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RANBP2 gene duplication in the pericentromeric region of chromosome 2.a, Gene composition. Each coloured bar/arrow represents a different gene; segmentally duplicated regions are highlighted with grey boxes. RANBP2 and its eight paralogues are shown as red and orange arrows, respectively. Regions of orthology in mouse chromosomes 17 (orange), 10 (yellow) and 2 (green) are reported above the human gene bar. Scale bar, 310 kb. b, Filled boxes indicate evidence for expression of genes in a. c, Gene and protein domain architecture of RanBP2 and the RGP family (RGP1–8). Black lines show exon/intron boundaries; pink boxes show Ran binding domains; blue boxes show zinc-finger domains; yellow box shows a cyclophilin A-homologous domain; green boxes show GRIP domains. Scale bar, 300 amino acids.
Source publication
Human chromosome 2 is unique to the human lineage in being the product of a head-to-head fusion of two intermediate-sized ancestral chromosomes. Chromosome 4 has received attention primarily related to the search for the Huntington's disease gene, but also for genes associated with Wolf-Hirschhorn syndrome, polycystic kidney disease and a form of m...
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... spot on chromosome 2q (ref. 38). Through a series of rearrange- ments, this region underwent exon shuffling, domain accretion and deletion, suggesting that this entire region has been extremely dynamic over the last several million years. In a detailed examin- ation of this region, we discovered eight new genes that arose by duplication of RANBP2 (Fig. 2). We called the new gene family RGP, for RanBP2-like, GRIP domain-containing proteins. The RGP copies are interspersed in a 9-Mb region on both sides of the centromere, and have significantly modified their gene structure compared with RANBP2. There is experimental evidence for expression of almost all of the copies 39 , including ...
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... performed a detailed analysis of duplicated sequence ($90% sequence identity and $1 kb in length), compar- ing the finished chromosome assemblies to the human genome sequence. Both chromosomes 2 and 4 show less segmental dupli- cation (4.2% and 2.3%, respectively) than the genome average (5.2%) (Supplementary Table 6 and Supplementary Fig. 2). The reduction in segmental duplications on chromosome 4 is especially noticeable within the pericentromeric regions of 4q11-q12, where not a single duplication could be detected within 2 Mb of the centromere. ...
Citations
... Currently, scholars at home and abroad have conducted systematic research on data annotation [3], which is widely used in the fields of automatic driving [4], intelligent security [5], smart medical care [6], Industry 4.0 [7], new retail and so on, and has played a significant role in promoting the development of artificial intelligence. For data annotation methods, according to the annotation object, it can be divided into image annotation, video annotation, voice annotation and text annotation; According to the form of the composition of the annotation, it can be divided into structured annotation, unstructured annotation and semi-structured annotation; According to the type of annotator, it can be divided into manual annotation and machine annotation; According to the task type, it can be divided into classification annotation [8], standard condition annotation [9], region annotation [10], point tracing annotation [11], abstract annotation [12], etc. Meanwhile, many enterprises and research institutions have launched public datasets with annotations, such as image annotation tool set ImageNet and COCO, video annotation dataset Youtube-8M and Kinetics, text annotation dataset Yelp [13] and IMDB [14], voice annotation dataset LibriSpeech and AudioSet. ...
With the development of information technology and the increasing complexity of industrial technology, there is an urgent need for a certain field to use big data and artificial intelligence to improve the management and decision-making level. In order to classify the field’s risk text data through intelligent algorithms, analysing the risk distribution and the major problems, this paper researches on the annotation methods of training data in this field. The proposed data annotation method is based on pattern matching, addressing the special problems of risk data annotation in this field (such as strong professionalism, small data volume, high accuracy requirement and timeliness requirements). A new matching pattern is generated through the steps of text segmentation, keyword extraction, pattern preliminary generation, pattern relation tree construction, pattern optimization, pattern generalization, pattern verification, classification and annotation, and final classification and annotation are performed after pattern matching. Performance tests in terms of accuracy, recall rate, and annotation time have shown that the overall performance of the proposed method outperforms that of traditional item-by-item manual annotation, and semi-automatic annotation methods through machine learning. The method described in this paper has strong application value for risk data annotation in this field, and also has certain reference significance for high-density, high-accuracy and high-timeliness data annotation in other fields.
... The primer sets were designed from the downstream region of the PCDH7 gene (location 30.7 to 31.1Mb) where 5.2 Mb is the gene desert region of chromosome 4 [53] is present. The primers sequences are (F: 5′-CATCACGCCCGGCTAATTTT-3′; R: 5′-TCATGCCTGTAATCCCAGCA-3′) and the product size was 132. ...
... Ring finger protein 149 (RNF149), a is a 400-amino acid protein located on chromosome 2 (2q11.2) which contains a C3H2C3 domain, was predicted to be involved in ubiquitin-dependent protein catabolic process and within cellular response to xenobiotic stimulusor regulation of protein stability [10,11]. Previously, by performing the Illumina Human Exome Array, Stephanie J Loomis reported that RNF149 association with the genetic architecture of nuclear sclerosis in 1488 participants of European ancestry in the Beaver Dam Eye Study [12]. ...
Chemo-resistance has been identified as a crucial factor contributing to tumor recurrence and a leading cause of worse prognosis in patients with ESCC. Therefore, unravel the critical regulators and effective strategies to overcome drug resistance will have a significant clinical impact on the disease. In our study we found that RNF149 was upregulated in ESCC and high RNF149 expression was associated with poor prognosis with ESCC patients. Functionally, we have demonstrated that overexpression of RNF149 confers CDDP resistance to ESCC; however, inhibition of RNF149 reversed this phenomenon both in vitro and in vivo. Mechanistically, we demonstrated that RNF149 interacts with PH domain and leucine rich repeat protein phosphatase 2 (PHLPP2) and induces E3 ligase-dependent protein degradation of PHLPP2, substantially activating the PI3K/AKT signalling pathway in ESCC. Additionally, we found that inhibition of PI3K/AKT signalling pathway by AKT siRNA or small molecule inhibitor significantly suppressed RNF149-induced CDDP resistance. Importantly, RNF149 locus was also found to be amplified not only in ESCC but also in various human cancer types. Our data suggest that RNF149 might function as an oncogenic gene. Targeting the RNF149/PHLPP2/PI3K/Akt axis may be a promising prognostic factor and valuable therapeutic target for malignant tumours.
... Ring nger protein 149 (RNF149), a is a 400-amino acid protein located on chromosome 2 (2q11.2) which contains a C3H2C3 domain, was predicted to be involved in ubiquitin-dependent protein catabolic process and within cellular response to xenobiotic stimulusor regulation of protein stability [13,14]. ...
Chemo-resistance has been identified as a crucial factor contributing to tumor recurrence and a leading cause of worse prognosis in patients with ESCC. Therefore, unravel the critical regulators and effective strategies to overcome drug resistance will have a significant clinical impact on the disease. In our study we found that RNF149 was upregulated in ESCC and high RNF149 expression was associated with poor prognosis with ESCC patients. Functionally, we have demonstrated that overexpression of RNF149 confers CDDP resistance to ESCC; however, inhibition of RNF149 reversed this phenomenon both in vitro and in vivo . Mechanistically, we demonstrated that RNF149 interacts with PH domain and leucine rich repeat protein phosphatase 2 (PHLPP2) and induces E3 ligase-dependent protein degradation of PHLPP2, substantially activating the PI3K/AKT signalling in ESCC. Additionally, we found that inhibition of PI3K/AKT signalling by AKT siRNA or small molecule inhibitor significantly suppressed RNF149-induced CDDP resistance. Importantly, RNF149 locus was also found to be amplified not only in ESCC but also in various human cancer types. Our data suggest that RNF149 might function as an oncogenic gene. Targeting the RNF149/PHLPP2/PI3K/Akt axis may be a promising prognostic factor and valuable therapeutic target for malignant tumours.
... In cells stimulated, reversible pores open in the plasma membrane and the membrane potential decreases transiently with an ion flux, both changes of which contribute to IL1B release [8,19]. The data of the Uniport dataset also indicate that in addition to secreted IL1B (IL1B-203 17 kDa), two splice variants exist, named IL1B-202 (12.8 kDa) and IL1B-204 (14.3 kDa), respectively [27]. Although seldom reported, the two variants are likely to be engaged in multiple biological events. ...
Inflammation, especially chronic inflammation, is closely linked to tumor development. As essential chronic inflammatory cytokines, the interleukin family plays a key role in inflammatory infections and malignancies. The interleukin-1 (IL-1) receptor antagonist (IL1RA), as a naturally occurring receptor antagonist, is the first discovered and can compete with IL-1 in binding to the receptor. Recent studies have revealed the association of the polymorphisms in IL1RA with an increased risk of squamous cell carcinomas (SCCs), including squamous cell carcinoma of the head and neck (SCCHN), cervical squamous cell carcinoma, cutaneous squamous cell carcinoma (cSCC), esophageal squamous cell carcinoma (ESCC), and bronchus squamous cell carcinoma. Here, we reviewed the antitumor potential of IL1RA as an IL-1-targeted inhibitor.
... Human chromosome 2 is a unique chromosome that had emerged from a head-to-head fusion of two different acrocentric chromosomes. 1,2 According to the Vega Genome Browser (http://vega. archive.ensembl.org/Homo_sapiens/Location/Chromosome?r52), chromosome 2 is the second largest human chromosome, with a length of 242,193,529 bp and comprises 3409 genes, 1236 protein coding genes, and 1031 pseudogenes. ...
Background:
Copy number variations (CNVs) on chromosome 2 are associated with a variety of human diseases particularly neurodevelopmental disorders. Array comparative genomic hybridization (aCGH) constitutes an added value for the diagnosis of neurodevelopmental or neuropsychiatric diseases. This study aims to establish a genotype-phenotype correlation, reporting CNVs on the chromosome 2, contributing for a better characterization of the molecular significance of rare CNVs in this chromosome.
Methods:
To accomplish this, a cross-sectional study was performed using genetic information included in a database of the Department of Genetics of the Faculty of Medicine and clinical data from Hospital database. CNVs were classified as pathogenic, benign, variants of unknown significance, and likely pathogenic or likely benign, in accordance with the ACMG Standards and Guidelines.
Results:
A total of 2897 patients were studied using aCGH, 32 with CNVs on chromosome 2, 24 classified as likely pathogenic, and 8 as pathogenic. Genomic intervals with a higher incidence were one 2p25.3 and 2q13 regions.
Conclusions:
This study will help to establish new genotype-phenotype correlations, allowing update of databases and literature and the improvement of diagnosis and genetic counseling which could be an added value for prenatal genetic counseling.
... We excluded mutations either not covered by our trimmed models or derived from an isoform different from the one available in the AlphaFold2 database. Concerning MSH2, we did not analyze G936D since our isoform had 934 residues, while R293Q refers to the A0A2R8Y-G02_HUMAN isoform (Hillier et al., 2005). In the case of MSH6, T1125M was removed since derived from the A0A494C0M1_HUMAN transcript (Hillier et al., 2005). ...
... Concerning MSH2, we did not analyze G936D since our isoform had 934 residues, while R293Q refers to the A0A2R8Y-G02_HUMAN isoform (Hillier et al., 2005). In the case of MSH6, T1125M was removed since derived from the A0A494C0M1_HUMAN transcript (Hillier et al., 2005). Furthermore, the following seven variants found in FANCL were also disregarded: S356N, S356N, G322V, F257C, T229A, I199V, and V181I. ...
Reliable prediction of free energy changes upon amino acid substitutions (ΔΔGs) is crucial to investigate their impact on protein stability and protein–protein interaction. Advances in experimental mutational scans allow high‐throughput studies thanks to multiplex techniques. On the other hand, genomics initiatives provide a large amount of data on disease‐related variants that can benefit from analyses with structure‐based methods. Therefore, the computational field should keep the same pace and provide new tools for fast and accurate high‐throughput ΔΔG calculations. In this context, the Rosetta modeling suite implements effective approaches to predict folding/unfolding ΔΔGs in a protein monomer upon amino acid substitutions and calculate the changes in binding free energy in protein complexes. However, their application can be challenging to users without extensive experience with Rosetta. Furthermore, Rosetta protocols for ΔΔG prediction are designed considering one variant at a time, making the setup of high‐throughput screenings cumbersome. For these reasons, we devised RosettaDDGPrediction, a customizable Python wrapper designed to run free energy calculations on a set of amino acid substitutions using Rosetta protocols with little intervention from the user. Moreover, RosettaDDGPrediction assists with checking completed runs and aggregates raw data for multiple variants, as well as generates publication‐ready graphics. We showed the potential of the tool in four case studies, including variants of uncertain significance in childhood cancer, proteins with known experimental unfolding ΔΔGs values, interactions between target proteins and disordered motifs, and phosphomimetics. RosettaDDGPrediction is available, free of charge and under GNU General Public License v3.0, at https://github.com/ELELAB/RosettaDDGPrediction.
... The following is a walkthrough of this assignment with the Programmed cell Death protein 1 (PD-1) 11 discussed at length in the previous review articles. ...
Over the past 64 years, since the first actual, three-dimensional structure of a protein was determined by X-Ray diffraction in 1958,1 the library of solved structures has grown to more than 170,000 (as of 2020).2 With the expansion of our knowledge of structures and the advent of applications to visualize them, the tools to aid in our understanding of these as physical objects have greatly improved. Incorporating these ideas, the following is a walkthrough of a project designed to overcome the lack of sense for proteins as real objects.
... Fluorescence in-situ hybridization (FISH) analyses confirmed that two ancestral Great Ape chromosomes fused at their telomeric repeats to form the HSA2 [4]. Subsequent studies confirmed also the presence of multiple subtelomeric segmental duplications (SD) homologous to other autosomal chromosomes [5] and described the gene content at the fusion site [6,7]. Additionally, the comparison of SDs between the chimpanzee and human genomes not only enabled estimation of the genomic duplication rate, but also suggested SDs as the key cause Poszewiecka et al. ...
Background
The reduction of the chromosome number from 48 in the Great Apes to 46 in modern humans is thought to result from the end-to-end fusion of two ancestral non-human primate chromosomes forming the human chromosome 2 (HSA2). Genomic signatures of this event are the presence of inverted telomeric repeats at the HSA2 fusion site and a block of degenerate satellite sequences that mark the remnants of the ancestral centromere. It has been estimated that this fusion arose up to 4.5 million years ago (Mya).
Results
We have developed an enhanced algorithm for the detection and efficient counting of the locally over-represented weak-to-strong (AT to GC) substitutions. By analyzing the enrichment of these substitutions around the fusion site of HSA2 we estimated its formation time at 0.9 Mya with a 95% confidence interval of 0.4-1.5 Mya. Additionally, based on the statistics derived from our algorithm, we have reconstructed the evolutionary distances among the Great Apes (Hominoidea).
Conclusions
Our results shed light on the HSA2 fusion formation and provide a novel computational alternative for the estimation of the speciation chronology.
... Sanger sequencing of the ATG9A gene was performed as previously described on an Applied Biosystems 96-capillary 3730XL DNA analyzer (ThermoFisher Scientific, 4,331,246) using the BigDye Terminator v3.1 cycle sequencing kit (ThermoFisher Scientific, 4,337,454) [67]. The following primers (F, forward; R, reverse; Table S3) were used: ATG9AF1 and ATG9AR1 to determine the maternal variant (reference sequence GCTCCATCCTG; Figure 1(d)), and ATG9AF2 and ATG9AR2 to determine the paternal variant (reference sequence AGATACCTGCT; Figure 1(d)). ...
Abbreviations:
BCL2: BCL2 apoptosis regulator; BCL10: BCL10 immune signaling adaptor; CARD11: caspase recruitment domain family member 11; CBM: CARD11-BCL10-MALT1; CR2: complement C3d receptor 2; EBNA: Epstein Barr nuclear antigen; EBV: Epstein-Barr virus; FCGR3A; Fc gamma receptor IIIa; GLILD: granulomatous-lymphocytic interstitial lung disease; HV: healthy volunteer; IKBKB/IKB kinase: inhibitor of nuclear factor kappa B kinase subunit beta; IL2RA: interleukin 2 receptor subunit alpha; MALT1: MALT1 paracaspase; MS4A1: membrane spanning 4-domain A1; MTOR: mechanistic target of rapamycin kinase; MYC: MYC proto-oncogene, bHLH: transcription factor; NCAM1: neural cell adhesion molecule 1; NFKB: nuclear factor kappa B; NIAID: National Institute of Allergy and Infectious Diseases; NK: natural killer; PTPRC: protein tyrosine phosphatase receptor type C; SELL: selectin L; PBMCs: peripheral blood mononuclear cells; TR: T cell receptor; Tregs: regulatory T cells; WT: wild-type.
