scholarly journals MRP8, A New Member of ABC Transporter Superfamily, Identified by EST Database Mining and Gene Prediction Program, Is Highly Expressed in Breast Cancer

2001 ◽  
Vol 7 (8) ◽  
pp. 509-516 ◽  
Author(s):  
Tapan K. Bera ◽  
Sanghyuk Lee ◽  
Giuliana Salvatore ◽  
Byungkook Lee ◽  
Ira Pastan
Keyword(s):  
Breast Cancer ◽  
Abc Transporter ◽  
Gene Prediction ◽  
Database Mining ◽  
Gene Prediction Program ◽  
Est Database ◽  
Prediction Program

scholarly journals ASPic-GeneID: A Lightweight Pipeline for Gene Prediction and Alternative Isoforms Detection

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Tyler Alioto ◽  
Ernesto Picardi ◽  
Roderic Guigó ◽  
Graziano Pesole
Keyword(s):  
Ab Initio ◽  
Gene Annotation ◽  
Gene Prediction ◽  
Gene Prediction Program ◽  
C Elegans ◽  
Prediction Program ◽  
First Pass ◽  
Main Components ◽  
Genome Projects ◽  
Alternative Isoforms

New genomes are being sequenced at an increasingly rapid rate, far outpacing the rate at which manual gene annotation can be performed. Automated genome annotation is thus necessitated by this growth in genome projects; however, full-fledged annotation systems are usually home-grown and customized to a particular genome. There is thus a renewed need for accurateab initiogene prediction methods. However, it is apparent that fullyab initiomethods fall short of the required level of sensitivity and specificity for a quality annotation. Evidence in the form of expressed sequences gives the single biggest improvement in accuracy when used to inform gene predictions. Here, we present a lightweight pipeline for first-pass gene prediction on newly sequenced genomes. The two main components are ASPic, a program that derives highly accurate, albeit not necessarily complete, EST-based transcript annotations from EST alignments, and GeneID, a standard gene prediction program, which we have modified to take as evidence intron annotations. The introns output by ASPic CDS predictions is given to GeneID to constrain the exon-chaining process and produce predictions consistent with the underlying EST alignments. The pipeline was successfully tested on the entireC. elegansgenome and the 44 ENCODE human pilot regions.

scholarly journals Genome resources of four distinct pathogenic races within Fusarium oxysporum f. sp. vasinfectum that cause vascular wilt disease of cotton

2020 ◽  
Author(s):  
Subodh K Srivastava ◽  
Kurt Zeller ◽  
James H Sobieraj ◽  
Mark K Nakhla
Keyword(s):  
Fusarium Oxysporum ◽  
Gene Prediction ◽  
Whole Genome Sequence ◽  
Vascular Wilt ◽  
Gene Prediction Program ◽  
Public Health Agencies ◽  
Prediction Program ◽  
Methods Development ◽  
Pathogenic Races ◽  
And Control

Whole Genome Sequence (WGS) based identifications are being increasingly used by regulatory and public health agencies to facilitate the detection, investigation, and control of pathogens and pests. Fusarium oxysporum f. sp. vasinfectum (FOV) is a significant vascular wilt pathogen of cultivated cotton, and consists of several pathogenic races that are not each other’s closest phylogenetic relatives. We have developed WGS assemblies for isolates of race 1 (FOV1), race 4 (FOV4), race 5 (FOV5), and race 8 (FOV8) using a combination of Nanopore (MinION) and Illumina sequencing technology (Mi-Seq). This resulted in assembled contigs with more than 100X coverage for each of the FOV races and estimated genome sizes of FOV1 52 Mb, FOV4 68 Mb, FOV5 68 Mb and FOV8 55 Mb. The AUGUSTUS gene prediction program predicted 16,263 genes in FOV1, 20,259 genes in FOV4, 20,375 genes in FOV5 and 16,615 genes in FOV8. We were able to identify 525 genes unique to FOV1, 570 unique to FOV4, 1242 unique to FOV5 and 383 unique to FOV8. We expect that these findings will help in comparative genomics, and in the identification of unique genes as candidate targets for diagnostic marker and methods development to permit rapid differentiation of FOV subgroups.

Narrowing and genomic annotation of the commonly deleted region of the 5q− syndrome

Blood ◽  
2002 ◽  
Vol 99 (12) ◽  
pp. 4638-4641 ◽  
Author(s):  
Jacqueline Boultwood ◽  
Carrie Fidler ◽  
Amanda J. Strickson ◽  
Fiona Watkins ◽  
Susana Gama ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Gene Prediction ◽  
The Novel ◽  
Gene Prediction Program ◽  
Hematopoietic Stem ◽  
Prediction Program ◽  
Genomic Annotation ◽  
Cd34 Cells ◽  
The Common ◽  
Complete Genomic

The 5q− syndrome is the most distinct of the myelodysplastic syndromes, and the molecular basis for this disorder remains unknown. We describe the narrowing of the common deleted region (CDR) of the 5q− syndrome to the approximately 1.5-megabases interval at 5q32 flanked by D5S413 and theGLRA1 gene. The Ensembl gene prediction program has been used for the complete genomic annotation of the CDR. The CDR is gene rich and contains 24 known genes and 16 novel (predicted) genes. Of 40 genes in the CDR, 33 are expressed in CD34+ cells and, therefore, represent candidate genes since they are expressed within the hematopoietic stem/progenitor cell compartment. A number of the genes assigned to the CDR represent good candidates for the 5q− syndrome, including MEGF1, G3BP, and several of the novel gene predictions. These data now afford a comprehensive mutational/expression analysis of all candidate genes assigned to the CDR.

scholarly journals d Rhamnose β-hederin reverses chemoresistance of breast cancer cells by regulating exosome-mediated resistance transmission

2018 ◽  
Vol 38 (5) ◽  
Author(s):  
Wei-xian Chen ◽  
Ling-yun Xu ◽  
Qi Qian ◽  
Xiao He ◽  
Wen-ting Peng ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Cells ◽  
Breast Cancer Cells ◽  
Target Gene ◽  
Gene Prediction ◽  
Docetaxel Resistance ◽  
Resistance Reversal ◽  
Mcf 7 ◽  
Chinese Medicinal Plant

d Rhamnose β-hederin (DRβ-H), an active component extracted from the traditional Chinese medicinal plant Clematis ganpiniana, has been reported to be effective against breast cancer. Recent studies have also indicated that the isolated exosomes (D/exo) from docetaxel-resistant breast cancer cells MCF-7 (MCF-7/Doc) were associated with resistance transmission by delivering genetic cargo. However, the relevance of D/exo during DRβ-H exposure remains largely unclear. In the present work, exosomes were characterized by morphology and size distribution. We reinforced the significant role of D/exo in spreading chemoresistance from MCF-7/Doc to recipient sensitive cells after absorption and internalization. DRβ-H could reduce the formation and release of D/exo. Next, we demonstrated that DRβ-H was able to reverse docetaxel resistance and that D/exo was responsible for DRβ-H-mediated resistance reversal. We also found that DRβ-H could decrease the expressions of several most abundant miRNAs (miR-16, miR-23a, miR-24, miR-26a, and miR-27a) transported by D/exo. Target gene prediction and pathway analysis showed the involvement of these selected miRNAs in pathways related to treatment failure. Our results suggested that DRβ-H could reduce D/exo secretion from MCF-7/Doc cells and induce the reduction in resistance transmission via D/exo.

scholarly journals A Novel Ferroptosis-Related Gene Signature Predicts Overall Survival of Breast Cancer Patients

Biology ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 151
Author(s):  
Haifeng Li ◽  
Lu Li ◽  
Cong Xue ◽  
Riqing Huang ◽  
Anqi Hu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Overall Survival ◽  
Prediction Model ◽  
Risk Score ◽  
Cox Regression ◽  
Gene Prediction ◽  
Clinical Information ◽  
Risk Groups ◽  
Gene Signature ◽  
Breast Cancer Patients

Breast cancer is the second leading cause of death in women, thus a reliable prognostic model for overall survival (OS) in breast cancer is needed to improve treatment and care. Ferroptosis is an iron-dependent cell death. It is already known that siramesine and lapatinib could induce ferroptosis in breast cancer cells, and some ferroptosis-related genes were closely related with the outcomes of treatments regarding breast cancer. The relationship between these genes and the prognosis of OS remains unclear. The data of gene expression and related clinical information was downloaded from public databases. Based on the TCGA-BRCA cohort, an 8-gene prediction model was established with the least absolute shrinkage and selection operator (LASSO) cox regression, and this model was validated in patients from the METABRIC cohort. Based on the median risk score obtained from the 8-gene model, patients were stratified into high- or low-risk groups. Cox regression analyses identified that the risk score was an independent predictor for OS. The findings from CIBERSORT and ssGSEA presented noticeable differences in enrichment scores for immune cells and pathways between the abovementioned two risk groups. To sum up, this prediction model has potential to be widely applied in future clinical settings.

Sign in / Sign up

Export Citation Format

Share Document