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Cheng, R.

Publications and source records attributed to Cheng, R..

At least 37 records · Page 2Linked to original sources

Encephalomyocarditis virus non-structural protein 2C degrades NDP52 autophagy protein to promote its own survival

Encephalomyocarditis virus (EMCV) is an important zoonotic pathogen that causes encephalitis and myocarditis, primarily in pigs and in some mammals. Nuclear dot protein (NDP) 52 is an important autophagy adaptor protein that is known to target microbial pathogens, including viruses into autophagosomes to facilitate the selective autophagy process. Here, we wanted to investigate how an important zoonotic virus such as EMCV interacts with NDP52. We found that NDP52 negatively regulates the entry and replication phases of EMCV and interacts with EMCV VP1/VP2 proteins to mediate its autophagic degradation. EMCV counteracts this by exerting autophagy induction through its encoded 2C protein. The autophagy machinery then hijacks NDP52 and transports it to lysosomes for subsequent degradation via late endosomal molecules Rab7 and Rab9. Our study describes a novel mechanism by which EMCV escapes the hosts antiviral response to promote its survival by hijacking the autophagy pathway using the non-structural protein 2C of EMCV. ImportanceEMCV is an important zoonotic pathogen that can induce autophagy, but the regulatory role of autophagy receptors in EMCV infection has been rarely reported. Herein, we show that NDP52 is a novel host limiting factor for EMCV, which not only inhibits early EMCV endocytosis, but also restricts EMCV replication in vitro by controlling autophagic degradation of EMCV structural proteins VP1 and VP2. In order to counteract this, EMCV uses the N-terminal region of its non-structural protein 2C to interact with NDP52, and hijacks the autophagy machine to transport NDP52 to lysosomes for degradation, which weakens NDP52-mediated degradation of VP1 and VP2. Importantly, we reveal a novel mechanism by which EMCV evades the host antiviral response, contributing to a deeper understanding of the infectious mechanism of EMCV and providing new ideas for the design of antiviral drug targets.

microbiology↗

PlantRing: A high-throughput wearable sensor system for decoding plant growth, water relations and innovating irrigation

The combination of flexible electronics and plant science has generated various plant-wearable sensors, yet challenges persist in their applications in real-world agriculture, particularly in high-throughput settings. Overcoming the trade-off between sensing sensitivity and range, adapting them to a wide range of crop types, and bridging the gap between sensor measurements and biological understandings remain the primary obstacles. Here we introduce PlantRing, an innovative, nano-flexible sensing system designed to address the aforementioned challenges. PlantRing employs bio-sourced carbonized silk georgette as the strain sensing material, offering exceptional resolution (tensile deformation: < 100 m), stretchability (tensile strain up to 100 %), and remarkable durability (season long), exceeding existing plant strain sensors. PlantRing effectively monitors plant growth and water status, by measuring organ circumference dynamics, performing reliably under harsh conditions and being adaptable to a wide range of plants. Applying PlantRing to study fruit cracking in tomato and watermelon reveals novel hydraulic mechanism, characterized by genotype-specific excess sap flow within the plant to fruiting branches. Its high-throughput application enabled large-scale quantification of stomatal sensitivity to soil drought, a traditionally difficult-to-phenotype trait, facilitating drought tolerant germplasm selection. Combing PlantRing with soybean mutant led to the discovery of a potential novel function of the GmLNK2 circadian clock gene in stomatal regulation. More practically, integrating PlantRing into feedback irrigation achieves simultaneous water conservation and quality improvement, signifying a paradigm shift from experience- or environment-based to plant-based feedback control. Collectively, PlantRing represents a groundbreaking tool ready to revolutionize botanical studies, agriculture, and forestry.

plant biology↗

Identification and determination of the urinary metabolite of iodotyrosine in vivo

BackgroundCongenital hypothyroidism screening traditionally relies on detecting elevated thyroid-stimulating hormone levels, yet this approach may not detect a specific type of congenital hypothyroidism caused by iodotyrosine dehalogenase-1 (Dehal1) deficiency. The deficiency of this enzyme prevents the deiodination of mono-iodotyrosine (MIT) and di-iodotyrosine (DIT) in the process of iodine recycling. This underscores the potential use of iodotyrosine or its metabolites as non-invasive urinary biomarkers for early diagnosis of congenital hypothyroidism. However, the urinary metabolites of MIT/DIT have not yet been discovered. Thus, this study aimed to identify the urinary metabolites of iodotyrosine in experimental models. MethodGas chromatography mass spectrometry was used to identify the urinary metabolites of iodotyrosine following intraperitoneal injection of MIT in rats. An isotope dilution mass spectrometric assay was developed for assessment of identified metabolites. Urine samples from Dehal1 knockout mice were used to confirm the results. ResultsWe identified novel iodotyrosine metabolites, 3-iodo-4-hydroxyphenylacetic acid (IHPA), and 3,5-diiodo-4-hydroxyphenylacetic acid (Di-IHPA) as the primary urinary metabolites of MIT and DIT respectively. The concentrations of urinary IHPA and Di-IHPA were significantly higher in Dehal1 knockout mice. ConclusionOur findings suggest that IHPA is detected in larger quantities and may hold more clinical significance than previously identified biomarkers like MIT and DIT, making it a promising candidate for diagnosing congenital hypothyroidism or other conditions associated with iodine recycling inhibition.

biochemistry↗

Diverse defense systems synergistically drive the microbe-virus arms race in deep sea cold seeps

Cold seeps host diverse microbes and viruses with numerous unexplored defense and anti-defense systems. Analysis of 3,813 microbial and 13,336 viral genomes from 191 metagenomes across 17 cold seep sites reveals extensive microbial defense repertoires, with over 60% representing candidate systems. Experimental validation confirms that several candidates protect against viral infection. These defense systems frequently co-occur, suggesting potential synergistic interactions, and are broadly distributed across sediments. In response, viruses have evolved diverse anti-defense genes, and the concurrent presence of multiple viral and microbial systems highlights intricate coevolution. Functionally critical lineages, such as anaerobic methanotrophic archaea, sulfate-reducing bacteria, and diazotrophs, appear to modify their defensive strategies under ecological and environmental pressures; for example, sulfate-reducing bacteria harbor multiple Gabija systems while corresponding viruses carry anti-Gabija genes, illustrating specific coevolutionary adaptations. Overall, these findings underscore the critical role of virus-microbe interactions in shaping microbial metabolic functions and environmental adaptation in deep-sea ecosystems.

microbiology↗

Integrative multiomic approaches reveal ZMAT3 and p21 as conserved hubs in the p53 tumor suppression network

TP53, the most frequently mutated gene in human cancer, encodes a transcriptional activator that induces myriad downstream target genes. Despite the importance of p53 in tumor suppression, the specific p53 target genes important for tumor suppression remain unclear. Recent studies have identified the p53-inducible gene Zmat3 as a critical effector of tumor suppression, but many questions remain regarding its p53-dependence, activity across contexts, and mechanism of tumor suppression alone and in cooperation with other p53-inducible genes. To address these questions, we used Tuba-seqUltra somatic genome editing and tumor barcoding in a mouse lung adenocarcinoma model, combinatorial in vivo CRISPR/Cas9 screens, meta-analyses of gene expression and Cancer Dependency Map data, and integrative RNA-sequencing and shotgun proteomic analyses. We established Zmat3 as a core component of p53-mediated tumor suppression and identified Cdkn1a as the most potent cooperating p53-induced gene in tumor suppression. We discovered that ZMAT3/CDKN1A serve as near-universal effectors of p53-mediated tumor suppression that regulate cell division, migration, and extracellular matrix organization. Accordingly, combined Zmat3-Cdkn1a inactivation dramatically enhanced cell proliferation and migration compared to controls, akin to p53 inactivation. Together, our findings place ZMAT3 and CDKN1A as hubs of a p53-induced gene program that opposes tumorigenesis across various cellular and genetic contexts.

cancer biology↗

A Cost-effective, High-throughput, Highly Accurate Genotyping Method for Outbred Populations

Affordable sequencing and genotyping methods are essential for large scale genome-wide association studies. While genotyping microarrays and reference panels for imputation are available for human subjects, non-human model systems often lack such options. Our lab previously demonstrated an efficient and cost-effective method to genotype heterogeneous stock rats using double-digest genotyping-by-sequencing. However, low-coverage whole-genome sequencing offers an alternative method that has several advantages. Here, we describe a cost-effective, high-throughput, high-accuracy genotyping method for N/NIH heterogeneous stock rats that can use a combination of sequencing data previously generated by double-digest genotyping-by-sequencing and more recently generated by low-coverage whole-genome-sequencing data. Using double-digest genotyping-by-sequencing data from 5,745 heterogeneous stock rats (mean 0.21x coverage) and low-coverage whole-genome-sequencing data from 8,760 heterogeneous stock rats (mean 0.27x coverage), we can impute 7.32 million bi-allelic single-nucleotide polymorphisms with a concordance rate >99.76% compared to high-coverage (mean 33.26x coverage) whole-genome sequencing data for a subset of the same individuals. Our results demonstrate the feasibility of using sequencing data from double-digest genotyping-by-sequencing or low-coverage whole-genome-sequencing for accurate genotyping, and demonstrate techniques that may also be useful for other genetic studies in non-human subjects. Article SummaryHeterogeneous stock rats were derived by interbreeding eight inbred founders in 1984, and have been maintained as an outbred population for more than 100 generations. Heterogeneous stock rats offer a high degree of genetic and phenotypic diversity, and have been extensively used for genetic studies. Here, we describe a cost-effective and high-throughput genotyping method for heterogeneous stock rats. We applied the method to 15,552 heterogeneous stock rats. The resulting genotypes were highly accurate. These techniques may be useful for genetic studies in other non-human subjects.

genetics↗

Cancer-associated snaR-A noncoding RNA interacts with core splicing machinery and disrupts processing of mRNA subpopulations

RNA polymerase III (Pol III) activity in cancer is linked to the production of small noncoding (nc)RNAs that are otherwise silent in most tissues. snaR-A (small NF90-associated RNA isoform A) - a hominid-specific ncRNA shown to enhance cell proliferation, migration, and invasion - is a cancer-emergent Pol III product that remains largely uncharacterized despite promoting growth phenotypes. Here, we applied a combination of genomic and biochemical approaches to study the biogenesis and subsequent protein interactions of snaR-A and to better understand its role as a putative driver of cancer progression. By profiling the chromatin landscapes across a multitude of primary tumor types, we show that predicted snaR-A upregulation is broadly linked with unfavorable outcomes among cancer patients. At the molecular level, we unexpectedly discover widespread interactions between snaR-A and mRNA splicing factors, including SF3B2 - a core component of the U2 small nuclear ribonucleoprotein (snRNP). We find that SF3B2 levels are sensitive to high snaR-A abundance and that depletion of snaR-A alone is sufficient to decrease intron retention levels across subpopulations of mRNA enriched for U2 snRNP occupancy. snaR-A sensitive genes are characterized by high GC content, close spatial proximity to nuclear bodies concentrated in pre-mRNA splicing factors, and functional enrichment for proteins involved in deacetylation and autophagy. We highlight examples of splicing misregulation and increased protein levels following snaR-A depletion for a wide-ranging set of factors, suggesting snaR-A-driven splicing defects may have far-reaching effects that re-shape the cellular proteome. These findings clarify the molecular activities and consequences of snaR-A in cancer, and altogether establish a novel mechanism through which Pol III overactivity may promote tumorigenesis.

molecular biology↗

Genome-wide association study for age-related hearing loss in CFW mice

Age-related hearing impairment is the most common cause of hearing loss and is one of the most prevalent conditions affecting the elderly globally. It is influenced by a combination of environmental and genetic factors. The mouse and human inner ears are functionally and genetically homologous. Investigating the genetic basis of age-related hearing loss (ARHL) in an outbred mouse model may lead to a better understanding of the molecular mechanisms of this condition. We used Carworth Farms White (CFW) outbred mice, because they are genetically diverse and exhibit variation in the onset and severity of ARHL. The goal of this study was to identify genetic loci involved in regulating ARHL. Hearing at a range of frequencies was measured using Auditory Brainstem Response (ABR) thresholds in 946 male and female CFW mice at the age of 1, 6, and 10 months. We obtained genotypes at 4.18 million single nucleotide polymorphisms (SNP) using low-coverage (mean coverage 0.27x) whole-genome sequencing followed by imputation using STITCH. To determine the accuracy of the genotypes we sequenced 8 samples at >30x coverage and used calls from those samples to estimate the discordance rate, which was 0.45%. We performed genetic analysis for the ABR thresholds for each frequency at each age, and for the time of onset of deafness for each frequency. The SNP heritability ranged from 0 to 42% for different traits. Genome-wide association analysis identified several regions associated with ARHL that contained potential candidate genes, including Dnah11, Rapgef5, Cpne4, Prkag2, and Nek11. We confirmed, using functional study, that Prkag2 deficiency causes age-related hearing loss at high frequency in mice; this makes Prkag2 a candidate gene for further studies. This work helps to identify genetic risk factors for ARHL and to define novel therapeutic targets for the treatment and prevention of ARHL.

genetics↗

Evidence of RNA polymerase III recruitment and transcription at protein-coding gene promoters

RNA polymerase (Pol) I, II, and III are most commonly described as having distinct roles in synthesizing ribosomal RNA (rRNA), messenger RNA (mRNA), and specific small noncoding (nc)RNAs, respectively. This delineation of transcriptional responsibilities is not definitive, however, as evidenced by instances of Pol II recruitment to genes conventionally transcribed by Pol III, including the co-transcription of RPPH1 - the catalytic RNA component of RNase P. A comprehensive understanding of the interplay between RNA polymerase complexes remains lacking, however, due to limited comparative analyses for all three enzymes. To address this gap, we applied a uniform framework for quantifying global Pol I, II, and III occupancies that integrates currently available human RNA polymerase ChIP-seq datasets. Occupancy maps are combined with a comprehensive multi-class promoter set that includes protein-coding genes, noncoding genes, and repetitive elements. While our genomic survey appropriately identifies recruitment of Pol I, II, and III to canonical target genes, we unexpectedly discover widespread recruitment of the Pol III machinery to promoters of specific protein-coding genes, supported by colocalization patterns observed for several Pol III-specific subunits. We show that Pol III-occupied Pol II promoters are enriched for small, nascent RNA reads terminating in a run of 4 Ts, a unique hallmark of Pol III transcription termination and evidence of active Pol III activity at these sites. Pol III disruption differentially modulates the expression of Pol III-occupied coding genes, which are functionally enriched for ribosomal proteins and genes broadly linked to unfavorable outcomes in cancer. Our map also identifies additional, currently unannotated genomic elements occupied by Pol III with clear signatures of nascent RNA species that are sensitive to disruption of La (SSB) - a Pol III-related RNA chaperone protein. These findings reshape our current understanding of the interplay between Pols II and III and identify potentially novel small ncRNAs with broad implications for gene regulatory paradigms and RNA biology.

genomics↗

Genome-Wide Association Study in Outbred Heterogeneous Stock Rats Identifies Multiple Loci for the Incentive Salience of Reward Cues.

Addiction vulnerability is associated with the tendency to attribute incentive salience to reward predictive cues; both addiction and the attribution of incentive salience are influenced by environmental and genetic factors. To characterize the genetic contributions to incentive salience attribution, we performed a genome-wide association study (GWAS) in a cohort of 1,645 genetically diverse heterogeneous stock (HS) rats. We tested HS rats in a Pavlovian conditioned approach task, in which we characterized the individual responses to food-associated stimuli ("cues"). Rats exhibited either cue-directed "sign-tracking" behavior or food-cup directed "goal-tracking" behavior. We then used the conditioned reinforcement procedure to determine whether rats would perform a novel operant response for unrewarded presentations of the cue. We found that these measures were moderately heritable (SNP heritability, h2 = .189-.215). GWAS identified 14 quantitative trait loci (QTLs) for 11 of the 12 traits we examined. Interval sizes of these QTLs varied widely. 7 traits shared a QTL on chromosome 1 that contained a few genes (e.g. Tenm4, Mir708) that have been associated with substance use disorders and other mental health traits in humans. Other candidate genes (e.g. Wnt11, Pak1) in this region had coding variants and expression-QTLs in mesocorticolimbic regions of the brain. We also conducted a Phenome-Wide Association Study (PheWAS) on other behavioral measures in HS rats and found that regions containing QTLs on chromosome 1 were also associated with nicotine self-administration in a separate cohort of HS rats. These results provide a starting point for the molecular genetic dissection of incentive salience and provide further support for a relationship between attribution of incentive salience and drug abuse-related traits.

neuroscience↗

TSC22D, WNK and NRBP gene families exhibit functional buffering and evolved with Metazoa for macromolecular crowd sensing

The ability to sense and respond to osmotic fluctuations is critical for the maintenance of cellular integrity. Myriad redundancies have evolved across all facets of osmosensing in metazoans, including among water and ion transporters, regulators of cellular morphology, and macromolecular crowding sensors, hampering efforts to gain a clear understanding of how cells respond to rapid water loss. In this study, we harness the power of gene co-essentiality analysis and genome-scale CRISPR-Cas9 screening to identify an unappreciated relationship between TSC22D2, WNK1 and NRBP1 in regulating cell volume homeostasis. Each of these genes have paralogs and are functionally buffered for macromolecular crowd sensing and cell volume control. Within seconds of hyperosmotic stress, TSC22D, WNK and NRBP family members physically associate into cytoplasmic biocondensates, a process that is dependent on intrinsically disordered regions (IDRs). A close examination of these protein families across metazoans reveals that TSC22D genes evolved alongside a domain in NRBPs that specifically binds to TSC22D proteins, which we have termed NbrT (NRBP binding region with TSC22D), and this co-evolution is concomitant with rapid IDR length expansion in WNK family kinases. Our study identifies functions for unrecognized components of the cell volume sensing machinery and reveals that TSC22D, WNK and NRBP genes evolved as cytoplasmic crowding sensors in metazoans to co-regulate rapid cell volume changes in response to osmolarity.

cell biology↗

Genome-wide association study and sequence similarity analysis for unilateral renal agenesis using heterogeneous stock rats undercovers the KIT gene and AHR, ATF3, GATA3, HNF1B, POU2F2, and TFCP2 transcription factors as potential candidates to explain incomplete penetrance

1Human unilateral renal agenesis is a congenital urinary tract malformation. Affected individuals have only one kidney, which is often an asymptomatic developmental defect. A total of 5,585 male and female HS rats were assessed for unilateral renal agenesis and genotyped for 3513,321 markers. The R package SAIGEgds was used for the association analysis. The adjusted p-value threshold for the association analysis determined by permutation was equal to 5.6 (-log10). Two additional datasets were used as validation tests. Population two included 1,577 rats genotyped for 7,425,889 markers and a case-control imbalance equal to 1:174; population three included 1,407 rats, genotyped for 254,932 markers and case-control ratio equal to 1:38. The python package GxTheta was used to perform a polygenic epistasis analysis for the analyzed HS rat population. A founder haplotype mosaic determination was performed using the R package QTL2. Associated regions were selected for further analysis, including long-read PacBio sequencing for founder individuals and a founder haplotype prediction test. A similarity analysis at a genomic level and for loci encoding transcription factors predicted to interact with selected sequences inside the associated loci were accomplished. A total of 1,181 polymorphisms were associated with URA. All associated polymorphisms were located on chromosome 14 between 32.9 and 36.6 Mb. The most significant polymorphism was chr14:36,411,266, a G/T transversion. The same associated region was identified in population three. Polygenic epistasis was determined as not predominant for the presentation of URA. Based on the haplotype mosaic probability estimation, cases display a higher probability of inheriting the ACI allele. The long-read sequencing analysis showed the presence of an Erv insertion inside the intron one of the KIT gene located inside the associated region. The Erv insertion comprises one Erv sequence and two Ltr sequences located downstream and upstream of the former. No Erv insertion was identified for the founder strain BN. For ACI and HSRA, only one Ltr sequence was identified. One hundred and seven genes encoding TFs that recognize binding sites on the Erv insertion were analyzed for sequence similarity against the reference HSRA. The TF similarity score analysis for the interaction genotype and phenotype showed significance after FDR correction for 20 TFs, including AHR, HNF1B, JUNB, RARG, and RXRA. A mechanism identifying URA as a threshold phenotype is suggested in HS rats. It implies the existence of a minimum threshold for the final number of nephrons and kidney associated structures required for stalling the apoptotic process of the metanephric rudiments. Animals exhibiting a quantitative cumulative defect would express URA, being this malformation identified as a phenotype with decreased penetrance in the assessed population of HS rats. All these processes are described as mediated by KIT and TFs able to interact with sequences of the Erv insertion.

genetics↗

Causal Genetic Loci for a Motivated Behavior Spectrum Harbor Psychiatric Risk Genes

Behavioral diversity is critical for population fitness. Individual differences in risk-taking are observed across species, but underlying genetic mechanisms and conservation are largely unknown. We examined dark avoidance in larval zebrafish, a motivated behavior reflecting an approach-avoidance conflict. Brain-wide calcium imaging revealed significant neural activity differences between approach-inclined versus avoidance-inclined individuals. We used a population of [~]6,000 to perform the first genome-wide association study (GWAS) in zebrafish, which identified 34 genomic regions harboring many genes that are involved in synaptic transmission and human psychiatric diseases. We used CRISPR to study several causal genes: serotonin receptor-1b (htr1b), nitric oxide synthase-1 (nos1), and stress-induced phosphoprotein-1 (stip1). We further identified 52 conserved elements containing 66 GWAS significant variants. One encoded an exonic regulatory element that influenced tissue-specific nos1 expression. Together, these findings reveal new genetic loci and establish a powerful, scalable animal system to probe mechanisms underlying motivation, a critical dimension of psychiatric diseases.

neuroscience↗

Prokaryotic Gabija complex senses and executes nucleotide depletion and DNA cleavage for antiviral defense

The Gabija antiviral system consists of the GajA and GajB proteins. We previously revealed that GajA is a DNA nicking endonuclease. In this work, we found that the DNA binding of GajA is strictly inhibited by NTP. Furthermore, the antiviral defense of GajA requires the assistance from GajB, which senses DNA termini produced from the DNA nicking by GajA to hydrolyze (d)A/(d)GTP. The synergy between the DNA cleavage by GajA and the nucleotide hydrolysis by GajB results in an efficient abortive infection defense against virulent bacteriophages. GajA binds to GajB to form stable complexes in vivo and in vitro. However, a functional Gabija complex requires the molecular ratio between GajB and GajA below 1:1. Through (i) sequential sensing and executing the nucleotide depletion and DNA cleavage to cause a cascade suicide effect and (ii) stoichiometry regulation of the DNA/nucleotide processing complex, the Gabija system exhibits a unique mechanism distinct from other known prokaryotic antiviral systems.

microbiology↗

Epidemiological evaluation and identification of the insect vector of soybean stay-green associated virus

In recent years, the emergence of soybean stay-green syndrome (SGS), also referred to as "zhengqing", in the Huang-Huai-Hai region of China has resulted in significant yield losses, with some areas experiencing a complete reduction in seed yield. SGS is a phenomenon characterized by the delayed senescence of soybean, resulting in stay-green leaves, flat pods, and stunted seed development at harvest. Our group was the first to identify a distinct geminivirus, named soybean stay-green associated geminivirus (SoSGV), as the causative agent of SGS by fulfilling Kochs postulate. To further understand the epidemiology of SoSGV, in this study, we collected 368 stay-green samples from 17 regions in 8 provinces including the Huang-Huai-Hai region and surrounding areas of China. The results showed that 228 samples tested positive for SoSGV (61.96%), and 96.93% of these positive samples showed severe pod deflation. Our epidemiological assessment reveals SGS caused by the SoSGV is prevalent in the fields, and it is undergoing geographical expansion and genetic differentiation. Additionally, we determined the other natural hosts grown in the Huang-Huai-Hai region of China. By capturing insects in the field and conducting laboratory vector transmission tests, we confirmed that the common brown leafhopper (Orosius orientalis) is the transmitting vector of SoSGV. With a better understanding of the epidemiology of SoSGV and its transmission, we can develop more effective strategies for managing and mitigating its impact on soybean yields.

microbiology↗

Exponential increase in QTL detection with increased sample size.

Power analyses are often used to determine the number of animals required for a genome wide association analysis (GWAS). These analyses are typically intended to estimate the sample size needed for at least one locus to exceed a genome-wide significance threshold. A related question that is less commonly considered is the number of significant loci that will be discovered with a given sample size. We used simulations based on a real dataset that consisted of 3,173 male and female adult N/NIH heterogeneous stock (HS) rats to explore the relationship between sample size and the number of significant loci discovered. Our simulations examined the number of loci identified in sub-samples of the full dataset. The sub-sampling analysis was conducted for four traits with low (0.15 {+/-} 0.03), medium (0.31 {+/-} 0.03 and 0.36 {+/-} 0.03) and high (0.46 {+/-} 0.03) SNP-based heritabilities. For each trait, we sub-sampled the data 100 times at different sample sizes (500, 1,000, 1,500, 2,000, and 2,500). We observed an exponential increase in the number of significant loci with larger sample sizes. Our results are consistent with similar observations in human GWAS and imply that future rodent GWAS should use sample sizes that are significantly larger than those needed to obtain a single significant result.

genetics↗

DeepCCI: a deep learning framework for identifying cell-cell interactions from single-cell RNA sequencing data

With the rapid development of high throughput single-cell RNA sequencing (scRNA-seq) technologies, it is of high importance to identify Cell-cell interactions (CCIs) from the ever-increasing scRNA-seq data. However, limited by the algorithmic constraints, current computational methods based on statistical strategies ignore some key latent information contained in scRNA-seq data with high sparsity and heterogeneity. To address the issue, here, we developed a deep learning framework named DeepCCI to identify meaningful CCIs from scRNA-seq data. Applications of DeepCCI to a wide range of publicly available datasets from diverse technologies and platforms demonstrate its ability to predict significant CCIs accurately and effectively.

bioinformatics↗

Coupled functional physiological phenotyping and simulation model to infer the transpiration sensitivity traits and its implications for transpiration ideotype design

As agricultural drought becomes more frequent worldwide, it is essential to improve crop productivity whilst reducing the water consumption to achieve a sustainable production. Plant transpiration rate and water use efficiency (WUE) collectively determine the yield performance, yet it is challenging to balance the two in breeding programs due to still insufficient mechanistic understanding of the traits. Here we demonstrate the feasibility and effectiveness of calculating dynamic and momentary WUE by coupling WUE model and the state-of-the-art functional physiological phenotyping (FPP). We also present the method of quantifying genotype-specific traits reflecting sensitivity of transpiration to radiation (STr-Rad) and vapor pressure deficit (STr-VPD), under evolving developmental stage and water availability. Using these methods, we revealed the genotypic difference of STr-Rad and STr-VPD in three watermelon accessions, the dramatic change in each of them across the drought treatment phases, and the quantitative impacts of them on dynamic WUE patterns. Based on our results and computational simulations, a general principle for transpiration ideotype design is proposed, which highlights the benefits of lowering STr-VPD to increase WUE and increasing STr-Rad to offset the decline of Tr. FPP-enabled phenomic selection will help screen for elite crops lines with desired transpiration sensitivities.

physiology↗