Identification of Induced Copy Number Variation from Low Coverage Sequence Data.

Induced mutations have been an important tool for plant breeding and functional genomics for more than 80 years. Novel mutations can be induced by treating seed or other plant cells with chemical mutagens or ionizing radiation. The majority of released mutant crop varieties were developed using ionizing radiation. This has been shown to create a variety of different DNA lesions including large (e.g., >=10,000 bps) copy number variations (CNV). Detection of induced DNA lesions from whole genome sequence data is useful for choosing a mutagen dosage prior to committing resources to develop a large mutant population for forward or reverse-genetic screening. Here I provide a method for detecting large induced CNV from mutant plants that utilizes a new tool to streamline the process of obtaining read coverage directly from BAM files, comparing non-mutagenized controls and mutagenized samples, and plotting the results for visual evaluation. Example data is provided from low coverage sequence data from gamma-irradiated vegetatively propagated triploid banana.

[Efficiency of CNV-seq in detecting fetal DMD gene deletion or duplication in prenatal diagnosis].

Objective: To evaluate the diagnostic efficiency of copy number variation sequencing (CNV-seq) to detect the deletion or duplication of DMD gene in prenatal diagnosis. Methods: A retrospective analysis was carried out on the CNV-seq results of 34 544 fetuses diagnosed in the First People's Hospital of Yunnan Province from January 2018 to July 2023. A total of 156 cases of fetuses were collected, including Group 1:125 cases with family history of Duchenne muscular dystrophy or Becker muscular dystrophy (DMD/BMD), and Group 2:31 cases with no family history but a DMD gene deletion or duplication was detected unexpectedly by CNV-seq. Multiplex ligation-dependent probe amplification (MLPA) was used as a standard method to detect the deletion or duplication. Consistency test was carried out basing on the results of CNV-seq and MLPA of all 156 cases. Results: Comparing to MLPA, CNV-seq had a coincidence rate of 92.3% (144/156) for DMD gene deletion or duplication, with a sensitivity and positive predictive value of 88.2%, with a specificity and negative predictive value of 94.3%, a missed detection rate of 3.8%, and a Kappa value of 0.839. CNV-seq missed 4 cases with deletions and 2 with duplications due to involved fragments less than 100 Kb, among 20 cases of deletions and 6 cases of duplications detected by MLPA in Group 1. In Group 2, the deletions and duplications detected by CNV-seq were 42% (13/31) and 58% (18/31), respectively, in which the percentage of duplication was higher than that in Group 1. Among those 18 cases with duplications, 3 cases with duplication locating in exon 42~67 were likely pathogenic; while 9 cases with duplication covering the 5' or 3' end of the DMD gene, containing exon 1 or 79 and with only one breakpoint within the gene, along with the last 6 cases with duplications locating at chrX: 32650635_32910000 detected only by CNV-seq, which might be judged as variants of uncertain significance. Conclusions: CNV-seq has a good efficiency to detect fetal DMD gene deletion or duplication in prenatal diagnosis, while a further verification test by MLPA is recommended. The duplications on chrX: 32650635_32910000, 5' or 3' end of DMD gene detected by CNV-seq should be carefully verified and assessed because those variants appear to be nonpathogenic polymorphisms.

Diagnostic yield of the chromosomal microarray analysis in turkish patients with unexplained development delay/intellectual disability(ID), autism spectrum disorders and/or multiple congenital anomalies and new clinical findings.

BACKGROUND: Chromosomal microarray analysis is an essential tool for copy number variants detection in patients with unexplained developmental delay/intellectual disability, autism spectrum disorders, and multiple congenital anomalies. The study aims to determine the clinical significance of chromosomal microarray analysis in this patient group. Another crucial aspect is the evaluation of copy number variants detected in terms of the diagnosis of patients. METHODS AND RESULTS: A Chromosomal microarray analysis was was conducted on a total of 1227 patients and phenotype-associated etiological diagnosis was established in 135 patients. Phenotype-associated copy number variants were detected in 11% of patients. Among these, 77 patients 77 (57%, 77/135) were diagnosed with well-recognized genetic syndromes and phenotype-associated copy number variants were found in 58 patients (42.9%, 58/135). The study was designed to collect data of patients in Kocaeli Derince Training and Research Hospital retrospectively. In our study, we examined 135 cases with clinically significant copy number variability among all patients. CONCLUSIONS: In this study, chromosomal microarray analysis revealed pathogenic de novo copy number variants with new clinical features. Chromosomal microarray analysis in the Turkish population has been reported in the largest patient cohort to date.

Genetic underpinnings explored: OPA1 deletion and complex phenotypes on chromosome 3q29.

BACKGROUND: Copy number variations (CNVs) have emerged as significant contributors to the elusive genetic causality of inherited eye diseases. In this study, we describe a case with optic atrophy and a brain aneurysm, in which a de novo CNV 3q29 deletion was identified. CASE PRESENTATION: A 40-year-old female patient was referred to our department after undergoing aneurysm transcatheter arterial embolization for a brain aneurysm. She had no history of systemic diseases, except for unsatisfactory best-corrected visual acuity (BCVA) since elementary school. Electrophysiological tests confirmed the findings in retinal images, indicating optic nerve atrophy. Chromosomal microarray analysis revealed a de novo deletion spanning 960 kb on chromosome 3q29, encompassing OPA1 and six neighboring genes. Unlike previously reported deletions in this region associated with optic atrophy, neuropsychiatric disorders, and obesity, this patient displayed a unique combination of optic atrophy and a brain aneurysm. However, there is no causal relationship between the brain aneurysm and the CNV. CONCLUSION: In conclusion, the optic atrophy is conclusively attributed to the OPA1 deletion, and the aneurysm could be a coincidental association. The report emphasizes the likelihood of underestimating OPA1 deletions due to sequencing technology limitations. Recognizing these constraints, healthcare professionals must acknowledge these limitations and consistently search for OPA1 variants/deletions in Autosomal Dominant Optic Atrophy (ADOA) patients with negative sequencing results. This strategic approach ensures a more comprehensive exploration of copy-number variations, ultimately enhancing diagnostic precision in the field of genetic disorders.

High clonal diversity and spatial genetic admixture in early prostate cancer and surrounding normal tissue.

Somatic copy number alterations (SCNAs) are pervasive in advanced human cancers, but their prevalence and spatial distribution in early-stage, localized tumors and their surrounding normal tissues are poorly characterized. Here, we perform multi-region, single-cell DNA sequencing to characterize the SCNA landscape across tumor-rich and normal tissue in two male patients with localized prostate cancer. We identify two distinct karyotypes: 'pseudo-diploid' cells harboring few SCNAs and highly aneuploid cells. Pseudo-diploid cells form numerous small-sized subclones ranging from highly spatially localized to broadly spread subclones. In contrast, aneuploid cells do not form subclones and are detected throughout the prostate, including normal tissue regions. Highly localized pseudo-diploid subclones are confined within tumor-rich regions and carry deletions in multiple tumor-suppressor genes. Our study reveals that SCNAs are widespread in normal and tumor regions across the prostate in localized prostate cancer patients and suggests that a subset of pseudo-diploid cells drive tumorigenesis in the aging prostate.

Disease modeling and pharmacological rescue of autosomal dominant retinitis pigmentosa associated with RHO copy number variation.

Retinitis pigmentosa (RP), a heterogenous group of inherited retinal disorder, causes slow progressive vision loss with no effective treatments available. Mutations in the rhodopsin gene (RHO) account for ~25% cases of autosomal dominant RP (adRP). In this study, we describe the disease characteristics of the first-ever reported mono-allelic copy number variation (CNV) in RHO as a novel cause of adRP. We (a) show advanced retinal degeneration in a male patient (68 years of age) harboring four transcriptionally active intact copies of rhodopsin, (b) recapitulated the clinical phenotypes using retinal organoids, and (c) assessed the utilization of a small molecule, Photoregulin3 (PR3), as a clinically viable strategy to target and modify disease progression in RP patients associated with RHO-CNV. Patient retinal organoids showed photoreceptors dysgenesis, with rod photoreceptors displaying stunted outer segments with occasional elongated cilia-like projections (microscopy); increased RHO mRNA expression (quantitative real-time PCR [qRT-PCR] and bulk RNA sequencing); and elevated levels and mislocalization of rhodopsin protein (RHO) within the cell body of rod photoreceptors (western blotting and immunohistochemistry) over the extended (300 days) culture time period when compared against control organoids. Lastly, we utilized PR3 to target NR2E3, an upstream regulator of RHO, to alter RHO expression and observed a partial rescue of RHO protein localization from the cell body to the inner/outer segments of rod photoreceptors in patient organoids. These results provide a proof-of-principle for personalized medicine and suggest that RHO expression requires precise control. Taken together, this study supports the clinical data indicating that RHO-CNV associated adRPdevelops as a result of protein overexpression, thereby overloading the photoreceptor post-translational modification machinery.

Biallelic variants identified in 36 Pakistani families and trios with autism spectrum disorder.

With its high rate of consanguineous marriages and diverse ethnic population, little is currently understood about the genetic architecture of autism spectrum disorder (ASD) in Pakistan. Pakistan has a highly ethnically diverse population, yet with a high proportion of endogamous marriages, and is therefore anticipated to be enriched for biallelic disease-relate variants. Here, we attempt to determine the underlying genetic abnormalities causing ASD in thirty-six small simplex or multiplex families from Pakistan. Microarray genotyping followed by homozygosity mapping, copy number variation analysis, and whole exome sequencing were used to identify candidate. Given the high levels of consanguineous marriages among these families, autosomal recessively inherited variants were prioritized, however de novo/dominant and X-linked variants were also identified. The selected variants were validated using Sanger sequencing. Here we report the identification of sixteen rare or novel coding variants in fifteen genes (ARAP1, CDKL5, CSMD2, EFCAB12, EIF3H, GML, NEDD4, PDZD4, POLR3G, SLC35A2, TMEM214, TMEM232, TRANK1, TTC19, and ZNF292) in affected members in eight of the families, including ten homozygous variants in four families (nine missense, one loss of function). Three heterozygous de novo mutations were also identified (in ARAP1, CSMD2, and NEDD4), and variants in known X-linked neurodevelopmental disorder genes CDKL5 and SLC35A2. The current study offers information on the genetic variability associated with ASD in Pakistan, and demonstrates a marked enrichment for biallelic variants over that reported in outbreeding populations. This information will be useful for improving approaches for studying ASD in populations where endogamy is commonly practiced.

scGAL: unmask tumor clonal substructure by jointly analyzing independent single-cell copy number and scRNA-seq data.

BACKGROUND: Accurately deciphering clonal copy number substructure can provide insights into the evolutionary mechanism of cancer, and clustering single-cell copy number profiles has become an effective means to unmask intra-tumor heterogeneity (ITH). However, copy numbers inferred from single-cell DNA sequencing (scDNA-seq) data are error-prone due to technically confounding factors such as amplification bias and allele-dropout, and this makes it difficult to precisely identify the ITH. RESULTS: We introduce a hybrid model called scGAL to infer clonal copy number substructure. It combines an autoencoder with a generative adversarial network to jointly analyze independent single-cell copy number profiles and gene expression data from same cell line. Under an adversarial learning framework, scGAL exploits complementary information from gene expression data to relieve the effects of noise in copy number data, and learns latent representations of scDNA-seq cells for accurate inference of the ITH. Evaluation results on three real cancer datasets suggest scGAL is able to accurately infer clonal architecture and surpasses other similar methods. In addition, assessment of scGAL on various simulated datasets demonstrates its high robustness against the changes of data size and distribution. scGAL can be accessed at: https://github.com/zhyu-lab/scgal . CONCLUSIONS: Joint analysis of independent single-cell copy number and gene expression data from a same cell line can effectively exploit complementary information from individual omics, and thus gives more refined indication of clonal copy number substructure.

Clustering of HR + /HER2- breast cancer in an Asian cohort is driven by immune phenotypes.

Breast cancer exhibits significant heterogeneity, manifesting in various subtypes that are critical in guiding treatment decisions. This study aimed to investigate the existence of distinct subtypes of breast cancer within the Asian population, by analysing the transcriptomic profiles of 934 breast cancer patients from a Malaysian cohort. Our findings reveal that the HR + /HER2- breast cancer samples display a distinct clustering pattern based on immune phenotypes, rather than conforming to the conventional luminal A-luminal B paradigm previously reported in breast cancers from women of European descent. This suggests that the activation of the immune system may play a more important role in Asian HR + /HER2- breast cancer than has been previously recognized. Analysis of somatic mutations by whole exome sequencing showed that counter-intuitively, the cluster of HR + /HER2- samples exhibiting higher immune scores was associated with lower tumour mutational burden, lower homologous recombination deficiency scores, and fewer copy number aberrations, implicating the involvement of non-canonical tumour immune pathways. Further investigations are warranted to determine the underlying mechanisms of these pathways, with the potential to develop innovative immunotherapeutic approaches tailored to this specific patient population.

Malformations of cortical development: Fetal imaging and genetics.

BACKGROUND: Malformations of cortical development (MCD) are a group of congenital disorders characterized by structural abnormalities in the brain cortex. The clinical manifestations include refractory epilepsy, mental retardation, and cognitive impairment. Genetic factors play a key role in the etiology of MCD. Currently, there is no curative treatment for MCD. Phenotypes such as epilepsy and cerebral palsy cannot be observed in the fetus. Therefore, the diagnosis of MCD is typically based on fetal brain magnetic resonance imaging (MRI), ultrasound, or genetic testing. The recent advances in neuroimaging have enabled the in-utero diagnosis of MCD using fetal ultrasound or MRI. METHODS: The present study retrospectively reviewed 32 cases of fetal MCD diagnosed by ultrasound or MRI. Then, the chromosome karyotype analysis, single nucleotide polymorphism array or copy number variation sequencing, and whole-exome sequencing (WES) findings were presented. RESULTS: Pathogenic copy number variants (CNVs) or single-nucleotide variants (SNVs) were detected in 22 fetuses (three pathogenic CNVs [9.4%, 3/32] and 19 SNVs [59.4%, 19/32]), corresponding to a total detection rate of 68.8% (22/32). CONCLUSION: The results suggest that genetic testing, especially WES, should be performed for fetal MCD, in order to evaluate the outcomes and prognosis, and predict the risk of recurrence in future pregnancies.

Biomarkers for progressive multifocal leukoencephalopathy: emerging data for use of JC virus DNA copy number in clinical trials.

Progressive multifocal leukoencephalopathy is a rare but devastating demyelinating disease caused by the JC virus (JCV), for which no therapeutics are approved. To make progress towards addressing this unmet medical need, innovations in clinical trial design are needed. Quantitative JCV DNA in CSF has the potential to serve as a valuable biomarker of progressive multifocal leukoencephalopathy disease and treatment response in clinical trials to expedite therapeutic development, as do neuroimaging and other fluid biomarkers such as neurofilament light chain. Specifically, JCV DNA in CSF could be used in clinical trials as an entry criterion, stratification factor, or predictor of clinical outcomes. Insights from the investigation of candidate biomarkers for progressive multifocal leukoencephalopathy might inform approaches to biomarker development for other rare diseases.

IQGAP3 promotes the progression of glioma as an immune and prognostic marker.

Background: IQGAP3 plays a crucial role in regulating cell proliferation, division, and cytoskeletal organization. Abnormal expression of IQGAP3 has been linked to various tumors, but its function in glioma is not well understood. Methods: Various methods, including genetic differential analysis, single-cell analysis, ROC curve analysis, Cox regression, Kaplan-Meier analysis, and enrichment analysis, were employed to analyze the expression patterns, diagnostic potential, prognostic implications, and biological processes involving IQGAP3 in normal and tumor tissues. The impact of IQGAP3 on immune infiltration and the immune microenvironment in gliomas was evaluated using immunofluorescence. Additionally, the cBioPortal database was used to analyze copy number variations and mutation sites of IQGAP3. Experimental validation was also performed to assess the effects of IQGAP3 on glioma cells and explore underlying mechanisms. Results: High IQGAP3 expression in gliomas is associated with an unfavorable prognosis, particularly in wild-type IDH and 1p/19q non-codeleted gliomas. Enrichment analysis revealed that IQGAP3 is involved in regulating the cell cycle, PI3K/AKT signaling, p53 signaling, and PLK1-related pathways. Furthermore, IQGAP3 expression may be closely related to the immunosuppressive microenvironment of glioblastoma. BRD-K88742110 and LY-303511 are potential drugs for targeting IQGAP3 in anti-glioma therapy. In vitro experiments showed that downregulation of IQGAP3 inhibits the proliferation and migration of glioma cells, with the PLK1/PI3K/AKT pathway potentially playing a crucial role in IQGAP3-mediated glioma progression. Conclusion: IQGAP3 shows promise as a valuable biomarker for diagnosis, prognosis, and immunotherapeutic strategies in gliomas.

[Prenatal diagnosis of fetal microdeletion and microduplication syndromes among pregnant women with advanced maternal ages].

OBJECTIVE: To assess the value of combined chromosomal karyotyping and chromosomal microarray analysis (CMA) and/or copy number variation sequencing (CNV-seq) for the prenatal diagnosis for women with advanced maternal ages, and to explore the challenges of prenatal genetic counseling brought by the types of fetal CNVs and uncertainty of related phenotypes. METHODS: A retrospective analysis was carried out on 1 841 women with advanced maternal age who underwent interventional prenatal diagnosis at the Prenatal Diagnosis Center of Xiamen University Affiliated Women and Children's Hospital from January 2017 to December 2020. Routine chromosomal karyotyping analysis and CMA/CNV-seq detection were carried out. RESULTS: CMA/CNV-seq had detected pathogenic variants in 2 cases which had failed karyotyping analysis. Two hundred and twenty one fetal chromosomal abnormalities were detected by karyotyping analysis, among which 187 were detected by CMA/CNV-seq. CMA/CNV-seq analysis of 23 cases with balanced chromosome structural aberrations and 10 cases with low proportion mosaicisms (including a marker chromosome) had yielded a negative result. In addition, 26 cases (26/1 841, 1.4%) with pathogenic CNVs were discovered among those with a normal karyotype, of which 13 (50.0%) were recurrent CNVs associated with neurocognitive impairment, with 22q11.21 microdeletions and microduplications being the most common types (26.92%). CONCLUSION: The combination of karyotyping analysis and CMA/CNV-seq not only increased the rate of prenatal diagnosis, but also complemented with each other, which has facilitated genetic counseling and formulation of prenatal diagnosis strategy for the affected families.

[Prenatal diagnosis of a case with Congenital myasthenic syndrome due to compound heterozygous variants of SCN4A gene].

OBJECTIVE: To explore the clinical and genetic characteristics of a fetus diagnosed with Congenital myasthenic syndrome type 16 (CMS16). METHODS: A couple who had visited Tianjin Medical University General Hospital in February 2018 due to "adverse outcome of two pregnancies" was selected as the study subject. Clinical data was gathered. Peripheral blood and amniotic fluid samples were collected and subjected to whole exome sequencing (WES). Candidate variant was verified by Sanger sequencing. Low-depth whole-genome sequencing was carried out to detect copy number variation (CNV) in the fetus. RESULTS: The couple's first pregnancy had resulted in a miscarriage at 27+5 weeks, when ultrasound had revealed pleural effusion and polyhydramnios in the fetus. Their second pregnancy was terminated at 30+5 weeks due to fetal hand malformations, polyhydramnios and pleural fluid. Both couple had denied family history of genetic conditions. For their third pregnancy, no CNV abnormality was detected, whilst a compound heterozygous variants, including a maternally derived c.3172C>T (p.R1058W) and paternal c.1431delG (p.K477fs*89) in the SCN4A gene were detected. Based on the guidelines from the American College of Medical Genetics and Genomics, the c.3172C>T (p.R1058W) was predicted as a likely pathogenic variant (PM1+PM2_supporting+PP3+PP4), whilst the c.1431delG (p.K477fs*89) was predicted as a pathogenic variant (PVS1+PM2_supporting+PP4). CONCLUSION: The c.3172C>T (p.R1058W) and c.1431delG (p.K477fs*89) compound heterozygous variants of the SCN4A gene probably underlay the CMS16 in the third fetus.

Genetic determinants of plasma protein levels in the Estonian population.

The proteome holds great potential as an intermediate layer between the genome and phenome. Previous protein quantitative trait locus studies have focused mainly on describing the effects of common genetic variations on the proteome. Here, we assessed the impact of the common and rare genetic variations as well as the copy number variants (CNVs) on 326 plasma proteins measured in up to 500 individuals. We identified 184 cis and 94 trans signals for 157 protein traits, which were further fine-mapped to credible sets for 101 cis and 87 trans signals for 151 proteins. Rare genetic variation contributed to the levels of 7 proteins, with 5 cis and 14 trans associations. CNVs were associated with the levels of 11 proteins (7 cis and 5 trans), examples including a 3q12.1 deletion acting as a hub for multiple trans associations; and a CNV overlapping NAIP, a sensor component of the NAIP-NLRC4 inflammasome which is affecting pro-inflammatory cytokine interleukin 18 levels. In summary, this work presents a comprehensive resource of genetic variation affecting the plasma protein levels and provides the interpretation of identified effects.

Spatial transcriptomics reveals discrete tumour microenvironments and autocrine loops within ovarian cancer subclones.

High-grade serous ovarian carcinoma (HGSOC) is genetically unstable and characterised by the presence of subclones with distinct genotypes. Intratumoural heterogeneity is linked to recurrence, chemotherapy resistance, and poor prognosis. Here, we use spatial transcriptomics to identify HGSOC subclones and study their association with infiltrating cell populations. Visium spatial transcriptomics reveals multiple tumour subclones with different copy number alterations present within individual tumour sections. These subclones differentially express various ligands and receptors and are predicted to differentially associate with different stromal and immune cell populations. In one sample, CosMx single molecule imaging reveals subclones differentially associating with immune cell populations, fibroblasts, and endothelial cells. Cell-to-cell communication analysis identifies subclone-specific signalling to stromal and immune cells and multiple subclone-specific autocrine loops. Our study highlights the high degree of subclonal heterogeneity in HGSOC and suggests that subclone-specific ligand and receptor expression patterns likely modulate how HGSOC cells interact with their local microenvironment.

Identification and validation of a novel anoikis-related prognostic model for prostate cancer.

BACKGROUND: Anoikis resistance is a hallmark characteristic of oncogenic transformation, which is crucial for tumor progression and metastasis. The aim of this study was to identify and validate a novel anoikis-related prognostic model for prostate cancer (PCa). METHODS: We collected a gene expression profile, single nucleotide polymorphism mutation and copy number variation (CNV) data of 495 PCa patients from the TCGA database and 140 PCa samples from the MSKCC dataset. We extracted 434 anoikis-related genes and unsupervised consensus cluster analysis was used to identify molecular subtypes. The immune infiltration, molecular function, and genome alteration of subtypes were evaluated. A risk signature was developed using Cox regression analysis and validated with the MSKCC dataset. We also identify potential drugs for high-risk group patients. RESULTS: Two subtypes were identified. C1 exhibited a higher level of CNV amplification, immune score, stromal score, aneuploidy score, homologous recombination deficiency, intratumor heterogeneity, single-nucleotide variant neoantigens, and tumor mutational burden compared to C2. C2 showed a better survival outcome and had a high level of gamma delta T cell and activated B cell infiltration. The risk signature consisting of four genes (HELLS, ZWINT, ABCC5, and TPSB2) was developed (area under the curve = 0.780) and was found to be an independent prognostic factor for overall survival in PCa patients. Four CTRP-derived and four PRISM-derived compounds were identified for high-risk patients. CONCLUSIONS: The anoikis-related prognostic model developed in this study could be a useful tool for clinical decision-making. This study may provide a new perspective for the treatment of anoikis-related PCa.

Genomic Copy Number Analysis Using Droplet Digital PCR: A Simple Method with EvaGreen Single-Color Fluorescent Design.

Droplet digital PCR (ddPCR) is an emerging method for the absolute quantification of PCR products, and it can detect DNA copy numbers accurately. It analyzes the end-point absolute fluorescence signals of the PCR-positive droplets and calculates the target concentration. EvaGreen is a nonspecific double-stranded DNA-binding fluorescent dye, and the ddPCR system also supports assays using this cost-effective hydrolysis probe. Here, we describe a simple method of quantification for DNA copy numbers using the EvaGreen single-color fluorescent design.

Multiomics-Based Feature Extraction and Selection for the Prediction of Lung Cancer Survival.

Lung cancer is a global health challenge, hindered by delayed diagnosis and the disease's complex molecular landscape. Accurate patient survival prediction is critical, motivating the exploration of various -omics datasets using machine learning methods. Leveraging multi-omics data, this study seeks to enhance the accuracy of survival prediction by proposing new feature extraction techniques combined with unbiased feature selection. Two lung adenocarcinoma multi-omics datasets, originating from the TCGA and CPTAC-3 projects, were employed for this purpose, emphasizing gene expression, methylation, and mutations as the most relevant data sources that provide features for the survival prediction models. Additionally, gene set aggregation was shown to be the most effective feature extraction method for mutation and copy number variation data. Using the TCGA dataset, we identified 32 molecular features that allowed the construction of a 2-year survival prediction model with an AUC of 0.839. The selected features were additionally tested on an independent CPTAC-3 dataset, achieving an AUC of 0.815 in nested cross-validation, which confirmed the robustness of the identified features.

Ancient Duplication and Lineage-Specific Transposition Determine Evolutionary Trajectory of ERF Subfamily across Angiosperms.

AP2/ERF transcription factor family plays an important role in plant development and stress responses. Previous studies have shed light on the evolutionary trajectory of the AP2 and DREB subfamilies. However, knowledge about the evolutionary history of the ERF subfamily in angiosperms still remains limited. In this study, we performed a comprehensive analysis of the ERF subfamily from 107 representative angiosperm species by combining phylogenomic and synteny network approaches. We observed that the expansion of the ERF subfamily was driven not only by whole-genome duplication (WGD) but also by tandem duplication (TD) and transposition duplication events. We also found multiple transposition events in Poaceae, Brassicaceae, Poales, Brassicales, and Commelinids. These events may have had notable impacts on copy number variation and subsequent functional divergence of the ERF subfamily. Moreover, we observed a number of ancient tandem duplications occurred in the ERF subfamily across angiosperms, e.g., in Subgroup IX, IXb originated from ancient tandem duplication events within IXa. These findings together provide novel insights into the evolution of this important transcription factor family.