Biology subjects

Guo, X.

Publications and source records attributed to Guo, X..

At least 199 records · Page 11Linked to original sources

bioRxiv2022

A unified classification system for HIV-1 5' long terminal repeats

The HIV-1 provirus mainly consists of internal coding region flanked by the 2 same long terminal repeats (LTRs) at each terminus. The LTRs play important roles in HIV-1 reverse transcription, integration, and transcription by the association with host factors. However, despite of the significant study advances of the internal coding regions of HIV-1 by using definite reference classification, there are no systematic classifications for HIV-1 5 LTRs, which hinders our elaboration on 5 LTR and a better understanding of the viral origin, spread and therapy. Here, by analyzing all available resources of 5 LTR sequences in public databases following 4 recognized principles for the reference classification, 83 representatives and 14 consensus sequences were identified as representatives of 2 groups, 6 subtypes, 6 sub-subtypes, and 9 CRFs. To test the reliability of our established classification system, the constructed references were applied to identify the 5 LTR assignment of the 22 clinical isolates in China. The results revealed that 16 out of 22 tested strains showed a consistent subtype classification with the previous LTR-independent classification system. However, 6 strains, for which recombination events within 5 LTR were demonstrated, unexpectedly showed a different subtype classification, leading a significant change of binding sites for important transcription factors including SP1, p53, and NF-{kappa}B. The binding change of these transcriptional factors would probably affect the transcriptional activity of 5 LTR. This study established a unified classification system for HIV-1 5 LTRs, which will facilitate HIV-1 characterization and be helpful for both basic and clinical research fields. IMPORTANCEHere, a scientific, reliable, and usable classification system based on the 5 LTR sequences was established, which will allow us to effectively facilitate the precise typing of HIV-1 strains. This classification system was applied to 22 HIV-1 strains circulating in China, we found that 6 out of 22 strains analyzed, belonged to a different subtype when our results were compared to those obtained with the previous LTR-independent classification system. Thus, these data demonstrated that our classification method could greatly improve the HIV-1 subtype classification. We found that 6 5 LTR sequences showed recombination events, leading to a significant exchange of the binding sites of transcriptional factors. Thus, this work established a comprehensive HIV-1 5 LTR classification system, which will help the scientific community to precisely characterize HIV-1 variants, and better understand the origin and spread of HIV-1 strains, and it also may be helpful for pathogenicity and transmissibility evaluation studies.

microbiology↗

bioRxiv2022

Analysis of spatial transcriptomics at varying resolution levels using the unified framework of SpaSEG

Spatially resolved transcriptomics (SRT) for characterizing cellular heterogeneities and activities requires systematic analysis approaches to decipher gene expression variations in physiological contexts. Here we develop SpaSEG, an unsupervised convolutional neural network-based model for multiple SRT analysis tasks by jointly learning the transcriptional similarity of spots and their spatial dependence. SpaSEG adopts an edge strength constraint to encourage spatial domain coherence and allows integrative analysis by automatically aligning the spatial domains across multiple adjacent sections. It also enables the detection of domain-specific gene expression patterns and the inference of intercellular interactions and colocalizations within a tissue. In an invasive ductal carcinoma sample analysis, SpaSEG facilitates the unraveling of intratumor heterogeneity and the understanding of immunoregulatory mechanisms. Through comprehensive evaluation over a collection of SRT datasets generated by different platforms at various resolutions, SpaSEG shows superior reliability and computational efficiency over existing methods, endowing it with a great potential for the exploration of tissue architectures and pathological biology.

bioinformatics↗

bioRxiv2022

Uncovering Cross-Cohort Molecular Features with Multi-Omics Integration Analysis

Integrative approaches that simultaneously model multi-omics data have gained increasing popularity because they provide holistic system biology views of multiple or all components in a biological system of interest. Canonical correlation analysis (CCA) is a correlation-based integrative method. It was initially designed to extract latent features shared between two assays by finding the linear combinations of features - referred to as canonical vectors (CVs) - within each assay that achieve maximal across-assay correlation. Sparse multiple CCA (SMCCA), a widely-used derivative of CCA, allows more than two assays but can result in non-orthogonal CVs when applied to high-dimensional data. Here, we incorporated a variation of the Gram-Schmidt (GS) algorithm with SMCCA to improve orthogonality among CVs. Applying our SMCCA-GS method to proteomics and methylomics data from the Multi-Ethnic Study of Atherosclerosis (MESA) and Jackson Heart Study (JHS), we identified strong associations between blood cell counts and protein abundance. This finding suggests that adjustment of blood cell composition should be considered in protein-based association studies. Importantly, CVs obtained from two independent cohorts demonstrate transferability across the cohorts. For example, proteomic CVs learned from JHS explain similar amounts of blood cell count phenotypic variance in MESA, explaining 39.0% ~ 50.0% variation in JHS and 38.9% ~ 49.1% in MESA, similar transferability was observed for other omics-CV-trait pairs. This suggests that biologically meaningful and cohort-agnostic variation is captured by CVs. We further developed Sparse Supervised Multiple CCA (SSMCCA) to allow supervised integration analysis for more than two assays. We anticipate that applying our SMCCA-GS and SSMCCA on various cohorts would help identify cohort-agnostic biologically meaningful relationships between multi-omics data and phenotypic traits. Author SummaryComprehensive understanding of human complex traits may benefit from incorporation of molecular features from multiple biological layers such as genome, epigenome, transcriptome, proteome, and metabolome. CCA is a correlation-based method for multi-omics data which reduces the dimension of each omic assay to several orthogonal components - commonly referred to as canonical vectors (CVs). The widely-used SMCCA method allows effective dimension reduction and integration of multi-omics data, but suffers from potentially highly correlated CVs when applied to high-dimensional omics data. Here, we improve the statistical independence among the CVs by adopting a variation of the GS algorithm. We applied our SMCCA-GS method to proteomic and methylomic data from two cohort studies, MESA and JHS. Our results reveal a pronounced effect of blood cell counts on protein abundance, strongly suggesting blood cell composition adjustment in protein-based association studies may be necessary. Finally, we present SSMCCA which allows supervised CCA analysis for the association between one phenotype of interest and more than two assays. We anticipate that SMCCA-GS would help reveal meaningful system-level factors from biological processes involving features from multiple assays; and SSMCCA would further empower interrogation of these factors for phenotypic traits related to health and diseases.

genomics↗

bioRxiv2022

Mosaic chromosomal alterations in blood across ancestries via whole-genome sequencing

Mosaic mutations in blood are common with increasing age and are prognostic markers for cancer, cardiovascular dysfunction and other diseases. This group of acquired mutations include megabase-scale mosaic chromosomal alterations (mCAs). These large mutations have mainly been surveyed using SNP array data from individuals of European (EA) or Japanese genetic ancestry. To gain a better understanding of mCA rates and associated risk factors in genetically diverse populations, we surveyed whole genome sequencing data from 67,390 individuals, including 20,132 individuals of African ancestry (AA), and 7,608 of Hispanic ancestry (HA) with deep (30X) whole genome sequencing data from the NHLBI Trans Omics for Precision Medicine (TOPMed) program. We adapted an existing mCA calling algorithm for application to WGS data, and observed higher sensitivity with WGS data, compared with array-based data, in uncovering mCAs at low mutant cell fractions. As in previous reports, we observed a strong association with age and a non-uniform distribution of mCAs across the genome. The presence of autosomal (but not chromosome X) mCAs was associated with an increased risk of both lymphoid and myeloid malignancies. After adjusting for age, we found that individuals of European ancestry have the highest rates of autosomal mCAs, mirroring the higher rate of leukemia in this group. Our analysis also uncovered higher rates of chromosome X mCAs in AA and HA compared to EA, again after adjusting for age. Germline variants in ATM and MPL showed strong associations with mCAs in cis, including ancestry specific variants. And rare variant gene-burden analysis confirmed the association of putatively protein altering variants in ATM and MPL with mCAs in cis. Individual rare variants in DCPS, ADM17, PPP1R16B, and TET2 were all associated with autosomal mCAs and rare variants in OR4C16 were associated with chromosome X mCAs in females. There was significant enrichment of co-occurrence of CHIP mutations and mCAs both altering cancer associated genes TET2, DNMT3A, JAK2, CUX1, and TP53. Overall, our study demonstrates that rates of mCAs differ across populations and that rare inherited germline variants are strongly associated with mCAs across genetically diverse populations. These results strongly motivate further studies of mCAs in under-represented populations to better understand the causes and consequences of this class of somatic variation.

genomics↗

bioRxiv2022

Integrated transcriptome and lineage analyses reveal novel catecholaminergic cardiomyocytes contributing to the cardiac conduction system in murine heart

Cardiac conduction system (CCS) morphogenesis is essential for correct heart function yet is incompletely understood. Here we established the transcriptional landscape of cell types populating the developing heart by integrating single-cell RNA sequencing and spatial enhanced resolution omics-sequencing (Stereo-seq). Stereo-seq provided a spatiotemporal transcriptomic cell fate map of the murine heart with a panoramic field of view and in situ cellular resolution of the CCS. This led to the identification of a previously unrecognized cardiomyocyte population expressing dopamine beta-hydroxylase (Dbh+-CMs), which is closely associated with the CCS in transcriptomic analyses. To confirm this finding, genetic fate mapping by using DbhCre/Rosa26-tdTomato reporter mouse line was performed with Stereo-seq, RNAscope, and immunohistology. We revealed that Dbh+-derived CMs first emerged in the sinus venosus at E12.5, then populated the atrial and ventricular CCS components at E14.5, with increasing abundance towards perinatal stages. Further tracing by using DbhCFP reporter and DbhCreERT/Rosa26-tdTomato inducible reporter, we confirmed that Dbh+-CMs are mostly abundant in the AVN and ventricular CCS and this persists in the adult heart. By using DbhCre/Rosa26-tdTomato/Cx40-eGFP compound reporter line, we validated a clear co-localization of tdTomato and eGFP signals in both left and right ventricular Purkinje fibre networks. Finally, electrophysiological optogenetic study using cell-type specific Channelrhodopsin2 (ChR2) expression further elucidated that Dbh+-derived CMs form a functional part of the ventricular CCS and display similar photostimulation-induced electrophysiological characteristics to Cx40CreERT/ChR2-tdTomato CCS components. Thus, by utilizing advanced transcriptomic, mouse genetic, and optogenetic functional analyses, our study provides new insights into mammalian CCS development and heterogeneity by revealing novel Dbh+-CMs. HighlightsO_LIStereo-seq provided a spatiotemporal transcriptomic cell fate map of the murine heart with a panoramic field of view and in situ cellular resolution of the CCS. C_LIO_LIEstablished the transcriptional landscape of cell types populating the developing murine heart. C_LIO_LIRevealed previously unreported catecholaminergic cardiomyocyte populations contributing to the developing and mature murine cardiac conduction system. C_LI

cell biology↗

bioRxiv2022

Searching across-cohort relatives via encrypted genotype regression

Explicitly sharing individual level data in genomics studies has many merits comparing to sharing summary statistics, including more strict QCs, common statistical analyses, relative identification and improved statistical power in GWAS, but it is hampered by privacy or ethical constraints. In this study, we developed encG-reg, a regression approach that can detect relatives of various degrees based on encrypted genomic data, which is immune of ethical constraints. The encryption properties of encG-reg are based on the random matrix theory by masking the original genotypic matrix without sacrificing precision of individual-level genotype data. We established a connection between the dimension of a random matrix, which masked genotype matrices, and the required precision of a study for encrypted genotype data. encG-reg has false positive and false negative rates equivalent to sharing original individual level data, and is computationally efficient when searching relatives. We split the UK Biobank into their respective centers, and then encrypted the genotype data. We observed that the relatives estimated using encG-reg was equivalently accurate with the estimation by KING, which is a widely used software but requires original genotype data. In a more complex application, we launched a finely devised multi-center collaboration across 5 research institutes in China, covering 9 cohorts of 54,092 GWAS samples. encG-reg again identified true relatives existing across the cohorts with even different ethnic backgrounds and genotypic qualities. Our study clearly demonstrates that encrypted genomic data can be used for data sharing without loss of information or data sharing barrier. Author SummaryEstimating pairwise genetic relatedness within a single cohort is straightforward. However, in practice, related samples are often distributed across different cohorts, making it challenging to estimate inter-cohort relatedness. In this study, we propose a method called encrypted genotype regression (encG-reg), which provides an unbiased estimation of inter-cohort relatedness using encrypted genotypes. The genotype matrix of each cohort is masked by a random matrix, which acts similarly to a private key in a cryptographic scheme. This masking process produces encrypted genotypes, which are a projection of the original genotype matrix. We derive the expectation and particularly the sampling variance for encG-reg, the latter involves eighth-order moments calculation. encG-reg allows us to accurately identify relatedness across cohorts, even for large-scale biobank data. To demonstrate the efficacy of encG-reg, we verified it in a multi-ethnicity UK Biobank dataset comprising 485,158 samples. For this case, we successfully tracked down to the 1st-degree relatedness (such as full sibs and parent-offspring). Furthermore, we used encG-reg in a collaboration involving 9 Chinese cohorts, encompassing a total of 54,092 samples from 5 genomic centers. It is worth noting that if the number of effective markers is sufficient encG-reg has the potential to detect even more distant degrees of relatedness beyond what we demonstrated.

genetics↗

bioRxiv2022

DELE1 oligomerization promotes integrated stress response activation

Mitochondria are dynamic organelles that must continually adapt and respond to cellular stress. Recent studies demonstrated that mitochondrial stress can be relayed from mitochondria to the cytosol by the release of a C-terminal proteolytic fragment of DELE1 that binds to the eIF2 kinase HRI to initiate integrate stress response (ISR) signaling. Here, we report the cryo-electron microscopy structure of the active, C-terminal cleavage product of human DELE1 at[~] 3.8 A{degrees} resolution. Our structure reveals that DELE1 assembles into a high-order oligomer that is observed both in vitro and in mammalian cells. Structurally, the oligomer consists of eight DELE1 monomers that assemble with D4 symmetry via two sets of distinct hydrophobic inter-subunit interactions. We identified the key residues involved in DELE1 oligomerization, and confirmed their role in stabilizing the octamer in vitro and in cells using mutagenesis. Further, we show that assembly impaired DELE1 mutants are compromised in their ability to induce ISR activation in cell culture models. Together, our findings provide molecular insights into the activity of DELE1 and how it signals to promote ISR activity following mitochondrial insult.

molecular biology↗

bioRxiv2022

Alternative mRNA polyadenylation bridges mitochondrion-to-nucleus communication in Arabidopsis

Mitochondria produce signals besides energy and metabolites that influence plant growth and fitness. However, how mitochondrial signals are relayed to other cellular compartments is largely unknown. By applying poly(A)-site RNA-sequencing (PAS-seq) to wildtype Arabidopsis seedlings and a mutant in the histone demethylase JMJ30 treated with the mitochondrial electron transfer chain inhibitor antimycin A (AA), we identified a previously undefined mitochondrion-to-nucleus communication pathway by which mitochondrial functional state regulates co-transcriptionally alternative polyadenylation (APA) of nuclear mRNA. We observed a global shortening of 3' untranslated regions (UTRs) as a molecular signature of AA-activated mitochondrial retrograde response (MRR), which contributed in part to translational regulation of auxin response and cell wall biogenesis. JMJ30 regulated AA-induced 3' UTR shortening, resulting in more transcripts with shortened 3' UTRs upon AA treatment in a JMJ30 gain-of-function mutant and overexpression lines. We also report on the JMJ30-interacting protein CPSF30, a cleavage and polyadenylation specificity factor that recruits JMJ30 to modulate H3K27me3 status at its target loci. Our study illustrates how epigenetic modification and APA coordinate mitochondrion-to-nucleus communication to allow cells to rapidly respond to changes in mitochondrial functional state and shape plant growth and fitness. One-sentence summaryEpigenetic modification and APA coordinate mitochondrion-to-nucleus communication to allow cells to rapidly respond to changes in mitochondrial functional state and shape plant growth and fitness.

molecular biology↗

bioRxiv2022

Down-regulated GAS6 impairs synovial macrophage efferocytosis and promotes obesity-associated osteoarthritis

Obesity has always been considered a significant risk factor in OA progression, but the underlying mechanism of obesity-related inflammation in OA synovitis remains unclear. The present study found that synovial macrophages infiltrated and polarized in the obesity microenvironment and identified the essential role of M1 macrophages in impaired macrophage efferocytosis using pathology analysis of obesity-associated OA. The present study revealed that obese OA patients and ApoE-/- mice showed a more pronounced synovitis and enhanced macrophage infiltration in synovial tissue, accompanied by dominant M1 macrophage polarization. Obese OA mice had a more severe cartilage destruction and increased levels of synovial apoptotic cells than OA mice in the control group. Enhanced M1-polarized macrophages in obese synovium decreased growth arrest-specific 6 (GAS6) secretion, resulting in impaired macrophage efferocytosis in synovial apoptotic cells. Intracellular contents released by accumulated apoptotic cells further triggered an immune response and lead to a release of inflammatory factors, such as TNF-, IL-1{beta}, and IL-6, which induce chondrocyte homeostasis dysfunction in obese OA patients. Intra-articular injection of GAS6 restored the phagocytic capacity of macrophages, reduced the accumulation of local apoptotic cells, and decreased the levels of TUNEL- and caspase-3-positive cells, preserving cartilage thickness and preventing the progression of obesity-associated OA. Therefore, blocking M1 macrophage polarization or intra-articular injection of GAS6 is a potential therapeutic strategy for obesity-associated OA.

immunology↗

bioRxiv2022

Guild-level microbiome signature associated with COVID-19 severity and prognosis

COVID-19 severity has been associated with alterations of the gut microbiota. However, the relationship between gut microbiome alterations and COVID-19 prognosis remains elusive. Here, we performed a genome-resolved metagenomic analysis on fecal samples collected from 300 in-hospital COVID-19 patients at time of admission. Among the 2,568 high quality metagenome-assembled genomes (HQMAGs), Redundancy Analysis identified 33 HQMAGs which showed differential distribution among mild, moderate, and severe/critical severity groups. Random Forest model based on these 33 HQMAGs classified patients from different severity groups (average AUC = 0.79). Co-abundance network analysis found that the 33 HQMAGs were organized as two competing guilds. Guild 1 harbored more genes for short-chain fatty acid biosynthesis, and fewer genes for virulence and antibiotic resistance, compared with Guild 2. Random Forest regression showed that these 33 HQMAGs at admission had the capacity to predict 8 clinical parameters, which are predictors for COVID-19 prognosis, at Day 7 in hospital. Moreover, the dominance of Guild 1 over Guild 2 at admission predicted the death/discharge outcome of the critical patients (AUC = 0.92). Random Forest models based on these 33 HQMAGs classified patients with different COVID-19 symptom severity, and differentiated COVID-19 patients from healthy subjects, non-COVID-19, and pneumonia controls in three independent datasets. Thus, this genome-based guild-level signature may facilitate early identification of hospitalized COVID-19 patients with high risk of more severe outcomes at time of admission.

microbiology↗

bioRxiv2022

Intrinsically disordered proteins SAID1/2 condensate on SERRATE/ARS2 for dual inhibition of miRNA biogenesis in Arabidopsis

Intrinsically disordered proteins (IDPs) SAID1/2 are hypothetic dentin sialophosphoprotein-like proteins, but their true functions are unknown. Here, we identified SAID1/2 as negative regulators of SERRATE(SE)/ARS2, a core factor in miRNA biogenesis complex (microprocessor). Loss-of-function double mutants of said1; said2 caused pleiotropic developmental defects and thousands of differentially-expressed genes that partially overlapped with those in se. said1; said2 also displayed increased assembly of microprocessor and elevated accumulation of miRNAs. Mechanistically, SAID1/2 promotes PRP4KA-mediated phosphorylation of SE, leading to its degradation in vivo. Unexpectedly, SAID1/2 have strong binding affinity to hairpin-structured pri-miRNAs and can sequester them from SE. Moreover, SAID1/2 directly inhibit pri-miRNA processing by microprocessor in vitro. Whereas SAID1/2 did not impact SE subcellular compartmentation, the proteins themselves exhibited liquid-liquid phase condensation that is nucleated on SE. Thus, we proposed that SAID1/2 reduce miRNA production through hijacking pri-miRNAs to prevent microprocessor activity while promoting SE phosphorylation and its destabilization in Arabidopsis.

plant biology↗

bioRxiv2022

The functional impact of rare variation across the regulatory cascade

Each human genome has tens of thousands of rare genetic variants; however, identifying impactful rare variants remains a major challenge. We demonstrate how use of personal multi-omics can enable identification of impactful rare variants by using the Multi-Ethnic Study of Atherosclerosis (MESA) which included several hundred individuals with whole genome sequencing, transcriptomes, methylomes, and proteomes collected across two time points, ten years apart. We evaluated each multi-omic phenotypes ability to separately and jointly inform functional rare variation. By combining expression and protein data, we observed rare stop variants 62x and rare frameshift variants 216x as frequently as controls, compared to 13x to 27x for expression or protein effects alone. We developed a Bayesian hierarchical model to prioritize specific rare variants underlying multi-omic signals across the regulatory cascade. With this approach, we identified rare variants that exhibited large effect sizes on multiple complex traits including height, schizophrenia, and Alzheimers disease.

genomics↗

bioRxiv2022

Identification of the Metaphyseal Skeletal Stem Cell

Identification of novel regional skeletal stem cells (SSCs) will provide a new cellular paradigm for bone physiology and dysfunction. Several populations of SSCs have been identified at distinct skeletal sites. However, a bona fide SSC population has not yet been formally characterized in the bone marrow. Here, we identify a metaphyseal SSCs (mpSSCs) population whose transcriptional landscape is distinct from other bone mesenchymal stromal cells (bMSCs) in the bone marrow. These mpSSCs emerge at the postnatal stage and reside just underneath the growth plate, consistent with the fact that these mpSSCs are exclusively derived from hypertrophic chondrocytes (HCs). These mpSSCs possess SSC properties such as self-renewal and multipotency in vitro and in vivo, stand at the top of the HC de-differentiation path, and produce most HC progeny. Genetic block of the conversion from HCs to mpSSCs significantly compromises trabecular bone formation and bone regeneration. Thus, metaphysis houses a unique HC-derived SSC population, which is a major source of osteoblasts and bMSCs supporting postnatal trabecular bone formation.

developmental biology↗

bioRxiv2022

Tyramine and its AmTYR1 receptor modulate attention in honey bees (Apis mellifera)

Animals must learn to ignore stimuli that are irrelevant to survival and attend to ones that enhance survival. When a stimulus regularly fails to be associated with an important consequence, subsequent excitatory learning about that stimulus can be delayed, which is a form of non-associative conditioning called latent inhibition. Honey bees show latent inhibition toward an odor they have experienced without association with food reinforcement. Moreover, individual honey bees from the same colony differ in the degree to which they show latent inhibition, and these individual differences have a genetic basis. To investigate the mechanisms that underly individual differences in latent inhibition, we selected two honey bee lines for high and low latent inhibition, respectively. We crossed those lines and mapped a Quantitative Trait Locus (QTL) for latent inhibition to a region of the genome that contains the tyramine receptor gene Amtyr11. We then show that disruption of Amtyr1 signaling either pharmacologically or through RNAi qualitatively changes the expression of latent inhibition but has little effect on appetitive conditioning, and these results suggest that AmTYR1 modulates inhibitory processing in the CNS. Electrophysiological recordings from the brain during pharmacological blockade are consistent with a model that AmTYR1 indirectly regulates Hebbian plasticity at inhibitory synapses in the CNS. Finally, sequencing Amtyr1 and its up and downstream genomic region for high and low line workers suggested that individual differences might arise from variation in transcriptional control rather than structural changes in the coding region. Our results therefore identify a distinct modulatory pathway for this type of non-associative learning, and we propose a model for how it modulates Hebbian plasticity at defined synapses in the CNS. We have shown elsewhere how this modulation also underlies potentially adaptive intracolonial learning differences among individuals that benefit colony survival.

animal behavior and cognition↗

bioRxiv2022

Nucleotide and structural polymorphisms of the eastern oyster genome paint a mosaic of divergence, selection, and human impacts

The eastern oyster, Crassostrea virginica, is a valuable fishery and aquaculture species that provides critical services as an ecosystem engineer. Oysters have a life-history that promotes high genetic diversity and gene flow while also occupying a wide range of habitats in variable coastal environments from the southern Gulf of Mexico to the southern waters of Atlantic Canada. To understand the interplay of genetic diversity, gene flow, and intense environmental selection, we used whole genome re-sequencing data from 90 individuals across the eastern United States and Gulf of Mexico, plus 5 selectively bred lines. Our data confirmed a large phylogeographic break between oyster populations in the Gulf of Mexico and the Atlantic coast of the USA. We also demonstrated that domestication has artificially admixed genetic material between the two ocean basins, and selected lines with admixed ancestry continue to maintain heterozygosity at these sites through several generations post admixture, possibly indicating relevance to desirable aquaculture traits. We found that genetic and structural variation are high in both wild and selected populations, but we also demonstrated that, when controlling for domestication admixture across ocean basins, wild populations do have significantly higher levels of nucleotide diversity and copy number variation than selected lines. Within the Atlantic coast, we detected subtle but distinct population structure, introgression of selected lines within wild individuals, an interaction between structural variation and putatively adaptive population structure, and evidence of candidate genes responding to selection from salinity. Our study highlights the potential for applying whole genome sequencing to highly polymorphic species and provides a road map for future work examining the genome variation of eastern oyster populations.

evolutionary biology↗

bioRxiv2022

A second unveiling: haplotig masking of the eastern oyster genome improves population-level inference

Genome assembly can be challenging for species that are characterized by high amounts of polymorphism, heterozygosity, and large effective population sizes. High levels of heterozygosity can result in genome mis-assemblies and a larger than expected genome size due to the haplotig versions of a single locus being assembled as separate loci. Here, we describe the first chromosome-level genome for the eastern oyster, Crassostrea virginica. Publicly released and annotated in 2017, the assembly has a scaffold N50 of 54 mb and is over 97.3% complete based on BUSCO analysis. The genome assembly for the eastern oyster is a critical resource for foundational research into molluscan adaptation to a changing environment and for selective breeding for the aquaculture industry. Subsequent resequencing data suggested the presence of haplotigs in the original assembly, and we developed a post hoc method to break up chimeric contigs and mask haplotigs in published heterozygous genomes and evaluated improvements to the accuracy of downstream analysis. Masking haplotigs had a large impact on SNP discovery and estimates of nucleotide diversity and had more subtle and nuanced effects on estimates of heterozygosity, population structure analysis, and outlier detection. We show that haplotig-masking can be a powerful tool for improving genomic inference, and we present an open, reproducible resource for the masking of haplotigs in any published genome.

genomics↗

bioRxiv2022

Genome-wide CRISPR/Cas9 Screens Reveal Shared and Bespoke Mechanisms of Resistance to SHP2 inhibition

SHP2 (PTPN11) acts upstream of SOS1/2 to enable RAS activation. Allosteric inhibitors (SHP2is) stabilize SHP2 auto-inhibition, preventing activation by upstream stimuli. SHP2is block proliferation of RTK- or cycling RAS mutant-driven cancers and overcome adaptive resistance to other RAS-ERK pathway drugs. Several SHP2is are in clinical trials. To identify potential SHP2i resistance mechanisms, we performed genome-wide CRISPR/Cas9 knockout screens on two SHP2i-sensitive AML cell lines and recovered genes expected to cause resistance, including tumor suppressor (NF1, PTEN, CDKN1B) and "RASopathy" (LZTR1, RASA2) genes, and several novel targets (INPPL1, MAP4K5, epigenetic modifiers). We then screened 14 cancer lines with a focused CRISPR library targeting common "hits" from the genome-wide screens. LZTR1 deletion conferred resistance in 12/14 lines, followed by MAP4K5 (8/14), SPRED2 (6/14), STK40 (6/14), and INPPL1 (5/14). INPPL1, MAP4K5, or LZTR1 deletion reactivated ERK signaling. INPPL1-mediated sensitization to SHP2i required its NPXY motif but not its lipid phosphatase domain. MAP4K5 acted upstream of MEK via a kinase-dependent target(s), whereas LZTR1 showed cell-dependent effects on RIT and RAS stability. INPPLI, MAP4K5, or LZTR1 deletion also conferred SHP2i resistance in mice. Our results reveal multiple SHP2i resistance genes, emphasizing the need for detailed understanding of the resistance landscape to arrive at effective combinations.

cancer biology↗

bioRxiv2022

Stability of SARS-CoV-2 in cold-chain transportation environments and the efficacy of disinfection measures

Cold-chain environment could extend the survival duration of SARS-CoV-2 and increases the risk of transmission. However, the effect of clod-chain environmental factors and packaging materials on SARS-CoV-2 stability and the efficacy of intervention measures to inactivate SARS-CoV-2 under cold-chain environment remains uncertain. This study aimed to unravel cold-chain environmental factors that preserved the stability of SARS-CoV-2 and disinfection measures against SARS-CoV-2 under the cold-chain environment. The spike gene of SARS-CoV-2 isolated from Wuhan hu-1 was used to construct the SARS-CoV-2 pseudovirus and used as model of the SARS-CoV-2 virus. The decay rate of SARS-CoV-2 pseudovirus in the cold-chain environment, various types of packaging material surfaces i.e., PE plastic, stainless steel, Teflon and cardboard, and in frozen seawater was investigated. The influence of LED visible light(wavelength 450 nm-780 nm) and airflow movement on the stability of SARS-CoV-2 pseudovirus at -18{degrees} C were subsequently assessed. The results show that SARS-CoV-2 pseudovirus decayed more rapidly on porous cardboard surface compared with the non-porous surfaces including PE plastic, stainless steel and Teflon. Compared with 25{degrees} C, the decay rate of SARS-CoV-2 pseudovirus was significantly lower at low temperature. Seawater preserved viral stability both at -18{degrees} C and repeated freeze-thawing cycles compared with deionized water. LED visible light illumination and airflow movement environment at -18{degrees} C reduced the SARS-CoV-2 pseudovirus stability. In conclusion, our results indicate cold-chain temperature and seawater as risk factors for SARS-CoV-2 transmission and LED visible light illumination and airflow movement as possible disinfection measures of SARS-CoV-2 under the cold-chain environment. ImportanceIt is widely recognized that low temperature is a condition for maintaining virus vitality, and cold-chain transportation spreads the events of the SARS-CoV-2 were reported. This study provides that the decay rate of the SARS-CoV-2 pseudovirus at low temperatures varies on different packaging materials, and salt ions present in frozen foods such as seafood may protect virus survival. These results provide evidence for the possibility of SARS-CoV-2 transmission through cold-chain transport and also suggest the importance for disinfection of items. However, the commonly used disinfection methods of ultraviolet radiation and chemical reagents are generally not suitable for the disinfection of frozen food. Our study shows LED visible light illumination and airflow movement as possible disinfection measures of SARS-CoV-2 under the cold-chain environment. This has implications for reducing the long-distance transmission of the virus through cold-chain transportation.

microbiology↗