Biology subjects

Ye, Y.

Publications and source records attributed to Ye, Y..

At least 145 records · Page 8Linked to original sources

bioRxiv2021

DNA replication stress stratifies prognosis and enables exploitable therapeutic vulnerabilities of HBV-associated hepatocellular carcinoma: an in silico strategy towards precision oncology

BackgroundHepatitis B virus (HBV), the main risk factor for hepatocellular carcinoma (HCC) development, integrates into the host genome, causing genetic instability, which may trigger malignancies to exhibit chronic DNA replication stress, providing exploitable therapeutic vulnerabilities. Therefore, customizing prognostication approach and expanding therapeutic options are of great clinical significance to HBV-associated HCCs. MethodsA robust machine-learning framework was designed to develop a DNA replication stress-related prognostic index (PIRS) based on 606 retrospectively collected HBV-associated HCC cases. Molecular profiles and drug response of HCC cell lines were leveraged to predict therapeutic targets and agents for patients with high mortality risk. ResultsCompared with established population-based predictors, PIRS manifested superior performance for prognostic prediction in HBV-associated HCCs. Lower PIRS tightly associated with higher expression of HBV oncoproteins, activated immune/metabolism pathways and higher likelihood of responding to immunotherapy; while higher PIRS showed co-occurrence manner with elevated Ki-67 progression marker and cancer stemness, and significantly enriched in DNA replication stress, cell cycle pathways, chromatin remodeling regulons, and presented an immune-cold phenotype with unfavorable clinical outcome. Through large-scale in silico drug screening, four potential therapeutic targets (TOP2A, PRMT1, CSNK1D, and PPIH) and five agents including three topoisomerase inhibitors (teniposide, doxorubicin, and epirubicin) and two CDK inhibitors (JNJ-7706621 and PHA-793887) were identified for patients with high PIRS. ConclusionsOverall, PIRS holds potential to improve the population-based therapeutic strategies in HCC and sheds new insight to the clinical management for those HBV carriers; current analytic framework provides a roadmap for the rational clinical development of personalized treatment.

bioinformatics↗

bioRxiv2021

Metaproteomics as a tool for studying the protein landscape of human-gut bacterial species

Host-microbiome interactions and the microbial community have broad impact in human health and diseases. Most microbiome based studies are performed at the genome level based on next-generation sequencing techniques, but metaproteomics is emerging as a powerful technique to study microbiome functional activity by characterizing the complex and dynamic composition of microbial proteins. We conducted a large-scale survey of human gut microbiome metaproteomic data to identify generalist species that are ubiquitously expressed across all samples and specialists that are highly expressed in a small subset of samples associated with a certain phenotype. We were able to utilize the metaproteomic mass spectrometry data to reveal the protein landscapes of these species, which enables the characterization of the expression levels of proteins of different functions and underlying regulatory mechanisms, such as operons. Finally, we were able to recover a large number of open reading frames (ORFs) with spectral support, which were missed by de novo protein-coding gene predictors. We showed that a majority of the rescued ORFs overlapped with de novo predicted proteincoding genes, but on opposite strands or on different frames. Together, these demonstrate applications of metaproteomics for the characterization of important gut bacterial species. Results are available for public access at https://omics.informatics.indiana.edu/GutBac. Author summaryMany reference genomes for studying human gut microbiome are available, but knowledge about how microbial organisms work is limited. Identification of proteins at individual species or community level provides direct insight into the functionality of microbial organisms. By analyzing more than a thousand metaproteomics datasets, we examined protein landscapes of more than two thousands of microbial species that may be important to human health and diseases. This work demonstrated new applications of metaproteomic datasets for studying individual genomes. We made the analysis results available through the GutBac website, which we believe will become a resource for studying microbial species important for human health and diseases.

bioinformatics↗

bioRxiv2021

Programmable RNA base editing with a single gRNA-free enzyme

Programmable RNA editing enables rewriting gene expression without changing genome sequences. Current tools for specific RNA editing dependent on the assembly of guide RNA into an RNA/protein complex, causing delivery barrier and low editing efficiency. We report a new gRNA-free system, RNA editing with individual RNA-binding enzyme (REWIRE), to perform precise base editing with a single engineered protein. This artificial enzyme contains a human-originated programmable PUF domain to specifically recognize RNAs and different deaminase domains to achieve efficient A-to-I or C-to-U editing, which achieved 60-80% editing rate in human cells, with a few non-specific editing sites in the targeted region and a low level off-target effect globally. The RNA-binding domain in REWIREs was further optimized to improve editing efficiency and minimize off-target effects. We applied the REWIREs to correct disease-associated mutations and achieve both types of base editing in mice. As a single-component system originated from human proteins, REWIRE presents a precise and efficient RNA editing platform with broad applicability.

bioengineering↗

bioRxiv2021

Estimating genetic correlation jointly using individual-level and summary-level GWAS data

With the increasing accessibility of individual-level data from genome wide association studies, it is now common for researchers to have individual-level data of some traits in one specific population. For some traits, we can only access public released summary-level data due to privacy and safety concerns. The current methods to estimate genetic correlation can only be applied when the input data type of the two traits of interest is either both individual-level or both summary-level. When researchers have access to individual-level data for one trait and summary-level data for the other, they have to transform the individual-level data to summary-level data first and then apply summary data-based methods to estimate the genetic correlation. This procedure is computationally and statistically inefficient and introduces information loss. We introduce GENJI (Genetic correlation EstimatioN Jointly using Individual-level and summary data), a method that can estimate within-population or transethnic genetic correlation based on individual-level data for one trait and summary-level data for another trait. Through extensive simulations and analyses of real data on within-population and transethnic genetic correlation estimation, we show that GENJI produces more reliable and efficient estimation than summary data-based methods. Besides, when individual-level data are available for both traits, GENJI can achieve comparable performance than individual-level data-based methods. Downstream applications of genetic correlation can benefit from more accurate estimates. In particular, we show that more accurate genetic correlation estimation facilitates the predictability of cross-population polygenic risk scores.

genetics↗

bioRxiv2021

Abnormal triaging of misfolded proteins by adult neuronal ceroid lipofuscinosis-associated CSPα mutants causes lipofuscin accumulation

Mutations in DNAJC5 (encoding the J domain-containing HSP70 co-chaperone CSP) are associated with adult neuronal ceroid lipofuscinosis (ANCL), a dominant-inherited neurodegenerative disease featuring lysosome-derived autofluorescent storage material (AFSM) termed lipofuscin. Functionally, CSP has been implicated in chaperoning synaptic proteins and in misfolding-associated protein secretion (MAPS), but how CSP dysfunction causes lipofuscinosis and neurodegeneration is unclear. Here we report two distinct protein quality control functions of CSP at endolysosomes and perinuclear vesicles, respectively. We show that the endolysosome-associated CSP promotes microautophagy of misfolded clients, but is dispensable for MAPS. By contrast, the perinuclear-localized CSP, regulated by a previously unknown CSP interactor named CD98hc, is critical for MAPS but unneeded for microautophagy. Importantly, these processes are coupled by CSP in a J-domain regulated manner. Uncoupling these two processes, as seen in cells lacking CD98hc or expressing ANCL-associated CSP mutants, generates CSP-containing AFSMs resembling NCL patient-derived lipofuscin, and also induces neurodegeneration in a Drosophila ANCL model. These findings suggest that blocking MAPS while allowing CSP-mediated microautophagy disrupts lysosome homeostasis, causing CSP-associated lipofuscinosis and neurodegeneration.

cell biology↗

bioRxiv2021

Targeting Gi/o protein-coupled receptor signaling blocks HER2-induced breast cancer development and enhances HER2-targeted therapy

G protein coupled receptors (GPCRs) are among the most desirable drug targets for human disease. Although GPCR dysfunction drives the development and progression of many tumors including breast cancer (BC), targeting individual GPCRs has limited efficacy as a cancer therapy because numerous GPCRs are activated. In this study, we sought a new way of blocking GPCR activation in HER2+-BC by targeting a subgroup of GPCRs that couple to Gi/o proteins (Gi/o-GPCRs). Using cell lines and transgenic mouse models, we showed in mammary epithelial cells, HER2 hyperactivation altered GPCR expression, particularly, Gi/o-GPCRs. Gi/o-GPCR stimulation transactivated EGFR and HER2, which in turn activated the PI3K/AKT and Src pathways. Uncoupling Gi/o-GPCRs from cognate Gi/o proteins by pertussis toxin (PTx) inhibited BC cell proliferation and migration in vitro and suppressed HER2-driven tumor formation and metastasis in vivo. Moreover, targeting Gi/o-GPCR signaling via PTx, PI3K, or Src inhibitors enhanced HER2-targeted therapy. These results indicate that HER2 hyperactivation in BC cells drives aberrant Gi/o-GPCR signaling, and Gi/o-GPCR signals converge on PI3K/AKT and Src signaling pathways to promote cancer progression and the development of resistance to HER2-targeted therapy. Our findings suggest a new way to pharmacologically deactivate GPCR signaling to block tumor growth and enhance therapeutic efficacy.

cancer biology↗

bioRxiv2021

Lysosome Lipid Signaling from the Periphery to Neurons Regulates Longevity

Lysosomes are key cellular organelles that metabolize extra- and intracellular substrates. Alterations in lysosomal metabolism are implicated in aging-associated metabolic and neurodegenerative diseases. However, how lysosomal metabolism actively coordinates the metabolic and nervous systems to regulate aging remains unclear. Here, we report a fat-to-neuron lipid signaling pathway induced by lysosomal metabolism and its longevity promoting role in Caenorhabditis elegans. We discovered that lysosomal lipolysis in peripheral fat storage tissue up-regulates the neuropeptide signaling pathway in the nervous system to promote longevity. This cell-non-autonomous regulation requires the secretion from the fat storage tissue of a lipid chaperone protein LBP-3 and polyunsaturated fatty acids (PUFAs). LBP-3 binds to specific PUFAs, and acts through a nuclear hormone receptor NHR-49 and neuropeptide NLP-11 in neurons to extend lifespan. Together, these results reveal lysosomes as a signaling hub to coordinate metabolism and aging, and a lysosomal signaling mechanism that mediates intertissue communication to promote longevity.

cell biology↗

bioRxiv2021

Single-Cell Profiling Resolved Transcriptional Alterations and Lineage Dynamics of Subventricular Zone after Mild Traumatic Brain Injury

Mild traumatic brain injury (mTBI) is the most common form of brain trauma caused by physical impact. The subventricular zone (SVZ) is a neurogenetic niche that contributes to homeostasis and repair after brain injury. It is particularly challenging to fully elucidate the molecular alterations in the SVZ occurring in response to injury due to its cell diversity and the complex network. In this study, we aimed to address this issue using a novel transcriptomic technique- unbiased single-cell RNA sequencing. We resolved previous unknown cell subpopulations harbored in the niche, and uncovered cell type-specific alterations in gene expression, enriched pathways, and cell-cell crosstalk following mTBI. Notably, we also report novel lineage trajectories and molecular hallmarks that govern neurogenesis. This study dissects the delicate transcriptome changes of individual cell types as well as the reprogramming process of cells in the SVZ niche after mTBI, and our findings are expected to facilitate the development of therapeutic interventions or diagnostic tests for mTBI.

neuroscience↗

bioRxiv2021

Magnetic Resonance Spectroscopy Frequency and Phase Correction Using Convolutional Neural Networks

We introduce DeepSPEC, a novel convolutional neural network (CNN) -based approach for frequency-and-phase correction (FPC) of MRS spectra to achieve fast and accurate FPC of single-voxel PRESS MRS and MEGA-PRESS data. In DeepSPEC, two neural networks, including one for frequency correction and one for phase correction were trained and validated using published simulated and in vivo PRESS and MEGA-PRESS MRS dataset with wide-range artificial frequency and phase offsets applied. DeepSPEC was subsequently tested and compared to the current deep learning solution - a "vanilla" neural network approach using multilayer perceptrons (MLP). Furthermore, random noise was added to the original simulated dataset to further investigate the model performance with noise at varied signal-to-noise (SNR) levels (i.e., 6 dB, 3 dB, and 1.5 dB). The testing showed that DeepSPEC is more robust to noise compared to the MLP-based approach due to having a smaller absolute error in both frequency and phase offset prediction. The DeepSPEC framework was capable of correcting frequency offset with 0.01{+/-}0.01 Hz and phase offset with 0.12{+/-}0.09{degrees} absolute errors on average for unseen simulated data at a high SNR (12 dB) and correcting frequency offset with 0.01{+/-}0.02 Hz and phase offset within -0.07{+/-}0.44{degrees} absolute errors on average at very low SNR (1.5 dB). Furthermore, additional frequency and phase offsets (i.e., small, moderate, large) were applied to the in vivo dataset, and DeepSPEC demonstrated better performance for FPC when compared to the MLP-based approach. Results also show DeepSPEC has superior performance than the model-based SR implementation (mSR) in FPC by having higher accuracy in a wider range of additional offsets. These results represent a proof of concept for the use of CNNs for preprocessing MRS data and demonstrate that DeepSPEC accurately predicts frequency and phase offsets at varying noise levels with state-of-the-art performance.

neuroscience↗

bioRxiv2021

ZHX2 Promotes HIF1α Oncogenic Signaling in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is an aggressive and highly lethal disease, which warrants the critical need to identify new therapeutic targets. We show that Zinc Fingers And Homeoboxes 2 (ZHX2) is amplified or overexpressed in TNBC cell lines and patients. Functionally, depletion of ZHX2 inhibited TNBC cell growth and invasion in vitro, orthotopic tumor growth and spontaneous lung metastasis in vivo. Mechanistically, ZHX2 bound with hypoxia inducible factor (HIF) family members and positively regulated HIF1 activity in TNBC. Integrated ChIP-Seq and gene expression profiling demonstrated that ZHX2 co-occupied with HIF1 on transcriptionally active promoters marked by H3K4me3 and H3K27ac, thereby promoting gene expression. Furthermore, multiple residues (R491, R581 and R674) on ZHX2 are important in regulating its phenotype, which correspond with their roles on controlling HIF1 activity in TNBC cells. These studies establish that ZHX2 activates oncogenic HIF1 signaling, therefore serving as a potential therapeutic target for TNBC.

cancer biology↗

bioRxiv2021

Unbiased screen of human transcriptome reveals an unexpected role of 3'UTRs in translation initiation

Although most eukaryotic mRNAs require a 5'-cap for translation initiation, some can also be translated through a poorly studied cap-independent pathway. Here we developed a circRNA-based system and unbiasedly identified more than 10,000 sequences in the human transcriptome that contain Cap-independent Translation Initiators (CiTIs). Surprisingly, most of the identified CiTIs are located in 3'UTRs, which mainly promote translation initiation in mRNAs bearing highly structured 5'UTR. Mechanistically, CiTI recruits several translation initiation factors including eIF3 and DHX29, which in turn unwind 5'UTR structures and facilitate ribosome scanning. Functionally, we showed that the translation of HIF1A mRNA, an endogenous DHX29 target, is antagonistically regulated by its 5'UTR structure and a new 3'-CiTI in response to hypoxia. Therefore, deletion of 3'-CiTI suppresses cell growth in hypoxia and tumor progression in vivo. Collectively, our study uncovers a new regulatory mode for translation where the 3'UTR actively participate in the translation initiation.

molecular biology↗

bioRxiv2021

Comparative genomics reveals insights into phylogenomic taxonomy and potential algae-bacteria interactions of novel versatile Mameliella alba strain LZ-28 isolated from highly-toxic marine phycosphere

Phycosphere harbors cross-kingdom interactions with significant ecological relevance for harmful algal blooms (HAB) and phycotoxins biosynthesis. Previously, a new red-pigmented bacterium designated as strain LZ-28 was isolated from phycosphere microbiota of typical HAB dinoflagellate Alexandrium catenella LZT09 which is a vitamin B12 auxotroph and produces high levels of paralytic shellfish poisoning toxins (PST). Strain LZ-28 exhibited obvious growth-promoting activity toward its algal host, along with the production of active bioflocculanting exopolysaccharides (EPS). But the phylogenetic affiliation and genomic potential of this versatile bacterium has not yet been elucidated. In this study, we carried out combined taxonomic and phylogenomic analysis to clarify the taxonomic classification of strain LZ-28. The obtained 16S rRNA phylogeny revealed close taxonomic relationship between strain LZ-28 and other Mameliella alba members. Additional calculations of key phylogenomic parameters, average nucleotide identity (ANI), the average amino acid identity (AAI) and the digital DNA-DNA hybridization (dDDH) values based on genomes of strain LZ-28 and type strain of Mameliella alba were all exceeded the limit of species circumscription. Collectively considering the phenotypic and biochemical characterizations, strain LZ-28 was therefore identified as a new member of Mameliella alba. Furthermore, based on the genomic evidence, potential algae-bacteria interactions of strain LZ-28 with host algae LZT09 were elucidated through the associations with photosynthetic and antioxidant carotenoids, supplying of bacterial VB12 to auxotroph host, and versatile EPS serving for bacterial colonization and nutrient exchange during their interactions, along with stress response systems to defense oxidative stress and quorum sensing (QS) signals benefited survival for bacteria in the symbiotic system. Comparative genomics shed light on similar genomic features between M. alba strains, revealed potential close associations of strain LZ-28 with its algae host, and further enriched the genomic repertoire of interactions between phycosphere microbiota and algal host LZT09.

microbiology↗

bioRxiv2021

Intermittent Fasting Enhances Hippocampal Npy Expression to Promote Neurogenesis Following Traumatic Brain Injury

Interventions for preventing cognitive dysfunction post traumatic brain injury (TBI) is limited. Given that adult hippocampal neurogenesis (AHN) after brain injury contributes to cognitive recovery, and that the AHN is potentially affected by nutritional factors, we asked whether fasting could promote AHN and thus ameliorates cognitive defects after TBI. Here we show that a one-month intermittent fasting (IF) regimen enhanced proliferation of neural stem cells (NSCs) in the subgranular zone (SGZ) of hippocampus 3 days post TBI, as well as improved cognitive performance in Morris water maze (MWM) test. Furthermore, an increase in hippocampal Npy expression was detected in IF group after injury, compared to the mice fed ad libitum (AL), and locally knock-down of Npy in vivo attenuated the aforementioned effects of IF in TBI. These findings suggest that IF promotes AHN following TBI by a mechanism involving enhancement of Npy expression, which may offer novel interventions that might prevent cognitive dysfunction caused by injury.

neuroscience↗

bioRxiv2021

A comprehensive urine proteome database generated from patients with various renal conditions and prostate cancer

Urine proteins can serve as viable biomarkers for diagnosing and monitoring various diseases. A comprehensive urine proteome database, generated from a variety of urine samples with different disease conditions, can serve as a reference resource for facilitating discovery of potential urine protein biomarkers. Herein, we present a urine proteome database generated from multiple datasets using 2D LC-MS/MS proteome profiling of urine samples from healthy individuals (HI), renal transplant patients with acute rejection (AR) and stable graft (STA), patients with non-specific proteinuria (NS), and patients with prostate cancer (PC). A total of ~28,000 unique peptides spanning ~2,200 unique proteins were identified with a false discovery rate of <0.5% at the protein level. Over one third of the annotated proteins were plasma membrane proteins and another one third were extracellular proteins according to gene ontology analysis. Ingenuity Pathway Analysis of these proteins revealed 349 potential biomarkers. Surprisingly, 43% (167) of all known cluster of differentiation (CD) proteins were identified in the various human urine samples. Interestingly, following comparisons with five recently published urine proteome profiling studies, which applied similar approaches, there are still ~400 proteins which are unique to this current study. These may represent potential disease-associated proteins. Among them, several proteins such as myoglobin, serpin B3, renin receptor, and periostin have been reported as pathological markers for renal failure and prostate cancer, respectively. Taken together, our data should provide valuable information for future discovery and validation studies of urine protein biomarkers for various diseases.

systems biology↗

bioRxiv2021

Identification and Classification of Reverse Transcriptases in Bacterial Genomes and Metagenomes

Reverse Transcriptases (RTs) are found in different systems including group II introns, Diversity Generating Retroelements (DGRs), retrons, CRISPR-Cas systems, and Abortive Infection (Abi) systems in prokaryotes. Different classes of RTs can play different roles, such as template switching and mobility in group II introns, spacer acquisition in CRISPR-Cas systems, mutagenic retrohoming in DGRs, programmed cell suicide in Abi systems, and recently discovered phage defense in retrons. While some classes of RTs have been studied extensively, others remain to be characterized. There is a lack of computational tools for identifying and characterizing various classes of RTs. In this study, we built a tool (called myRT) for identification and classification of prokaryotic RTs. In addition, our tool provides information about the genomic neighborhood of each RT, providing potential functional clues. We applied our tool to predict and classify RTs in all complete and draft bacterial genomes, and created a collection that can be used for exploration of putative RTs. Application of myRT to gut metagenomes showed that gut metagenomes encode proportionally more RTs related to DGRs, outnumbering retron-related RTs, as compared to the collection of reference genomes. MyRT is both available as a standalone software and also through a website.

bioinformatics↗

bioRxiv2020

Identification of inhibitors of SARS-CoV-2 3CL-Pro enzymatic activity using a small molecule in-vitro repurposing screen

Compound repurposing is an important strategy for the identification of effective treatment options against SARS-CoV-2 infection and COVID-19 disease. In this regard, SARS-CoV-2 main protease (3CL-Pro), also termed M-Pro, is an attractive drug target as it plays a central role in viral replication by processing the viral polyproteins pp1a and pp1ab at multiple distinct cleavage sites. We here report the results of a repurposing program involving 8.7 K compounds containing marketed drugs, clinical and preclinical candidates, and small molecules regarded as safe in humans. We confirmed previously reported inhibitors of 3CL-Pro, and have identified 62 additional compounds with IC50 values below 1 M and profiled their selectivity towards Chymotrypsin and 3CL-Pro from the MERS virus. A subset of 8 inhibitors showed anti-cytopathic effect in a Vero-E6 cell line and the compounds thioguanosine and MG-132 were analysed for their predicted binding characteristics to SARS-CoV-2 3CL-Pro. The X-ray crystal structure of the complex of myricetin and SARS-Cov-2 3CL-Pro was solved at a resolution of 1.77 [A], showing that myricetin is covalently bound to the catalytic Cys145 and therefore inhibiting its enzymatic activity. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=154 SRC="FIGDIR/small/422677v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@17ca2aeorg.highwire.dtl.DTLVardef@19c5159org.highwire.dtl.DTLVardef@1a0adf6org.highwire.dtl.DTLVardef@1fd05cd_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOAbstract Figure.C_FLOATNO Workflow for identification and profiling of inhibitors of SARS-CoV-2 3CL-Pro using a large scale repurposing and bioactive compound collection (rhs). Primary assay principle based on quenched FRET peptide substrate of SARS-CoV-2 3CL-Pro (lhs). Inhibiting compounds reduce fluorescence signal relative to DMSO controls. Hit profiling using X-ray. C_FIG

molecular biology↗

bioRxiv2020

LncRNA H19X is required for placenta development and angiogenesis through regulating a noncoding RNA regulatory network

H19X is a lncRNA specifically expressed in the placenta, whose expression is induced by hypoxia. H19X overexpression promoted trophoblast proliferation and invasion, while its knockdown or knockout inhibited trophoblast proliferation and invasion. Mechanistically, we demonstrated that reciprocal regulation exists with miR-424/miR-503 in the control of genes related to placental development and angiogenesis, including VEGF and VEGFR2. H19X inhibited ubiquitination of PIWIL1, thereby maintaining its stability and homeostatic expression of piRNAs. PIWIL1 overexpression rescued the defects of cell behavior caused by H19X KO. H19X deletion led to compromised HIF-1A/HIF-2A expression, which was correlated with the dysregulation of downstream genes under hypoxic conditions. CRISPR/Cas-9 knockout of H19X in animals led to defective placenta differentiation and compromised embryo development under hypoxic conditions. Western blotting showed reduced expression levels of PIWIL1 as well as angiogenesis marker genes, including VEGF and VEGFR2, in H19X KO mice. Thus, this study provides evidence of an unexpected link among lncRNA, miRNA, PIWIL1-related piRNA, and angiogenesis in placentation, the dysregulation of which leads to poor placental development and embryo loss under hypoxic conditions.

developmental biology↗

bioRxiv2020

Comparison of methods for estimating genetic correlation between complex traits using GWAS summary statistics

Genetic correlation is the correlation of additive genetic effects on two phenotypes. It is an informative metric to quantify the overall genetic similarity between complex traits, which provides insights into their polygenic genetic architecture. Several methods have been proposed to estimate genetic correlations based on data collected from genome-wide association studies (GWAS). Due to the easy access of GWAS summary statistics and computational efficiency, methods only requiring GWAS summary statistics as input have become more popular than methods utilizing individual-level genotype data. Here, we present a benchmark study for different summary-statistics-based genetic correlation estimation methods through simulation and real data applications. We focus on two major technical challenges in estimating genetic correlation: marker dependency caused by linkage disequilibrium (LD) and sample overlap between different studies. To assess the performance of different methods in the presence of these two challenges, we first conducted comprehensive simulations with diverse LD patterns and sample overlaps. Then we applied these methods to real GWAS summary statistics for a wide spectrum of complex traits. Based on these experiments, we conclude that methods relying on accurate LD estimation are less robust in real data applications compared to other methods due to the imprecision of LD obtained from reference panels. Our findings offer a guidance on how to appropriately choose the method for genetic correlation estimation in post-GWAS analysis in interpretation.

genetics↗