In a few minutes of computation, DiffSegR could rightfully predict the role of chloroplast ribonuclease Mini-III in rRNA maturation and chloroplast ribonuclease PNPase in (3′/5′)-degradation of rRNA, mRNA and tRNA precursors as well as intron accumulation. We believe DiffSegR will benefit biologists working on transcriptomics as it allows access to information from a layer of the transcriptome overlooked by the classical differential expression analysis pipelines widely used today. DiffSegR is available at https://aliehrmann.github.io/DiffSegR/index.html.To fully understand gene regulation, it is necessary to have a thorough understanding of both the transcriptome and the enzymatic and RNA-binding activities that shape it. While many RNA-Seq-based tools have been developed to analyze the transcriptome, most only consider the abundance of sequencing reads along annotated patterns (such as genes). These annotations are typically incomplete, leading to errors in the differential expression analysis. To address this issue, we present DiffSegR - an R package that enables the discovery of transcriptome-wide expression differences between two biological conditions using RNA-Seq data. DiffSegR does not require prior annotation and uses a multiple changepoints detection algorithm to identify the boundaries of differentially expressed regions in the per-base log It has long been recognized that transcriptomes largely surpass genomes in complexity . BesidesAs a consequence, there is a massive effort to improve transcriptomic annotations with the help of the third generation (long-read) sequencing technologies from Oxford Nanopore Technologies or Pacific Bioscience. Long RNA-Seq reads may cover an entire RNA isoform from start to end, directly illustrating the exon structure, splicing patterns and UTR composition . They caBecause most RNA-Seq experiments aim at identifying RNA processes that vary between two biological conditions , an alternative to this issue is to identify portions of the transcriptome that vary between both experimental conditions  directly from the RNA-Seq data, without relying on annotations and bypassing assembly altogether. This is performed by a class of methods sometimes referred to as identify-then-annotate tools . Their g2 fold change (log2-FC) using FPOP, a method designed to identify changepoints in the mean of a Gaussian signal  is given byWe describe alternative approaches that use either the full length or the 5′ or 3′ end of the reads, and compare them with our geometric mean heuristic in Notes S1–S3, R1 and R2 stand for the number of replicates in condition 1 and 2, respectively.where D changepoints 1<…< τDτ within the range 1 and n – 1. These changepoints correspond to unknown positions along the genome where a shift in the mean of the per-base log2-FC (eq: 2) is observed. We adopt the convention that τ0= 0 and τ|τ| = n. These changepoints define |τ| = D + 1 distinct segments. The jth segment includes the data j-1,τjτj-1+τ1,…,jτ}. Each segment is premised on the assumption that the iY therein are independent and follow the same Gaussian distribution, with a mean jμ specific to that segment and a common variance σ2. Expressed mathematically, we have:We consider 1<…< τDτ, can be estimated using penalized maximum likelihood inference. To achieve this, DiffSegR uses the FPOP algorithm (6< n <107) in a matter of seconds. The number of changepoints estimated by FPOP is a decreasing function of the penalty 2λσ log(n). The constant λ is a hyperparameter that can be adjusted by the user. A good starting point, based on theoretical arguments (λ = 2. The variance 2σis estimated on the data using the unbiased sample variance estimator.The parameters of the model (eq: 3), including lgorithm   of the last segment. This idea is referred to as ‘functional pruning’. In the Gaussian case, the resulting function is piecewise quadratic. For a new observation at time t+ 1, it is possible to efficiently update this function  using a formula similar to that of the Viterbi algorithm. This formula is applied piece by piece, that is by intervals. At each step, the algorithm searches for the best possible value of the parameter of the last segment to maximize the penalized likelihood.Informally, the idea of the FPOP algorithm is to consider the penalized maximum likelihood of the data from observation 1 to ijrμ is composed of a sample-specific size factor jrs and a parameter ijrq proportional to the expected true concentration of transcripts overlapping position i in replicate r of condition j verifying ijr= sjr qijrμ(2-FC (eq: 2) depends on sample-specific size factors. One can show that the non-normalized and normalized per-base log2-FC are linked together by an offset denoted ρ such thatTo account for differences in the total number of sequenced reads per sample, we assume that the mean of the coverage  sjr qijr,35,36. AFor a given penalty the output of FPOP is shift invariant. That is if the data is shifted by a given value the returned changepoints will be the same. Therefore the segmentation returned by DiffSegR does not depend on the knowledge of the normalization factors. This is a key difference with threshold based methods .2-FC, the previous argument is approximately true for large counts but does not hold for small counts.We acknowledge that when taking into account the offset to the logarithms (+1) in the per-base logwww.R-project.org/) and can be found on GitHub  with the installation procedure as well as a vignette with functional examples. The package implements the four steps of a conventional pipeline for identify-then-annotate methods . Alternative approaches use either the full length or the 5′ or 3′ end of the reads (Note S1). loadData then converts the coverage profiles into the per-base log2-FC (eq: 2) (one per strand) using the reference biological condition specified by the user as the denominator. The function returns the coverage profiles and the differential transcription profile as a list of run-length encoded objects.The segmentation function uses FPOP (2-FC of both strands to identify the segment's boundaries (or changepoints). The number of returned segments is controlled by the hyperparameter λ specified by the user. The segments are stored as GenomicRanges object and the segmentation function finally uses featurecounts  procedure to control the false discovery rate (FDR), which is a common approach in DEA. However, this approach does not guarantee that the proportion of false discoveries (FDP) will be upper bounded, and there is no statistical guarantee on the number of false discoveries in subsets of segments selected using FDR thresholding. For example, while a widespread practice in DEA is to select a subset of segments whose absolute log2-FC passes a threshold it can potentially result in an inflated FDR. To address these limitations, the dea function can also call a post-hoc inference procedure that provides guarantees on the FDP in arbitrary segment selections : antisense, upstream, downstream, inside, overlapping 3′, overlapping 5′ and overlapping both 5′ and 3′. These labels allow users to easily understand the relationships between the DERs and their nearest annotations, and to analyze the potential functional significance of the DERs in the context of the annotated genomic features.The exportResults function saves the DERs, not-DERs, segmentation, the mean of coverage profiles from both biological conditions and per-base log2-FC information, for both strands, in formats readable  by genome viewers like the Integrative Genome Viewer (IGV)  . For IGV bed, gff by genomEvaluation metrics) of DiffSegR and competitors were evaluated on two RNA-Seq datasets comparing Arabidopsis thaliana control plants (col0) to mutants deficient in the PNPase and Mini-III chloroplast ribonucleases  to a mutant deficient for the Rae1 ribonuclease (SSB1002 strain)  contained ten RNA-Seq replicates of the Col-0 Arabidopsis thaliana accession grown in nitrogen deficiency condition with about 32.7 million reads each. The plants were grown at the IJPB Phenoscope platform (https://phenoscope.versailles.inrae.fr/) to ensure maximal homogeneity between the replicates (see the GEO database with the accession number GSE234377 for more details). RNA-Seq datasets were aligned to the Arabidopsis thaliana chloroplast genome using the OGE pipeline (https://forgemia.inra.fr/GNet/pipelineoge)  . We refelineoge) . This pilineoge) . The BAM aligner . These aFor the purpose of benchmarking DiffSegR against other methods in terms of true positive rate (see below), one or more parameters likely to change the number and/or the positions of the identified changepoints were adjusted.minDepth) is common to derfinder RL and srnadiff. All contiguous positions with mean of coverages above this threshold are kept. For each method, on both datasets, one hundred minDepth values evenly spaced within the interval  were tested. The default minDepth value of derfinder RL and srnadiff are 5 and 10, respectively.The minimum depth threshold (2-FC threshold (minLogFC) is used by srnadiff to keep only contiguous positions with absolute normalized log2-FC above the threshold. For both methods, on both datasets, one hundred minLogFC values evenly spaced within the interval  were tested. The default minLogFC value of srnadiff is 0.5.The minimum logemissionThreshold) is used by srnadiff to define the HMM states. For both methods, on both datasets, one hundred (emissionThreshold) values evenly spaced within the interval  were tested. The default emissionThreshold value of srnadiff is 0.1.The emission threshold  stand for the largest set of segments with a fold change >1.5  and a false discovery proportion upper bound set to 5%. Both per-segment fold change and g DESeq2 . The posg DESeq2 ,43. Unler pnp1-1 , rnc3/4   and a three-level segmentation approach on the per-base log2-FC (srnadiff IR)  Figure . Consequ) Figure , compariAll the simulations presented here were performed with an Intel Core i7-10810U CPU @ 1.10GHz, 16 Go of RAMs and 10 logical cores. On both chloroplast RNA-Seq datasets, DiffSegR returns results in less than 2 minutes. In comparison, it takes less than 30 s for a standard differential gene expression (DGE) analysis. The identification of segment boundaries using changepoint detection analysis runs in less than a second on both datasets. The slowest step of the DiffSegR pipeline is the construction of the coverage profiles followed later by the segment count table using the featureCounts program and the BAMs files . Less thcol0) to a mutant deficient in the PNPase chloroplast ribonuclease (pnp1-1), a major 3′ processing enzyme  matches an area previously shown to over accumulate RNA 5′ ends in pnp1-1 (psbH and antisense to psbN (DER 2 with genomic positions 74224 to 74846) corresponds to various 400–700 nt long RNA isoforms previously characterized in WT or pnp1-1 mutants  (pnp1-1 and 6 in rnc3/4) where a DER was expected to be found  ,37. In crnc3/4) ,32. Thesectively , includiTPR of 1 . As expeTPR of 1  using a 2-FC. As a consequence, distinct DER events stemming from distinct RNA maturation processes could be wrongly associated together  in pnp1-1. In rnc3/4 respective median lengths are equal to 15 and 97 nt  . In rnc3/4, derfinder fails to detect DERs, accounting for the absence of overlapping DERs between DiffSegR and derfinder RL in this particular dataset  Figure . An idenbona fide transcriptional differences   in pnp1-1. In rnc3/4 respective median lengths are equal to 294 and 86 nt  . In the rnc3/4 dataset, respective median lengths are equal to 327 and 122 nt   . As a co) Figure . An iden) Figure . We concBacillus subtilis RNA-Seq dataset previously used to decipher the role of the Rae1 ribonuclease  and eventually selected seven of them  as candidates for direct degradation by Rae1. DiffSegR returned significant up-regulated DERs overlapping 45 of the 46 genes identified by Leroy et al. including the seven candidates of interests (pnp1-1 dataset were 55 (1.7%), 73 (1.7%), 83 (1.1%), 204 (1.1%), 56 (0.8%) nt long.Sparsity refers to the fraction of a genomic region with a null RNA-Seq coverage and is known to cause artifacts in statistical analyses . Becausenuclease  and whosnterests . In addinterests . A strikWe here introduced DiffSegR, an R package that allows the discovery of transcriptome-wide expression differences between two biological conditions using RNA-Seq data Figure . While sLike other methods willing to automatically identify transcription differences along the genome, DiffSegR addresses a well-defined statistical problem known as the multiple changepoints detection or segmentation problem. Among the many algorithmically and statistically well-established methods that have been developed to tackle this problem ,56, Diff2-FC signal for segmentation analysis, a strategy that carries three main advantages. First, it scales with the intensity of the difference up to a normalization constant. Second, it discriminates between up-regulated and down-regulated DERs and third, it is largely insensitive to local variations in coverage as they are reproducible (2-FC). Moreover, in contrast to the two-level (DER and not-DER or expressed and not-expressed) and three-level  segmentation models used by other approaches , a procedure so-called double dipping, first for segmentation and then for differential analysis may result in an inflated false positive rate  or the degradation of tRNA 5′ precursor (DER 5 with genomic positions 51889–51991 for trnV)  in the mutant, along with the corresponding intron (DER 3 with genomic positions 51283–51832). The segmentation in three different DERs is, once again, an accurate interpretation of the two different biological mechanisms targeting tRNAs and introns in the mutant (We are therefore confident that the numerous DERs identified outside of the predefined labels in the two chloroplastic RNA-Seq datasets represent e mutant . Neitheror trnV) . Finallye mutant ,62.Bacillus subtilis . Alternative strategies would be to integrate more advanced segmentation methods already available. More specifically, we believe it could be useful to (i) weight the base pair according to its coverage  identifying those genomic portions is a segmentation problem itself, multiplying the genomic areas complexifies selection, and (ii) this leads to a of FPOP, ), (ii) cof FPOP, , and (iiof FPOP, .In conclusion, DiffSegR is a powerful tool that provides researchers with a systematic and accurate way to discover expression differences between two conditions using RNA-Seq data, without the need for prior annotations. Because it is designed to compare two conditions, we believe that DiffSegR has the potential to change the way researchers approach differential expression analysis, especially considering the wealth of RNA-Seq based strategies aimed at capturing specific events . For exalqad098_Supplemental_FilesClick here for additional data file.


Whole-genome resequencing was performed on five Shanghai local pig breeds, aiming to analyze their population’s genetic structure and genomic characteristics. Through selective sweep analysis between the indigenous Shanghai pig breed and commercial pig breed populations, some of the selection genes and their polymorphisms in these two populations were identified and explored.Sus scrofa 11.1. The results of admixture structure analysis also clearly demonstrated the genetic differences between the Shanghai local pig breeds and the three commercial pig breeds . The genetic infiltration of Landrace and Yorkshire pig breeds in the SHW breed was detected, which is consistent with the early history of crossbreeding in this breed. Selective sweep analysis between four indigenous Shanghai pig breed populations and three commercial pig breed populations identified 270 and 224 genes with selective signatures in the commercial and indigenous Shanghai pig populations, respectively. Six genes  were found to be associated with animal growth in the commercial pig population through gene enrichment and protein–protein interaction analysis. In contrast, the MSRB3 gene in the indigenous Shanghai pig population was significantly under selection, which correlated with the long pendulous ear phenotype of the indigenous Shanghai pig population. In conclusion, this study is the first genomic profiling of five representative local pig breeds in Shanghai, which provides molecular genetic data and foundations for better conservation and utilization of local pig breed resources in Shanghai, China.China has rich genetic resources of local pig breeds. In this study, whole-genome resequencing was performed on five Shanghai local pig breeds, aiming to analyze their population genetic structure and unique genomic characteristics. Tens of millions of single nucleotide variants were obtained through the resequencing of a total of 150 individual pigs from five local pig breeds  after mapping them with the pig reference genome of  Phenotype variation and genomic differences between cosmopolitan and indigenous pig breeds are due to natural and artificial directional selection, which shapes the reservoir of animal genetic diversity. Shanghai local pig breeds have a long history of domestication. However, with the urbanization process, only four indigenous breeds have been preserved, and only in a few designated breeding farms. These include the national middle-sized Meishan pig (MMS) breeding farm in Jiading district, the Fengjing pig (FJ) breeding farm in Jinshan district, the Pudong White pig (PD) breeding farm in the new Pudong district, and the Shawutou pig (SW) breeding farm on Chongming Island. In addition to these four indigenous Shanghai pig breeds, there is also a Shanghai White pig (SHW) breed, which was bred by crossing the Shanghai local breed with the Landrace, Yorkshire, and Jiangsu White pig in early years and passed breed validation in 1978, and is currently kept in the breeding farm of the Zhuanghang Experimental Station of Shanghai Academy of Agricultural Sciences .The genetic diversity and unique genomic characteristics of Shanghai local pig breeds are valuable biological heritage, which can be used to discover superior traits of pig breeds as well as to improve genetic breeding. Although indigenous pig breeds are not as good as cosmopolitan breeds and strains used in intensive production systems in terms of growth rate and feed conversion rate, these autochthonous genetic resources have unique advantages in terms of certain traits; for example, Meishan pigs have been widely used for the improvement of many commercial breeds , and itsST), polymorphism level statistic (θπ), extended haplotype homozygosity (EHH) [ST, which was first introduced by Sewall Wright [π) statistic was measured for each individual using nucleotide diversity π [ST and θπ crossover methods helps detect selection features and has been successfully applied to identify genomically selected regions in domestic pigs [The selected region is often a chromosomal region with low genetic diversity within the group and a high genetic differentiation rate between groups. A series of statistical approaches called “classical selective sweeps” have been proposed for the detection of “signatures of selection” ,7, such ty (EHH) , integraty (EHH) , and comty (EHH) . The metl Wright  and devel Wright . The polersity π ,14, usuatic pigs ,16,17.In this study, we performed whole-genome resequencing on the abovementioned five representative local pig breeds. Through genome-wide genetic variation analysis, aimed to explore the genomic characteristics of Shanghai local pig breeds, the genes with selective signatures and the association of related phenotypes are explored through comparative analysis with the cosmopolitan commercial pig population.https://www.ncbi.nlm.nih.gov/ (accessed on 16 December 2022)) were placed together in ® DNA Library Prep Kit for ILM , constructed from resequencing libraries from QC-qualified DNA, proceeding as follows: end repair, A-tailing, ligation to paired aptamers, and PCR amplification with a 300–350 bp insert. After the library construction was completed, Qubit 2.0 was used for preliminary quantification, and qPCR was used to accurately quantify the effective concentration of the library to ensure the quality of the library. Sequencing was performed using the MGI-2000 sequencing platform , and the sequencing mode was PE150 mode.The blood samples collected from designated breeding farms of five local breeds in Shanghai  and whole-genome sequencing (WGS) data from 31 Duroc, 21 Landrace, and 24 Yorkshire pigs downloaded from the NCBI database (Sus scrofa 11.1 using Burrows-Wheeler Aligner (BWA) v0.7.17. [https://asia.ensembl.org/index.html (accessed on 23 January 2023)).The raw reads were filtered using the software fastp  ) [All SNPs located on the autosomes (Chr1-18) of the eight breeds were controlled by a multiple filtering process using Plink v1.9, with parameters such as missing rate (--mind 0.1), minimum allele frequency (--maf 0.05), Hardy–Weinberg equilibrium (--hwe 0.000001), and LD pruning (--indep-pairwise 100 50 0.2) being filtered, and the final retained SNPs were used for the analysis of the population structure. Principal component analysis (PCA) was performed via Plink v1.9 software, in which the principal components were calculated with “--pca” option. The PCA plot demonstrated the first two principal components using the ggplot2 package  in the Re 2023)) .ST and θπ ratios on all autosomes and X chromosomes using a 40 kb sliding window approach with a step size of 20 kb by aligning genomic windows to match the top 5% FST and combining θπ ratios , taking the log2-transformed top 5% percentile at each end of the overlapping windows and using them as candidate selective regions. The candidate genes were subsequently extracted using bcftools v1.10.2 [Based on the results of the genetic structure analysis of the eight breeds mentioned above, we decided to identify some potential selection signals in the polymorphism level of the genomic regions of the Shanghai native pig herd  and the commercial herd . A crossover approach was used to calculate F v1.10.2 . The genhttp://ftp.esembl.org/pub/curent_gtf/sus_scrofa/Sus_scrofa.Sscrofa11.1.106.gtf.gz (accessed on 8 February 2023)). The biological process of Gene Ontology (GO) terms and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the WEB-based Gene Set Analysis Toolkit ) [https://string-db.org/ (accessed on 25 June 2023)) [The candidate genes in these selection regions were identified through assembly (e 2023)) . Next, te 2023)) , which chttp://www.cncb.ac.cn (accessed on 17 October 2023)  [Sus scrofa 11.1 reference genome, resulting in an average depth of 12–15.25 folds  generated a total size of 3.42 Tb clean data, which was deposited in the publicly accessible website: n, CNCB) ,32 with 25 folds . A totalAfter multiple screening of all SNPs on the autosomes (Chr1-18) of the eight pig breeds for missing rate, minimum allele frequency, and linkage disequilibrium (LD) pruning using Plink v1.9, 223 individuals and 569,301 SNPs were retained for population structure analysis. The PCA results showed that three foreign breeds  were clustered together. Three indigenous Shanghai pig breeds  were also clustered together, while the indigenous Pudong White Pig breed (PD) was clustered separately A. The poThe IBS matrix among the individuals also showed results consistent with the above admixture’s inferred results. The three foreign breeds  were relatively close to the SHW breed with relatedly low IBS distance A. On theThe individual SHW pigs were removed in the selection sweep analysis since this breed was bred by crossbreeding Shanghai native pigs with foreign breeds in the early years, and the results of the genetic structure analysis confirmed that some of the individuals in the population had obvious genetic infiltrations of Landrace and Yorkshire; thus, we removed this breed in the analysis of the selection signals.ST) and polymorphism level (θπ). To minimize false-positive candidate regions, regions that reached the top 5% threshold for both methods were selected as candidate regions. The results of the study showed that 542 genomic regions under selection were identified as belonging to the Shanghai indigenous population  by using 40 K length as the genomic sliding window and 20 K as the step. Genome-wide selection signals were investigated by aligning all windows and using two complementary approaches, genetic differentiation , whereas these two loci were pure reference genome genotypes in 76 commercial pig breeds (0/0), and higher polymorphisms existed in four indigenous pig breeds in Shanghai; for example, high polymorphisms in these two loci were found in the SW breed, with 25 out of 31 individual pigs and 19 out of 31 individual pigs, respectively.Enrichment analysis of the gene sets (GO/KEGG) revealed that pathways such as ovarian steroidogenesis and steroid hormone biosyntheses were enriched , and thaAfter analyzing the PPI of 270 selected genes identified in commercial pigs and 224 genes detected in the indigenous Shanghai pig population, a total of 68 PPI subnetworks were obtained for the 270 genes in commercial pigs. One PPI subnetwork of six genes A attractOn the other hand, from the PPI analysis of 224 genes selected from the indigenous Shanghai pig population, a subnetwork of three genes B is noteCHCHD7 on chromosome 4 between the two populations, which revealed that all 27 SNP loci were pure reference genome genotypes in foreign pigs such as Duroc, Landrace, and Yorkshire, whereas significant polymorphisms were demonstrated in four indigenous Shanghai pig breeds such as the Meishan pig, of which about two-thirds were heterozygous 0/1 or pure 1/1 genotypes.Our study further investigated the differences in SNP polymorphisms  in the MSRB3 that has been suggested by several studies to be potentially associated with the trait of long pendulous ears in animals. In contrast, all four indigenous pig breeds in Shanghai have a distinctive long pendulous ear phenotype  of this gene showed a significant decrease in the indigenous Shanghai pig breed population compared to the commercial pig population  identified in this study that are associated with growth or body size of animals [This study revealed the genetic structure of local Shanghai pig breeds, in which four indigenous Shanghai breeds showed significant differences from commercial pig breeds. The SHW population, which was bred through crossbreeding in the 1970s, shows significant gene infiltration from Landrace and Yorkshire genetic backgrounds, which is consistent with the early crossbreeding process. The results of selective sweep analysis of the four indigenous Shanghai breed populations and the cosmopolitan population, respectively, suggested that hundreds of genes under selection, and the linkage between these genes and the phenotypic traits of the animals, are key candidates for research on the molecular genetics of local Shanghai pig breeds. For example, n cattle . The pron cattle . Despite animals ,36,37 arMSRB3, WIF1, and LEMD3, which are located adjacent to each other on the genome. Boyko et al. [MSRB3 was significantly higher in 60-day-old Minzhu pigs than in Large White pigs of the same age, and that individual pigs with higher expression had larger ears. Evidence at the protein level indicated that MSRB3 expression was higher in 60-day-old two-flower-face pigs than in same-day-old Large White pigs. Chen et al. [MSRB3, which was only present in six native Chinese Long Pendulous and Half Pendulous pigs. The experiment also showed that miR-584-5p inhibited the mRNA translation of MSRB3, which led to the enlargement of pig ears.One of the more obvious common features of the appearance phenotype of the four indigenous pig breeds in Shanghai is the possession of a long pendulous large ear phenotype, and the features shown on the genome suggest three related genes including o et al.  conducteo et al.  found thn et al.  identifiMSRB3 were significantly decreased in the four indigenous Shanghai pig breed groups in this study compared with the commercial pig breeds. In contrast, some of the SHW pigs showed similar genotypes to some individuals in commercial pigs, especially Yorkshire pigs, many of which have erect ears. And we also visually inspected part of the SHW population, in which there are some individual pigs with an erect ear phenotype. Therefore, there should be a clear link between MSRB3 and the morphology of pig ears, but the mechanism remains to be further elucidated. On the other hand, although the overall polymorphism of MSRB3 was significantly reduced in the indigenous Shanghai pig population, some of the loci showed high polymorphism on the contrary; for example, the four adjacent intron loci found in this study, which we analyzed were possibly related to the evolution of pig breeds, are also part of the genomic characteristics of the indigenous Shanghai pig breeds, which can possibly be used as genetic markers for breed identification in the future.In this study, the nucleotide polymorphisms of TGS1, PLAG1, CHCHD7, LCORL, TMEM68, and TMEM8B are closely related to animal growth traits and had higher polymorphisms in the indigenous Shanghai pig population However, the MSRB3 gene, which is linked to the long pendulous ear phenotype, showed a significant characterization of reduction in genetic diversity in the indigenous Shanghai pig breeds. Our study provides molecular genetic data and a foundation for better conservation and utilization of local pig breed resources in Shanghai, China.In this study, whole-genome resequencing was performed on five local Shanghai pig breeds, and information on tens of millions of single nucleotide variants on the genomes of these local Shanghai pig breeds was obtained. Selective sweep analysis revealed that selection genes such as


AHL17 or AHL28 greatly enhanced root hair production by increasing the transcription of an array of genes downstream of RHD6. RHD6 is a key transcription factor that regulates root hair development. Mutation of RHD6 completely suppressed the overproduction of root hairs by blocking the transcription of AHL17‐activated genes. The overexpression of AHL17 or AHL28, however, neither affected the transcription of RHD6 nor the accumulation of RHD6 protein. These two AHL proteins also did not directly interact with RHD6. Furthermore, we found that three members of the Heat Shock Protein70 family, which have been annotated as the subunits of the plant Mediator complex, could form a complex with both AHL17 and RHD6. Our research might reveal a previously unrecognized mechanism of how AHL proteins regulate gene transcription.AT‐HOOK MOTIF NUCLEAR LOCALIZED (AHL) proteins occur in all sequenced plant species. They bind to the AT‐rich DNA sequences in chromosomes and regulate gene transcription related to diverse biological processes. However, the molecular mechanism underlying how AHL proteins regulate gene transcription is poorly understood. In this research, we used root hair production as a readout to study the function of two Arabidopsis AHL proteins, AHL17, and its closest homolog AHL28. Overexpression of  When one of the upregulated genes, that is, AHL17 (AT5G49700) was overexpressed in WT plants under a strong constitutive CaMV 35S promoter  exhibited enhanced root hair production, in terms of both root hair length and root hair density  also resulted in an overproduction of root hairs, indicating that the GFP‐AHL17 fusion protein was functional  with rhd6 and generated progeny that were homozygotes for both the 35S::AHL17 transgene and the rhd6 allele (AHL17 OX rhd6 line). These plants showed strong defects in root hair production, which were similar to the defects of rhd6 in terms of both root hair length and root hair density  and FDR  ≤.01 were used as the cut‐off for the selection of the genes whose expression levels significantly differed from those of the WT. In the AHL17 OX line, there were 544 genes whose expression was upregulated and 361 genes whose expression was downregulated compared with the WT  . The potential AT‐hook binding motifs were identified in the promoters of these two genes  using the full‐length recombinant AHL17 and AHL28 proteins produced in E. coli cells. The recombinant AHL17 protein contained an MBP  tag at its N‐terminus and a 6× His tag at its C‐terminus (MBP‐AHL17‐His), whereas the recombinant AHL28 protein only contained an MBP tag at its N‐terminus (MBP‐AHL28). The DNA probes used in EMSA were sequences that displayed high binding affinity to AHL17 in the ChIP assays  or C‐terminal half (cLUC) of the LUC gene and were co‐transformed into the leaves of N. benthamiana with proper controls. The co‐expression of cLUC‐AHL17 and AHL17‐nLUC, cLUC‐AHL28 and AHL17‐nLUC, cLUC‐AHL17 and AHL28‐nLUC, or cLUC‐AHL28 and AHL28‐nLUC all resulted in a strong fluorescence signal from reconstituted LUC activity  technique  assay was performed using total proteins extracted from 7‐day‐old seedlings of on Table . These ron Table . At leason Table . Intereson Table . These pon Table .in planta, we performed LIC assays in the leaves of N. benthamiana. The CDS of AHL17 was fused to the N‐terminal half of LUC (AHL17‐nLUC), and the CDS of HSP70‐1 was fused to the C‐terminal half of LUC (cLUC‐HSP70‐1). The leaves that were co‐transformed with AHL17‐nLUC and cLUC‐HSP70‐1 displayed strong fluorescence, whereas those co‐transformed with AHL17‐nLUC and cLUC‐HSP70‐5 or AHL19‐nLUC and cLUC‐HSP70‐1 displayed no fluorescence, demonstrating that the interaction between AHL17 and HSP70‐1 in vivo was sequence‐specific  and GFP‐tagged AHL17 (AHL17‐GFP). The results showed that the HSP70‐myc protein could be co‐precipitated with AHL17‐GFP by anti‐GFP antibodies  the N‐terminal half, which contained the entire AT‐hook domain and half of the PPC domain; (2) the C‐terminal half, which contained half of the PPC domain; and (3) the middle part, which contained the entire PPC domain. Using LIC assays, we found that the PPC domain but not the AT‐hook domain of AHL17 was required and sufficient for AHL17 to interact with HSP70‐1 and HSP20‐2 Figure .2.9RHD6 could suppress the effects of overexpression of AHL17 on root hair production and gene transcription and because HSP70 proteins interact with AHL17, we wondered whether HSP70 proteins serve as the molecular links that enable AHL17 and RHD6 to form a complex in planta. To test this hypothesis, we first demonstrated the interactions between HSP70‐1 and RHD6 using LIC assays in the leaves of N. benthamiana , and certain gene‐specific transcription factors to form the pre‐initiation complex that initiates transcription  plants used in this study were in the Col‐0 ecotype background. The SALK T‐DNA insertional line of rhd6 (CS877302) was obtained from the Arabidopsis Biological Resource Center (ABRC).All Arabidopsis (2O). After being stratified at 4°C for 2 days, the seeds were sown on Petri plates containing half‐strength Murashige and Skoog (MS) medium with 1% (w/v) sucrose, .1% (w/v) MES, and 1.2% (w/v) agar (Sigma‐Aldrich). The plates with seeds were placed vertically in a growth room with a photoperiod of 16 h of light and 8 h of dark at 22–24°C. The light intensity was 100 μmol m−2 s−1. Nicotiana benthamiana plants were grown in soil under the same lighting conditions.Arabidopsis seeds were surface sterilized in 20% (v/v) bleach for 10 min and were then washed three times with sterile‐distilled water (ddH4.2Images of root hairs on the agar plates were captured with a stereomicroscope (Olympus SZ61) equipped with a digital camera (Olympus DP72) with 1.5× or 4.5× magnification. The lengths of root hairs located 5 to 6 mm from the root tip were measured at 1.5× magnification with the assistance of Digimizer software. For root hair numbers, both mature and immature root hairs including bulges in the region 5 to 6 mm from the root tip were counted. At least 15 seedlings for each genotype were used for root hair measurements.To quantify root hair cells and non‐root hair cells in the root epidermis, two areas along the root of a 7‐day‐old seedling were selected randomly and were examined at 4.5× magnification. For each region, five contiguous cells from an H file and five contiguous cells from a neighboring N file were examined, and the numbers of hair cells and non‐hair cells were recorded.4.3The histological analysis of root hair formation was performed according to Hou et al. . Basical4.435S::AHL17 and 35S::AHL28, the genomic sequences of the corresponding genes were amplified from genomic DNA of WT Arabidopsis plants. The genomic sequence of each gene was cloned into the BamHI and SacI restriction sites between the CaMV 35S promoter and the NOS terminator of the plant expression vector pZH01.To generate plant overexpressing vectors of AHL17 and AHL28 were also generated in the WT using a CRISPR/Cas9‐based genome editing system developed by Xing et al. . The RNA‐seq analyses were performed at Bionova Company. The RNA‐seq libraries were constructed through adaptor ligation and were subjected to single‐ended sequencing with a 50‐nucleotide reading length. FastQC software was used to assess the quality of raw sequencing reads. The adaptor and the low‐quality reads were removed before data analysis. The remaining reads were aligned to the Arabidopsis TAIR 10.0 reference genome using TopHat2. After the sequences of rRNA or tRNA were removed, the TopHat read alignments were assembled by Cufflinks software to produce a transcriptome annotation of the genome. The expression levels for all transcripts were normalized to per million mapped reads. The differentially expressed genes were identified using DESeq2  were observed with a confocal microscope (Zeiss LSM710META or Leica STED). The wavelengths of excitation/emission were 488 nm/491–535 nm for GFP and 514 nm/520–550 nm for YFP proteins. The captured fluorescence images were processed and analyzed with Zen Black, Zen Blue software, or LAS X.4.9NotI and SalI restriction sites at the N terminus of an MBP tag to generate MBP‐AHL28 recombinant protein. For better purification, the full‐length CDSs of AHL17 were cloned into vector pMAL‐c5x (NEB) with a 6x His tag sequence in its C terminus, thus generating MBP‐AHL17‐His. These constructs were separately transformed into E. coli strain Rosseta. The MBP‐AHL28 was purified using Amylose Resin gravity flow columns (NEB), whereas the MBP‐AHL17‐His was purified using Ni‐NTA agarose columns (QIAGEN).The full‐length CDSs of AHL28 were cloned into vector pMAL‐c5x (NEB) using The FAM‐labeled hot probes containing the putative AT‐hook binding motifs and its cold probes were generated by annealing the FAM‐labeled complementary oligonucleotides. The sequences of the oligonucleotides used for generating various probes are listed in Table 4.10GFP‐AHL17. The isolated chromatins were cross‐linked with 1% formaldehyde, sonicated, and precipitated by Anti‐GFP Magarose Beads (Smart Lifesciences). The precipitated DNA fragments were released by 200‐mM NaCl and subjected to qPCR analysis.ChIP‐qPCR assays were performed essentially as described by Saleh et al. . Briefly4.11AHL17, AHL28, AHL19, RHD6, HSP70‐1, HSP70‐2, HSP70‐4, and HSP70‐5 genes were amplified by PCR from plant cDNAs and were individually inserted into the vectors of pCAMBIA‐nLUC and pCAMBIA‐cLUC . Western blots were performed according to Song et al.  through Xbal and BamHI restriction sites to generate 35S::HSP70‐1‐myc and 35S::HSP70‐2‐myc constructs. Agrobacterium strains carrying 35S::AHL17‐GFP and 35S::HSP70‐1‐myc or 35S::HSP70‐2‐myc, as well as 35S::RHD6‐GFP and 35S::HSP70‐1‐myc or 35S::HSP70‐2‐myc, were co‐infiltrated into the leaves of N. benthamiana. The infiltrated leaves with empty GFP construct were used as a negative control. Two days after infiltration, the infiltrated leaves were harvested, ground in liquid nitrogen, and suspended in an ice‐cold protein extraction buffer to extract the total proteins. Anti‐GFP Magarose Beads (Smart Lifesciences) were then added to the extracts, which were incubated at 4°C for 1 h with gentle shaking. The precipitated proteins were washed at least six times using ice‐cold protein extraction buffer, and bound proteins were eluted by heating the beads in SDS protein loading buffer at 95°C for 10 min. The precipitated AHL17 and RHD6 proteins were detected by Western blotting using anti‐GFP antibody (Abmart), whereas the HSP70‐1 and HSP70‐2 proteins were detected by Western blotting using anti‐myc antibody (Abmart).For testing the interaction between AHL17 and HSP70‐1/2 as well as the interaction between RHD6 and HSP70‐1/2, the full‐length CDSs of 35S::RHD6‐GFP, 35S::HSP70‐1‐myc, and 35S::AHL17‐FLAG (the CDS of AHL17 was amplified from cDNA and inserted into modified PS1300).Co‐IP assays for testing the association of AHL17, HSP70‐1, and RHD6 were similar except that the protein extracts contained three co‐transformation proteins, including 4.1435S::GFP‐AHL17 plants and were precipitated using anti‐GFP antibody (Abmart) before analysis as mentioned earlier. The IP‐MS analysis of the precipitated proteins was performed at the Center of Biomedical Analysis of Tsinghua University. WT plants were used as a negative control.For IP‐MS experiments, proteins were extracted from roots of 7‐day‐old seedlings of Qike Zeng, Li Song, and Dong Liu designed the research. Qike Zeng, Li Song, Mingzhe Xia, Zai Zheng, Ziang Chen, and Ximing Che performed the experiments. Qike Zeng, Li Song, Mingzhe Xia, Ziang Chen, and Dong Liu analyzed the data. Qike Zeng and Dong Liu wrote the manuscript.The authors declare no conflict of interest.Fig. S1. Overexpression of AHL17 and AHL28 in transgenic plants.(A) Phylogenetic tree of the Arabidopsis AHL family.(B) Relative expression of AHL17 and AHL28 in the root of 7‐day‐old WT, 35S::AHL17 and 35S::AHL28 seedlings as determined by qPCR. Values are means ± SD of three technical replications in one experiment. The experiment was repeated three times with similar results. Asterisks indicate a significant difference from the WT .Figure S2. Comparison of the seedling morphologies and root epidermal cells between the WT and AHL17‐ and AHL28‐overexpressing lines.35S::AHL17, and 35S::AHL28 lines. (B) Length of root epidermal cells of 7‐d‐old seedlings of the WT, 35S::AHL17, and 35S::AHL28 lines. Values are means ± SD of 15 root epidermal cells for each line. Student t‐test was used to analyze the difference between the WT and each overexpressing line and no significance was found (P < .01).(A) Morphologies of 7‐d‐old seedlings of the WT, Figure S3. Root hair phenotypes of AHL17 and AHL28 mutants.AHL17 and AHL28 gene sequences generated by CRISPR/Cas9 editing technology and resultant changes in their encoded proteins. Red arrows indicate the editing sites where the sequences between them are deleted. The red box indicates a premature stop codon introduced into the AHL28 gene.(A) and (B) The altered ahl17, ahl28, and ahl17ahl28 grown under normal growth condition (1/2 MS), phosphate deficiency (‐Pi) and presence of .1 μM ACC and .5 μM ACC.(C) Root hair phenotypes of 7‐d‐old seedlings of the WT, Figure S4. Root hair phenotypes of 35S::GFP‐AHL17 transgenic lines. (A) Relative expression of the AHL17 gene in the roots of 7‐d‐old seedlings of the WT and three independent 35S::GFP‐AHL17 lines. Values are means ± SD of three technical replications in one experiment. The experiment was repeated three times with similar results. Asterisks indicate a significant difference from the WT . (B) Root hair phenotypes of 7‐d‐old seedlings of the WT and three independent 35S::GFP‐AHL17 lines. (C) Confocal microscopy images of the roots of 7‐d‐old 35S::GFP‐AHL17 seedlings. The GFP signals indicated that the GFP‐AHL17 fusion proteins are localized in the nucleus.Figure S5. Effects of ACC treatment on gene transcription and protein accumulation of AHL17.AHL17 in 7‐day‐old seedlings of the WT grown on medium in absence (−) or presence (+) of 5 μM ACC as determined by RT‐qPCR. Values are means ± SD of three biological replications. The expression of AHL17 in the seedlings grown on medium without ACC was set to 1.0. Asterisks indicate a significant difference from the WT . (B) Histochemical staining of 7‐day‐old AHL17::GUS seedlings grown in the absence or presence of ACC. (C) Quantification of GFP fluorescence signals in seedlings shown in (D). Values are means ± SD of 15 roots of ACC‐treated or non‐treated seedlings, respectively. Asterisks indicate a significant difference from the WT . (D) Confocal microscopy images showing the accumulation of GFP‐AHL17 proteins in 7‐d‐old seedlings in absence or presence of 5 μM ACC.(A) Relative expression of Figure S6. AHL28 binds to the promoters of the COW1 and PRP3 genes.COW1 and PRP3 genes. The experiment was performed using 1.5 μg MBP‐AHL28 and 3 μg MBP proteins. The working concentration FAM‐labeled probe was 1 μM. Different amounts of excess unlabeled probe (cold probe) were added as competitors.EMSAs showing the binding of AHL28 to the putative AT‐hook binding elements in the promoters of the Figure S7. Accumulation of RHD6‐GFP fusion proteins in the WT, 35S::AHL17, and 35S::AHL28 transgenic plants.1 progeny derived from the cross between RHD6::RHD6‐GFP and WT, 35S::AHL17, or 35S::AHL28 lines. (B) Western blot analysis of RHD6 protein accumulation in the roots of F1 plants derived from cross between RHD6::RHD6‐GFP and WT, 35S::AHL17, or 35S::AHL28 lines. The total proteins were extracted from roots of 7‐d‐old seedlings and RHD6‐GFP were detected by Western blot analysis with anti‐GFP antibody. Actin was used as a loading control.(A) Confocal microscopy images of the root tips of 7‐day‐old seedlings of FFigure S8. Interaction between AHL17/AHL28 and major root transcription factors involved in root hair development.N. benthamiana. LUC activity was detected 2 d after infiltration to determine the interaction between various transcription factors with AHL17 (A) or AHL28 (B). The co‐transformation of AHL17‐nLUC and cLUC‐AHL28, cLUC‐AHL17 and AHL28‐nLUC, AHL17‐nLUC and cLUC‐AHL17, or AHL28‐nLUC and cLUC‐AHL28 was used as a positive control. (C) BiFC assays. A pair of constructs of various combinations were co‐transformed into the leaves of N. benthamiana. Yellow fluorescence signals were detected 2 d after infiltration to determine the interaction between AHL17 and AHL28 with RHD6 and RSL1, respectively. The co‐transformation of cYFP‐AHL17 and AHL28‐nYFP or cYFP‐AHL28 and AHL17‐nYFP was used as the positive control.(A) and (B) LIC assays. A pair of constructs with various combinations (indicated in the diagrams on right) were co‐transformed into the leaves of Figure S9. Interaction between AHL17/AHL28 and three HSP70 proteins.Nicotiana benthamiana to examine the interactions between AHL17 with three HSP70 proteins. Luciferase activity was detected 2 d after infiltration. (A) and (B) Interactions between AHL17 and HSP70–2 and HSP70–4. (C) Relative strength of the interactions between AHL17 with HSP70–1, HSP70–2, HSP70–4, and HSP70–5. (D) to (G) LCI assays. The interactions between AHL28 and HSP70–2 (D), AHL28 and HSP70–4 (E). (F) Comparison of the relative strength of the interactions between AHL28 with HSP70–1, HSP70–2, HSP70–4, and HSP70–5. (G) Specific interactions between AHL28 and HSP70–1. (H) Specific interactions between AHL17 and HSP70–2, between AHL28 and HSP70–1, and between AHL28 and HSP70–2 as indicated by BiFC assays in N. benthamiana.(A) to (C) LIC assays. A pair of constructs with various combinations (indicated in the diagrams on right) were co‐infiltrated into the leaves of Figure S10. The protein domain of AHL17 involved in the interactions between AHL17 and HSP70–1 and HSP70–2.N. benthamiana. Yellow fluorescence signals were detected 2 d after infiltration to determine the interaction between different parts of AHL17 and HSP70–1 and HSP70–2, respectively. The co‐transformation of LUC‐nYFP with cYFP‐AHL17 was used as the negative control.(A) Diagrams showing different parts of AHL17 that were used in BiFC assays. (B) BiFC assays. A pair of constructs of various combinations (as indicated on the left and top of the panel) were co‐transformed into the leaves of Figure S11. Interactions between AHL17/AHL28 and AHL19.Nicotiana benthamiana to examine the interactions between AHL17/AHL28 and AHL19. Luciferase activity was detected 2 d after infiltration. The co‐infiltration of the constructs of AHL17‐nLUC and AHL28‐cLUC was used as a positive control and co‐infiltration of the constructs nLUC and cLUC was used as a negative control.LCI assays were used to test the interaction between AHL17/AHL28 and AHL19. The CDS of AHL17 and AHL28 were fused to the N‐terminal half (nLUC) of the LUC gene and the CDS of AHL19 was fused with the C‐terminal half (cLUC) of the LUC gene. A pair of constructs with various combinations (indicated in the diagrams on right) were co‐infiltrated into the leaves of Click here for additional data file.Table S1. Specification of cell types in root epidermis of various genotypes.Click here for additional data file.Table S2. RNA‐seq results of AHL17 OX, rhd6, and AHL17 OX rhd6 vs the WT (Col‐0), respectively.Click here for additional data file.Table S3. Go term analyses of the differentially expressed genes in AHL17 OX (35S::AHL17–3), rhd6, and AHL17 OX rhd6 lines vs the WT.Click here for additional data file.Table S4. The genes whose expression is up‐regulated in AHL17 OX but down‐regulated in rhd6 and AHL17 OX rhd6.Click here for additional data file.Table S5. Putative AT‐hook binding motifs in the promotes of the COW1 and PRP3 genes analyzed by ChIP‐qPCR.Click here for additional data file.Table S6. Mass spectroscopy analysis of immunoprecipitated proteins.Click here for additional data file.Table S7. Sequences of the primers used in different experiments.Click here for additional data file.


RNA-binding proteins (RBPs) are essential for regulating RNA metabolism, stability, and translation within cells. Recent studies have shown that RBPs are not restricted to intracellular functions and can be found in extracellular vesicles (EVs) in different mammalian cells. EVs released by fungi contain a variety of proteins involved in RNA metabolism. These include RNA helicases, which play essential roles in RNA synthesis, folding, and degradation. Aminoacyl-tRNA synthetases, responsible for acetylating tRNA molecules, are also enriched in EVs, suggesting a possible link between these enzymes and tRNA fragments detected in EVs. Proteins with canonical RNA-binding domains interact with proteins and RNA, such as the RNA Recognition Motif (RRM), Zinc finger, and hnRNP K-homology (KH) domains. Polyadenylate-binding protein (PABP) plays a critical role in the regulation of gene expression by binding the poly(A) tail of messenger RNA (mRNA) and facilitating its translation, stability, and localization, making it a key factor in post-transcriptional control of gene expression. The presence of proteins related to the RNA life cycle in EVs from different fungal species suggests a conserved mechanism of EV cargo packing. Various models have been proposed for selecting RNA molecules for release into EVs. Still, the actual loading processes are unknown, and further molecular characterization of these proteins may provide insight into the mechanism of RNA sorting into EVs. This work reviews the current knowledge of RBPs and proteins related to RNA metabolism in EVs derived from distinct fungi species, and presents an analysis of proteomic datasets through GO term and orthology analysis, Our investigation identified orthologous proteins in fungal EVs on different fungal species. Cell-to-cell communication involves distinct pathways, such as direct contact, secretion of diverse molecules, and the transfer of information through extracellular vesicles (EVs) . EVs areThe main functions of EVs related to cellular communication include the transfer of molecules, changing gene expression patterns, and surface rearrangements . In addiA remarkably diverse array of proteins has been identified in the EVs of different fungal species. For example, the most abundant proteins identified in four fungi species are the elongation factor 1 alpha, nuclear proteins such as Histone H4.2, and other proteins related to stress response, carbohydrate, lipid, and protein metabolism . The mosEVs containing RNA molecules were first described in murine and human cells in 2007 raising the assumption that these structures participate in cell-to-cell communication and modulate protein expression in recipient cells .Cryptococcus neoformans, Candida albicans, Paracoccidiodes brasiliensis, Saccharomyces cerevisiae, Malassezia sympodialis, and Histoplasma capsulatum  are essential in cellular processes involved in RNA metabolism, from transcription to decay. During transcription, RBPs associate with RNA to protect it from degradation and regulate its fate in the cell. RNA processing, including splicing, alternative splicing, and trans-splicing, relies on the proper recognition and exposure of RNA sequences to the splicing machinery . After pThe arrangement and assembly of RBPs in mRNP complexes are highly dynamic . Differehttp://microvesicles.org];  by assembling with snRNAs during nuclear mRNA splicing, the process of removing introns from pre-mRNA. Various complexes can be formed depending on the protein family bound to the snRNA molecules . As snRNTranslation initiation factors are a group of proteins crucial for initiating protein synthesis. EVs derived from human and mouse cells also contain translation initiation factors, such as eIF4E and eIF4G, and some are used as biomarkers for certain cancer types . We alsoAnother group of proteins related to translation identified in the EVs are elongation factors 1 (EF1) and 2 (EF2). They are vital proteins involved in the elongation phase of translation. EF2 is a very abundant protein in the cell and is also the top protein identified in EVs derived from proteomic studies in distinct species .Helicases are another class of proteins involved in RNA metabolism . The DEARNA-binding proteins are essential in most, if not all, stages of the RNA life cycle. Distinct structural features and RNA-binding mechanisms characterize several types of RNA-binding domains. The RRM domain is the most common RNA binding domain, with each domain being specific for RNA sequences and interacting with single-stranded RNA molecules. Proteins with RRM domains are involved in all steps of RNA metabolism. Many fungal species have RNA-binding proteins with RRM domains enclosed in EVs, as listed in Zinc finger proteins constitute a large family of proteins primarily associated with DNA binding but also capable of binding to RNA and small molecules, such as the CCCH zinc finger proteins involved in regulating RNA metabolism. Proteomics data in The hnRNP K-homology (KH) domain is one of the most prevalent RNA binding domains and is found in proteins responsible for regulating gene expression in prokaryotes and eukaryotes. In addition, this domain binds specific sequences on nucleic acids Table 4.To determine the RNA pathways enriched in fungal EVs and to compare them among the species, we performed a gene ontology (GO) term analysis with each proteomic dataset Figure 2C. albicans, H. capsulatum, C. neoformans, C. deuterogattii, P. brasiliensis, and A. fumigatus, with at least 84% similarity among them; the ATP-dependent RNA helicase eIF4A/Helicase FAL1 with eight orthologs in H. capsulatum, C. neoformans, C. deuterogattii, C. albicans, and A. fumigatus, with at least 68% similarity; and Elongation Factor 2 with seven orthologs in C. albicans, A. fumigatus, C. neoformans, C. deuterogattii, H. capsulatum, and P. brasiliensis, with at least 75% similarity among the proteins. The top clusters are listed in Next, we conducted a comparative analysis of the proteins present in the EVs of various fungal species, aiming to identify orthologs. Through this analysis, we observed the formation of forty-nine protein clusters, each comprising at least three species Figure 3The relevant finding is that many proteins participating in different steps of RNA metabolism were conserved among other fungal species, such as eukaryotic translation initiation factors, helicases, elongation factors, and tRNA synthetases. Among the proteins containing known RNA binding domains, we observed the Polyadenylate-binding protein (PAB1), RRM-containing protein, KH domain RNA-binding protein, and nuclear and cytoplasmic polyadenylated RNA-binding protein (pub1).These observations reinforce the hypothesis that RBPs, or even mRNPs, drive the selection and direction of RNA to the EVs, as many of them are conserved in phylogenetically distant fungal species. A summary of the RNA life cycle, the main proteins identified in the EVs, and the connection between the RNA metabolism and extracellular vesicles is depicted in The biogenesis of EVs is complex and involves distinct pathways. Exosomes are produced in endosomes and later secreted upon fusion with the cell surface, while microvesicles are formed by outward budding from the plasma membrane . In bothHowever, this literature primarily focuses on mammalian EVs, and our knowledge of RNA associations with fungal EVs is limited. Our orthology analysis reveals that conserved proteins participate in RNA metabolism among different fungi species. For example, two of the proteins with the highest number of orthologous matches among the top 100 most identified proteins are the eukaryotic translation elongation factor 1 alpha 1 (EEF1A1) and elongation factor 2. The presence of full-length mRNA transcript on exosomes-like vesicles of Toxoplasma-infected cells has been observed, and among the most highly represented mRNA was the EEF1A1 . This prAmong the proteins found in our analysis, there were many ribosomal proteins, which are a variety of proteins that compose the ribosome and participate in the folding of rRNA molecules into a structure that is required for the interaction of mRNA codons and tRNA anticodons . We exclArabidopsis, among other RNA-binding proteins contributing to the sRNA loading into EVs  below 5%.The GO term analysis was carried out in the database: FungiFun v. 2.2.8, available at: We used the CD-HIT v.4.8.1 software tool to cluster protein sequences from our dataset . The inpThe datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/MD performed the database search and analysis and wrote the manuscript. WKO performed the ortholog analysis. LA performed the analysis and helped to write the manuscript. MR and SG discussed all the results and contributed to writing the manuscript. All authors contributed to the article and approved the submitted version.


Lying flatism, a new emerging lifestyle by refusing to participate in consumerist lifestyles, is anticipated to be related to singlehood. Based on the Theory of Reasoned Action, we proposed a mediation model to examine the indirect relationship between feelings towards lying flatism and attitudes toward singlehood via individuals’ belief in that happiness can be achieved without romantic relationships (happiness belief).Using purposive and snowball sampling methods, 232 single Malaysian young adults participated in an online experiment consisting of a writing task (to manipulate feelings toward lying flatism), single-item measures of manipulation checking and happiness belief, Attitudes toward Singlehood Scale, Negative Stereotyping of Single Persons Scale (a measure of singlism) and Fear of Being Single Scale.T-Test results support the writing task that successfully induced positive feelings toward lying flatism. Mediation analysis showed that the feelings toward lying flatism measured before the writing task, but not the manipulation of lying flatism, has an indirect relationship with attitudes toward singlehood via happiness belief, after controlling for gender, singlism, and fear of being single.The findings offer preliminary support to the hypothetical relationships among feelings towards lying flatism, happiness belief, and attitudes toward singlehood. Implications of the findings are discussed. Marriage is no longer perceived as a universal life goal –3 since A similar trend has also been documented in China. Young advocators of lying flatism  portray a blameless and silent protest against the unfairness of society whereby personal efforts can no longer be effective to alter the industrial and structural factors . These yThe hypothetical mediation model is congruent with the Theory of Reasoned Action (TRA) , 13. AccIn the remaining sections, we first reviewed the concept of lying flatism, attitudes toward singlehood, and their relationship. Then, we reviewed happiness belief and its relationship with feelings toward lying flatism and attitudes toward singlehood respectively and provided an overview of the present study. Finally, we presented the methodology of the study and analysis results and discussed the findings and their implications.Lying flatism is a trending philosophy introduced in an April 2022 online post named “Lying down flat signifies justice (躺平即是正义)” on Baidu Tieba, a mainland China forum , 16. ResThe emergence of the lying flatism can attribute to two reasons. First, lying flatism is attributed to the severe working overtime culture in the China Industry . For insSinglehood refers to a state of being unmarried or not involved in a romantic relationship , 25 and A romantic relationship is the most crucial relationship among most adults . IndividHowever, it has been found that staying single can be beneficial to individuals’ well-being , 37. IndMeanwhile, the inconsistent findings of the relationship between singlehood and well-being could be due to people’s choice to stay single . Involuntary singlehood refers to people experiencing difficulties in attracting a partner due to poor qualities , while vIt is assumed that lying flatism has a positive relationship with attitudes toward singlehood. According to News qq , more anAs reviewed, lying flatism is assumed to have a positive relationship with attitudes toward singlehood. However, it is believed that there is an indirect relationship between the two constructs. In this section, we reviewed the theoretical and empirical rationales for the hypothetical mediating role of happiness belief in the association between feelings toward lying flatism and attitudes toward singlehood.There are three reasons to assume a positive relationship between lying flatism and the belief that happiness can be achieved without a romantic relationship. First, individuals who follow the lying flatism perspective prefer lives with minimum spending . To achiSecond, staying single leads lying flatists to experience happiness by having a sense of control. In certain societies such as China and Malaysia, success in life is defined as getting married and having children , 52, whiTaken together, individuals who have positive feelings toward lying flatism are likely to believe that their happiness can be achieved without engaging in a romantic relationship as they can reserve resources, have higher control, and reduce stress when staying single.Literature e.g., , 60) has has60]) Taken together, people who have supportive social networks and enjoy the benefits of singlehood are likely to believe that well-being can be achieved without romantic relationships and hence, they tend to have positive attitudes toward singlehood .Both lying flatism and voluntary singlehood are new and rising trends in the young generation. The present study aimed to expand our understanding of these individual choices by examining whether and how feelings toward lying flatism are related to attitudes toward singlehood. To our best knowledge, measurement of the state-like lying flatism is not available. Hence, we manipulated people’s feelings toward lying flatism using a writing task to understand if having a positive  view of lying flatism influences one’s happiness belief and attitudes toward singlehood. In addition, we focused on young adults in Malaysia because the proportion of singles has been increasing gradually in Malaysia over the years .The present study adopted a part of the TRA to explain the relationships among feelings toward lying flatism, happiness belief, and attitudes toward singlehood. Specifically, it is hypothesized that (1) feelings towards lying flatism have a positive relationship with happiness belief, (2) feelings toward lying flatism have a positive relationship with attitudes toward singlehood, (3) happiness belief is positively associated with attitudes toward singlehood, (4) happiness belief mediates the relationship between feelings toward lying flatism and attitudes toward singlehood. In addition, we statistically controlled for three variables  to get rid of their confounding effects on the relationships among the three target variables.The present study is expected to shed light on the inquiry of whether and how lying flatism plays a role in shaping people’s positive attitudes toward singlehood. The findings will not only broaden our understanding of lying flatism but may also offer insights into the negative impact of lying flatism on the birth rate.The present study adopts a quantitative cross-sectional research design. According to Xin , lying fAccording to the Monte Carlo Power Analysis for Indirect Effects , a minimM = 21.37, SD = 1.332). In terms of ethnicity, the majority were Chinese (86.6%), followed by Indians (6.9%), Malays (5.6%), and other ethnic groups (0.9%). Most of the participants never engaged in a romantic relationship (62.5%). All the participants were currently single (not in a romantic relationship) with the highest singlehood duration being less than 3 months (53.4%). In terms of working status, the majority of the participants were currently studying (88.4%), 19 participants (8.2%) were currently employed, three participants (1.3%) were undergoing internship, working as a freelancer, and waiting for a job offer, four participants were looking for a job (1.7%), and one missing value.The sample consisted of 139 females (59.9%) and 93 males (40.1%) with ages ranging from 18 to 24  Practising lying flatism allows individuals to stay away from stressful circumstances; (2) Lying flatism allows us to live in the current movement and focus on our states of feelings; (3) Practising lying flatism can avoid pressure and expectations of family, friends, and society, were provided to help participants to understand the writing task.To induce positive feelings toward lying flatism, participants in the experimental group were instructed to write an essay to indicate their support of lying flatism. Three sample statements regarding lying flatism: (1) How is the weather today? Was it the same as yesterday’s? (2) In which month has the most comfortable weather occurred in your hometown? (3) Share with us any interesting myths about the weather.On the other hand, participants in the control group were assigned to write an essay on a neutral topic “weather”. Similarly, they were provided with three questions as references to write about the topic. The questions and statements provided were To what extent are you feeling positive toward lying flatism?”) was created to examine the effectiveness of the writing task in manipulating an individual’s feelings toward lying flatism. All participants answered twice on the single item using a 5-point Likert point from 1 (very negative) to 5 (very positive): before the commencement of the writing task  and right after the completion of the writing task . Individuals who score high tend to have positive feelings toward lying flatism. Moreover, the manipulation is considered effective if the post-manipulation measured score is higher than the pre-manipulation measured score and if the difference is statistically significant.A single-item self-report (“(strongly disagree) to 7 (strongly agree). The higher the score, the stronger the belief that happiness can be achieved without a romantic relationship.We adapted and integrated the measures of the belief that happiness can be achieved without marriage for men and women  into a sI feel happy when I am single , I stay single to have more personal space , and Engaging in a romantic relationship is not important . Participants used a 7-point Likert point  to indicate the extent to which they agreed with the items. A higher (average) score indicates higher participants’ positive attitudes toward singlehood, and vice versa. The AtSS showed excellent reliability in the present study with Cronbach alpha (α) = 0.91, McDonald omega (ω) = 0.91, and good validity for Malaysian young adults . The experimental group  reported a higher score than their counterparts in the control group .The second t-Test compared the feelings toward lying flatism score measured after the writing task. Levene’s test was not significant, t(115) = 4.79, p < .001, d = 0.45 95% CI . Specifically, after completing the essay writing task, participants reported a higher score  than their baseline score . The consistent results indicate that the manipulation is effective.We also conducted a paired sample t-Test to further examine the effectiveness of the essay writing task by comparing the pre- and post-measured feelings toward lying flatism of the experimental group. Results showed a significant difference: The writing task successfully manipulated participants’ feelings toward lying flatism. Drawing from the Theory of Reasoned Action, the induced feeling is hypothesized to have an indirect impact on attitudes toward singlehood via happiness belief. Before testing the hypothetical mediation model, we examined the descriptive statistics and correlations for the target variables  did not correlate with any of the variables. Happiness belief, on the other hand, had a positive relationship with gender  and attitudes toward singlehood besides a negative relationship with singlism and fear of being single. Finally, attitudes toward singlehood were positively associated with gender and negatively associated with singlism and fear of being single.Next, we examined the proposed mediation model with the group condition  as the predictor variable, happiness belief as the mediator, and attitudes toward singlehood as the outcome variable. We included gender, singlism, and fear of being single as covariate variables because the three variables were correlated with happiness belief and attitudes toward singlehood respectively.B = 0.39, p < .001), on the other hand, was positively correlated with attitudes toward singlehood. Finally, the mediating effect of happiness belief was not significant.Table r = .281, p < .001) and attitudes toward singlehood , but did not have a relationship with singlism and fear of being single, respectively.The mediation analysis showed that happiness belief does not mediate the effect of lying flatism manipulation on attitudes toward singlehood. It was also found that the manipulation of feelings toward lying flatism did not influence happiness belief and attitudes toward singlehood respectively. One possibility is that the effect of the manipulation task is too small, and our sample size is insufficient to detect its impact. To clarify the relationships between the three variables, we conducted another mediation analysis with the feelings toward lying flatism measured before the writing manipulation task, which represents the participants’ initial feelings toward lying flatism, as the predictor. Before that, we conducted a Pearson correlation analysis to understand if the pre-measured feelings toward lying flatism are associated with the target and controlled variables. Results showed that the pre-measured feelings toward lying flatism had a positive relationship with happiness belief  and attitudes toward singlehood in the total effect model  and direct effect model . Likewise, there was a positive relationship between happiness belief and attitudes toward singlehood . Finally, the mediating effect of happiness belief was found significant: B = 0.13, SE = 0.04, 95% CI .Table Singlehood is a favorable lifestyle in both Western and Asia regions , 50. TheIn contrast to our hypothesis, happiness belief did not mediate the impact of feelings toward lying flatism on attitudes toward singlehood. Inspection of the results found that the manipulation of feelings toward lying flatism did not have any impacts on happiness belief and attitudes toward singlehood respectively. As mentioned above, the results could be attributed to three reasons: (a) the manipulation task is not effective, (b) feelings toward lying flatism do not have a relationship with the two constructs, and (c) the induced effect is too small, and the sample size of the current study is insufficient to detect the effect. Among them, the third reason seems more plausible. This is because our manipulation checking indicates that the participants in the experimental group reported a higher score in feelings toward lying flatism than their counterparts in the control group. Furthermore, the exploratory mediation analysis showed that the pre-measured feelings toward lying flatism are positively associated with both happiness belief and attitudes toward singlehood. Taken together, the results imply that the writing task is effective to manipulate an individual’s feelings toward lying flatism but the induced effect is insufficient to influence happiness belief and attitudes toward singlehood. Future studies, therefore, are suggested to replicate the present study with a larger sample size or another manipulation task.The (main) mediation analysis also showed a positive relationship between happiness belief and attitudes toward singlehood. It indicates that individuals who believe that romantic relationships are not the only way to achieve happiness are more likely to perceive staying single as advantageous. The finding is in line with the findings that single people can still achieve happiness by developing their sense of belonging and maintaining low levels of loneliness. As a result, they are likely to perceive singlehood positively , 25. LikIt is intriguing to note that the exploratory analysis (with the feelings toward lying flatism measured before the manipulation task as the predictor) supports the hypothesized mediation model. The findings offer additional insights though they shall be interpreted with caution. First, the positive relationship between the initial feelings toward lying flatism and attitudes toward singlehood indicates that individuals who have positive feelings toward lying flatism are more likely to perceive singlehood as desirable. The result is line with the lying-flat view of a romantic relationship (躺平式恋爱观) whereby individuals who have positive feelings toward lying flatism do not believe in romantic relationships as staying single can be less troublesome  than engaging in romantic relationships or marriage . SimilarThe present study offers suggestions for the theoretical development of singlehood. First, we demonstrate that the initially measured, but not the manipulated, feelings toward lying flatism, are positively associated with attitudes toward singlehood and happiness belief plays a mediating role in this relationship. Although these exploratory results shall be interpreted with care, the findings reveal a possible direction for future researchers to unveil the underlying process of lying flatism and attitudes toward singlehood. Moreover, the present study lends further support to the Theory of Reasoned Action and extends it to the context of singlehood.The present study also has some remarkable practical implications. First, the present study successfully manipulated participants’ feelings toward lying flatism using a writing task. The finding not only highlights the effectiveness of writing tasks in influencing people’s feelings but also offers a new methodological direction for future studies on lying flatism. Furthermore, to our best knowledge, our study is the first to examine the roles of feelings toward lying flatism and happiness belief in one’s attitudes toward singlehood. The findings not only reveal new antecedent factors of attitudes toward singlehood on top of the literature , but alOur findings also lend support to the Theory of Reasoned Action (TRA) by confirming the role of background factors and behavioral beliefs in shaping one’s attitudes toward a behavior. Furthermore, we elucidate the applicability of the theory in the context of singlehood, indicating its potential for understanding the behavior of individuals who choose to remain single.Several limitations of the present study deserve our attention. First, as participants provided personal information  for verification purposes, the present study is no longer anonymous. Participants might provide answers that seem desirable to avoid judgment due to the social desirability effect . Second,Apart from that, the present study only focused on single individuals who were currently not in a romantic relationship regardless of their voluntary or involuntary singlehood status. The findings, therefore, are unable to be generalized to people in another relationship status . With this, we are also unable to examine if there is a difference in attitudes toward singlehood when individuals from the other relationship status group are having positive feelings toward lying flatism, and if the mediating role of happiness belief still holds among people other than single individuals. Finally, feelings toward lying flatism and happiness belief were measured by a single item, which may be seen as questionable or unreliable .To address the above-mentioned limitations, future studies are recommended to use longitudinal design and procedures that can ensure anonymity. The former can furnish a clear picture of the causal relationship between the variables, while the latter can offer a sense of safety for participants to reveal their truthful responses. Moreover, future researchers are also recommended to expand the inclusion criteria to incorporate individuals other than those who are currently single and to replicate the study in other cultural contexts for examining the effectiveness of the writing task in inducing feelings towards lying flatism, as well as the mediating effect of happiness belief in the relationship between feelings toward lying flatism and attitudes toward singlehood. In terms of measurement, future researchers are urged to either develop and employ multi-item measurements or use different approaches  to capture participants’ feelings toward lying flatism and happiness belief levels in verifying the findings of the present study. In particular, a more comprehensive measurement of happiness belief is urgently needed to address this issue and to clarify the conceptual differences between happiness belief and attitudes toward singlehood. Finally, researchers are also recommended to use double randomization designs  (see 7272 for exLying flatism is a new lifestyle embraced by young people to cope with the over-competition of limited resources in society . The pre


Background: Immune checkpoint inhibitors (ICIs) have become the standard treatment for advanced non-small cell lung cancer (NSCLC). ICIs can provide durable responses and prolong survival for some patients. With the increasing routine of next-generation sequencing (NGS) in clinical practice, it is essential to integrate prognostic factors to establish novel nomograms to improve clinical prediction ability in NSCLC with ICIs treatment.Methods: Clinical information, response data, and genome data of advanced NSCLC treated ICIs were obtained from cBioPortal. The top 20 gene alterations in durable clinical benefit (DCB) were compared with those genes in no durable benefit (NDB). Survival analyses were performed using the Kaplan-Meier plot method and selected clinical variables to develop a novel nomogram.Results: The mutation of PTPRD was significantly related to progression free survival (PFS) and overall survival (OS) in advanced NSCLC with ICIs treatment . The PTPRD mutation was closely related to tumor mutational burden (TMB) and tumor-infiltrating immune cells (TIICs). Two novel nomograms were built to predict the PFS and OS of advanced NSCLC patients with ICIs treatment.Conclusions: Our study suggested that PTPRD mutations could serve as a predictive biomarker for the sensitivity to ICIs treatment and PFS and OS in advanced NSCLC with ICIs. Our systematic nomograms showed great potential value in clinical application to predict the PFS and OS for advanced NSCLC patients with ICIs. Among various cancers, Lung cancer was the most incident and lethal malignant tumor worldwide . Lung caAt present, there are some biomarkers related to ICIs that have been approved by many clinical trials, including PD-L1 expression, TMB, and MSI-H , 9. MostIn this study, genomic and clinical data of advanced NSCLC treated with ICIs were downloaded from cBioPortal , 19, 20.Three ICIs cohorts of advanced NSCLC with immunotherapy were obtained from cBioPortal. The first cohort  consisted of targeted NGS of 240 advanced NSCLC with anti-PD-(L)1 monotherapy or in combination with anti–CTLA-4 . The secrms was used to construct the nomogram. And the predictive accuracy and discriminative value of nomogram mainly included the concordance index (C-index), calibration curve, and ROC curve.Survival analyses were conducted using the Kaplan-Meier plot method and selected clinical variables to develop a novel nomogram. Based on the patient’s clinical data and other information, nomograms can predict the likelihood of an event, including PFS, OS, and recurrence. In this work, the construction of the nomogram was based on clinicopathological information and mutational data. The “rms” package, which stands for Regression Modeling Strategies, is a collection of functions that facilitates and simplifies regression modeling, testing, estimation, validation, plotting, prediction, and presentation by incorporating enhanced model design attributes. The “rms” package serves as a valuable tool for assisting and streamlining the modeling process. And the R package GO is a common technique for studying the biological function of genetic data, which mainly includes biological process, cellular component, and molecular function . KEGG daThe gene mutation, gene expression, and clinical data of LUAD and LUSC were obtained from TCGA database. The TMB score was further calculated for each sample. According to the comparison between single gene mutation group and wild group, the different degree of whole genes was obtained, which was performed by the gene set enrichment analysis (GSEA). In addition, the relative abundance of TIICs in NSCLC was determined by converting the genes expression into the fraction of immune cells.External validation of the prognostic significance of gene was performed by another ICIs cohort . This cohort consisted of 75 NSCLC with anti-PD-1 combination with anti–CTLA-4 [P-value< 0.05 indicating statistically significant.In this work, GraphPad Prism 9.0 and R 4.2.2 were used for statistical analyses. One-way Student’s t tests were used to determine statistical significance. Survival analyses were performed using the Kaplan-Meier plot method and compared using the log-rank test. And All data included in this study are available including cBioPortal of Cancer Genomics  and TCGA database.The top 20 gene alterations in DCB group include TP53, KRAS, KEAP1, PTPRT, PTPRD, STK11, MLL3, FAT1, SMARCA4, EPHA5, EPHA3, TERT, NF1, MGA, ERBB4, ATRX, ARID1A, PIK3CG, PIK3C2G, PGR . We alsoThe results of GO analysis suggested that the significant enrichment of the top 20 genes was mainly associated with cellular response to chemical stimulus, anatomical structure morphogenesis, cell development, and nervous system development . In addiBased on gene mutation and survival data, we selected the survival related gene from top 20 alterations in DCB group by the Kaplan-Meier plot method. ATRX, PTPRD, and PTPRT were closely related to PFS of NSCLC with immunotherapy in the first cohort  and the second cohort . Next, we analyzed the mutation status of ATRX, PTPRD, and PTPRT in the third cohort  . MutatioSurvival analyses were performed using the Kaplan-Meier plot method and selected clinical variables to develop a novel nomogram. TMB , PD-L1 expression , line of treatment , smoking status , treatment type  and PTPRD  were significantly related to the PFS in advanced NSCLC patients with ICIs treatment –1H, 3B. The GSEA enrichment analysis performed with TCGA-LUAD cohort showed that riboflavin metabolism, RNA degradation, cell cycle, mismatch repair, and homologous recombination were significantly enriched in PTPRD mutation samples . In TCGAWe also evaluated the relationship between PTPRD mutation and TIICs in NSCLC. In TCGA-LUAD cohort, activated memory CD4 T cells, and M0 macrophages were more enriched in PTPRD mutant sample . As for We further explored the prognostic value of PTPRD mutation in another ICIs cohort  as an independent external validation. Similarly, mutation frequency of PTPRD was 12% . The samAt present, PD-L1 expression or TMB alone did not demonstrate a satisfactory ability to select advanced NSCLC patients who are likely to respond to ICIs. Apart from the expression of PD-L1 and TMB, there are some specific gene mutations including KRAS/TP53, STK11, EGFR, EPHA, and NOTCH, that are related to efficacy of ICIs by regulating the tumor microenvironment and served as potential biomarkers to predict the clinical benefits of immunotherapy –27. Sun PTPRD is a member of protein tyrosine phosphatases, which negatively regulate tyrosine phosphorylation . It has In this study, mutation frequencies of PTPRD in DCB group, NDB group, the third cohort , and the last cohort  were 18.4%, 9.8%, 13.4%, and 12%, respectively. The Kaplan–Meier survival curves showed the mutation of PTPRD was associated with the PFS ) and OS ) in NSCLC with ICIs treatment. The prognostic value of PTPRD mutation was validated in the last ICIs cohort as an independent external validation ). Besides, the PTPRD mutation was closely associated with higher TMB values in all ICIs cohort and TCGA cohort (P < 0.0001). Therefore, we reasonably deduced that the mutation PTPRD can be used as a potential biomarker for the sensitivity to ICIs treatment and prognosis of advanced NSCLC.+ T cell infiltration via its phosphatase activity, and promote the occurrence of “hot” TME with enhanced anti-tumor immunity in advanced NSCLC patients.To explain why PTPRD mutations were associated with favorable ICIs prognosis, we evaluated the role of PTPRD mutation in GSEA and immune infiltration. The GSEA enrichment analysis showed that PTPRD mutation samples were mainly associated with riboflavin metabolism, RNA degradation, cell cycle, and mismatch repair in LUAD, and glycosphingolipid biosynthesis ganglio series, other glycan degradation, bile acid biosynthesis, and regulation of autophagy in LUSC, respectively. Besides that, we found that activated memory CD4 T cells, M0 macrophages, and eosinophils were more enriched in PTPRD mutant sample. Some studies revealed that eosinophils were closely associated with clinical outcomes in patients with ICIs treatment –44. The Moreover, NSCLC patient’s clinical variables and genomic data that we included were screened by the Kaplan-Meier plot method. TMB, PD-L1 expression, line of treatment, smoking status, treatment type, and PTPRD mutant were significantly related to the PFS in advanced NSCLC patients with ICIs treatment. Besides that, treatment type and PTPRD mutant were significantly related to the OS in advanced NSCLC patients with ICIs treatment. According to the above results, we constructed two novel systematic nomograms that are based on the patient’s clinicopathological parameters and genome data to predict the prognosis for advanced NSCLC with ICIs. Based on our novel nomograms, clinicians can obtain the total point based on all variable points for each patient and can then predict the 6-month PFS, 1-year PFS, 1-year OS, and 3-year OS of advanced NSCLC patients with immunotherapy. Our novel nomograms can be used to assess the PFS and OS of NSCLC patients ICIs and formulate the appropriate type of treatment and follow-up time before immunotherapy.The existing literature suggested that the mechanism of PTPRD mutation in NSCLC with ICIs still needs to be further explored. This study is the first to use the large database to establish two systematic nomograms for predicting the PFS and OS of advanced NSCLC patients with ICIs treatment, which undoubtedly provides a new clinical strategy for advanced NSCLC patients. This work is the first to illustrate the role of PTPRD mutations as a potential biomarker for the sensitivity to ICIs treatment and prognosis of advanced NSCLC. PTPRD can be used as a potential biomarker in regulating the TME and associating with the PFS and OS in advanced NSCLC with immunotherapy. Nevertheless, there remains some limitations in our work. First, this work employed four ICIs cohorts from the cBioPortal database. Due to the utilization of different platforms and detection depths, four cohorts may exhibit potential heterogeneity. Second, clinical information, response data, and genome data of NSCLC with ICIs were downloaded from four public datasets, some specific patients’ information and clinicopathological variables were unclear or not available. Third, four ICIs cohorts used different treatment types, such as immunotherapy monotherapy or combination with anti-CTLA-4, resulting in a certain degree of research heterogeneity. In addition, the mechanism of PTPRD affecting TME and immunotherapy in NSCLC needs further experiments to explore.To conclude, our study demonstrated that PTPRD mutation could serve as a prognostic biomarker predicting the PFS and OS in advanced NSCLC treated ICIs. PTPRD mutation is strongly associated with high TMB levels and immune infiltration and enhanced anti-tumor microenvironment. Our systematic nomograms showed great potential value in clinical application to predict the PFS and OS in advanced NSCLC with immunotherapy.Supplementary Figure 1Supplementary Table 1