The Contribution of Mosaic Chromosomal Alterations to Schizophrenia.

BACKGROUND: Mosaic chromosomal alterations (mCAs) are implicated in neuropsychiatric disorders, yet the contribution to schizophrenia (SCZ) risk for somatic copy number variations (sCNVs) emerging in early developmental stages is not fully established. METHODS: We analyzed blood-derived genotype arrays from 9,715 SCZ patients and 28,822 controls of Chinese descent using a computational tool (MoChA) based on long-range chromosomal information to detect mCAs. We focused on probable early developmental sCNVs through stringent filtering. We assessed the sCNVs' burden across varying cell fraction (CF) cutoffs, as well as the frequency with which genes were involved in sCNVs. We integrated this data with the Psychiatric Genomics Consortium (PGC) dataset, which comprises 12,834 SCZ cases and 11,648 controls of European descent, and complemented it with genotyping data from postmortem brain tissue of 936 subjects (449 cases and 487 controls). RESULTS: Patients with SCZ had a significantly higher somatic losses detection rate than control subjects (1.00% vs 0.52%; odds ratio (OR) = 1.91; 95% CI, 1.47-2.49; two-sided Fisher's exact test, p=1.49×10-6). Further analysis indicated that the ORs escalated proportionately (from 1.91 to 2.78) with the increment in CF cutoffs. Recurrent sCNVs associated with SCZ (OR>8; Fisher's exact test, p<0.05) were identified, including notable regions at 10q21.1 (ZWINT), 3q26.1 (SLITRK3), 1q31.1 (BRINP3) and 12q21.31-21.32 (MGAT4C and NTS) in the Chinese cohort, some regions validated with PGC data. Cross-tissue validation pinpointed somatic losses at loci like 1p35.3-35.2 and 19p13.3-13.2. CONCLUSIONS: The study highlights mCAs' significant impact on SCZ, suggesting their pivotal role in the disorder's genetic etiology.

Bioinformatics Analysis Reveals Prognostic Significance of the Macrophage Marker Gene Signature in Gastric Adenocarcinoma.

BACKGROUND: Gastric adenocarcinoma (GAC) is a malignant tumor with the highest incidence in the digestive system. Macrophages have been proven to play important roles in tumor microenvironment. METHODS: Herein, single-cell RNA sequencing (scRNA-seq) profiles from the Gene Expression Omnibus (GEO) and bulk RNA-seq data from the Cancer Genome Atlas (TCGA) database were utilized to construct a macrophage marker gene signature (MMGS) to predict the prognosis of GAC patients. Subsequently, a risk score model based on the MMGS was built to predict the prognosis of GAC patients; further, this was validated in the GEO cohort. The risk score categorized patients into the high- and low-risk groups. A nomogram model based on the risk score and clinic-pathological characteristics was developed. RESULTS: Seven genes, ABCA1, CTHRC1, GADD45B, NPC2, PLTP, PRSS23, and RNASE1, were included in the risk score model. Patients with a low-risk score showed a better prognosis. The MMGS had good sensitivity and specificity for predicting the prognosis inGAC patients. The risk score was an independent prognostic factor. The constructed nomogram exhibited favorable predictability and reliability for predicting GAC prognosis. CONCLUSION: In conclusion, the risk score model based on the seven MMGSs performed well in the predicting prognosis of GAC patients. Our study may provide new insights into clinical decision-making for the personalized treatment of patients with gastric cancer (GC).

Evaluation of vital genes correlated with CD8 + T cell infiltration as prognostic biomarkers in stomach adenocarcinoma.

BACKGROUND: Infiltration of CD8 + T cells in the tumor microenvironment is correlated with better prognosis in various malignancies. Our study aimed to investigate vital genes correlated with CD8 + T cell infiltration in stomach adenocarcinoma (STAD) and develop a new prognostic model. METHODS: Using the STAD dataset, differentially expressed genes (DEGs) were analyzed, and co-expression networks were constructed. Combined with the CIBERSORT algorithm, the most relevant module of WGCNA with CD8 + T cell infiltration was selected for subsequent analysis. The vital genes were screened out by univariate regression analysis to establish the risk score model. The expression of the viral genes was verified by lasso regression analysis and in vitro experiments. RESULTS: Four CD8 + T cell infiltration-related genes (CIDEC, EPS8L3, MUC13, and PLEKHS1) were correlated with the prognosis of STAD. Based on these genes, a risk score model was established. We found that the risk score could well predict the prognosis of STAD, and the risk score was positively correlated with CD8 + T cell infiltration. The validation results of the gene expression were consistent with TCGA. Furthermore, the risk score was significantly higher in tumor tissues. The high-risk group had poorer overall survival (OS) in each subgroup. CONCLUSIONS: Our study constructed a new risk score model for STAD prognosis, which may provide a new perspective to explore the tumor immune microenvironment mechanism in STAD.

Regulatory mechanisms of macrophage polarization in adipose tissue.

In adipose tissue, macrophages are the most abundant immune cells with high heterogeneity and plasticity. Depending on environmental cues and molecular mediators, adipose tissue macrophages (ATMs) can be polarized into pro- or anti-inflammatory cells. In the state of obesity, ATMs switch from the M2 polarized state to the M1 state, which contributes to chronic inflammation, thereby promoting the pathogenic progression of obesity and other metabolic diseases. Recent studies show that multiple ATM subpopulations cluster separately from the M1 or M2 polarized state. Various factors are related to ATM polarization, including cytokines, hormones, metabolites and transcription factors. Here, we discuss our current understanding of the potential regulatory mechanisms underlying ATM polarization induced by autocrine and paracrine factors. A better understanding of how ATMs polarize may provide new therapeutic strategies for obesity-related diseases.

Transcriptome sequencing and miRNA-mRNA network construction in exosome of macrophage M2 in stomach adenocarcinoma.

BACKGROUND: Stomach adenocarcinoma (STAD) is the most common histological type of gastric cancer (GC). Macrophages are an essential part of the tumor microenvironment. We attempted to search for potential molecular markers associated with macrophages, which might be helpful for STAD diagnosis and treatment. METHODS: Firstly, exosome in macrophages was extracted for RNA sequencing to identify differentially expressed microRNAs (miRNAs) (DEmiRNAs). Then, DEmiRNAs and differentially expressed mRNAs (DEmRNAs) were screened in the Cancer Genome Atlas (TCGA) database. The miRNAs related to macrophage M2 polarization were obtained by intersecting the DEmiRNAs obtained from the sequencing data and TCGA data. Using the Pearson correlation coefficient method, the mRNAs significantly related to macrophage M2 were screened out, followed by construction of the macrophage M2-miRNA-mRNA network. Subsequently, real-time-polymerase chain reaction (RT-PCR) and online datasets were applied to validate the expression of DEmiRNAs and DEmRNAs. RESULTS: A total of 6 DEmiRNAs were identified in RNA sequencing; 59 DEmiRNAs and 1838 DEmRNAs were identified in TCGA database. Among which, a common miRNA (hsa-miR-133a-3p) associated with the M2 polarization of macrophages was identified. Fifteen common mRNAs were obtained between DEmRNAs and mRNAs targeted by DEmiRNAs. Eventually, a core macrophage M2-1 down-regulated miRNA-7 and up-regulated mRNAs network was constructed, including hsa-miR-133a-3p, SLC39A1, TTYH3, HAVCR2, TPM3, XPO1, POU2F1, and MMP14. The expression of miRNA and mRNAs was in line with the validation results of RT-PCR and online datasets. CONCLUSION: In this study, the screening of biomarkers in exosome of macrophage M2 may contribute to the prognosis of STAD patients.

DROEG: a method for cancer drug response prediction based on omics and essential genes integration.

Predicting therapeutic responses in cancer patients is a major challenge in the field of precision medicine due to high inter- and intra-tumor heterogeneity. Most drug response models need to be improved in terms of accuracy, and there is limited research to assess therapeutic responses of particular tumor types. Here, we developed a novel method DROEG (Drug Response based on Omics and Essential Genes) for prediction of drug response in tumor cell lines by integrating genomic, transcriptomic and methylomic data along with CRISPR essential genes, and revealed that the incorporation of tumor proliferation essential genes can improve drug sensitivity prediction. Concisely, DROEG integrates literature-based and statistics-based methods to select features and uses Support Vector Regression for model construction. We demonstrate that DROEG outperforms most state-of-the-art algorithms by both qualitative (prediction accuracy for drug-sensitive/resistant) and quantitative (Pearson correlation coefficient between the predicted and actual IC50) evaluation in Genomics of Drug Sensitivity in Cancer and Cancer Cell Line Encyclopedia datasets. In addition, DROEG is further applied to the pan-gastrointestinal tumor with high prevalence and mortality as a case study at both cell line and clinical levels to evaluate the model efficacy and discover potential prognostic biomarkers in Cisplatin and Epirubicin treatment. Interestingly, the CRISPR essential gene information is found to be the most important contributor to enhance the accuracy of the DROEG model. To our knowledge, this is the first study to integrate essential genes with multi-omics data to improve cancer drug response prediction and provide insights into personalized precision treatment.

Regulation of programmed cell death by Brd4.

Epigenetic factor Brd4 has emerged as a key regulator of cancer cell proliferation. Targeted inhibition of Brd4 suppresses growth and induces apoptosis of various cancer cells. In addition to apoptosis, Brd4 has also been shown to regulate several other forms of programmed cell death (PCD), including autophagy, necroptosis, pyroptosis, and ferroptosis, with different biological outcomes. PCD plays key roles in development and tissue homeostasis by eliminating unnecessary or detrimental cells. Dysregulation of PCD is associated with various human diseases, including cancer, neurodegenerative and infectious diseases. In this review, we discussed some recent findings on how Brd4 actively regulates different forms of PCD and the therapeutic potentials of targeting Brd4 in PCD-related human diseases. A better understanding of PCD regulation would provide not only new insights into pathophysiological functions of PCD but also provide new avenues for therapy by targeting Brd4-regulated PCD.

Identification of 8-gene risk prediction signature associated with NOTCH1 in stomach adenocarcinoma based on bioinformatics analysis.

Background: Stomach adenocarcinoma (STAD), is the most common histological type of gastric cancer (GC) with high mortality and poor prognosis. We sought to investigate the contribution of Notch receptor 1 (NOTCH1) to STAD immunity. Methods: The profiles of immune cells in STAD cohorts were compared, and a correlation analysis between the NOTCH1 gene and tumor immune cell infiltration was then conducted. The immune-related genes (IRGs) associated with the NOTCH1 gene were identified. Based on the NOTCH1-associated IRGs, multiple-gene risk prediction signatures were established. The relationship between the expression levels of the selected IRGs and overall survival (OS) was analyzed by a univariate analysis. The risk score was calculated using the formula of ß1x1 + ß2x2 +... + ßixi. A prognostic nomogram was constructed to predict individuals' survival probabilities. Results: In STAD, NOTCH1 expression levels were significantly negatively associated with tumor-infiltrating lymphocyte (TIL) Act dendritic cells (DCs) (r=-0.196, P value =6.24e-05), TIL cluster of differentiation (CD) 56 bright cells (r=-0.115, P value =0.0193), TIL immature DCs (r=-0.293, P value =1.16e-09), TIL monocyte cells (r=-0.185, P value =0.000149), TIL central memory T CD4 cells (r=-0.126, P value =0.0103), and TIL gamma delta T cells (r=-0.149, P value =0.00229). The resulting risk scores of the 8-gene risk prediction signature (corticotrophin releasing hormone receptor 2 (CRHR2) (HR =1.858, P value =0.048), fms related receptor tyrosine kinase 1 (FLT1) (HR =1.268, P value =0.048), fms related receptor tyrosine kinase 4 (FLT4) (HR =1.334, P value =0.031), glial fibrillary acidic protein (GFAP) (HR =2.739, P value =0.008), platelet-derived growth factor receptor beta (PDGFRB) (HR =1.192, P value =0.02), prostaglandin D2 receptor (PTGDR) (HR =1.564, P value =0.049), semaphorin 5B (SEMA5B) (HR =1.154, P value =0.029), and tyrosine kinase 2 (TYK2) (HR =0.734, P value =0.041) were independent prognostic predictors for STAD patients. Conclusions: NOTCH1 could be a potential target for STAD. The mechanisms underpinning NOTCH1-medicated prognostic values of immune signatures should be further explored.

Association analysis of risk genes identified by SCHEMA with schizophrenia in the Chinese Han population.

BACKGROUND: Schizophrenia is a chronic brain disorder. Previously, the Schizophrenia Exome Sequencing Meta-analysis consortium identified 10 highest risk genes related to schizophrenia. This study aimed to analyze the relationship between the 10 highest risk genes identified by the SCHEMA and schizophrenia in a Chinese population. METHODS: A total of 225 variants in 10 genes were screened in a Chinese population of 6836 using a customized array. All variants were annotated through the Variant Effect Predictor tool, and the functional impacts of missense variants were assessed based on sorting intolerant from tolerant and PolyPhen-2 scores. The SHEsisPlus tool was used to analyze the association between risk genes and schizophrenia at the locus and gene levels. RESULTS: At the locus level, no missense variants significantly related to schizophrenia were found, but we detected three missense variants that appeared only in cases, including TRIO p. Arg1185Gln, RB1CC1 p. Arg1514Cys, and HERC1 p. Val4517Leu. At the gene level, five genes (TRIO, RB1CC1, HERC1, GRIN2A, and CACAN1G) with more than one variant analyzed were kept for the gene-level association analysis. Only the association between RB1CC1 and schizophrenia reached a significant level (OR = 1.634; 95% CI, 1.062-2.516; P = 0.025). CONCLUSION: In this study, we determined that RB1CC1 might be a risk gene for schizophrenia in the Chinese population. Our results provide new evidence for recognizing the correlation of these risk genes with the Chinese schizophrenia population.

Structural Comparison and Drug Screening of Spike Proteins of Ten SARS-CoV-2 Variants.

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) has evolved many variants with stronger infectivity and immune evasion than the original strain, including Alpha, Beta, Gamma, Delta, Epsilon, Kappa, Iota, Lambda, and 21H strains. Amino acid mutations are enriched in the spike protein of SARS-CoV-2, which plays a crucial role in cell infection. However, the impact of these mutations on protein structure and function is unclear. Understanding the pathophysiology and pandemic features of these SARS-CoV-2 variants requires knowledge of the spike protein structures. Here, we obtained the spike protein structures of 10 main globally endemic SARS-CoV-2 strains using AlphaFold2. The clustering analysis based on structural similarity revealed the unique features of the mainly pandemic SARS-CoV-2 Delta variants, indicating that structural clusters can reflect the current characteristics of the epidemic more accurately than those based on the protein sequence. The analysis of the binding affinities of ACE2-RBD, antibody-NTD, and antibody-RBD complexes in the different variants revealed that the recognition of antibodies against S1 NTD and RBD was decreased in the variants, especially the Delta variant compared with the original strain, which may induce the immune evasion of SARS-CoV-2 variants. Furthermore, by virtual screening the ZINC database against a high-accuracy predicted structure of Delta spike protein and experimental validation, we identified multiple compounds that target S1 NTD and RBD, which might contribute towards the development of clinical anti-SARS-CoV-2 medicines. Our findings provided a basic foundation for future in vitro and in vivo investigations that might speed up the development of potential therapies for the SARS-CoV-2 variants.

Ionic Current Fluctuation and Orientation of Tetrahedral DNA Nanostructures in a Solid-State Nanopore.

Understanding the dynamic behavior of a nanostructure translocating through a nanopore is important for various applications. In this paper, the characteristics in ion current traces of tetrahedral DNA nanostructures (TDN) translocating through a solid-state nanopore are examined, by combined experimental and theoretical simulations. The results of finite element analysis reveal the correlation between orientation of TDN and the conductance blockade. The experimentally measured fluctuations in the conductance blockade, expressed as voltage-dependent histogram profiles, are consistent with the simulation, revealing the nature of a random distribution in orientation and weak influence of electrostatic and viscous torques. The step changes in orientation of a TDN during translocation are further explained by the collision with the nanopore, while the gradual changes in orientation illustrate the impact of a weak torque field in the nano-fluidic channel. The results demonstrate a general method and basic understanding in the dynamic behavior of nanostructures translocating through solid-state nanopores.

Genetic risk of clozapine-induced leukopenia and neutropenia: a genome-wide association study.

BACKGROUND: Clozapine is considered to be the most effective antipsychotic medication for schizophrenia. However, it is associated with several adverse effects such as leukopenia, and the underlying mechanism has not yet been fully elucidated. The authors performed a genome-wide association study (GWAS) in a Chinese population to identify genetic markers for clozapine-induced leukopenia (CIL) and clozapine-induced neutropenia (CIN). METHODS: A total of 1879 patients (225 CIL cases, including 43 CIN cases, and 1,654 controls) of Chinese descent were included. Data from common and rare single nucleotide polymorphisms (SNPs) were tested for association. The authors also performed a trans-ancestry meta-analysis with GWAS results of European individuals from the Clozapine-Induced Agranulocytosis Consortium (CIAC). RESULTS: The authors identified several novel loci reaching the threshold of genome-wide significance level (P < 5 × 10-8). Three novel loci were associated with CIL while six were associated with CIN, and two T cell related genes (TRAC and TRAT1) were implicated. The authors also observed that one locus with evidence close to genome-wide significance (P = 5.08 × 10-8) was near the HLA-B gene in the major histocompatibility complex region in the trans-ancestry meta-analysis. CONCLUSIONS: The associations provide novel and valuable understanding of the genetic and immune causes of CIL and CIN, which is useful for improving clinical management of clozapine related treatment for schizophrenia. Causal variants and related underlying molecular mechanisms need to be understood in future developments.

Performance comparison of four types of target enrichment baits for exome DNA sequencing.

BACKGROUND: Next-generation sequencing technology is developing rapidly and target capture sequencing has become an important technique. Several different platforms for library preparation and target capture with different bait types respectively are commercially available. Here we compare the performance of the four platforms with different bait types to find out their advantages and limitations. The purpose of this study is to help investigators and clinicians select the appropriate platform for their particular application and lay the foundation for the development of a better target capture platform for next-generation sequencing. RESULTS: We formulate capture efficiency as a novel parameter that can be used to better evaluations of specificity and coverage depth among the different capture platforms. Target coverage, capture efficiency, GC bias, AT Dropout, sensitivity in single nucleotide polymorphisms, small insertions and deletions detection, and the feature of each platform were compared for low input samples. In general, all platforms perform well and small differences among them are revealed. In our results, RNA baits have stronger binding power than DNA baits, and with ultra deep sequencing, double stranded RNA baits perform better than single stranded RNA baits in all aspects. DNA baits got better performance in the region with high GC content and RNA baits got lower AT dropout suggesting that the binding power is different between DNA and RNA baits to genome regions with different characteristics. CONCLUSIONS: The platforms with double stranded RNA baits have the most balanced capture performance. Our results show the key differences in performance among the four updated platforms with four different bait types. The better performance of double stranded RNA bait with ultra deep sequencing suggests that it may improve the sensitivity of ultra low frequent mutation detection. In addition, we further propose that the mixed baits of double stranded RNA and single stranded DNA may improve target capture performance.

Association analysis of potentially functional variants within 8p12 with schizophrenia in the Han Chinese population.

OBJECTIVES: Chromosome 8p12 was first identified as a schizophrenia (SCZ) risk locus in Chinese populations and replicated in European populations. However, the underlying functional variants still need to be further explored. In this study, we sought to identify plausible causal variants within this locus. METHODS: A total of 386 potentially functional variants from 29 genes within the 8p12 locus were analysed in 2403 SCZ cases and 2594 control subjects in the Han Chinese population using Affymetrix customised genotyping assays. SHEsisplus was used for association analysis. A multiple testing corrected p value (false discovery rate (FDR)) < .05 was considered significant, and an unadjusted p value < .05 was considered nominal evidence of an association. RESULTS: We did not find significant associations between the tested variants and SCZ. However, nominal associations were found for rs201292574 (unadjusted p = .033, FDR p = .571; 95% confidence interval (CI): 0.265-0.945; TACC1, NP_006274.2:p.Ala211Thr) and rs45563241 (unadjusted p = .039, FDR p = .571; 95% CI: 1.023-1.866; a synonymous mutation in ADRB3). CONCLUSIONS: Our results provide limited evidence for the associations between variants from protein coding regions in 8p12 and SCZ in the Chinese population. Analyses of both coding and regulatory variants in larger sample sizes are required to further clarify the causal variants for SCZ with this risk locus.

The amino acid variants in HLA II molecules explain the major association with adult-onset Still's disease in the Han Chinese population.

Adult-onset Still's disease (AOSD) is a rare autoinflammatory disease with systemic involvement, and its pathophysiology remains unclear. Genome-wide association studies (GWAS) in the Chinese population have revealed an association between AOSD and the major histocompatibility complex (MHC) locus; however, causal variants in the MHC remain undetermined. In the present study, we identified independent amino-acid polymorphisms in human leukocyte antigen (HLA) molecules that are associated with Han Chinese patients with AOSD by fine-mapping the MHC locus. Through conditional analyses, we identified position 34 in HLA-DQα1 (p = 1.44 × 10-14) and Asn in HLA-DRß1 position 37 (p = 5.12 × 10-11) as the major determinants for AOSD. Moreover, we identified the associations for three main HLA class II alleles: HLA-DQB1*06:02 (OR = 2.70, p = 3.02 × 10-14), HLA-DRB1*15:01 (OR = 2.44, p = 3.66 × 10-13), and HLA-DQA1*01:02 (OR = 1.97, p = 1.09 × 10-9). This study reveals the relationship between functional variations in the class II HLA region and AOSD, implicating the MHC locus in the pathogenesis of AOSD.

SNX29, a new susceptibility gene shared with major mental disorders in Han Chinese population.

OBJECTIVES: Environmental and genetic factors play important roles in the development of schizophrenia (SCZ), bipolar disorder (BPD) or major depressive disorder (MDD). Some risk loci are identified with shared genetic effects on major psychiatric disorders. To investigate whether SNX29 gene played a significant role in these psychiatric disorders in the Han Chinese population. METHODS: We focussed on 11 single-nucleotide polymorphisms (SNPs) harbouring SNX29 gene and carried out case-control studies in patients with SCZ (n = 1248), BPD (n = 1344), or MDD (n = 1056), and 1248 healthy controls (HC) recruited from the Han Chinese population. We constructed weighted gene co-expression network analysis (WGCNA) and extracted significant modules by R package. RESULTS: We found that rs3743592 was significantly associated with MDD and rs6498263 with BPD in both allele and genotype distributions. Before correction, rs3743592 showed allelic and genotypic significance with SCZ, rs6498263 showed allelic significance with SCZ. WGCNA identified top 10 modules of co-expressed genes. Gene Ontology (GO) and pathway analysis were used to examine the functions of SNX29, which revealed that SNX29 was involved in the regulation of a number of biological processes, such as TGF-beta, ErbB, and Wnt signalling pathway, etc. CONCLUSIONS: Our results supported common risk factors in SNX29 might share among these three mental disorders in the Han Chinese population.

Common variants in FAN1, located in 15q13.3, confer risk for schizophrenia and bipolar disorder in Han Chinese.

Multiple genetic risk factors have been associated with psychiatric disorders which provides the genetic insight to these disorders; however, the etiology of these disorders is still elusive. 15q13.3 was previously associated with schizophrenia, bipolar and other neurodevelopmental disorders. Whereas, the FAN1 which encodes the Fanconi anemia associated nuclease 1 was suggested to be causal gene for 15q13.3 related psychiatric disorders. This study aimed to investigate the association of FAN1 with three major psychiatric disorders. Herein, we conducted a case-control study with the Chinese Han population. Three single nucleotide polymorphisms (SNPs) of FAN1 were genotyped in 1248 schizophrenia cases, 1344 bipolar disorder cases, 1056 major depressive disorder cases and 1248 normal controls. We found that SNPs rs7171212 was associated with bipolar (pallele = 0.023, pgenotype = 0.022, OR = 0.658) and schizophrenia (pallele = 0.021, pgenotype = 0.019, OR = 0.645). Whereas, rs4779796 was associated with schizophrenia (pgenotype = 0.001, adjusted pgenotype = 0.003, OR = 1.089). In addition, rs7171212 (adjusted pallele = 0.018, adjusted pgenotype = 0.018, OR = 0.652) and rs4779796 (adjusted pgenotype = 0.024, OR = 1.12) showed significantly associated with combined cases of schizophrenia and bipolar disorder. Further, meta-analysis was performed with the case-control data and dataset extracted from previously reported genome-wide association study to validate the promising SNPs. Our results provide the new evidence that FAN1 may be a common susceptibility gene for schizophrenia and bipolar disorder in Han Chinese. These novel findings need further validation with larger sample size and functional characterization to understand the underlying pathogenic mechanism behind FAN1 in the prevalence of schizophrenia and bipolar disorders.

STRsearch: a new pipeline for targeted profiling of short tandem repeats in massively parallel sequencing data.

BACKGROUND: Short tandem repeats (STRs) are important polymorphism makers for human identification and kinship analyses in forensic science. With the continuous development of massively parallel sequencing (MPS), more laboratories have utilized this technology for forensic applications. Existing STR genotyping tools, mostly developed for whole-genome sequencing data, are not effective for MPS data. More importantly, their backward compatibility with the conventional capillary electrophoresis (CE) technology has not been evaluated and guaranteed. RESULTS: In this study, we developed a new end-to-end pipeline called STRsearch for STR-MPS data analysis. The STRsearch can not only determine the allele by counting repeat patterns and INDELs that are actually in the STR region, but it also translates MPS results into standard STR nomenclature (numbers and letters). We evaluated the performance of STRsearch in two forensic sequencing datasets, and the concordance with CE genotypes was 75.73 and 75.75%, increasing 12.32 and 9.05% than the existing tool named STRScan, respectively. Additionally, we trained a base classifier using sequence properties and used it to predict the probability of correct genotyping at a given locus, resulting in the highest accuracy of 96.13%. CONCLUSIONS: All these results demonstrated that STRsearch was a better tool to protect the backward compatibility with CE for the targeted STR profiling in MPS data. STRsearch is available as open-source software at https://github.com/AnJingwd/STRsearch.