs-host disease (GVHD) and disease progression has hindered widespread clinical application. Allogeneic NK cell therapy can be a safe and feasible treatment but has had limited efficacy in NBL. TIM-3 blockade has shown encouraging results for a variety of tumors but has not been explored for NBL nor used to enhance the GVT effect. C_LI WHAT THIS STUDY ADDSO_LIEx vivo stimulated allogeneic NK cells demonstrate robust expansion, proliferation, activation and cytotoxicity against NBL which is further augmented by the addition of TIM-3 checkpoint blockade. In an allo-HCT model of NBL relapse, mice treated with IL-15/IL-15R/AgN2a-4P (15-4P) stimulated NK cells and anti-TIM-3 exhibited prolonged overall survival and reduced tumor growth without exacerbating GVHD. C_LI HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICYO_LIRelapse of NBL after TCD allo-HCT can be successfully treated with the combination of adoptively transferred 15-4P stimulated allogeneic NK cells and TIM-3 checkpoint blockade, representing a novel therapeutic approach that can be translated to the clinic or used as a platform to treat other solid tumors with high TIM-3 ligand expression. C_LI

immunology↗
bioRxiv2024

Intra-genomic genes-to-genes correlation enables genome representaion

The bacterial pan-genome consists of core genes shared by all members of a taxonomy and accessory genes found in only a subset. The correlation among genes within the pan-genome could advance our understanding of evolution and tackle medical challenges. Here, we discovered a strong intra-genomic correlation among bacterial pan-genes within each of Escherichia coli, Listeria monocytogenes, Staphylococcus aureus, and Campylobacter jejuni. With a convolutional neural network assisted core genome knock-out simulation, we found that different combinations of fewer than 20 highly variable core genes could recover the sub-species type classified by complete core genome with accuracy >95%. This observation led us to test the genes-to-genes predictability: with more than 52,000 assemblies from each species, combinations of highly variable core genes could predict the sequence variants of other core genes (average accuracy >94%) within the same genome and could also predict sequence variants (average accuracy >91%) as well as the presence (average AUROC >0.91) of some accessory genes. Furthermore, combinations of highly variable core genes could also predict multiple antibiotic resistances (AUROC >0.80) in large published datasets of E. coli, S. aureus, and Mycobacterium tuberculosis. Collectively, we propose that genes within the same genome can strongly correlate with each other. Therefore, the strain phylogeny and the status of other genes could be uniformly represented by combinations of highly variable core genes, which could further represent certain phenotypes including in vitro resistance.

bioinformatics↗
bioRxiv2024

MSAGPT: Neural Prompting Protein Structure Prediction via MSA Generative Pre-Training

Multiple Sequence Alignment (MSA) plays a pivotal role in unveiling the evolutionary trajectories of protein families. The accuracy of protein structure predictions is often compromised for protein sequences that lack sufficient homologous information to construct high-quality MSA. Although various methods have been proposed to generate virtual MSA under these conditions, they fall short in comprehensively capturing the intricate co-evolutionary patterns within MSA or require guidance from external oracle models. Here we introduce MSAGPT, a novel approach to prompt protein structure predictions via MSA generative pre-training in the low-MSA regime. MSAGPT employs a simple yet effective 2D evolutionary positional encoding scheme to model the complex evolutionary patterns. Endowed by this, its flexible 1D MSA decoding framework facilitates zero-or few-shot learning. More-over, we demonstrate that leveraging the feedback from AlphaFold2 can further enhance the models capacity via Rejective Fine-tuning (RFT) and Reinforcement Learning from AF2 Feedback (RLAF). Extensive experiments confirm the efficacy of MSAGPT in generating faithful virtual MSA to enhance the structure prediction accuracy (up to +8.5% TM-Score on few-shot scenarios). The transfer learning capabilities also highlight its great potential for facilitating other protein tasks.

bioinformatics↗
bioRxiv2024

Training Compute-Optimal Protein Language Models

We explore optimally training protein language models, an area of significant interest in biological research where guidance on best practices is limited. Most models are trained with extensive compute resources until performance gains plateau, focusing primarily on increasing model sizes rather than optimizing the efficient compute frontier that balances performance and compute budgets. Our investigation is grounded in a massive dataset consisting of 939 million protein sequences. We trained over 300 models ranging from 3.5 million to 10.7 billion parameters on 5 to 200 billion unique tokens, to investigate the relations between model sizes, training token numbers, and objectives. First, we observed the effect of diminishing returns for the Causal Language Model (CLM) and that of overfitting for the Masked Language Model (MLM) when repeating the commonly used Uniref database. To address this, we included metagenomic protein sequences in the training set to increase the diversity and avoid the plateau or overfitting effects. Second, we obtained the scaling laws of CLM and MLM on Transformer, tailored to the specific characteristics of protein sequence data. Third, we observe a transfer scaling phenomenon from CLM to MLM, further demonstrating the effectiveness of transfer through scaling behaviors based on estimated Effectively Transferred Tokens. Finally, to validate our scaling laws, we compare the large-scale versions of ESM-2 and PROGEN2 on downstream tasks, encompassing evaluations of protein generation as well as structure- and function-related tasks, all within less or equivalent pre-training compute budgets.

bioinformatics↗
bioRxiv2024

iResNetDM: Interpretable deep learning approach for four types of DNA modification prediction

MotivationDespite the development of several computational methods to predict DNA modifications, two main limitations persist in the current methodologies: 1) All existing models are confined to binary predictor which merely determine the presence or absence of DNA modifications, constraining comprehensive analyses of the interrelations among varied modification types. While multi-class classification models for RNA modifications have been developed, a comparable approach for DNA remains a critical need. 2) The majority of previous studies lack adequate explanations of how models make decisions, relying on the extraction and visualization of attention matrices which identified few motifs, and do not provide sufficient insight into the model decision making process. ResultIn this study, we introduce iResNetDM, a deep learning model that integrates ResNet and self-attention mechanisms. To the best of our knowledge, iResNetDM is the first model capable of distinguishing between four types of DNA modifications. It not only demonstrates high performance across various DNA modifications but also unveils the potential capabilities of CNN and ResNet in this domain. To augment the interpretability of our model, we implemented the integrated gradients technique, which was pivotal in demystifying the models decision-making framework, allowing for the successful identification of multiple motifs. Importantly, our model exhibits remarkable robustness, successfully identifying unique motifs across different modifications. Furthermore, we compared the motifs discovered in various modifications, revealing that some motifs share significant sequence similarities which suggests that these motifs may be subjected to different types of modifications, underscoring their potential importance in gene regulation. Contactzeruiyang2-c@my.cityu.edu.hk

bioinformatics↗
bioRxiv2024

Single-Cell multiomics reveals ENL mutation perturbs kidney developmental trajectory by rewiring gene regulatory landscape

Cell differentiation during organogenesis relies on precise epigenetic and transcriptional control. Disruptions to this regulation can result in developmental abnormalities and malignancies, yet the underlying mechanisms are not well understood. Wilms tumors, a type of embryonal tumor closely linked to disrupted organogenesis, harbor mutations in epigenetic regulators in 30-50% of cases. However, the role of these regulators in kidney development and pathogenesis remains unexplored. By integrating mouse modeling, histological characterizations, and single-cell transcriptomics and chromatin accessibility profiling, we show that a Wilms tumor-associated mutation in the chromatin reader protein ENL disrupts kidney development trajectory by rewiring the gene regulatory landscape. Specifically, the mutant ENL promotes the commitment of nephron progenitors while simultaneously restricting their differentiation by dysregulating key transcription factor regulons, particularly the HOX clusters. It also induces the emergence of abnormal progenitor cells that lose their chromatin identity associated with kidney specification. Furthermore, the mutant ENL might modulate stroma-nephron interactions via paracrine Wnt signaling. These multifaceted effects caused by the mutation result in severe developmental defects in the kidney and early postnatal mortality in mice. Notably, transient inhibition of the histone acetylation binding activity of mutant ENL with a small molecule displaces transcriptional condensates formed by mutant ENL from target genes, abolishes its gene activation function, and restores developmental defects in mice. This work provides new insights into how mutations in epigenetic regulators can alter the gene regulatory landscape to disrupt kidney developmental programs at single-cell resolution in vivo. It also offers a proof-of-concept for the use of epigenetics-targeted agents to rectify developmental defects.

cancer biology↗
bioRxiv2024

Expanding the genome information on Bacillales for biosynthetic gene cluster discovery

This study showcases 121 new genomes of spore-forming Bacillales from strains collected globally from a variety of habitats, assembled using Oxford Nanopore long-read and MGI short-read sequences. Bacilli are renowned for their capacity to produce diverse secondary metabolites with use in agriculture, biotechnology, and medicine. These secondary metabolites are encoded within biosynthetic gene clusters (smBGCs). smBGCs have significant research interest due to their potential for the discovery of new bioactivate compounds. Our dataset includes 62 complete genomes, 2 at chromosome level, and 57 at contig level, covering a genomic size range from 3.50 Mb to 7.15 Mb. Phylotaxonomic analysis revealed that these genomes span 16 genera, with 69 of them belonging to Bacillus. A total of 1,176 predicted BGCs were identified by in silico genome mining. We anticipate that the open-access data presented here will expand the reported genomic information of spore-forming Bacillales and facilitate a deeper understanding of the genetic basis of Bacillales potential for secondary metabolite production.

microbiology↗
bioRxiv2024

Hierarchal single-cell lineage tracing reveals differential fate commitment of CD8 T-cell clones in response to acute infection.

Generating balanced populations of CD8 effector and memory T cells is necessary for immediate and durable immunity to infections and cancer. Yet, a definitive understanding of CD8 differentiation remains unclear. We used CARLIN, a processive lineage recording mouse model with single-cell RNA-seq and TCR-seq to track endogenous antigen-specific CD8 T cells during acute viral infection. We identified a diverse repertoire of expanded T-cell clones represented by seven transcriptional states. TCR enrichment analysis revealed differential memory- or effector-fate biases within clonal populations. Shared Vb segments and amino acid motifs were found within biased categories despite high TCR diversity. Using single-cell CARLIN barcode-seq we tracked multi-generational clones and found that unlike unbiased or memory-biased clones, which stably retain their fate profiles, effector-biased clones could adopt memory- or effector-bias within subclones. Collectively, our study demonstrates that a heterogenous T-cell repertoire specific for a shared antigen is composed of clones with distinct TCR-intrinsic fate-biases.

immunology↗
bioRxiv2024

Modeling Hereditary Diffuse Leukoencephalopathy with Axonal Spheroids using microglia-sufficient brain organoids

Hereditary diffuse leukoencephalopathy with axonal spheroids (HDLS) is a rare, fatal, adult-onset neurodegenerative disease that is most often caused by mutations affecting the Colony Stimulating factor-1 Receptor (CSF-1R). To understand how CSF-1R-mutation affects human microglia - the specialized brain-resident macrophages of the central nervous system - and the downstream consequences for neuronal cells, we used a macrophage and forebrain organoid co-culture system based on induced pluripotent stem cells generated from two patients with HDLS, with CSF-1R gene-corrected isogenic organoids as controls. Macrophages derived from iPSC (iMacs) of patients exhibited a metabolic shift towards the glycolytic pathway and reduced CSF-1 sensitivity, which was associated with higher levels of IL-1{beta} production and an activated inflammatory phenotype. Single-cell RNA sequencing revealed that iMacs adopt a reactive state that leads to impaired regulation of neuronal cell populations in organoid cultures, thereby identifying microglial dysregulation and specifically IL-1{beta} production as key contributors to the degenerative neuro-environment in HDLS.

neuroscience↗
bioRxiv2024

AttentionPert: Accurately Modeling Multiplexed Genetic Perturbations with Multi-scale Effects

Genetic perturbations (i.e. knockouts, variants) have laid the foundation for our understanding of many diseases, implicating pathogenic mechanisms and indicating therapeutic targets. However, experimental assays are fundamentally limited in the number of perturbation conditions they can measure. Computational methods can fill this gap by predicting perturbation effects under unseen conditions, but accurately predicting the transcriptional responses of cells to unseen perturbations remains a significant challenge. We address this by developing a novel attention-based neural network, AttentionPert, which accurately predicts gene expression under multiplexed perturbations and generalizes to unseen conditions. AttentionPert integrates global and local effects in a multi-scale model, representing both the non-uniform system-wide impact of the genetic perturbation and the localized disturbance in a network of gene-gene similarities, enhancing its ability to predict nuanced transcriptional responses to both single and multi-gene perturbations. In comprehensive experiments, AttentionPert demonstrates superior performance across multiple datasets outperforming the state-of-theart method in predicting differential gene expressions and revealing novel gene regulations. AttentionPert marks a significant improvement over current methods, particularly in handling the diversity of gene perturbations and in predicting out-of-distribution scenarios.

bioinformatics↗
bioRxiv2024

Full resolution HLA and KIR genes annotation for human genome assemblies

The HLA (Human Leukocyte Antigen) genes and the KIR (Killer cell Immunoglobulin-like Receptor) genes are critical to immune responses and are associated with many immune-related diseases. Located in highly polymorphic regions, they are hard to be studied with traditional short-read alignment-based methods. Although modern long-read assemblers can often assemble these genes, using existing tools to annotate HLA and KIR genes in these assemblies remains a non-trivial task. Here, we describe Immuannot, a new computation tool to annotate the gene structures of HLA and KIR genes and to type the allele of each gene. Applying Immuannot to 56 regional and 212 whole-genome assemblies from previous studies, we annotated 9,931 HLA and KIR genes and found that almost half of these genes, 4,068, had novel sequences compared to the current Immuno Polymorphism Database (IPD). These novel gene sequences were represented by 2,664 distinct alleles, some of which contained non-synonymous variations resulting in 92 novel protein sequences. We demonstrated the complex haplotype structures at the two loci and reported the linkage between HLA/KIR haplotypes and gene alleles. We anticipate that Immuannot will speed up the discovery of new HLA/KIR alleles and enable the association of HLA/KIR haplotype structures with clinical outcomes in the future.

immunology↗