DOCSLIB.ORG

Jgiid Symbol Entrez.Geneid Unigeneid XT Gi Accession Gene.Name Gene.Function Gene.Synonyms XB.Genpageid XB.Geneid Unigeneid XL M

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Jgiid Symbol Entrez.Geneid Unigeneid XT Gi Accession Gene.Name Gene.Function Gene.Synonyms XB.Genpageid XB.Geneid Unigeneid XL M JgiID symbol Entrez.GeneID UnigeneID_XT gi accession gene.name gene.function gene.synonyms XB.GenpageID XB.GeneID UnigeneID_XL MGI_Symbol EntrezGeneID.MM Seo2007_Ngnr1_NeuroD Seo2007_Ngnr1 Seo2007_NeuroD Masui2010 Thompson2012 baseMean baseMean_Cc_25h_Dex baseMean_Ptf1a-GR_25h_Dex FC_Ptf1a-GR_25h_Dex_vs_Cc_25h_Dex log2FC_Ptf1a-GR_25h_Dex_vs_Cc_25h_Dex FDR Xetrov72000709 prdm13 100490238 301605112 XM_002932160 NA NA NA XB-GENEPAGE-960154 XB-GENE-960155 Prdm13 230025 - - - - - 570,22 1,16 1139,28 528,42 9,05 0,00% Xetrov72003700 nhlh1 100125788 Str.53224 112807514,301615704 CU075470,XM_002937261 nescient helix loop helix 1 transcription factor hen1|nscl|nscl1|bhlha35|hen-1 XB-GENEPAGE-989789 XB-GENE-989790 Xl.49521,Xl.437 Nhlh1 18071 - - Xl.437 - - 261,60 0,00 523,20 524,20 9,03 0,00% Xetrov72009806 sox10 100101700 Str.9225 154147638,134025635 NM_001100221,BC136047 SRY (sex determining region Y)-box 10 HMG-box transcription factor XB-GENEPAGE-480303 XB-GENE-480304 Xl.1588 Sox10 20665 - - - - - 1043,98 3,07 2084,88 512,16 9,00 0,00% Xetrov72b000114 stmn3 779780 Str.53953 111306041,118403633 BC121398,NM_001078859 NA NA NA XB-GENEPAGE-5918430 XB-GENE-5918431 Xl.53848,Xl.11,Xl.49734 Stmn3 20262 - - - - - 198,84 0,00 397,69 398,69 8,64 0,00% Xetrov72025610 dpysl4 548482 Str.9826 77620778,59809116,62751611 CR761623,BC089704,NM_001015765 dihydropyrimidinase-like 4 dihydropyrimidinase crmp3|Collapsin response mediator protein 3 XB-GENEPAGE-960291 XB-GENE-960292 Xl.77348,Xl.75492 Dpysl4 26757 - - - - Dpysl4 1682,62 7,88 3357,37 378,09 8,56 0,00% Xetrov72040456 sncb 394467 Str.65762 37590937,89886433,77626901 BC059756,NM_203541,CR760873 NA NA NA XB-GENEPAGE-973306 XB-GENE-973307 Xl.6203,Xl.14705 Sncb 104069 - - - - - 696,83 2,98 1390,67 349,33 8,45 0,00% Xetrov72038993 pax8 780226 Str.51436 116487492,284413689 BC125805,NM_001079301 paired box 8 paired box transcription factor pax-8|XPax-8|XPax8 XB-GENEPAGE-483692 XB-GENE-483693 Xl.2754,Xl.9880 Pax8 18510 - - - - - 263,57 0,58 526,57 334,12 8,38 0,00% Xetrov72008730 cdh11 548575 Str.56287 59861871,62751445 BC090368,NM_001015858 cadherin 11, type 2, OB-cadherin (osteoblast) cell adhesion OB-cadherin|cadherin-11|Xcad-11 XB-GENEPAGE-483598 XB-GENE-483599 Xl.16169 Cdh11 12552 - - - - - 150,95 0,00 301,90 302,90 8,24 0,00% Xl.60388 - - - - - BP734875 Osada Taira anterior neuroectoderm (ANE) pCS105 cDNA library Xenopus laevis cDNA clone XL503f02ex 3', mRNA sequence [BP734875] - - - Xl.60388 - - - - - - - 148,84 0,00 297,68 298,68 8,22 0,00% Xetrov72012871 slc8a2 100495074 Str.28043 301619836 XM_002939246 solute carrier family 8 (sodium/calcium exchanger), member 2 transmembrane solute exchange ncx2 XB-GENEPAGE-992834 XB-GENE-992835 Slc8a2 110891 - - - - Slc8a2 283,70 1,16 566,24 262,87 8,04 0,00% Xetrov72029702 klhl35 100486151 Str.31425 301623815 XM_002941162 NA NA NA XB-GENEPAGE-1009037 XB-GENE-1009038 Klhl35 72184 - - - - - 122,50 0,00 245,00 246,00 7,94 0,00% Xetrov72036539 fam59b NA Str.34813 NA NA NA NA NA XB-GENEPAGE-5890900 XB-GENE-5890901 Xl.48680 Fam59b 242915 - - - - - 393,56 2,40 784,71 230,76 7,85 0,00% Xetrov72b000002 mllt11 100380181 Str.53950 301615708,110645746,159155861 XM_002937262,BC118826,BC154950 NA NA NA XB-GENEPAGE-5918937 XB-GENE-5918938 Xl.20705 Mllt11 56772 - - - - - 112,07 0,00 224,14 225,14 7,81 0,00% Xetrov72038665 dpysl3 448103 Str.2981 62732444,54020782,49250893 CR942629,NM_001005637,BC074633 NA NA NA XB-GENEPAGE-944728 XB-GENE-944729 Xl.5161,Xl.68131 Dpysl3 22240 - Xl.68131 - - - 14532,52 131,60 28933,45 218,22 7,77 0,00% Xetrov72038386 sv2b 100497731 301607529 XM_002933309 NA NA NA XB-GENEPAGE-6041858 XB-GENE-6041859 NA Sv2b 64176 - - - - - 622,35 4,72 1239,97 216,93 7,76 0,00% Xetrov72043409 c7orf52 NA NA NA NA NA NA NA NA NA Xl.14656 NA NA - - - - - 96,76 0,00 193,52 194,52 7,60 0,00% Xetrov72004164 unc80 779473 Str.83026 301618842,111306122,157423398 XM_002938770,BC121485,BC153327 NA NA NA XB-GENEPAGE-5889668 XB-GENE-5889669 NA Unc80 329178 - - - - - 95,76 0,00 191,53 192,53 7,59 0,00% Xetrov72014674 prdm12 780360 Str.52298 118405051,110645421 NM_001079430,BC118858 NA NA NA XB-GENEPAGE-953728 XB-GENE-953729 Xl.19035 Prdm12 381359 - - - - - 312,65 2,40 622,90 183,24 7,52 0,00% Xetrov72021266 shd 100124932 Str.30857 134024100,301608980 BC135801,XM_002934002 Src homology 2 domain containing transforming protein D Protein tyrosine phosphatase Corkscrew and related SH2 domain enzymes XB-GENEPAGE-492408 XB-GENE-492409 Xl.13544 Shd 20420 - - - - - 251,05 1,83 500,28 177,39 7,47 0,00% Xetrov72027346 NA NA NA NA NA NA NA NA NA NA NA NA - - - - - 499,59 4,99 994,19 166,21 7,38 0,00% Xetrov72038339 skor1 100491438 Str.40049 301606765 XM_002932958 NA NA NA XB-GENEPAGE-877132 XB-GENE-877133 NA Skor1 207667 - - - - - 933,68 10,20 1857,16 165,93 7,37 0,00% Xetrov72017212 slc32a1 448348 Str.5507 49523024,52345793 BC075429,NM_001004943 solute carrier family 32 (GABA vesicular transporter), member 1 solute transport xVIAAT XB-GENEPAGE-489829 XB-GENE-489830 Xl.19057 Slc32a1 22348 - - - - - 120,21 0,58 239,85 152,54 7,25 0,00% Xetrov72030361 lhx1 100101708 Str.12750 154147695,138519842 NM_001100228,BC135731 LIM homeobox 1 LIM and homeodomain containing transcription factor lim-1|Lim1|Xlim-1|Xlim1|lim1 XB-GENEPAGE-482481 XB-GENE-482482 Xl.32655,Xl.79655,Xl.81258,Xl.82262 Lhx1 16869 - - - - - 253,19 2,32 504,07 152,32 7,25 0,00% Xetrov72001651 c20orf103 NA NA NA NA NA NA NA NA NA NA NA NA - - - - - 71,95 0,00 143,90 144,90 7,18 0,00% Xetrov72005859 tmem163 100127636 Str.13755 163914924,158254136 NM_001112984,BC154065 NA NA NA XB-GENEPAGE-5808412 XB-GENE-5808413 Xl.75537 Tmem163 72160 - - - - - 70,54 0,00 141,07 142,07 7,15 0,00% Xetrov72005817 NA NA NA NA NA NA NA NA NA NA NA NA - - - - - 149,77 1,16 298,38 138,74 7,12 0,00% Xetrov72019090 megf10 780183 Str.46279 118404387,116487752 NM_001079258,BC125696 multiple EGF-like-domains 10 Proteins containing Ca2+-binding EGF-like domains XB-GENEPAGE-491973 XB-GENE-491974 NA Megf10 70417 - - - - - 235,31 2,40 468,22 137,81 7,11 0,00% Xetrov72038650 arsi 100487216 301621595 XM_002940086 NA NA NA XB-GENEPAGE-6046189 XB-GENE-6046190 Arsi 545260 - - - - - 177,38 1,74 353,03 129,35 7,02 0,00% Xetrov72015904 syp 100144928 Str.68622 77623009,187607470,165971075 CT030505,NM_001126502,BC158217 NA NA NA XB-GENEPAGE-943860 XB-GENE-943861 Xl.230,Xl.232 Syp 20977 - - - - - 175,36 1,83 348,89 123,82 6,95 0,00% Xetrov72018659 apc2 100487473 Str.84778 301623723 XM_002941120 NA NA NA XB-GENEPAGE-995290 XB-GENE-995291 Xl.8904,Xl.13877,Xl.50320 Apc2 23805 - - - - - 360,91 4,81 717,01 123,59 6,95 0,00% Xetrov72003639 onecut1.2 100488409 301611996 XM_002935458 one cut homeobox 1, gene 2 homeodomain transcription factor XB-GENEPAGE-1021673 XB-GENE-1021674 Onecut1 15379 - - - - - 647,79 9,44 1286,14 123,27 6,95 0,00% Xetrov72005175 srl 493203 Str.1480 301605732,51703839 XM_002932431,BC080922 NA NA NA XB-GENEPAGE-981744 XB-GENE-981745 Xl.33138,Xl.48656 Srl 106393 - - - - Srl 60,74 0,00 121,48 122,48 6,94 0,00% Xetrov72025327 kirrel2 100216155 Str.17737 213982860,195539753 NM_001142126,BC168130 kin of IRRE like 2 Immunoglobulin C-2 Type/fibronectin type III domains XB-GENEPAGE-854069 XB-GENE-854070 Xl.76492,Xl.60720,Xl.76486,Xl.81573 Kirrel2 243911 - - - - Kirrel2 1410,90 21,91 2799,89 122,25 6,93 0,00% Xetrov72010206 dmbx1 100493907 301603586,301603584 XM_002931404,XM_002931403 diencephalon/mesencephalon homeobox 1 homeodomain transcription factor otx3 XB-GENEPAGE-486745 XB-GENE-486746 ,Xl.32187 Dmbx1 140477 - - - - Dmbx1 699,47 10,55 1388,38 120,25 6,91 0,00% Xl.72338 - - - - - BJ048556 NIBB Mochii normalized Xenopus neurula library Xenopus laevis cDNA clone XL020d15 3', mRNA sequence [BJ048556] - - - Xl.72338 - - - - - - - 57,72 0,00 115,45 116,45 6,86 0,00% Xetrov72008463 sipa1 100490716 Str.60346 301611772 XM_002935362 NA NA NA XB-GENEPAGE-6065316 XB-GENE-6065317 Xl.24360,Xl.13462,Xl.81387 Sipa1 20469 - - - - - 329,01 4,81 653,20 112,61 6,82 0,00% Xetrov72005179 uncx 100492016 301618085 XM_002938411 UNC homeobox homeodomain transcription factor uncx4.1|uncx-4.1 XB-GENEPAGE-920200 XB-GENE-920201 Xl.23533 Uncx 22255 - - - - - 217,18 2,89 431,47 111,04 6,79 0,00% Xetrov72037002 kank2 100495496 301627449 XM_002942843 NA NA NA XB-GENEPAGE-997066 XB-GENE-997067 Xl.16647 Kank2 235041 - - - - - 52,70 0,00 105,39 106,39 6,73 0,00% Xetrov72016175 plekhd1 100485012 301611723 XM_002935342 NA NA NA XB-GENEPAGE-6044239 XB-GENE-6044240 NA NA NA - - - - - 83,55 0,58 166,52 106,10 6,73 0,00% Xl.12377 - - - - - BX847776 NICHD_XGC_Eye1 Xenopus laevis cDNA clone IMAGp998P1210623 ; IMAGE:4757627 5', mRNA sequence [BX847776] - - - Xl.12377 - - - - - - - 51,87 0,00 103,74 104,74 6,71 0,00% Xetrov72030919 neurod4 100124310 Str.53567 54038737,196259965,195539842 BC084160,NM_001131041,BC168092 neurogenic differentiation 4 helix-loop-helix transcription factor atonal homolog-3|Xath-3|Xath3|ath3|ath-3|atoh3|math-3|bhlha4 XB-GENEPAGE-972703 XB-GENE-972704 Xl.1263 Neurod4 11923 Xl.1263 - - - Neurod4 372,77 6,15 739,40 103,62 6,70 0,00% Xetrov72005526 neurod1 100038290 Str.12084 134023808,148539977 BC135312,NM_001097399 neurogenic differentiation 1 helix-loop-helix transcription factor neurod|XNeuroD|neuroD XB-GENEPAGE-963756 XB-GENE-963757 Xl.26304,Xl.330 Neurod1 18012 - Xl.330 - - - 602,42 10,87 1193,98 100,70 6,65 0,00% Xetrov72028450 cyp26c1 100489980 Str.67330 301619511 XM_002939091 cytochrome P450, family 26, subfamily C, polypeptide 1 electron transport XB-GENEPAGE-1219114 XB-GENE-1219115 Xl.82105,Xl.1946,Xl.41946 Cyp26c1 546726 - - - - - 2312,68 44,53 4580,84 100,63 6,65
Load more

Recommended publications
  • Integrative Genomic and Epigenomic Analyses Identified IRAK1 As a Novel Target for Chronic Inflammation-Driven Prostate Tumorigenesis
    bioRxiv preprint doi: https://doi.org/10.1101/2021.06.16.447920; this version posted June 16, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Integrative genomic and epigenomic analyses identified IRAK1 as a novel target for chronic inflammation-driven prostate tumorigenesis Saheed Oluwasina Oseni1,*, Olayinka Adebayo2, Adeyinka Adebayo3, Alexander Kwakye4, Mirjana Pavlovic5, Waseem Asghar5, James Hartmann1, Gregg B. Fields6, and James Kumi-Diaka1 Affiliations 1 Department of Biological Sciences, Florida Atlantic University, Florida, USA 2 Morehouse School of Medicine, Atlanta, Georgia, USA 3 Georgia Institute of Technology, Atlanta, Georgia, USA 4 College of Medicine, Florida Atlantic University, Florida, USA 5 Department of Computer and Electrical Engineering, Florida Atlantic University, Florida, USA 6 Department of Chemistry & Biochemistry and I-HEALTH, Florida Atlantic University, Florida, USA Corresponding Author: [email protected] (S.O.O) Running Title: Chronic inflammation signaling in prostate tumorigenesis bioRxiv preprint doi: https://doi.org/10.1101/2021.06.16.447920; this version posted June 16, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Abstract The impacts of many inflammatory genes in prostate tumorigenesis remain understudied despite the increasing evidence that associates chronic inflammation with prostate cancer (PCa) initiation, progression, and therapy resistance.
    [Show full text]
  • Hypopituitarism May Be an Additional Feature of SIM1 and POU3F2 Containing 6Q16 Deletions in Children with Early Onset Obesity
    Open Access Journal of Pediatric Endocrinology Case Report Hypopituitarism may be an Additional Feature of SIM1 and POU3F2 Containing 6q16 Deletions in Children with Early Onset Obesity Rutteman B1, De Rademaeker M2, Gies I1, Van den Bogaert A2, Zeevaert R1, Vanbesien J1 and De Abstract Schepper J1* Over the past decades, 6q16 deletions have become recognized as a 1Department of Pediatric Endocrinology, UZ Brussel, frequent cause of the Prader-Willi-like syndrome. Involvement of SIM1 in the Belgium deletion has been linked to the development of obesity. Although SIM1 together 2Department of Genetics, UZ Brussel, Belgium with POU3F2, which is located close to the SIM1 locus, are involved in pituitary *Corresponding author: De Schepper J, Department development and function, pituitary dysfunction has not been reported frequently of Pediatric Endocrinology, UZ Brussel, Belgium in cases of 6q16.1q16.3 deletion involving both genes. Here we report on a case of a girl with typical Prader-Willi-like symptoms including early-onset Received: December 23, 2016; Accepted: February 21, hyperphagic obesity, hypotonia, short hands and feet and neuro-psychomotor 2017; Published: February 22, 2017 development delay. Furthermore, she suffered from central diabetes insipidus, central hypothyroidism and hypocortisolism. Her genetic defect is a 6q16.1q16.3 deletion, including SIM1 and POU3F2. We recommend searching for a 6q16 deletion in children with early onset hyperphagic obesity associated with biological signs of hypopituitarism and/or polyuria-polydipsia syndrome. The finding of a combined SIM1 and POU3F2 deletion should prompt monitoring for the development of hypopituitarism, if not already present at diagnosis. Keywords: 6q16 deletion; SIM1; POU3F2; Prader-Willi-like syndrome; Hypopituitarism Introduction insipidus and of some specific pituitary hormone deficiencies in children with a combined SIM1 and POU3F2 deficiency.
    [Show full text]
  • Targeting Non-Oncogene Addiction for Cancer Therapy
    biomolecules Review Targeting Non-Oncogene Addiction for Cancer Therapy Hae Ryung Chang 1,*,†, Eunyoung Jung 1,†, Soobin Cho 1, Young-Jun Jeon 2 and Yonghwan Kim 1,* 1 Department of Biological Sciences and Research Institute of Women’s Health, Sookmyung Women’s University, Seoul 04310, Korea; [email protected] (E.J.); [email protected] (S.C.) 2 Department of Integrative Biotechnology, Sungkyunkwan University, Suwon 16419, Korea; [email protected] * Correspondence: [email protected] (H.R.C.); [email protected] (Y.K.); Tel.: +82-2-710-9552 (H.R.C.); +82-2-710-9552 (Y.K.) † These authors contributed equally. Abstract: While Next-Generation Sequencing (NGS) and technological advances have been useful in identifying genetic profiles of tumorigenesis, novel target proteins and various clinical biomarkers, cancer continues to be a major global health threat. DNA replication, DNA damage response (DDR) and repair, and cell cycle regulation continue to be essential systems in targeted cancer therapies. Although many genes involved in DDR are known to be tumor suppressor genes, cancer cells are often dependent and addicted to these genes, making them excellent therapeutic targets. In this review, genes implicated in DNA replication, DDR, DNA repair, cell cycle regulation are discussed with reference to peptide or small molecule inhibitors which may prove therapeutic in cancer patients. Additionally, the potential of utilizing novel synthetic lethal genes in these pathways is examined, providing possible new targets for future therapeutics. Specifically, we evaluate the potential of TONSL as a novel gene for targeted therapy. Although it is a scaffold protein with no known enzymatic activity, the strategy used for developing PCNA inhibitors can also be utilized to target TONSL.
    [Show full text]
  • Plenary and Platform Abstracts
    American Society of Human Genetics 68th Annual Meeting PLENARY AND PLATFORM ABSTRACTS Abstract #'s Tuesday, October 16, 5:30-6:50 pm: 4. Featured Plenary Abstract Session I Hall C #1-#4 Wednesday, October 17, 9:00-10:00 am, Concurrent Platform Session A: 6. Variant Insights from Large Population Datasets Ballroom 20A #5-#8 7. GWAS in Combined Cancer Phenotypes Ballroom 20BC #9-#12 8. Genome-wide Epigenomics and Non-coding Variants Ballroom 20D #13-#16 9. Clonal Mosaicism in Cancer, Alzheimer's Disease, and Healthy Room 6A #17-#20 Tissue 10. Genetics of Behavioral Traits and Diseases Room 6B #21-#24 11. New Frontiers in Computational Genomics Room 6C #25-#28 12. Bone and Muscle: Identifying Causal Genes Room 6D #29-#32 13. Precision Medicine Initiatives: Outcomes and Lessons Learned Room 6E #33-#36 14. Environmental Exposures in Human Traits Room 6F #37-#40 Wednesday, October 17, 4:15-5:45 pm, Concurrent Platform Session B: 24. Variant Interpretation Practices and Resources Ballroom 20A #41-#46 25. Integrated Variant Analysis in Cancer Genomics Ballroom 20BC #47-#52 26. Gene Discovery and Functional Models of Neurological Disorders Ballroom 20D #53-#58 27. Whole Exome and Whole Genome Associations Room 6A #59-#64 28. Sequencing-based Diagnostics for Newborns and Infants Room 6B #65-#70 29. Omics Studies in Alzheimer's Disease Room 6C #71-#76 30. Cardiac, Valvular, and Vascular Disorders Room 6D #77-#82 31. Natural Selection and Human Phenotypes Room 6E #83-#88 32. Genetics of Cardiometabolic Traits Room 6F #89-#94 Wednesday, October 17, 6:00-7:00 pm, Concurrent Platform Session C: 33.
    [Show full text]
  • Supplementary Materials
    Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine
    [Show full text]
  • Negative Breast Cancer Patients Without Germline BRCA1/2 Mutation
    An 8-lncRNA signature predicts survival of triple- negative breast cancer patients without germline BRCA1/2 mutation Minling Liu The Seventh Aliated Hospital Sun Yat-sen University https://orcid.org/0000-0001-7317-5600 Wei Dai the aliated hospital of guangdong medical university Mengyuan Zhu The Seventh Aliated Hospital Sun Yat-sen University Xueying Li The Seventh Aliated Hospital Sun Yat-sen University Shan Huang The Seventh Aliated Hospital Sun Yat-sen University Min Wei The Seventh Aliated Hospital Sun Yat-sen University Lei Li ( [email protected] ) University of Hong Kong Shuo Fang ( [email protected] ) The Seventh Aliated Hospital Sun Yat-sen University Research article Keywords: long non-coding RNA, triple-negative breast cancer, germline BRCA1/2 mutation, overall survival Posted Date: August 28th, 2020 DOI: https://doi.org/10.21203/rs.3.rs-66893/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/19 Abstract Background Triple-negative breast cancer (TNBC) is a particular breast cancer subtype with poor prognosis due to its aggressive biological behavior and strong heterogeneity. TNBC with germline BRCA1/2 mutation (gBRCAm) have higher sensitivity to DNA damaging agents including platinum-based chemotherapy and PARP inhibitors. But the treatment of TNBC without gBRCAm remains challenging. This study aimed to develop a long non-coding RNA (lncRNA) signature of TNBC patients without gBRCAm to improve risk stratication and optimize individualized treatment. Methods 98 TNBC patients without gBRCAm were acquired from The Cancer Genome Atlas (TCGA) database. The univariable Cox regression analysis and LASSO Cox regression model were applied to establish an lncRNA signature in the training cohort (N = 59).
    [Show full text]
  • Systematic Screening Reveals a Role for BRCA1 in the Response to Transcription-Associated DNA Damage
    Downloaded from genesdev.cshlp.org on October 6, 2021 - Published by Cold Spring Harbor Laboratory Press RESOURCE/METHODOLOGY Systematic screening reveals a role for BRCA1 in the response to transcription-associated DNA damage Sarah J. Hill,1,2 Thomas Rolland,1,2,3 Guillaume Adelmant,1,4,5 Xianfang Xia,1,2,3 Matthew S. Owen,1,2,3 Amelie Dricot,1,2,3 Travis I. Zack,1,6 Nidhi Sahni,1,2,3 Yves Jacob,1,2,3,7,8,9 Tong Hao,1,2,3 Kristine M. McKinney,1,2 Allison P. Clark,1,2 Deepak Reyon,10,11,12 Shengdar Q. Tsai,10,11,12 J. Keith Joung,10,11,12 Rameen Beroukhim,1,6,13 Jarrod A. Marto,1,4,5 Marc Vidal,1,2,3 Suzanne Gaudet,1,2,3 David E. Hill,1,2,3,14 and David M. Livingston1,2,14 1Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA; 2Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA; 3Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA; 4Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts 02115, USA; 5Blais Proteomics Center, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA; 6The Broad Institute, Cambridge, Massachusetts 02142, USA; 7Departement de Virologie, Unite de Gen etique Moleculaire des Virus a ARN, Institut Pasteur, F-75015 Paris, France; 8UMR3569, Centre National de la Recherche Scientifique, F-75015 Paris, France; 9UnitedeG en etique Moleculaire des Virus a ARN, Universite Paris Diderot, F-75015 Paris, France; 10Molecular Pathology Unit, Center for Computational and Integrative Biology, 11Center for Cancer Research, Massachusetts General Hospital, Charlestown, Massachusetts 02129, USA; 12Department of Pathology, Harvard Medical School, Boston, Massachusetts 02115, USA; 13Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA BRCA1 is a breast and ovarian tumor suppressor.
    [Show full text]
  • Appendix 2. Significantly Differentially Regulated Genes in Term Compared with Second Trimester Amniotic Fluid Supernatant
    Appendix 2. Significantly Differentially Regulated Genes in Term Compared With Second Trimester Amniotic Fluid Supernatant Fold Change in term vs second trimester Amniotic Affymetrix Duplicate Fluid Probe ID probes Symbol Entrez Gene Name 1019.9 217059_at D MUC7 mucin 7, secreted 424.5 211735_x_at D SFTPC surfactant protein C 416.2 206835_at STATH statherin 363.4 214387_x_at D SFTPC surfactant protein C 295.5 205982_x_at D SFTPC surfactant protein C 288.7 1553454_at RPTN repetin solute carrier family 34 (sodium 251.3 204124_at SLC34A2 phosphate), member 2 238.9 206786_at HTN3 histatin 3 161.5 220191_at GKN1 gastrokine 1 152.7 223678_s_at D SFTPA2 surfactant protein A2 130.9 207430_s_at D MSMB microseminoprotein, beta- 99.0 214199_at SFTPD surfactant protein D major histocompatibility complex, class II, 96.5 210982_s_at D HLA-DRA DR alpha 96.5 221133_s_at D CLDN18 claudin 18 94.4 238222_at GKN2 gastrokine 2 93.7 1557961_s_at D LOC100127983 uncharacterized LOC100127983 93.1 229584_at LRRK2 leucine-rich repeat kinase 2 HOXD cluster antisense RNA 1 (non- 88.6 242042_s_at D HOXD-AS1 protein coding) 86.0 205569_at LAMP3 lysosomal-associated membrane protein 3 85.4 232698_at BPIFB2 BPI fold containing family B, member 2 84.4 205979_at SCGB2A1 secretoglobin, family 2A, member 1 84.3 230469_at RTKN2 rhotekin 2 82.2 204130_at HSD11B2 hydroxysteroid (11-beta) dehydrogenase 2 81.9 222242_s_at KLK5 kallikrein-related peptidase 5 77.0 237281_at AKAP14 A kinase (PRKA) anchor protein 14 76.7 1553602_at MUCL1 mucin-like 1 76.3 216359_at D MUC7 mucin 7,
    [Show full text]
  • Lncrna TONSL-AS1 Regulates Mir-490-3P/CDK1 to Affect Ovarian
    Liu et al. Journal of Ovarian Research (2020) 13:60 https://doi.org/10.1186/s13048-020-00657-0 RESEARCH Open Access LncRNA TONSL-AS1 regulates miR-490-3p/ CDK1 to affect ovarian epithelial carcinoma cell proliferation Yan Liu1†, Ling Li1†, Xiangyang Wang2, Ping Wang1 and Zhongxian Wang1* Abstract Background: LncRNA TONSL-AS1 has been characterized as a critical player in gastric cancer. By analyze the TCGA dataset, we observed the upregulation of TONSL-AS1 in ovarian epithelial carcinoma (EOC). We therefore investigated the involvement of TONSL-AS1 in EOC. Methods: The differential expression of TONSL-AS1 in EOC was first explored by analyzing the TCGA dataset. The effects of overexpression of TONSL-AS1 and miR-490-3p on the expression of CDK1 mRNA and protein in OVCAR3 cells were evaluated by qPCR and western blot, respectively. CCK-8 assay was performed to investigate the effects of overexpression of TONSL-AS1, miR-490-3p and CDK1 on proliferation of OVCAR3 cells. Results: We observed that TONSL-AS1 was upregulated in EOC tumor tissues from EOC patients, and its high expression level was correlated with poor survival. Dual luciferase assay and RNA interaction prediction showed the direct interaction between TONSL-AS1 and miR-490-3p. However, overexpression of miR-490-3p did not affect the expression of TONSL- AS1. Instead, overexpression of TONSL-AS1 resulted in the upregulation of CDK1, a target of miR-490-3p, in EOC cells. Overexpression of TONSL-AS1 and CDK1 resulted in increased proliferation rate of EOC cells. Overexpression of miR-490- 3p played an opposite role and reduced the effects of overexpression of TONSL -AS1 and CDK1.
    [Show full text]
  • Karla Alejandra Vizcarra Zevallos Análise Da Função De Genes
    Karla Alejandra Vizcarra Zevallos Análise da função de genes candidatos à manutenção da inativação do cromossomo X em humanos Dissertação apresentada ao Pro- grama de Pós‐Graduação Inter- unidades em Biotecnologia USP/ Instituto Butantan/ IPT, para obtenção do Título de Mestre em Ciências. São Paulo 2017 Karla Alejandra Vizcarra Zevallos Análise da função de genes candidatos à manutenção da inativação do cromossomo X em humanos Dissertação apresentada ao Pro- grama de Pós‐Graduação Inter- unidades em Biotecnologia do Instituto de Ciências Biomédicas USP/ Instituto Butantan/ IPT, para obtenção do Título de Mestre em Ciências. Área de concentração: Biotecnologia Orientadora: Profa. Dra. Lygia da Veiga Pereira Carramaschi Versão corrigida. A versão original eletrônica encontra-se disponível tanto na Biblioteca do ICB quanto na Biblioteca Digital de Teses e Dissertações da USP (BDTD) São Paulo 2017 UNIVERSIDADE DE SÃO PAULO Programa de Pós-Graduação Interunidades em Biotecnologia Universidade de São Paulo, Instituto Butantan, Instituto de Pesquisas Tecnológicas Candidato(a): Karla Alejandra Vizcarra Zevallos Título da Dissertação: Análise da função de genes candidatos à manutenção da inativação do cromossomo X em humanos Orientador: Profa. Dra. Lygia da Veiga Pereira Carramaschi A Comissão Julgadora dos trabalhos de Defesa da Dissertação de Mestrado, em sessão pública realizada a ........./......../.........., considerou o(a) candidato(a): ( ) Aprovado(a) ( ) Reprovado(a) Examinador(a): Assinatura: ..............................................................................
    [Show full text]
  • Improving the Detection of Genomic Rearrangements in Short Read Sequencing Data
    Improving the detection of genomic rearrangements in short read sequencing data Daniel Lee Cameron orcid.org/0000-0002-0951-7116 Doctor of Philosophy July 2017 Department of Medical Biology, University of Melbourne Bioinformatics Division, Walter and Eliza Hall Institute of Medical Research Submitted in total fulfilment of the requirements of the degree of Doctor of Philosophy Produced on archival quality paper Page i Abstract Genomic rearrangements, also known as structural variants, play a significant role in the development of cancer and in genetic disorders. With the bulk of genetic studies focusing on single nucleotide variants and small insertions and deletions, structural variants are often overlooked. In part this is due to the increased complexity of analysis required, but is also due to the increased difficulty of detection. The identification of genomic rearrangements using massively parallel sequencing remains a major challenge. To address this, I have developed the Genome Rearrangement Identification Software Suite (GRIDSS). In this thesis, I show that high sensitivity and specificity can be achieved by performing reference-guided assembly prior to variant calling and incorporating the results of this assembly into the variant calling process itself. Utilising a novel genome-wide break-end assembly approach, GRIDSS halves the false discovery rate compared to other recent methods on human cell line data. A comparison of assembly approaches reveals that incorporating read alignment information into a positional de Bruijn graph improves assembly quality compared to traditional de Bruijn graph assembly. To characterise the performance of structural variant calling software, I have performed the most comprehensive benchmarking of structural variant calling software to date.
    [Show full text]
  • Metabolites OH
    H OH metabolites OH Article Metabolite Genome-Wide Association Study (mGWAS) and Gene-Metabolite Interaction Network Analysis Reveal Potential Biomarkers for Feed Efficiency in Pigs Xiao Wang and Haja N. Kadarmideen * Quantitative Genomics, Bioinformatics and Computational Biology Group, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Richard Petersens Plads, Building 324, 2800 Kongens Lyngby, Denmark; [email protected] * Correspondence: [email protected] Received: 1 April 2020; Accepted: 11 May 2020; Published: 15 May 2020 Abstract: Metabolites represent the ultimate response of biological systems, so metabolomics is considered the link between genotypes and phenotypes. Feed efficiency is one of the most important phenotypes in sustainable pig production and is the main breeding goal trait. We utilized metabolic and genomic datasets from a total of 108 pigs from our own previously published studies that involved 59 Duroc and 49 Landrace pigs with data on feed efficiency (residual feed intake (RFI)), genotype (PorcineSNP80 BeadChip) data, and metabolomic data (45 final metabolite datasets derived from LC-MS system). Utilizing these datasets, our main aim was to identify genetic variants (single-nucleotide polymorphisms (SNPs)) that affect 45 different metabolite concentrations in plasma collected at the start and end of the performance testing of pigs categorized as high or low in their feed efficiency (based on RFI values). Genome-wide significant genetic variants could be then used as potential genetic or biomarkers in breeding programs for feed efficiency. The other objective was to reveal the biochemical mechanisms underlying genetic variation for pigs’ feed efficiency. In order to achieve these objectives, we firstly conducted a metabolite genome-wide association study (mGWAS) based on mixed linear models and found 152 genome-wide significant SNPs (p-value < 1.06 10 6) in association with 17 metabolites that included 90 significant SNPs annotated × − to 52 genes.
    [Show full text]