Next generation sequencing and RNA-seq characterization of adipose tissue in the Nile crocodile (Crocodylus niloticus) in South Africa: Possible mechanism(s) of pathogenesis and pathophysiology of pansteatitis


Autoři: Odunayo I. Azeez aff001;  Jan G. Myburgh aff003;  Ana-Mari Bosman aff004;  Jonathan Featherston aff005;  Kgomotso P. Sibeko-Matjilla aff004;  Marinda C. Oosthuizen aff004;  Joseph P. Chamunorwa aff001
Působiště autorů: Anatomy and Physiology Dept., Faculty of Veterinary Science, University of Pretoria, Onderstepoort, Pretoria, South Africa aff001;  Dept. of Veterinary Physiology and Biochemistry, Faculty of Veterinary Medicine, University of Ibadan, Ibadan, Nigeria aff002;  Paraclinical Science Dept., Faculty of Veterinary Science, University of Pretoria, Onderstepoort, Pretoria, South Africa aff003;  Veterinary Tropical Diseases Dept., Faculty of Veterinary Science, University of Pretoria, Onderstepoort, Pretoria, South Africa aff004;  Biotechnology Platform, Agricultural Research Council, Onderstepoort, Pretoria, South Africa aff005
Vyšlo v časopise: PLoS ONE 14(11)
Kategorie: Research Article
doi: 10.1371/journal.pone.0225073

Souhrn

Background

Concerted efforts to identify the pathogenesis and mechanism(s) involved in pansteatitis, (a generalized inflammation of the adipose tissue), that was attributed to the recent crocodile die off in the Olifants River and Loskop Dam in Kruger National Park, Mpumalanga, South Africa have been in the forefront of research in recent time. As part of the efforts, molecular characterization of healthy and pansteatitis adipose tissue was carried out by RNA sequencing (RNA-Seq) using Next Generation Sequencing (NGS) and de novo assembly of the adipose transcriptome, followed by differential gene expression analysis.

Methodology

Healthy adipose tissue consisting of fifty samples was collected from the subcutaneous, visceral, intermuscular adipose tissues and the abdominal fat body of ten 4 years old juvenile crocodiles from a local crocodile farm in Pretoria, South Africa. Ten pansteatitis samples were collected from visceral and intermuscular adipose tissues of five crocodiles that were dying of pansteatitis.

Results

Forty-two thousand, two hundred and one (42,201) transcripts were assembled, out of which 37, 835 had previously been characterized. The de novo assembled transcriptome had an N50 (average sequence) of 436 bp, percentage GC content of 43.92, which compared well with previously assembled transcripts in the saltwater crocodile. Seventy genes were differentially expressed and upregulated in pansteatitis. These included genes coding for extracellular matrix (ECM) signaling ligands, inflammatory cytokines and tumour necrosis factor alpha (TNFα) receptors, fatty acid synthase and fatty acid binding proteins, peroxisome proliferator-activated receptor gamma (PPARγ), nuclear factor and apoptosis signaling ligands, and mitogen activated protein kinase enzymes among others. Majority (88.6%) of the upregulated genes were found to be involved in hypoxia inducible pathways for activation of NFkβ and inflammation, apoptosis, Toll-like receptor pathway and PPARγ. Bicaudal homologous 2 Drosophila gene (BICD2) associated with spinal and lower extremity muscle atrophy was also upregulated in pansteatitis while Sphingosine -1-phosphate phosphatase 2 (SGPP2) involved in Sphingosine -1- phosphate metabolism was downregulated. Futhermore, Doublesex–mab-related transcription factor 1 (DMRT1) responsible for sex gonad development and germ cell differentiation was also downregulated.

Conclusion

Thus, from the present study, based on differentially expressed genes in pansteatitis, affected Nile crocodiles might have died partly due to their inability to utilize stored triglycerides as a result of inflammation induced insulin resistance, leading to starvation in the midst of plenty. Affected animals may have also suffered muscular atrophy of the lower extremities and poor fertility.

Klíčová slova:

Adipose tissue – Apoptosis – Cytokines – Gene expression – Inflammation – Protein kinase signaling cascade – Transcriptome analysis – Crocodiles


Zdroje

1. Chang Z, Li G, Liu J, Zhang Y, Ashby C, Liu D, et al. Bridger: a new framework for de novo transcriptome assembly using RNA-seq data. Genome Biol. 2015;16(1):30.

2. Miller HC, Biggs PJ, Voelckel C, Nelson NJ. De novo sequence assembly and characterisation of a partial transcriptome for an evolutionarily distinct reptile, the tuatara (Sphenodon punctatus). BMC genomics. 2012;13(1):1.

3. Tzika AC, Helaers R, Schramm G, Milinkovitch MC. Reptilian-transcriptome v1.0, a glimpse in the brain transcriptome of five divergent Sauropsida lineages and the phylogenetic position of turtles. EvoDevo. 2011;2(1):1–19. doi: 10.1186/2041-9139-2-1

4. Tzika AC, Ullate-Agote A, Grbic D, Milinkovitch MC. Reptilian Transcriptomes v2.0: An Extensive Resource for Sauropsida Genomics and Transcriptomics. Genome Biology and Evolution. 2015;7(6):1827–41. doi: 10.1093/gbe/evv106 26133641

5. St John J, Braun E, Isberg S, Miles L, Chong A, Gongora J, et al. Sequencing three crocodilian genomes to illuminate the evolution of archosaurs and amniotes. Genome Biology. 2012;13(1):415. doi: 10.1186/gb-2012-13-1-415 22293439

6. Revol B. Crocodile farming and conservation, the example of Zimbabwe. Biodivers Conserv. 1995;4(3):299–305. doi: 10.1007/BF00055975

7. Dzoma BM, Sejoe S, Segwagwe BVE. Commercial crocodile farming in Botswana. Trop Anim Health Prod. 2008;40(5):377–81. doi: 10.1007/s11250-007-9103-4 18509947

8. Gibbons JW, Scott DE, Ryan TJ, Buhlmann KA, Tuberville TD, Metts BS, et al. The Global Decline of Reptiles, Déjà Vu Amphibians: Reptile species are declining on a global scale. Six significant threats to reptile populations are habitat loss and degradation, introduced invasive species, environmental pollution, disease, unsustainable use, and global climate change. BioScience. 2000;50(8):653–66. doi: 10.1641/0006-3568(2000)050[0653:tgdord]2.0.co;2

9. Botha PJ. The distribution, conservation status and blood biochemistry of Nile crocodiles in the Olifants river system, Mpumalanga, South Africa. Pretoria: University of Pretoria; 2011.

10. Ashton PJ. The demise of the Nile crocodile (Crocodylus niloticus) as a keystone species for aquatic ecosystem conservation in South Africa: The case of the Olifants River. Aquatic Conservation: Marine and Freshwater Ecosystems. 2010;20(5):489–93. doi: 10.1002/aqc.1132

11. Lane EP, Huchzermeyer FW, Govender D, Bengis RG, Buss PE, Hofmeyr M, et al. Pansteatitis of unknown etiology associated with large-scale nile crocodile (Crocodylus niloticus) mortality in Kruger National Park, South Africa: Pathologic findings. Journal of Zoo and Wildlife Medicine. 2013;44(4):899–910. doi: 10.1638/2012-0264R.1 24450048

12. Osthoff G, Hugo A, Bouwman H, Buss P, Govender D, Joubert CC, et al. Comparison of the lipid properties of captive, healthy wild, and pansteatitis-affected wild Nile crocodiles (Crocodylus niloticus). Comparative biochemistry and physiology Part A, Molecular & integrative physiology. 2010;155(1):64–9. doi: 10.1016/j.cbpa.2009.09.025 19800020.

13. Huchzermeyer KD, Osthoff G, Hugo A, Govender D. Comparison of the lipid properties of healthy and pansteatitis-affected African sharptooth catfish, Clarias gariepinus (Burchell), and the role of diet in pansteatitis outbreaks in the Olifants River in the Kruger National Park, South Africa. Journal of fish diseases. 2013;36(11):897–909. doi: 10.1111/jfd.12010 23634747.

14. Oberholster PJ, Myburgh JG, Ashton PJ, Coetzee JJ, Botha A-M. Bioaccumulation of aluminium and iron in the food chain of Lake Loskop, South Africa. Ecotoxicology and Environmental Safety. 2012;75:134–41. doi: 10.1016/j.ecoenv.2011.08.018 21924494

15. Oberholster PJ, Hill L, Jappie S, Truter JC, Botha A-M. Applying genotoxicology tools to identify environmental stressors in support of river management. Chemosphere. 2016;144:319–29. doi: 10.1016/j.chemosphere.2015.08.024 26372886

16. Lubick N. Hunting a croc killer: Mass deaths of South African’s Nile crocodiles puzzle biologists. Scientific America. 2009:12–3.

17. Huchzermeyer KD. Prevalence of pansteatitis in African sharptooth catfish, Clarias gariepinus (Burchell), in the Kruger National Park, South Africa. Journal of the South African Veterinary Association. 2012;83(1):916. doi: 10.4102/jsava.v83i1.916 23327137.

18. Bays HE, González-Campoy JM, Bray GA, Kitabchi AE, Bergman DA, Schorr AB, et al. Pathogenic potential of adipose tissue and metabolic consequences of adipocyte hypertrophy and increased visceral adiposity. Expert Review of Cardiovascular Therapy. 2008;6(3):343–68. doi: 10.1586/14779072.6.3.343 18327995

19. Tilg H, Moschen AR. Adipocytokines: mediators linking adipose tissue, inflammation and immunity. Nature Reviews Immunology. 2006;6(10):772–83. doi: 10.1038/nri1937 16998510

20. Keuper M, Bluher M, Moller P, Debatin K-M, Wabitsch M. Apoptosis of Fat Cells Is Linked to Macrophage Infiltration in Human Adipose Tissue. Apoptosis. 2016;2:484.

21. Henegar C, Tordjman J, Achard V, Lacasa D, Cremer I, Guerre-Millo M, et al. Adipose tissue transcriptomic signature highlights the pathological relevance of extracellular matrix in human obesity. Genome Biology. 2008;9(1):1–32. doi: 10.1186/gb-2008-9-1-r14 18208606

22. Boutens L, Stienstra R. Adipose tissue macrophages: going off track during obesity. Diabetologia. 2016;59(5):879–94. doi: 10.1007/s00125-016-3904-9 26940592

23. Rio DC, Ares M, Hannon GJ, Nilsen TW. Purification of RNA Using TRIzol (TRI Reagent). Cold Spring Harbor Protocols. 2010;2010(6):pdb.prot5439. doi: 10.1101/pdb.prot5439 20516177

24. Pfaffl M, Fleige S, Riedmaier I. Validation of lab-on-chip capillary electrophoresis systems for total RNA quality and quantity control. Biotechnology & Biotechnological Equipment. 2008;22(3):829–34.

25. O'Neil D, Glowatz H, Schlumpberger M. Ribosomal RNA Depletion for Efficient Use of RNA‐Seq Capacity. Current protocols in molecular biology. 2013:4.19. 1–4. 8.

26. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014:btu170.

27. Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC bioinformatics. 2011;12(1):323.

28. Leng N, Dawson J, Kendziorski C. EBSeq: An R package for differential expression analysis using RNA-seq data. R package version. 2015;1(10).

29. Smith-Unna R, Boursnell C, Patro R, Hibberd J, Kelly S. TransRate: reference free quality assessment of de novo transcriptome assemblies. Genome research. 2016:gr. 196469.115.

30. Green RE, Braun EL, Armstrong J, Earl D, Nguyen N, Hickey G, et al. Three crocodilian genomes reveal ancestral patterns of evolution among archosaurs. Science. 2014;346(6215). doi: 10.1126/science.1254449 25504731

31. Mi H, Poudel S, Muruganujan A, Casagrande JT, Thomas PD. PANTHER version 10: expanded protein families and functions, and analysis tools. Nucleic Acids Research. 2016;44(D1):D336–D42. doi: 10.1093/nar/gkv1194 26578592

32. Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics. 2011;12(1):1–16. doi: 10.1186/1471-2105-12-323 21816040

33. Croft D, Mundo AF, Haw R, Milacic M, Weiser J, Wu G, et al. The Reactome pathway knowledgebase. Nucleic Acids Research. 2014;42(Database issue):D472–D7. doi: 10.1093/nar/gkt1102 PMC3965010. 24243840

34. Fabregat A, Sidiropoulos K, Garapati P, Gillespie M, Hausmann K, Haw R, et al. The Reactome pathway Knowledgebase. Nucleic Acids Research. 2016;44(Database issue):D481–D7. doi: 10.1093/nar/gkv1351 PMC4702931. 26656494

35. Francis WR, Christianson LM, Kiko R, Powers ML, Shaner NC, Haddock SH. A comparison across non-model animals suggests an optimal sequencing depth for de novo transcriptome assembly. BMC genomics. 2013;14(1):1.

36. Montero-Mendieta S, Grabherr M, Lantz H, De la Riva I, Leonard JA, Webster MT, et al. A practical guide to build de-novo assemblies for single tissues of non-model organisms: the example of a Neotropical frog. PeerJ. 2017;5:e3702. doi: 10.7717/peerj.3702 28879061

37. Bolshoy A. DNA sequence analysis linguistic tools: contrast vocabularies, compositional spectra and linguistic complexity. Applied bioinformatics. 2002;2(2):103–12.

38. Rajgor D, Mellad JA, Autore F, Zhang Q, Shanahan CM. Multiple Novel Nesprin-1 and Nesprin-2 Variants Act as Versatile Tissue-Specific Intracellular Scaffolds. PLOS ONE. 2012;7(7):e40098. doi: 10.1371/journal.pone.0040098 22768332

39. Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson Da, Amit I, et al. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nature Biotechnology. 2011;29. doi: 10.1038/nbt.1883

40. Wan Q-H, Pan S-K, Hu L, Zhu Y, Xu P-W, Xia J-Q, et al. Genome analysis and signature discovery for diving and sensory properties of the endangered Chinese alligator. Cell research. 2013;23(9):1091–105. doi: 10.1038/cr.2013.104 23917531

41. Vinogradov AE. DNA helix: the importance of being GC‐rich. Nucleic acids research. 2003;31(7):1838–44. doi: 10.1093/nar/gkg296 12654999

42. Varriale A, Bernardi G. Distribution of DNA methylation, CpGs, and CpG islands in human isochores. Genomics. 2010;95(1):25–8. doi: 10.1016/j.ygeno.2009.09.006 19800400

43. Gómez-Martín C, Lebrón R, Oliver JL, Hackenberg M. Prediction of CpG Islands as an Intrinsic Clustering Property Found in Many Eukaryotic DNA Sequences and Its Relation to DNA Methylation. CpG Islands: Springer; 2018. p. 31–47.

44. Frenkel S, Kirzhner V, Korol A. Organizational Heterogeneity of Vertebrate Genomes. PloS one. 2012;7(2):e32076. doi: 10.1371/journal.pone.0032076 PMC3288070. 22384143

45. Mendizabal I, Soojin VY. Whole-genome bisulfite sequencing maps from multiple human tissues reveal novel CpG islands associated with tissue-specific regulation. Human molecular genetics. 2015:ddv449.

46. Long HK, King HW, Patient RK, Odom DT, Klose RJ. Protection of CpG islands from DNA methylation is DNA-encoded and evolutionarily conserved. Nucleic Acids Research. 2016. doi: 10.1093/nar/gkw258 27084945

47. Troyanskaya OG, Arbell O, Koren Y, Landau GM, Bolshoy A. Sequence complexity profiles of prokaryotic genomic sequences: A fast algorithm for calculating linguistic complexity. Bioinformatics. 2002;18(5):679–88. doi: 10.1093/bioinformatics/18.5.679 12050064

48. Flisiak R, Pytel-Krolczuk B, Prokopowicz D. Circulating transforming growth factor β1as an indicator of hepatic function impairment in liver cirrhosis. Cytokine. 2000;12(6):677–81. doi: 10.1006/cyto.1999.0660 10843744

49. Lin L, Gu Z-T, Chen W-H, Cao K-J. Increased expression of the long non-coding RNA ANRIL promotes lung cancer cell metastasis and correlates with poor prognosis. Diagnostic pathology. 2015;10(1):14.

50. Tanti J-F, Ceppo F, Jager J, Berthou F. Implication of inflammatory signaling pathways in obesity-induced insulin resistance. Frontiers in Endocrinology. 2013;3(181). doi: 10.3389/fendo.2012.00181 23316186

51. Chen GY, Nuñez G. Sterile inflammation: sensing and reacting to damage. Nature Reviews Immunology. 2010;10(12):826–37. doi: 10.1038/nri2873 21088683

52. Feng H, Su R, Song Y, Wang C, Lin L, Ma J, et al. Positive Correlation between Enhanced Expression of TLR4/MyD88/NF-κB with Insulin Resistance in Placentae of Gestational Diabetes Mellitus. PloS one. 2016;11(6):e0157185. doi: 10.1371/journal.pone.0157185 27340831

53. Yin J, Wang Y, Gu L, Fan N, Ma Y, Peng Y. Palmitate induces endoplasmic reticulum stress and autophagy in mature adipocytes: Implications for apoptosis and inflammation. International journal of molecular medicine. 2015;35(4):932–40. doi: 10.3892/ijmm.2015.2085 25647410

54. Yew Tan C, Virtue S, Murfitt S, Robert LD, Phua YH, Dale M, et al. Adipose tissue fatty acid chain length and mono-unsaturation increases with obesity and insulin resistance. Scientific Reports. 2015;5:18366. doi: 10.1038/srep18366 PMC4683622. 26679101

55. Sun K, Tordjman J, Clément K, Scherer Philipp E. Fibrosis and Adipose Tissue Dysfunction. Cell Metabolism. 2013;18(4):470–7. doi: 10.1016/j.cmet.2013.06.016 23954640

56. Fujisaka S, Usui I, Ikutani M, Aminuddin A, Takikawa A, Tsuneyama K, et al. Adipose tissue hypoxia induces inflammatory M1 polarity of macrophages in an HIF-1α-dependent and HIF-1α-independent manner in obese mice. Diabetologia. 2013;56(6):1403–12. doi: 10.1007/s00125-013-2885-1 23494472

57. Fuki IV, Kuhn KM, Lomazov IR, Rothman VL, Tuszynski GP, Iozzo RV, et al. The syndecan family of proteoglycans. Novel receptors mediating internalization of atherogenic lipoproteins in vitro. Journal of Clinical Investigation. 1997;100(6):1611. doi: 10.1172/JCI119685 9294130

58. Tkachenko E, Rhodes JM, Simons M. Syndecans new kids on the signaling block. Circulation research. 2005;96(5):488–500. doi: 10.1161/01.RES.0000159708.71142.c8 15774861

59. Rovira-Clavé X, Angulo-Ibáñez M, Noguer O, Espel E, Reina M. Syndecan-2 can promote clearance of T-cell receptor/CD3 from the cell surface. Immunology. 2012;137(3):214–25. doi: 10.1111/j.1365-2567.2012.03626.x PMC3482679. 22881146

60. Kwon M-J, Kim Y, Choi Y, Kim SH, Park S, Han I, et al. The extracellular domain of syndecan-2 regulates the interaction of HCT116 human colon carcinoma cells with fibronectin. Biochemical and Biophysical Research Communications. 2013;431(3):415–20. doi: 10.1016/j.bbrc.2012.12.155 23333331

61. Oh T, Kim N, Moon Y, Kim MS, Hoehn BD, Park CH, et al. Genome-Wide Identification and Validation of a Novel Methylation Biomarker, SDC2, for Blood-Based Detection of Colorectal Cancer. The Journal of Molecular Diagnostics. 2013;15(4):498–507. doi: 10.1016/j.jmoldx.2013.03.004 23747112

62. Schwartzman RA, Cidlowski JA. Apoptosis: The Biochemistry and Molecular Biology of Programmed Cell Death. Endocrine Reviews. 1993;14(2):133–51. doi: 10.1210/edrv-14-2-133 8325248.

63. Tracey D, Klareskog L, Sasso EH, Salfeld JG, Tak PP. Tumor necrosis factor antagonist mechanisms of action: a comprehensive review. Pharmacology & therapeutics. 2008;117(2):244–79.

64. Wang N, Lu H-S, Guan Z-P, Sun T-Z, Chen Y-Y, Ruan G-R, et al. Involvement of PDCD5 in the regulation of apoptosis in fibroblast-like synoviocytes of rheumatoid arthritis. Apoptosis. 2007;12(8):1433–41. doi: 10.1007/s10495-007-0070-z 17468978

65. Xu L, Hu J, Zhao Y, Hu J, Xiao J, Wang Y, et al. PDCD5 interacts with p53 and functions as a positive regulator in the p53 pathway. Apoptosis. 2012;17(11):1235–45. doi: 10.1007/s10495-012-0754-x 22914926

66. Park S-Y, Choi H-K, Choi Y, Kwak S, Choi K-C, Yoon H-G. Deubiquitinase OTUD5 mediates the sequential activation of PDCD5 and p53 in response to genotoxic stress. Cancer letters. 2015;357(1):419–27. doi: 10.1016/j.canlet.2014.12.005 25499082

67. Fulda S, Debatin K. Extrinsic versus intrinsic apoptosis pathways in anticancer chemotherapy. Oncogene. 2006;25(34):4798–811. doi: 10.1038/sj.onc.1209608 16892092

68. Tanti J-F, Ceppo F, Jager J, Berthou F. Implication of inflammatory signaling pathways in obesity-induced insulin resistance. Obesity-induced inflammation and insulin resistance. 2013;3(181):6.

69. Park S-Y, Choi H-K, Seo JS, Yoo J-Y, Jeong J-W, Choi Y, et al. DNAJB1 negatively regulates MIG6 to promote epidermal growth factor receptor signaling. Biochimica et Biophysica Acta (BBA)—Molecular Cell Research. 2015;1853(10, Part A):2722–30. http://dx.doi.org/10.1016/j.bbamcr.2015.07.024.

70. Abella V, Scotece M, Conde J, Pino J, Gonzalez-Gay MA, Gomez-Reino JJ, et al. Leptin in the interplay of inflammation, metabolism and immune system disorders. Nature Reviews Rheumatology. 2017;13(2):100. doi: 10.1038/nrrheum.2016.209 28053336

71. Carow B, Rottenberg ME. SOCS3, a Major Regulator of Infection and Inflammation. Frontiers in Immunology. 2014;5:58. doi: 10.3389/fimmu.2014.00058 PMC3928676. 24600449

72. Jiang B-g, Yang Y, Liu H, Gu F-m, Yang Y, Zhao L-H, et al. SOCS3 Genetic Polymorphism Is Associated With Clinical Features and Prognosis of Hepatocellular Carcinoma Patients Receiving Hepatectomy. Medicine. 2015;94(40):e1344. doi: 10.1097/MD.0000000000001344 PMC4616756. 26447993

73. Donath MY, Shoelson SE. Type 2 diabetes as an inflammatory disease. Nature Reviews Immunology. 2011;11(2):98–107. doi: 10.1038/nri2925 21233852

74. Esser N, Paquot N, Scheen AJ. Anti-inflammatory agents to treat or prevent type 2 diabetes, metabolic syndrome and cardiovascular disease. Expert opinion on investigational drugs. 2015;24(3):283–307. doi: 10.1517/13543784.2015.974804 25345753

75. Nolan CJ, Ruderman NB, Kahn SE, Pedersen O, Prentki M. Insulin resistance as a physiological defense against metabolic stress: implications for the management of subsets of type 2 diabetes. Diabetes. 2015;64(3):673–86. doi: 10.2337/db14-0694 25713189

76. Matanis T, Akhmanova A, Wulf P, Del Nery E, Weide T, Stepanova T, et al. Bicaudal-D regulates COPI-independent Golgi–ER transport by recruiting the dynein–dynactin motor complex. Nature Cell Biology. 2002;4(12):986–92. doi: 10.1038/ncb891 12447383

77. Bullock SL, Ish-Horowicz D. Conserved signals and machinery for RNA transport in Drosophila oogenesis and embryogenesis. Nature. 2001;414(6864):611–6. doi: 10.1038/414611a 11740552

78. Hoogenraad CC, Akhmanova A. Bicaudal D Family of Motor Adaptors: Linking Dynein Motility to Cargo Binding. Trends in cell biology. 2016;26(5):327–40. doi: 10.1016/j.tcb.2016.01.001 26822037

79. Oates Emily C, Rossor Alexander M, Hafezparast M, Gonzalez M, Speziani F, MacArthur Daniel G, et al. Mutations in BICD2 Cause Dominant Congenital Spinal Muscular Atrophy and Hereditary Spastic Paraplegia. The American Journal of Human Genetics. 2013;92(6):965–73. doi: 10.1016/j.ajhg.2013.04.018 23664120

80. Rossor AM, Oates EC, Salter HK, Liu Y, Murphy SM, Schule R, et al. Phenotypic and molecular insights into spinal muscular atrophy due to mutations in BICD2. Brain. 2015;138(2):293–310. doi: 10.1093/brain/awu356 25497877

81. Rivera J, Proia RL, Olivera A. The alliance of sphingosine-1-phosphate and its receptors in immunity. Nat Rev Immunol. 2008;8(10):753–63. doi: 10.1038/nri2400 18787560

82. Mechtcheriakova D, Wlachos A, Sobanov J, Kopp T, Reuschel R, Bornancin F, et al. Sphingosine 1-phosphate phosphatase 2 is induced during inflammatory responses. Cellular signalling. 2007;19(4):748–60. doi: 10.1016/j.cellsig.2006.09.004 17113265

83. Mandala SM, Thornton R, Galve-Roperh I, Poulton S, Peterson C, Olivera A, et al. Molecular cloning and characterization of a lipid phosphohydrolase that degrades sphingosine-1-phosphate and induces cell death. Proceedings of the National Academy of Sciences. 2000;97(14):7859–64.

84. Takada Y, Ye X, Simon S. The integrins. Genome Biology. 2007;8(5):215. doi: 10.1186/gb-2007-8-5-215 17543136

85. Avraamides CJ, Garmy-Susini B, Varner JA. Integrins in angiogenesis and lymphangiogenesis. Nature Reviews Cancer. 2008;8(8):604–17. doi: 10.1038/nrc2353 18497750

86. Murphy MW, Sarver AL, Rice D, Hatzi K, Ye K, Melnick A, et al. Genome-wide analysis of DNA binding and transcriptional regulation by the mammalian Doublesex homolog DMRT1 in the juvenile testis. Proceedings of the National Academy of Sciences. 2010;107(30):13360–5. doi: 10.1073/pnas.1006243107 20616082

87. Schieck M, Schouten JP, Michel S, Suttner K, Toncheva AA, Gaertner VD, et al. Doublesex and mab-3 related transcription factor 1 (DMRT1) is a sex-specific genetic determinant of childhood-onset asthma and is expressed in testis and macrophages. Journal of Allergy and Clinical Immunology. 2016;138(2):421–31. doi: 10.1016/j.jaci.2015.12.1305 26906082


Článek vyšel v časopise

PLOS One


2019 Číslo 11